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Understanding plantinvasions:A global scale meta-analysis

Alejandro Ordonez Gloria

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Rijksuniversiteit Groningen

Understanding plant invasions: a global scale meta-analysis

Proefschrift

ter verkrijging van het doctoraat in deWiskunde en Natuurwetenschappenaan de Rijksuniversiteit Groningen

op gezag van deRector Magnificus, dr. E. Sterken,in het openbaar te verdedigen op

maandag 17 oktober 2011om 16:15 uur

door

Alejandro Ordonez Gloriageboren op 13 mei 1978

Bogota, Colombia

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Promotor: Prof. dr H. OlffBeoordelingscommissie: Prof. dr. F. Berendse

Prof. dr. R. AertsProf. dr. W.H van der Putten

ISBN:978-90-367-5016-5 (printed version)978-90-367-5015-8 (digital version)

v

This research was supported by an Ubbo Emmius Scholarship from the University ofGroningen with additional support from a Netherlands Organization for Scientific re-search (NOW) Pionier grant awarded to Prof dr. Han Olff. The research for this thesiswas carried out in the Community and Conservation Ecology group (COCON) at theCenter for Ecological and Evolutionary Studies (CEES) of the University of Groningen,The Netherlands.All rights are reserved. No part of this book may be reproduced or transmitted withoutwritten permission from the author or, when appropriate, the publisher of the article.

Layout: Alejandro OrdonezCover: Irene van NesPrinted by:

Abstract:

Ordonez A. (2011) Understanding plant invasions: A global scale meta-analysis. PhDThesis, Rijksuniversiteit Groningen. Community and Conservation Ecology Group. Ni-jenborgh 7 - 9747AG Groningen. [email protected]

The globalization of human activities has resulted in the intentional and un-intentionalmovement of species to areas beyond their natural range; ultimately causing biotic ho-mogenization and irreversible changes to ecosystems. This dissertation addresses theinvasiveness and invasibility question by exploring global patters of trait similarity be-tween co-occurring alien and native plants. To do this, two questions were asked: Cantrait similarity between aliens and natives explain aliens success?; and, are the observedsimilarity patterns a product of evolution?. Aliens were found to display higher leaftraits, lower canopy height and smaller seeds. The magnitude of trait differences be-tween co-occurring aliens and natives remained the same along climatic edaphic andhuman disturbance gradients. These differences showed a strong dependence to the phy-logenetic relation between aliens and the native community; with phylogenetically closeco-occurring alien and native plants being more phenotypically similar than expectedby chance. These differences in traits were the result of aliens conserving their traitsonce introduced to a new area; something we suggest emerges from core ecological,evolutionary physiological and genetic constraints. The work presented here is a con-tribution to the long lasting quest for understanding the causes and mechanisms behindthe success of invasive species. Lastly, It is shown how species, community and evolu-tionary patterns must be accounted together to determine invasion risk.

Key words: Alien/native plants, biological invasions, functional traits, SLA specificleaf area, plant height, seed size, foliar nitrogen, photosynthetic capacity, trait evolu-tion, phylogenetic community structure, Darwin naturalization hypothesis, phenotypicattraction hypothesis, trait conservatism, niche, niche conservatism/differentiation, en-vironmental filtering

Contents

List of illustrations page xiList of tables xiiiList of contributors xvNotation xvi

Part I General introduction 1

1 Biological Invasions, why they matter and how can we predict them 31.1 Introduction 41.2 The problem with species introductions 61.3 From casual to invasive the introduction continuum 71.4 Conceptual approaches in invasive biology research 71.5 Using traits to evaluate community assemblies and patterns of alien

introductions 101.6 Functional response traits and plant ecological strategies 13

1.6.1 Leaf economics 151.6.2 Seed mass–Seed output 151.6.3 Potential maximum canopy height 17

1.7 Limits to trait variation from biophysical costs 171.8 Scale dependence of trait differentiation patterns 181.9 Outline of the dissertation 20

Part II Species perspective: Predicting successful aliens from life historycharacteristics 23

2 Alien plants conserve their traits between their native and introducedrange 25

2.1 Introduction 262.2 Methods 27

2.2.1 Database compilation and trait selection 272.2.2 Single trait comparisons 282.2.3 Comparisons between ranges in multidimensional trait space 29

2.3 Results 302.3.1 Single trait comparisons 30

viii Contents

2.3.2 Multivariate comparisons 332.4 Discussion 34

3 Functional differences between native and alien species 383.1 Introduction 393.2 Methods 40

3.2.1 Selection of traits 403.2.2 Database compilation 413.2.3 Individual trait comparisons 423.2.4 Multidimensional trait comparisons 42

3.3 Results 433.3.1 Individual trait comparisons 433.3.2 Multidimensional trait comparisons 43

3.4 Discussion 46

Part III Community perspective: Biological invasions in the context of plantcommunities 51

4 Cross scale functional differentiation of native and alien plants 534.1 Introduction 544.2 Methods 55

4.2.1 Data sources and evaluated traits 554.2.2 Statistical comparisons 564.2.3 Multi–dimensional comparison 58

4.3 Results 594.4 Discussion 61

5 Environment does not regulate differences in leaf traits 665.1 Introduction 675.2 Methods 68

5.2.1 Database compilation and selection of traits 685.2.2 Trait differentiation between native and alien species 695.2.3 Association with the environmental conditions 695.2.4 Multivariate trait: position along the leaf economics spectrum 70

5.3 Results 715.3.1 Trait differentiation between native and alien species 715.3.2 Association of traits and environmental parameters 725.3.3 Influence of climate in native and aliens multivariate trait

space differentiation 765.4 Discussion 78

Part IV Evolutionary perspective: Impact for predicting successful aliens 81

6 Darwin’s naturalization conundrum revisited 83

Contents ix

6.1 Introduction 846.2 Methods 85

6.2.1 Selection of traits and database compilation 856.2.2 Phylogeneny assembly 866.2.3 Evaluating the phylogenetic community structure 87

6.3 Results 886.3.1 Trait conservatism or convergence 886.3.2 Phylogenetic Structure of Communities 906.3.3 Trait evolution and trait similarity within communities 90

6.4 Discussion 92

7 Niche conservatism in invasive plants 967.1 Introduction 977.2 The starting point: an adequate niche concept 977.3 Trait conservatism as a driver of niche conservatism 997.4 Bioclimatic niche conservatism in invasive species 1007.5 Phylogenetic niche conservatism and the success of introduced aliens 1037.6 Conclusion 105

Part V Synthesis and closing features 107

8 Synthesis: are we closer to understanding and predicting invasions? 1098.1 Introduction 1108.2 Attributes of success: What traits tell us about invasions? 1108.3 Possible mechanisms responsible for aliens’ trait differentiation/similarity 1148.4 From patterns to mechanisms 118

8.4.1 Species based hypothesis 1188.4.2 Community based hypotheses 1198.4.3 Evolutionary based hypotheses 120

8.5 Final conclusions 122

9 Summary 124

10 Samenvatting 129

11 Acknowledgments 134

12 Curriculum vitae 13712.1 Personal information 13712.2 Education and training 13712.3 Work experience 13712.4 Publications 13812.5 Conferences, congress and presentations 138

x Contents

Appendix A Description of the protocol used to build the trait database 140A.1 Data set compilation. 140

A.1.1 Information gathering 140A.1.2 Trait measurements 140

A.2 Community assignment and data summary. 141A.3 Mixed effect models specification 142A.4 Phylogeny assembly 145A.5 Habitat and environmental coverage 146

Appendix B Summary of studies determining the conservation of traits betweenthe native and alien range 147

Appendix C Summary studies showing direct or indirect support for or againstthe idea of (bioclimatic or phylogenetic) niche conservatism(NC) or lability (NL) in natural and invaded communities 153

Appendix D Correlations between leaf traits and climatic, edaphic and humandisturbance 163

Appendix E Correlations between leaf traits and climatic, edaphic and humandisturbance 166

Notes 171References 173

Illustrations

1.1 Impacts of global change on invasions and the associated processes. 41.2 Representation of the ”Ecological sorting” process. 51.3 Summary of studies comparing aliens with their native congeners or related

taxa, and aliens congeners with different degree of invasiveness. 91.4 Schematic representation of the source–target approach for comparing at-

tributes of alien plants. 101.5 Theoretical example of variability of trait in response to environmental changes. 121.6 Schematic representation of the bi–variant relation between traits composing

an ecological dimension. 161.7 Predictions regarding coexistence or co–occurrence of native and aline species

according to the spatial scale of study and the phylogenetic (or functional)similarity between introduced aliens species and the native species assemblage. 19

2.1 Log response ratios for conspecifics native vs. alien/naturalized/invasive rangecomparisons. 33

2.2 Log response ratios of conspecifics comparisons between their native andalien/naturalized/invasive range. 34

3.1 Minimum convex hull projections of native and alien species, showing thedifferences between these species-groups in the multidimensional trait spacethat they occupy. 48

4.1 Log response contrast between co–occurring alien and native plants for threespecies traits (Specific leaf area–SLA, typical maximum canopy height–Hmax, Specific seed Weight–SWT). Comparisons are mede across a series ofhierarchically nested scales and for three contrast criteria. 60

4.2 Variance decomposition of the difference between native and aliens specificleaf area–SLA, typical maximum canopy height–Hmax, specific seed weight–SWT and multi-traits. 61

4.3 ariance decomposition of the difference between native and alien speciesin a) Specific leaf area–SLA, b) typical maximum canopy height–Hmax, c)Specific seed Weight–SWT and d) multi–traits, according to growth from (i.e.Shrubs/Trees, Graminoids/Herbs–forbs and Vines and climbers). 63

5.1 Differences between alien and native plants specific leaf area (SLA), foliarnitrogen per mass bases (Nmass), maximum photosynthetic rate per mass bases(Amass), and the position in the multi–trait leaf economics spectrum (Multi)between alien and native plants. 72

xii Illustrations

5.2 Plots for the alien–native differences in leaf traits (i.e. SLA, Nmass and Amass),and the position in the multi–trait leaf economics spectrum (Multi) and forWoody (Shrubs and Trees) and Non–woody (Graminoids and Herbs/Forbs)plants. 73

5.3 Correlations between alien and native leaf traits and compound measurementsof soil fertility and disturbance. 77

5.4 Standardized major axis regression (SMA) relationships between specific leafarea (SLA), foliar nitrogen (Nmass) and photosynthetic capacity (Amass). 78

6.1 Tests of conservatism–convergence of alien species traits in relation to co-occurring native species. 89

6.2 Conservatism of traits in relation to trait similarity within communities forparticular growth forms (woody, non-woody and vines and climbers). 93

7.1 Summary of the results of 34 studies comparing ecological traits of introducedplants between its’ alien (A) and native (N) range. 101

7.2 Summary of 70 studies showing direct or indirect evidence, in favor or against,the idea of niche conservatism (NC) or lability (NL). 102

8.1 Conceptualization of the ”’alien introduction continuum” and the ’alienintroduction continuum and the barriers any introduced plant must overcometo establish viable communities in a new area. 115

8.2 Strategy shifts between alien and native plants along an ecological strategy. 117A.1 Relationships between the mean difference in traits of co–occurring alien and

native species (y–axis) and size of the grouping scale (x–axis) 142A.2 Model residuals histograms from lineal mixed effect models using log10

transformed traits. 143A.3 Spatial location of locations with data for either or the analyzed traits. 146D.1 Correlations between evaluated alien and native leaf traits and climatic,

edaphic and human impact. 164D.2 Correlations between evaluated alien and native leaf traits and climatic,

edaphic and human impact, Continued... 165E.1 Correlations between alien and native leaf trait differences and climatic,

edaphic and human impact. 167E.2 Correlations between alien and native leaf trait differences and climatic,

edaphic and human impact. Continued... 168E.3 Correlations between alien and native leaf trait differences and climatic,

edaphic and human impact. Continued... 169E.4 Correlations between alien and native leaf trait differences and climatic,

edaphic and human impact. Continued... 170

Tables

1.1 Alternative strategies used in comparative studies aiming to determine patternsof (dis)similarity between alien and native species or aliens original andintroduced ranges. 8

1.2 Summary of trait definitions used in the literature, with the function, compo-nent or process they are supposed to capture. 11

1.3 Summary of cost and benefits, and associated trade-offs in three dimensions ofecological variation from Westoby (1998) LHS scheme. 14

2.1 Regression coefficients of mixed–effect models comparing conspecifics traitvalues between their native and alien/naturalized/invasive range. 31

2.2 Regression coefficients of mixed–effect models comparing conspecifics traitvalues, of particular growth form, between their native and alien/naturalized/invasiverange. 32

2.3 Conspecific PERMANOVAs comparing the trait composition of speciesbetween its native and alien/naturalized or invasive range. 35

2.4 Within growth from PERMANOVAs comparing the trait composition ofspecies between its native and alien/naturalized or invasive range. 35

3.1 Comparison of mean trait values of alien and native species, considering allspecies, and species grouped by growth form. 44

3.2 Summary of discriminant analyses used to determine which traits bestdifferentiated between native and alien species in multivariate trait-space,considering all species, and species grouped by growth form. 45

3.3 Descriptive attributes of multi-trait convex hulls describing native and alienspecies, considering all species, and species grouped by growth form. 47

4.1 Estimation of mean trait values and components of nested ANOVA’s withrandom effects for the used hierarchical structure. 57

4.2 Variance components (removing the species scale) of the difference betweennative and alien species traits. 62

5.1 Correlations between alien and native leaf traits and site climatic, edaphic orhuman disturbance factors. 74

5.2 Correlations between alien and native leaf traits differences and site climatic,edaphic or human disturbance factors. 75

xiv Tables

6.1 Tests for patterns of trait evolution (i.e. traits are either conserved or convergentor there is no phylogenetic signal) for datasets that vary in the communityphylogenetic structure (null model 1a–b) or the community trait composition(null model 2). 91

6.2 Tests for patterns of phylogenetic trait similarity between communities (i.e.communities are either over–dispersed, clustered or there is no relation). 92

7.1 Leading hypotheses in invasion biology and their relationship to nicheconservatism (NC) or lability (NL). 99

8.1 Synthesis of results from comparative and congeneric studies on traitspromoting invasiveness in plant. 112

A.1 Variance components from a linear mixed model comparing the differences inSLA Hmax and SWT between native and alien species 145

A.2 Variance components from a linear mixed model evaluating the differences inSLA, Hmax and SWT between native and alien species. The model includedthe full taxonomic identity structure (i.e. family/genus/species). 145

List of contributors

Alejandro Ordonez GloriaCommunity and conservation ecology Group (COCON) University of Groningen

Ian J. WirghtDepartment of Biological Sciences, Macquarie University

Han OlffCommunity and conservation ecology Group (COCON) University of Groningen

Notation

SLA Specific leaf area (cm2 × g−1)Hmax Typical maximum height (m)SWT Individual seed weight (mg)Amass Photosynthetic capacity (nmol × g−1 × s−1)Nmass Leaf nitrogen content per mass bases (g × g−1 or %)BGD Between group differencesAlien–to-All Alien contrasted to all co–occurring natives in a siteAlien–to–PhyloClose Alien contrasted to the phylogenetically closer native in a siteAlien–to–Mean Alien contrasted to the mean of all co–occurring natives in a siteDNH Darwin’s naturalization hypothesisPAH Phenotypic attraction hypothesisNC Niche conservatismNL Niche labilityPNC Phylogenetic niche conservatismBNC Bio–Climatic niche conservatismSDM Species distribution modelingSMAR Standardized Major-Axis regressionCCR correct classification rateAUC area under the receiver–operator curve

Part I

General introduction

1 Biological Invasions, why theymatter and how can we predictthemAlejandro Ordonez Gloriaab

a Community and Conservation Ecology Group, University of Groningenb Correspondence author. E–mail: [email protected]

4 Biological Invasions, why they matter and how can we predict them

1.1 Introduction

As non–native species are able to invade, they have the potential to transform its newenvironment via the displacement of elements of the native biota (Rejmanek, Richard-son, Higgins, Pitcairn, Grotkopp, Mooney, Mack, Mc Neely, Neville, Schei & Waage2005, Richardson & Pysek 2006), modification of natural disturbance regimes (Brooks,D’Antonio, Richardson, Grace, Keeley, DiTomaso, Hobbs, Pellant & Pyke 2004, Mack,Simberloff, Lonsdale, Evans, Clout & Bazzaz 2000, Schmitz, Simberloff, Hofstetter,Haller & Sutton 1997, Vitousek & Walker 1989) and the transformation of ecosystemstructure and functioning (Chapin III, Zavaleta, Eviner, Naylor, Vitousek, Reynolds,Hooper, Lavorel, Sala, Hobbie, Mack & Diaz 2000, Dukes 2002, Levine & D’Antonio2003, Mack et al. 2000, Vitousek, Mooney, Lubchenco & Melillo 1997). This hasresulted (as schematized in Fig. 1.1) in major local–extinction events, widespreadchanges in the distribution of organisms, alterations in ecosystem processes and ser-vices, and changes in ecosystem resilience. Given that these changes pose significantthreats to indigenous flora and natural ecosystems, understanding the why, when andhow of invasions is crucial.

Global changes Human Impacts

Changes to natural systems

Ecosystem processes Ecosystem goods

and services

Biogeochemical cyclesElevated CO2Nutrient loadingWater consumption

Land useUrban/AgriculturalIntensity

Species invasions

Humanactivities

Economicbenefits

Culturalbenefits

BiodiversityRichnessCompositionInteractions

Species traitsCompositionInteractions

Nutrient cyclingNatural disturbances

Natural cycles

Figure 1.1 Impacts of global change on invasions and the associated processes. Diagram basedon the ideas and diagrams of Chapin III et al. (2000); Thuiller et al. (2007), Vitousek (1997);Mack et al. (2000), with modifications.

One of the main goals of invasion biologist and community ecologists has been toprovide an answer to these questions, as it could potentially provide a series of tools

1.1 Introduction 5

for the screening, monitoring and eradicating noxious aliens. Various approaches havebeen used to reach this goal. Of these, the use of life history traits has proven to be oneof the most promising to evaluate the link between traits, performance and introductionsuccess. There are two fundamental assumption of this trait–based approach. First, theimportance of certain traits (e.g. carbon capture, reproductive effort or light competi-tion) in determining plant performance, and hence its success under particular environ-ments. Secondly, similarity or dissimilarity in particular life history traits (specificallyresponse traits sensu Lavorel & Garnier 2002) are key in determining the way plantspecies overcome geographical, environmental and biological barriers (as presented inFig. 1.2). Both of these assumptions are the base of this, and other works (e.g. Cadotte& Lovett-Doust 2001, Crawley, Harvey & Purvis 1996, Daehler 2003, Forcella, Wood& Dillon 1986, Noble 1989, Pysek & Richardson 2007, Roy 1990, Thompson, Hodgson& Rich 1995, Thompson & Davis 2011, van Kleunen, Weber & Fischer 2010) identifyplant characteristics correlated with invasiveness.

Geo

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Rep

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Pred

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Para

site

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Com

petit

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Dis

turb

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Envi

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Trait Similarity Trait Differentiation

Casual

Naturalized

Invasive

Figure 1.2 Schematic representation of the ”Ecological sorting” process showing some of themajor filtering barriers plant face after being introduced. Arrows indicate the paths followed bytaxa coming form the meta–community or introduced form an external pool (aliens introduction)from arrival to establishment. Crossing of the barriers is not irreversible. For example, climaticfluctuations can either pose new barriers (which could drive alien taxa to extinction at localand/or regional scales), or enable the taxon to survive or spread. Invasions are context specificprocess that only materializes when certain requirements are fullfiled.

This dissertation explores if the observed patterns of trait (dis)similarity between co–occurring native and alien plants relate to introduction success, and are consistent along


and across taxonomic, spatial, phylogenetic and resource gradients. For this, two ques-tions were specifically asked: i) Can trait (dis)similarity between aliens and natives ex-plain non–natives success?; and are the observed (dis)similarity patterns a product ofevolution?. To answer these, first the relationship between native and alien plant perfor-mance related traits was evaluated, aiming to determine the existence of a pattern of trait(dis)similarity between both groups. Second, native–alien trait (dis)similarity patternswere assessed in relation to the ecological setup (community phylogenetic composition,scale and resource availability) of the area where they are introduced. Lastly, the roleof evolutionary dynamics (i.e. niche and trait conservatism) in generating the observedpatters of trait (dis)similarity was determined.

1.2 The problem with species introductions

From all the human–induced changes in natural ecosystems, biotic exchanges are cur-rently one of the main global problems faced by natural ecosystems (as schematizedin Fig. 1.1). This is due to the direct effects of these exchanges on ecosystem pro-cesses, their threats to native biodiversity and the associated severe loses to human eco-nomic wealth (Chapin III et al. 2000, Pimentel 2005, Rejmanek et al. 2005, Srivastava& Vellend 2005, Vitousek et al. 1997). Due to the magnitude and relevance of these im-pacts, understanding what makes either a given species a successful alien or a particularhabitat more suitable to be invaded is fundamental for conservation efforts.

Among the most important effects of alien species on ecological communities, thedisruption of ecosystems processes ranks the highest. Examples of such changes rangefrom variations in frequency and intensity of natural fires, as is the case of invasivegrasses (Brooks et al. 2004, D’Antonio & Vitousek 1992); changes in nitrogen (or othernutrients) deposition rates, as the case of Myrica faya in Hawaii Volcanoes NationalPark (Vitousek, Loope & Stone 1987, Vitousek & Walker 1989) and several species ineastern Australia (Leishman, Hughes & Gore 2004, Leishman & Thomson 2005); andgreater water use, as the case of invasions by eucalypts, pines, Acacia spp., and Hakeaspp. in the fynbos in South Africa’s Cape Province (Holmes & Cowling 1997, LeMaitre,VanWilgen, Chapman & McKelly 1996, Stock, Wienand & Baker 1995, van Wilgen,de Wit, Anderson, Le Maitre, Kotze, Ndala, Brown & Rapholo 2004, Witkowski 1991).Additionally, successful aliens have the possibility to transform the landscape of theintroduced region. Examples of this are changes in the Florida Everglades due to the in-vasion of the Australian paperbark tree (Melaleuca quinquenervia, where invaders havechanged the landscape from a seasonally flooded marsh to a fire–prone forest of inva-sive trees (Bodle, Ferriter & Thayer 1994, Schmitz et al. 1997); or changes in the Ama-zon basin through the burning of forests and their replacement with palatable Africangrasses (as Melinis minutiflora, Hyparrhenia rufa, Panicum spp., and Rhynchelytrumrepens) during the creation of grasslands for cattle grazing (Fearnside 1993, Shukla,Nobre & Sellers 1990).

How aliens are able to do this in their alien but not in their native range is perhapsone of the most intriguing questions still to be answered by invasion biology. Ideas such

1.3 From casual to invasive the introduction continuum 7

as niche construction (Odling-Smee, Laland & Feldman 2003) and changes in effecttraits (i.e. functional traits that are related to the effect of a plant on its surroundingenvironment sensu Lavorel & Garnier 2002) could provide and answer to this question.Based on these ideas, introduced aliens have the potential to change the depletion ratesof light and soil water or nutrients (Fargione & Tilman 2006, Violle & Jiang 2009,Wedin & Tilman 1993, Westoby & Wright 2006) through their attributes (Fig. 1.1). Thiswould result in a modification of the environmental balance in the introduced region andhence the environmental filters determining community composition.

As globalizing processes pick–up speed and strength, the complete loss of naturallyimposed biogeographical boundaries will lead to many more alien species everywhere.As a result, an increasing number of these aliens would have the potential to becomeinvasive. This makes biological invasions a problem of global scope, not only involvingthe small group of scientist and experts addressing it from a scientific perspective; butrather demanding the involvement of governments, local administrations and stakehold-ers.

1.3 From casual to invasive the introduction continuum

For understanding what makes a species to become a successful alien or what makesa particular habitat more suitable to be invaded, a consistent and unambiguous set ofconcepts describing what is an alien, a naturalized and an invasive species is required.Richardson, Pysek, Rejmanek, Barbour, Panetta & West (2000) highlight the need forsuch conceptual framework, and propose a description of the status of an introducedspecies based on the series of environmental and biological filters it manages to over-come (Fig. 1.2). The proposed classification (which is the one used in this disertation)defines Alien plants as those taxa in a given area whose presence in the new region isdue to intentional or accidental introduction resulting from human activity. Two maingroups of alien species can then be described. Naturalized plants, which are those aliensthat reproduce consistently and sustain populations over many life cycles without directintervention by humans; and Invasive plants, which are those naturalized aliens that pro-duce reproductive offspring, often in very large numbers, at considerable distances fromparent plants and thus have the potential to spread over a considerable area.

As shown in Fig. 1.2, only a few alien species can overcome the many barriers toestablishment and persistence, resulting in incorporating in the biota of the new region(these are naturalized or invasive aliens). From the hand full of species that manage toproliferate, only a small proportion do so to an extent that they have major effects onthe local biota, and therefore have the potential to cause substantial changes in com-munity structure and ecosystem functioning (these are invasive aliens exclusively). Thissequential process is what in invasive literature is called the ”tens rule” (Williamson,Brown, Holdgate, Kornberg, Southwood & Mollison 1986) which states that 10% ofintroduced species escape to become casual, 10% of casuals become naturalized, and10% of naturalized species become invasive. It is important to say that the same processalso applies to native plants moving from the meta–community pool to a particular area;


Table 1.1 Alternative strategies used in comparative studies aiming to determine patternsof (dis)similarity between alien and native species or aliens original and introduced ranges

Taxonomical Geographical Comparison Analyticalcontrast approach Scale methods

Native–Alien Source area Local Simple comparisonAlien–Alien Target area (neighborhood, Phylogenetic corrections

plot or community) Net effects: residence timeRegional (Land scape unit, Net effects: distributioncountry, Biome,Eco–region)Continental

making invasions a particular case of community composition changes (Thompson &Davis 2011).

Despite efforts to create lists of invasive alien species for different regions and forthe whole world (e.g. Global Invasive Species Information Network– GISIN; GlobalInvasive Species database; ALARM Project; DAISIE; Plant DATABASE), informa-tion about most species is insufficient so that they can be objectively classified as ei-ther naturalized or invasive (sensu Richardson, Pysek, Rejmanek, Barbour, Panetta &West 2000). This has limited our ability to make sound generalizations on the correlatesand determinants of species invasiveness and community invasibility. Accurately com-piled lists of native and alien floras (using objective criteria as the one used here) areclearly essential for the progress of invasion biology (Binggeli 1996, Pysek, Richardson,Rejmanek, Webster, Williamson & Kirschner 2004, Richardson & Pysek 2006, Richard-son, Pysek, Rejmanek, Barbour, Panetta & West 2000).

1.4 Conceptual approaches in invasive biology research

Various approaches are possible to establish the role of plant life history attributes in thesuccess of biological introductions. These expand on both taxonomic and geographicaldimensions (Table 1.1). Selecting the best approach involves a clear idea of what isasked, which groups are compared, the spatial domain relevant to the question, the typeof data available and the most adequate analytical method. This perspective also holdsfor producing predictive models for invasions or prioritizing alien species control.

Taxonomical approaches (first column in Table 1.1) fall into one of two categories:pairwise or multi–species comparisons (Pysek & Richardson 2007). The first approachinvolves the experimental pairing of alien species with native or non–invasive species,usually conspecific, congeneric or confamilial; or with a species of the same Plant Func-tional Type. The aim of this approach is to determine if there are consistent differencesbetween the alien–native or alien–alien pair, which might help to explain success ofsome introduced taxa. Although these efforts have provided a set of possible explana-tions for the success of aliens based on the level of similarity/dissimilarity of charac-

1.4 Conceptual approaches in invasive biology research 9

Alien/invasive has more vigorous spatial growth (5)

Alien/invasive is more fecund (13)

Alien/invasive has higher water, N and/or P use efficiency (9)

Alien/invasive exhibits faster growth (8)

Alien/invasive is more resistant to herbivory (11)

Alien/invasive has higher photosynthetic rate/capacity (15)

Alien/invasive has higher specific leaf area (11)

Alien/invasive is taller (6)

Alien/invasive has larger and longer persistent seed bank (10)

Alien/invasive has higher leaf area ratio (8)

Alien/invasive has higher biomass (15)

Alien/invasive has more leaves (10)

Alien/invasive has higher total leaf area (10)

Alien/invasive allocate more to reproduction (7)

0% 25% 50% 75% 100%

Yes (%) No (%)

Figure 1.3 Summary of the results from several studies comparing aliens with their nativecongeners or related taxa, and aliens congeners with different degree of invasiveness.Percentages of significant results supporting (yes) or rejecting (no) given statements, or yieldingno difference are shown. Traits are listed according to decreasing unambiguousness of results.References and data used for this figure are included in Richardson & Pysek (2006)

teristics [as shown in Fig. 1.3, and reviewed by Pysek & Richardson (2007) and vanKleunen et al. (2010)], it has been difficult to generalize on attributes which differentiatealiens from native species. Perhaps, the major drawback of this approach is the difficultyof direct comparisons and extrapolations between studies. In practice the methods usedappear to be specifically suited for a given set of species pairs, regions of interest and/orthe investigator’s research priorities.

In contrast, a multi–species approach is based on comparisons of whole floras, paringtwo sets of communities (e.g., native vs. alien, alien non invasive vs. alien invasive)and contrasting individual traits between these groups, using methodologies somewhatanalogous to those ones used in community ecology. Studies using this approach haveonly been possible in recent years, as large trait and community datasets have onlyrecently become available. Results from this type of analysis have provided a fairlyrobust set of generalization on the role of trait (dis)similarity for the success of alienspecies (e.g. Cadotte, Murray & Lovett-Doust 2006, Hamilton, Murray, Cadotte, Hose,Baker, Harris & Licari 2005, Lake & Leishman 2004, Leishman, Thomson & Cooke2010, Ordonez, Wright & Olff 2010, Pysek & Richardson 2007, Thompson et al. 1995,


Source-areaapproach

Source-areaapproach

Source area 1 Source area 2

Target area

Target-areaapproach

Target-areaapproach

Figure 1.4 Schematicrepresentation of thesourcetarget approach forcomparing attributes of alienplants. The ”source areaapproach” compares invasiveand non-invasive speciescoming from a particularregion. The ”target areaapproach” comparessuccessful and un-successfulaliens reaching an area aimingto find generalities on theattributes of the successfulalien species

van Kleunen et al. 2010). This is because studies with this approach tackle the problemfrom a general point of view, seeking for generalities among the set of particularities.

An additional level of consideration in determining the role of plant life history inbiological invasions is the geographical context of the contrast (Fig. 1.4 and column2 in Table 1.1). Specifically, two alternative approaches are available. First, a source–area approach where aliens are compared between their native and introduced range(Prinzing, Durka, Klotz & Brandl (2002), and schematized in Fig. 1.4). An alternativelyapplication of this approach compares invasive and non–invasive species coming from aspecific geographic source region. The goal here is to characterize the attributes of thosespecies that are able to pass through the early transition phases of the invasion process(i.e. geographic and environmental barriers in Fig. 1.2) and become naturalized orinvasive in a new region. It is also suitable for identifying net effects of traits becauseit eliminates or reduces the bias and variation associated with different species origins,and pathways and distance of introduction

The second method is a target–area approach (Hamilton et al. (2005) and schema-tized in Fig. 1.4). It focuses in determining either similarities between successful aliensin a particular area; or on establishing the dissimilarities between aliens know to besuccessful and those non–natives that having arrive did not succeed. Alternatively, atarget area contrast could compare aliens and natives known to co–occur in a region ofinterest. Both approaches (schematized in Fig. 1.4) try to determine what traits of theinvading species enhance their potential to increase in abundance over native speciesin a particular location. Additionally, this contrast tries to establish if successful alienshave unique properties not seen in native expanding taxa.

The target–area approach has been the most commonly used (e.g. Brandle, Stadler,Klotz & Brandl 2003, Cadotte & Fukami 2005, Cadotte, Hamilton & Murray 2009,Cadotte et al. 2006, Hamilton et al. 2005, Lake & Leishman 2004, Lambdon & Hulme2006, Lambdon, Lloret & Hulme 2008, Leishman et al. 2010, Lloret, Medail, Brundu &Hulme 2004, Ordonez et al. 2010, Pysek & Richardson 2007, Thompson et al. 1995, vanKleunen et al. 2010). Nonetheless, two important factors should be considered in its’

1.5 Using traits to evaluate community assemblies and patterns of alien introductions 11

application. First, which aliens and natives are compared, as not all aliens spread in theintroduced area (i.e. casual or naturalized aliens sensu Richardson, Pysek, Rejmanek,Barbour, Panetta & West 2000). Second, analyses of this type should try control forthe influence of residence time among non–native species, prior to examination of therole of life history in invasion. This is to remove the potentially confounding issue thatthe longer a species has been in a new area, the greater the chance that it has becomeabundant and widespread (Pysek, Brock, Bimova, Mandak, Jarosik, Koukolikova, Pergl& Stepanek 2003).

1.5 Using traits to evaluate community assemblies and patterns ofalien introductions

Current advances in ecology have advocated a trait–based renaissance of communityecology (McGill, Enquist, Weiher & Westoby 2006). This suggestion is based on threeimportant ideas. First, on the link between performance traits (e.g. leaf nitrogen con-centrations, rooting depths, wood densities, leaf sizes and potential canopy) and thedistribution of particular species (Chuine 2010, Kearney, Simpson, Raubenheimer &Helmuth 2010, Morin & Lechowicz 2008). Second, on the importance of traits in shap-ing a species fundamental niche within a specific abiotic context (McGill et al. 2006, Vi-olle & Jiang 2009). And third, on the functional relationship between traits and theenvironment and how this affects the performance of individuals of a species (McGillet al. 2006, Morin & Lechowicz 2008, Violle & Jiang 2009).

Describing ecological processes in terms of life–history attributes (from individ-ual to communities as described in Table 1.2), and especially those related to per-formance and metabolic homeostasis, has allowed scientist: i) to devise the role ofspecies–level trait differences in patterns of plant species coexistence (Cornwell &Ackerly 2009, Cornwell & Ackerly 2010, Kraft, Valencia & Ackerly 2008); ii) to estab-lish a link between individual performance and species niche (Kearney et al. 2010, Vi-olle & Jiang 2009); iii) to devise a functional classifications of organisms and its in-fluence on ecosystem functioning (Lavorel, McIntyre, Landsberg & Forbes 1997, No-ble & Gitay 1996, Woodward & Cramer 1996); iv) to define emerging properties ofcommunities on the bases of the observed functional variation (Mason, Mouillot, Lee& Wilson 2005, Petchey & Gaston 2002, Petchey & Gaston 2006, Walker, Kinzig &Langridge 1999); and v) to assess species effects on its ecosystems (Eviner & Chapin2003, Lavorel & Garnier 2002). These are all important patterns studied in moderncommunity ecology.

In the case of invasion biology, such a trait–based approach has produced some of themost accepted theories explaining aliens success (e.g. evolution of competitive ability,novel weapons, new niches, Darwin’s naturalization hypothesis among others). As inclassical community ecology, the most cited mechanism allowing alien species to estab-lish and persist in a community is the conection between species–level trait differencesand niche overlap. Therefore, the success of alien plants can be described in a similarway as the success of colonizing native species could be described, irrespective of their


Table 1.2 Summary of trait definitions used in the literature, with the function, component orprocess they are supposed to capture.

Terms Examples Definitions

Individual level

Trait SLA, Height, Seed mass,corolla shape, Number ofsepals, bark toughness

Any morphological, physiological orphenological feature measurable at theindividual level, from the cell to thewhole–organism level, without refer-ence to the environment or any otherlevel of organization.

Attribute LAI, Mean Height, Seed Num-ber, Seed bank input

Value or modality taken by a trait at apoint of an environmental gradient.

Functional trait SLA, Height, Seed Mass, Amax,Rmass

Any trait that impacts fitness indirectlyvia its effects on growth, reproductionand survival.

Performancetrait

Relative growth rate (RGR),life time reproductive success,plant lifespan

Direct measure of fitness. In plants,only three types of performance traitsare recognized: vegetative biomass, re-productive output (e.g. seed biomass,seed number), and plant survival.

Interactions with environment

Response trait SLA, Nmass/area, Pmass/area Any attribute for which its values variesin response to changes in environmentalconditions.

Ecological per-formance

Mean RGR, Response of the whole–organism per-formance, assessed by one or more per-formance traits (maximum, mean orvariance), to an environmental gradient.

Effect trait Nitrogen fixer (Y/N) Any trait that reflects the effects ofa plant on environmental conditions;community or ecosystem properties.

Population, community and ecosystem levels

Demographicparameter

(λ) , percapita populationgrowth - r, Mortality rate

Population feature that directly condi-tions the finite rate of increase (λ) ofthe population: age– or stage–specificrates of survival, reproduction, growth,development.

Communityor ecosystemproperty

Nitrogen / Carbon flow Any feature or process measured at thecommunity or ecosystem level

Communityfunctionalparameter

Species richness, Diversity, traitdiversity

Any feature resulting from thecommunity–aggregation of functionaltraits

1.5 Using traits to evaluate community assemblies and patterns of alien introductions 13

Trai

t

Traitbreadth

Trait optimum

EcologicalPerformance

Environmental gradient

Figure 1.5 Theoreticalexamples of variability of trait inresponse to environmentalchanges. Each pointcorresponds to the trait valuetaken by one individual at apoint of an environmentalgradient (x–axis). The linerepresents an example of fittedfunctions representing thevariation of trait valuesaccording to environmentalconditions.

alien or native status (Thompson & Davis 2011). This somewhat universal mechanismsis based on the idea that a species’ fundamental niche determines the performance ofits individuals under particular environmental conditions. However, balance betweenspecies performance, niche and traits is what determines the success of a species as afunction of abiotic environmental gradients, and the biotic interactions a species willencounter.

This conceptual outline is the base of the morphology, performance, and fitnessparadigm proposed by Arnold (Arnold 1983) for animals and adapted by Violle, Navas,Vile, Kazakou, Fortunel, Hummel & Garnier (2007) to explain the ensemble process ofplant communities. According to this paradigm, morphological traits influence (directlyand indirectly) performance traits, which in turn influence (directly or indirectly) fit-ness. This performance paradigm constitutes a very useful framework, introduced onlyvery recently in plant ecology to determine the role of functional traits in plant adapta-tion and community composition (Ackerly, Dudley, Sultan, Schmitt, Coleman, Linder,Sandquist, Geber, Evans, Dawson & Lachowicz 2000, Geber & Griffen 2003).

This dissertation builds from these ideas by assessing the influence of functionaltraits related to specific ecological strategies (i.e. leaf economics, seed number–sizeand height, all discussed below) on plant success. Specifically, this work is centeredon the idea that such plant functional traits are useful tools to represent niches overenvironmental gradients. Following this, a species mean trait values indicates its nichepositions along main gradients, its variability indicates its niche breadth (as schematizedin Fig. 1.5), and the relation between the trait distribution of two species would reflecttheir niche overlap and possible competitive dynamics. This trait–based approach doesprovide an operational assessment of the possible effects of niche overlap/segregationfor a potentially large number of species, making it possible to explain differences insuccess among alien species.


1.6 Functional response traits and plant ecological strategies

As all plant species use the same major resources (light, nutrients, water, etc), ecolog-ical differences are bound to emerge (i.e. different functional response traits) in orderto secure carbon profits during vegetative growth and ensure gene transmission into thefuture (Schimper 1903, Westoby & Wright 2006). In the case of plants, constructioncosts, lifespan, and relative allocation of resources vary between different plant organs(leaves, stems, roots, and seeds). These alternative solutions represent major axes ofecological variation (also called dimensions of ecological variation), where the posi-tion of an individual on it is determined by the optimization constrains imposed by thecoevolution of associated functional traits (Marks & Lechowicz 2006, Marks 2007).

Summarizing the observed ecological variation between species into ecological strate-gies (i.e. the arrangement of species in categories or along spectra according to their eco-logical attributes) is then useful to understand the patterns of coexistence observed innature. This classification can be done using a variety of schemes (as reviewed Westoby,Falster, Moles, Vesk & Wright 2002); among which Grime’s CSR triangle (Grime 1974,Grime 1998) and Westobys’ leaf–height–seed (LHS) strategy (Westoby 1998, Westobyet al. 2002) are the best documented. The CSR triangle profiles plant species usingtwo major dimensions of ecological variation: coping with disturbance (Ruderals or theR–axis) and adapting to fast versus slow growth opportunities (Competitors to Stress–tolerators or C–S axis). Although these axes have been proven helpful to classify speciesunder particular conditions, they show limitations to capture geographical–scale varia-tion (Westoby 1998). Additional limitations with the CSR scheme are the classificationof species intermediate strategies (are species always a clear competitor, stress tolerantor ruderal?); and how patterns that can’t be condensed into the CSR triangle should behandled. For this reason, attempted syntheses of the accumulated experimental literatureon plant ecological strategies have been forced back to growth–form, life–form, or habi-tat categorizations (e.g. Connell 1983, Goldberg 1996, Goldberg & Barton 1992, Gure-vitch, Morrison & Hedges 2000, Schoener 1983, Vesk & Westoby 2001, Wilson &Agnew 1992).

An alternative ecological strategy classification (the one used in this dissertation) isWestoby’s (1998) leaf–height–seed (LHS) scheme. It classifies plant species using a se-ries of independent dimensions of ecological variation defined by trade–offs betweencharacteristic traits (discussed below and in Table 1.3). Each of these dimensions cap-tures the way a species copes with the physical environment or the presence of com-petitors and other biota. As a result, the position of a species along each dimension,expresses meaningful differences in its’ ecological behavior in relation to other plantspecies. The advantage of such an approach is its ability to provide a consistent way tocompile and analyze, under a simple framework, the knowledge gained from hundredsof experiments worldwide (Westoby et al. 2002).

The LHS scheme focuses, not exclusively, in three main dimensional strategies: Theleaf economics spectrum (Reich, Walters & Ellsworth 1997, Westoby et al. 2002, Wright,Reich, Cornelissen, Falster, Groom, Hikosaka, Lee, Lusk, Niinemets, Oleksyn, Osada,Poorter, Warton & Westoby 2005, Wright, Reich, Westoby, Ackerly, Baruch, Bongers,

Table1.3

Sum

mary

ofcostandbenefits,and

associatedtrade-offs

inthree

dimensions

ofecologicalvariationfrom

Westoby

(1998)LHS

scheme.

TraitsL

eafEconom

icsH

eightSeed

size–

Output)

High

traitvalues

Cost

Shorterm

eanresidence

time

ofnutrients,low

er-ing

Nitrogen

sequestrationcapacity;H

ighersus-

ceptibilityand

costsfrom

damage

byherbivores;

Investment

incostly

quantitativedefense

sub-stances

(i.e.secondary

metabolites);

Higher

perm

assw

aterlossrate

Higher

longterm

investment

instem

sand

sup-porttissues;H

ighercostin

water

nutrienttrans-port

”Hydraulic-lim

itationhypothesis”

;L

ower

investmentto

photosynthetictissue;L

ongertim

eto

reproductivem

aturity

Low

seedoutput,

hencefew

erpossible

propag-ules;L

owprobability

toreach

andem

ptypatch;

Longer

developingtim

es-

”cotyledonfunctional

morphology

hypothesis”;N

eedfor

specializeddispersers

i.e.Zoochory.

Benefits

Shortertim

esfor

returnin

photosynthetictissue

investment;

Higher

photosyntheticcapacity

andN

concentrationspergroftissue;Fasterturnover

ofplantpartsperm

itflexibleresponse

tothe

spa-tialpatchiness

oflightand

soilresources;Adap-

tationto

fastgrowing

situations

Com

petitiveadvantage

throughprior

accessto

light;Longerw

holeplantlife

spansL

argeseedlings;

Better

performance

underseedling

hazardsituations

(Defoliation,N

utrientw

aterdeficiency,Shading);Com

petitionfrom

es-tablished

vegetation;Greater

reservesrelative

tothe

autotrophicfunctioning

partsofthe

seedling

Low

traitvalues

Benefits

Longerm

eanresidence

time

ofnutrients,permit-

tinggrater

Nitrogen

sequestration;Adaptation

toslow

growing

situations;Low

ersusceptibilityand

costsfrom

damage

byherbivores;

Less

invest-m

entinquantitative

defensesubstances

(i.e.sec-ondary

metabolites)

Low

investment

instem

sand

supporttissues;

Low

ercost

inw

aternutrient

transport;H

igherinvestm

enttophotosynthetic

tissue;Shortertime

toreproductive

maturity

Large

seedoutput,hence

more

possiblepropag-

ules;High

probabilityto

reachand

empty

patch;Shorterdeveloping

times

-”cotyledonfunctional

morphology

hypothesis”;No

needforspecialized

dispersers;i.e.Anem

ochory-H

ydrochory.

Cost

Longer

times

forreturn

inphotosynthetic

tissueinvestm

ent;Low

erphotosyntheticcapacity

andN

concentrationsper

grof

tissue;Shorterturnover

ofplantparts

constrainsresponses

tothe

spatialpatchiness

oflightandsoilresources

Com

petitivedisadvantage

foraccess

tolight;

Shorterwhole

plantlifespans

Small

seedlings;H

ighseedling

mortality

underhazard

situations;Low

reservesrelative

tothe

au-totrophic

functioningparts

oftheseedling

Relevant

traittradeo

ffsSL

AV

sL

L;

SLA

Vs

Am

ass-Nm

ass;SL

AV

sPotR

GR

Hm

axV

s.rateof

heightgrow

th;

Hm

axV

s.Light

access;Hm

axV

s.ageto

firstreproductionSW

TV

sSeed

Output(Potentialto

occupya

va-cantpatch)


Cavender-Bares, Chapin, Cornelissen, Diemer, Flexas, Garnier, Groom, Gulias, Hikosaka,Lamont, Lee, Lee, Lusk, Midgley, Navas, Niinemets, Oleksyn, Osada, Poorter, Poot,Prior, Pyankov, Roumet, Thomas, Tjoelker, Veneklaas & Villar 2004), the seed mass–seed output trade–off (Leishman, Westoby & Jurado 1995, Leishman, Wright, Moles &Westoby 2000, Moles & Westoby 2006, Westoby et al. 2002) and plant height (Falster &Westoby 2003, Moles, Warton, Warman, Swenson, Laffan, Zanne, Pitman, Hemmings& Leishman 2009, Westoby et al. 2002). Each of these dimensions can be readily quan-tified by at least one of the associated characteristic traits: Specific leaf area for the leafeconomics spectrum, individual seed weight for the seed mass–seed output trade–off;and typical canopy height for the height dimension. These traits and the association withkey attributes within each dimension are discussed in Table 1.3.

It’s important to say, as Westoby (1998) points out, that the LHS scheme oper-ates on the assumption that ecological patterns reflect the balance between phenotypicdissimilarity between species and trait plasticity within species (The balance repre-sented in Fig. 1.5). Additionally, each of these dimensions is independent from eachother, so that species vary widely between species at any given level of the other two.An example of these is the independence of variation in seed mass with plant height(Leishman et al. 1995); or the weak correlation between SLA and SWT and Hmax

(Westoby et al. 2002, Westoby & Wright 2006).

1.6.1 Leaf economics

A leaf represents a resource investment per unit time by the plant (carbon, nitrogen,phosphorus, leaf respiration and of root and stem activity and energy). The cumulativereturn of this investment, over the lifespan of a leaf, is the evolutionary response tobalance the costs of producing a leaf (highly efficient but costly versus inefficient butcheap), the risk of it being damaged (due to aging, herbivory or any other source ofphysical damage) and the time taken to return the investment (leaf lifespan); with thereturns due to photosynthetic activity. A verbal formulation of this is that leaf lifespanneeds to be, at least long enough to either pay back or cover the initial investmentcosts (Niinemets 2001, Poorter 1994, Williams, Field & Mooney 1989) and longer ifthe investment is to result in growth (Westoby et al. 2002). This is of course a contextdepended process, so that in nutrient or stressful situations revenue accumulates moreslowly, while in areas with surplus of nutrients revenue builds up more rapidly.

The relations and trade–offs of four key features of leaves could be used to describethis leaf economics spectrum (although other traits can also be included). Specific leafarea, that measures the leaf area investment per unit of dry–mass; photosynthetic ca-pacity, that compiles measurements of photosynthetic assimilation rates; leaf nitrogencontent, that is an integral part of a plant photosynthetic machinery; and leaf lifespan,that describes the average duration of the leaf investment return. As shown by Wrightet al. (2004) and Reich et al. (1997) species with high SLA generally also have higherphotosynthetic capacity, leaf nitrogen content (as shown in Fig. 1.6A) and long leaf lifespans. Typically, species towards the high–SLA end of the spectrum are relatively fastgrowing and good light competitors, but tend also to be highly palatable to herbivores

1.6 Functional response traits and plant ecological strategies 17

SLA (cm2 x g-1)

Nitr

ogen

(g

x g-1

)

Seed Weight (mg)

Seed

Rai

n (N

o-yr x

m-2)

A

B

Trait A

Trai

t B

Not possible

Not competitiveor efficient

C

0.01

0.1

1

10

100

1000

10000

100000

0.01 0.1 1 10 100 100010000

0.1

1

10

100

1000

10 100 1000

0.1

1

10

1 10 100 1000

Figure 1.6 Bi–variant relation between pairs of correlated traits and the representation of thetrait envelope determined by the set of constraining costs limiting the range of trait variation. A)Relation between SLA and Leaf lifespan, data from Wright et al (2004); B) Relation betweenseed mass and seed number, data from Moles & Westoby (2006); and C) representation of thetrait envelope set by the containing costs on trait variation).

(Table 1.3). Herbs, grasses and deciduous trees tend towards the high–SLA end of thisspectrum, and evergreen shrubs and trees towards the low SLA end, but there is wideoverlap between growth forms.

1.6.2 Seed mass–Seed output

The trade off between the mass of an individual seed and the total number of seedproduced by a given species has been generally understood by ecologist as a trade off

between seed number and the probability of successful establishment. The logic behindthis assertion is that a plant with a fixed amount of resources available for reproductioncan produce either many small seeds or a few large seeds (as shown in Fig. 1.6B, anddiscussed by Henery & Westoby 2001). Species producing only a few larger number ofseeds will have and advantage when competing to occupy empty patches nearby (dis-cussed in Table 1.3), (e.g. Leishman et al. 2000, Moles & Westoby 2006). Species withmany small seeds on the other hands will have advantages in dispersing long distances.

These trade–offs also translate into future life cycle stages (Table 1.3). Seedlingsfrom large– seeded species generally have higher rates of survival than seedlings from


small–seeded species (Dalling & Hubbell 2002, Moles & Westoby 2004, Moles &Westoby 2006). This trade–off between the size (measured as seed weight in this dis-sertation) and survival of seeds/seedlings relates to the idea that better provisionedseedlings arise from large seeds, something that would give them and advantage un-der stress situations (water, light or carbon) imposed by extreme conditions, such asdrought, shade, and herbivory (Leishman et al. 2000). From this, individual seed weightcan be used as an index of a species’ position along the Seed mass–Seed output strategydimension emerging from the trade–off between the number, the size, and the survivalof seeds (Moles, Falster, Leishman & Westoby 2004, Moles & Westoby 2006, Westobyet al. 2002). This resembles the classic axis of r–K strategies (MacArthur & Wilson1967), where producing many small seeds generally improves dispersal distances (inthe case of wind dispersal) and promotes longevity in the seed bank; while producingfewer big seeds promotes establishment success in situations of low resource availabil-ity. Thus, small seeds may be beneficial in disturbed habitats where random juvenilemortality due to disturbance is high. That said, seedlings of smaller–seeded species tendto be outcompeted by those of larger–seeded species, under a variety of environmentalconditions (Leishman et al. 2000, Moles & Westoby 2006, Westoby et al. 2002).

1.6.3 Potential maximum canopy height

Height, contrary to the other ecological dimensions discussed above (SLA–N–Amax–LLor seed weight–seed output) reflects several implicit trade–offs by it self. Specifically,the upper limit on height, and the duration over which stems persist at their upper heightreflects the balance between totally separate costs and benefits; for example the time–trajectory and pace of height growth as well as the benefits of acquiring a particularheight. Nonetheless, these costs and benefits can not be easily elucidated by the useof independent traits (Falster & Westoby 2003, Westoby et al. 2002). This has resultedthe adoption of height as a default attribute in most comparative plant ecology studies(Bugmann 1996, Chapin, BretHarte, Hobbie & Zhong 1996, Grime 1998, Moles et al.2009, Weiher, van der Werf, Thompson, Roderick, Garnier & Eriksson 1999, Westoby1998, Wilson & Agnew 1992).

Height (as shown in Table 1.3) could then be considered to represent the outcomebetween benefits associated with greater light interception of taller plants, the costs ofreaching a taller statue, a greater investment in stem tissue, higher maintenance respira-tion costs of stem tissue, and a greater risk of breakage (Falster & Westoby 2003, Loehle2000, Weiher et al. 1999, Westoby et al. 2002). However, the benefit of reaching a givenstature in a community clearly depends on relative rather than on absolute height. Thismeans that the benefit of expressing a particular height cannot be understood by con-sidering a single realization in isolation, but rather evaluating it in the context of otherco–occurring species. The result of these trade–offs is that species with a wide range ofmaximum heights often co–occur at a site (e.g. in forest with gap–phase dynamics).

1.7 Limits to trait variation from biophysical costs 19

1.7 Limits to trait variation from biophysical costs

The trade–off within ecological dimensions are difficult to escape from. Due to this,any species can’t optimize all traits simultaneously, as a change in trait often impliesa change on several other within the same dimension. Said differently, a plant speciescan’t be a jack–of all traits, but just a master of some. For example, is inevitable thata plant species can not deploy a large light–capturing area per gram (high SLA) andalso build strongly reinforced leaves that may have long lives (Reich et al. 1997, Wrightet al. 2004); also they can not produce very large and heavily–provisioned seeds on eachreproductive event without producing fewer of them (Leishman et al. 1995, Leishmanet al. 2000, Moles & Westoby 2006); or can not reach the upper levels of the canopywithout incurring the expense of a tall stem, dense wood and xylem hydraulics limita-tions.

The fundamental idea explaining the existence of these fundamental trade–offs is thatfunctional traits do not evolve independently (Marks & Lechowicz 2006, Marks 2007).These evolutionary restrictions determine the optimization costs and biophysical con-strains (as enumerated in Table 1.3) generating the trade–offs describing each eco-logical dimension. These limits to trait variation are then reflected on what could beconsidered as a trait envelope enclosing the viable trait combinations of related traits(Fig. 1.6C). An example of this is the relation between SLA and leaf lifespan (Fig.1.6A). SLA gives a measurement of the investment per unit of area in structural tissueby the plant, whereas leaf lifespan represents the return time for a given investment inleaf tissue and photosynthetic machinery. In this sense, the relation between SLA andLL reflects the trade–offs in the investment return per gram of leaf tissue; where havinglow SLA values represent highly costly nutrient rich leafs (highly prone to herbivoryand the related costs on herbivory defences, Table 1.3) that need a long leaf lifespanto reimburse the investment in leaf tissue and photosynthetic machinery (increasing therisks of leaf investment). In this scenario, occurring on one a particular extreme of thetrait envelope is counterbalanced by a series of disadvantages represented in the limita-tions to trait variation of correlated traits.

A last point to address here is how the use of these ecological dimensions or traitsfundamental trade–offs could help the understanding of species introductions. The start-ing point is the idea that differences in functional response traits is what allows differentplant species to be more successful in different regions. Nonetheless, several traits, eachone representing an ecological dimension must be considered simultaneously to under-stand how a species responds to the environmental conditions on a site. This is becauseeach ecological dimension represents independent facets of an species niche (Violle &Jiang 2009). Then, by measuring differences or similarities between pairs of species(e.g. alien Vs. native or alien Vs. alien), or communities (e.g. Native range Vs. Alienrange, Native community pool Vs. introduced alien) in this multi trait space, it will bepossible to determine which ecological processes drive the coexistence of competitiveexclusion of native and alien plants.


1.8 Scale dependence of trait differentiation patterns

Ecological differentiation between co–occurring plants under natural conditions is be-lieved to be the result of a strategy segregation or ecological sorting’ between coexistingspecies using the same major resources (e.g. light, water, CO2, and mineral nutrients,Fig. 1.2). The result of this process is thought to be a community whose trait compo-sition reflects the best possible alternative designs which optimize the acquisition of re-sources, metabolism regulation, growth, survival and reproduction (Ackerly 2003, Diaz,Cabido & Casanoves 1998, Lavorel & Garnier 2002).

Based on this, an accurate comparison of life history traits related to key ecologicaldimensions, both individually (mean and variation of individual values) and in a com-munity context (how similar/ dissimilar are species belonging to a particular group),could indicate which factors allow a particular species to colonize and maintain viablepopulations once introduced. In the field of invasive biology, this approach would alsohelp in the understanding of what allows a particular alien species to be successful onceintroduced.

Two lines of thought concerning the role of similarity between natives and alienspecies have been generally considered in literature: The idea of limiting similarity(MacArthur & Levins 1967b) and the idea of habitat filtering (Cornwell, Schwilk &Ackerly 2006, Weiher & Keddy 2001). Both of these suggest that the success of analien species in establishing viable populations depends on how its traits match thenative community trait composition. Is clear that both of these alternative explana-tions are not mutually exclusive, and they act at different spatial and phylogenetic ex-tents (Fig. 1.7). For example, at small scales (Zone A , Fig. 1.7) aliens very sim-ilar to native species are less likely to coexist with native species because of com-petitive exclusion (Chesson 2000, Gause 1934) driven by limiting similarity. Mean-while, at larger scales (Zones B and C, Fig. 1.7), aliens are able to coexist with eco-logical and phylogenetically related natives due to neutral processes, dispersal limita-tion (Chesson 2000, Hubbell 2001) and habitat filtering (Weiher & Keddy 2001). Itis important to highlight, as shown by recent studies (Cadotte et al. 2009, Hamiltonet al. 2005, Kuhn & Klotz 2007, Pysek & Hulme 2005, Thuiller, Gallien, Boulangeat,de Bello, Munkemuller, Roquet & Lavergne 2010), that understanding the mechanismbehind successful aliens introduction is not possible by only focusing on processes at asingle scale.

Consequently, analyzing how (dis)similarity between aliens and natives in ecologicalattributes and/or phylogenetic spaces relates to the idea that explanations of patterns ofcoexistence should explicitly consider the effects of spatial [as proposed by Chesson(2000), Pysek & Hulme (2005) and Kuhn & Klotz (2007)] and phylogenetic [as pro-posed by Proches, Wilson, Richardson & Rejmanek (2008) and Thuiller et al. (2010)]scale. Phylogenetic scales indicate the level of relatedness between species, and couldbe used as a measure of (dis)similarity in ecological niches. Spatial scale may vary fromsmall scales at which species frequently interact and potentially compete (coexistence)to large spatial scales at which species only rarely interact because of dispersal limita-tions (co–occurrence). Combining these two factors would help determining to which

1.9 Outline of the dissertation 21

Zone DCompetitive

exclusion

Zone ANot able to

colonize

Zone CCo-occurrence

due to nice convergence

Zone CCo-occurrence

due to nice convergence or neutral dynamics

Phylogenetic similarity

Spat

ial s

cale

of t

he c

ontr

ast

Smal

lLa

rge

Similar Dissimilar

Figure 1.7 Predictions regarding coexistence or co–occurrence of native and aline speciesaccording to the spatial scale of study and the phylogenetic (or functional) similarity betweenintroduced alien species and the native species assemblage. Y-axis represents the spatial scale atwhich the native and aliens are compared; it ranges form small (e.g. neighborhood plot, orcommunity) to large (e.g. area, region or continent). X-axis shows the level of phylogeneticsimilarity/relatedness of the introduced species to the native species assemblage. Boxes in thefigure represent the areas where particular processes are hypothesized to be important for onegiven combination of spatial scale and phylogenetic relatedness. Figure based on Thuiller et al.(2010) with modifications.

extent the observe patterns of alien species occurrence result from a balance betweensmall–scale competitive exclusion (Zone D, Fig. 1.7) and large–scale co–occurrencedue to neutral dynamics or habitat suitability (Zone C and B, Fig. 1.7).

1.9 Outline of the dissertation

The aim of this dissertation is to evaluate the role of trait (dis)similarity in both the estab-lishment of viable populations of alien species, and its role in determining the resistanceor susceptibility of a community to introductions of non–native species. For this, eachof the studies that compose this dissertation focuses on key fictional response traits rep-resenting important axes of ecological variation. Specifically, this thesis addresses howalien–native and alien–alien patterns of trait (dis)similarity change across various func-tional, spatial, phylogenetic, environmental and disturbance gradients. This was doneusing a global scale, multi–species, target–area, and a native–alien or alien–alien com-parative approach. This allowed asking the following questions in a biogeographical


context: i) Can trait (dis)similarity between aliens and natives explain non–nativessuccess? and ii) are the observed (dis)similarity patterns a product of evolution?.

The premise of this dissertation is that scale (spatial and phylogenetic) dependentpatterns of trait (in uni– and multivariate spaces) convergence–divergence have the po-tential to provide a holistic framework for the prediction of successful introductions.The remaining chapters of this thesis address three specific dimensions affecting pat-terns trait (dis)similarity:

SPECIES PERSPECTIVE: PREDICTING SUCCESSFUL ALIENS FROM LIFEHISTORY CHARACTERISTICS

Invasion biology has searched extensively for traits that predict invasiveness, mostlyassuming that species express the same attributes in their native and alien range. InChapter 2, I address this assumption of trait conservatism by comparing, using a sourcearea approach, the level of trait convergence–divergence of alien species between theirnative and introduced, naturalized and invasive range.

Building from this, I explore in Chapter 3 if aliens are inherently ecologically differ-ent to the native species in the communities that they invade. For this, native and alienplant species were compared in three key traits (specific leaf area –SLA; average indi-vidual seed weight – SWT; typical maximum height of adults – Hmax) and their multi-dimensional trait composition. The main assumption of this chapter is that phenotypicdivergence (and thus of limiting similarity and empty niches) determines aliens success.

COMMUNITY PERSPECTIVE: BIOLOGICAL INVASIONS IN THE CONTEXTOF PLANT COMMUNITIES

By comparing the attributes of co–occurring native and alien species, researchershave tried to explain variation in introduction success, but meanwhile have given littleattention to the spatial scale at which comparisons are made. In Chapter 6, I evaluate,using a hierarchical spatially explicit framework, the effect of scale in the variability ofstandardized differences between co–occurring aliens and native plants. Specifically, inChapter 6 I ask if the patterns of trait (uni– and multivariate) similarity/dissimilarity be-tween co–occurring aliens and natives change across hierarchically nested ecologicallyrelevant scales.

An additional dimension of the community perspective is the question: What drivescommunity invisibility?. Several factors have been proposed to drive this, with re-source availability receiving special attention. Previous studies have suggested that highresource availability promotes invasions, because these conditions specifically allowaliens to outperform natives due to differences in key traits. In Chapter 5, I evaluate thisidea by exploring how trait differentiation between aliens and natives changes along

1.9 Outline of the dissertation 23

continuous resource availability (i.e. climatic and edaphic) and disturbance gradients.

EVOLUTIONARY PERSPECTIVE: IMPACT FOR PREDICTING SUCCESSFULALIENS

Two contrasting arguments have been proposed to explain the success of alien species:i) high relatedness to the native community is beneficial due to similar adaptations tothe environment; ii) low relatedness to the native community is beneficial due to lessniche overlap and less shared natural enemies. InChapter 6 these alternative argumentswere explored by determining if the phylogenetic community patterns of alien speciesin relation to co–occurring natives shows an over–dispersed (as predicted by Darwin’snaturalization hypotheses) or clustered structure (as predicted by phenotypic attractionhypothesis). For this, the relationship between trait evolution (conservative vs. conver-gent) and the patterns of trait similarity (clustered vs. over–dispersed) was evaluatedbetween alien and native species co–occurring within a community.

Both Darwin’s naturalization and the phenotypic attraction hypothesis explain thesuccess of alien species based on their degree of niche overlap with native species.Therefore, in order to predict and understand future invasions, we thus need to knowif ecological traits/requirements of aliens remain similar [niche conservatism (NC)] orchange [niche lability (NL)] in their novel habitat. In Chapter 7 three of the major top-ics concerning NC and its importance for understanding invasive plant species dynam-ics were reviewed. Specifically, the importance of ecological traits for NC, the idea ofbioclimatic niche conservatism in alien plants, and the prevalence of phylogenetic nicheconservatism in non–native species were reviewed and evaluated using a meta–analysis.

SYNTHESIS

The final chapter of this dissertation (Chapter 8), integrate the results of all chapters,and provide a synthesis of the ecological and evolutionary mechanisms generating theobserved patterns of trait (dis)similarity between alien and native species.

Part II

Species perspective:Predicting successful aliensfrom life historycharacteristics

2 Alien plants conserve their traitsbetween their native andintroduced rangeAlejandro Ordonez Gloriaab and Han Olffa

Abstract

Invasion biology has searched extensively for traits that predict invasiveness, mostly as-suming that species express the same attributes in their native and alien range. This traitconservatism assumption needs critical evaluation if we aim to predict which introducedspecies might become invasive.

Using a global database of three key plant functional traits (specific leaf area, max-imum canopy height and individual seed weight) we evaluated this assumption across129 different species. Traits of conspecifics showed no differences between their nativeand naturalized or invasive range. This pattern was consistent after controlling for en-vironmental conditions, the phylogenetic relation between analyzed clades, and whenviewed in multidimensional trait space.

Our results in uni– and multivariate trait spaces show for the first time that success-ful aliens conserve their attributes once introduced to a new area. We suggest that theobserved pattern of trait conservatism originates from core ecological, physiologicaland genetic constraints. Our conclusions are important because we show that i) aliensmaintain trait conservatism post–introduction and that ii) predicting and understandingbiological invasions can be effectively investigated by comparing species traits across alarge number of taxa and regions which is a promising approach for future studies onbiological invasions.


28 Alien plants conserve their traits between their native and introduced range

2.1 Introduction

An important aim in the study of invasions has been to predict which alien species arelikely to expand in a new geographic range (Rejmanek & Richardson 1996) and whichcommunities are more sensitive to be invaded (Olyarnik, Bracken, Byrnes, Hughes,Hultgren & Stachowicz 2009, Richardson & Pysek 2006). To achieve this, invasionbiologists have searched extensively for methods and indicators that could predict theinvasiveness of a species or the invasibility of a community. If successful, this wouldnot only contribute to the understanding of the mechanisms of biological invasions, butalso would support invasive species screening programs, and help targeting recentlynaturalized species before they become major problems.

An important assumption of both the species and community centered studies, asdone so far, is that species characteristics are on average constant within each species(that is the mean over all genetic and environmental variation in the native range); thusthey neither differ between the native and the initial alien range, nor do they changethroughout the invasion progress. Clearly, this assumption of trait conservatism (i.e.phenotypic similarities across space, time and phylogeny) needs critical assessment.

There are various a priori reasons of why trait conservatism between the native andalien ranges may not hold. For example, introductions may start from a few individu-als or genotypes (e.g. founder effects) that due to chance may not represent the aver-age trait values of the species in the native range (Wilson, Dormontt, Prentis, Lowe &Richardson 2009). Also, the new conditions encountered in the introduced range maylead to phenotypic adjustments due to plasticity beyond the mean or variation found inthe native range (Ackerly 2003). Additionally, during the expansion phase of invasions,traits may change due to selection pressures (Maron, Vila, Bommarco, Elmendorf &Beardsley 2004). As a result, the possibility that traits might change between the nativeand alien range should be considered in the process of determining and predicting aspecies invasiveness.

Evaluating the degree of alien trait conservatism is also important to understandwhich communities are most susceptible to invasions (Olyarnik et al. 2009). Specifi-cally, if traits were conserved between ranges, hypotheses that assume an alien is suc-cessful in areas with conditions similar to those of the native range would be supported(Daehler 2003). Alternatively, the variability in traits between the native and alien rangewould support those hypotheses where rapid evolutionary process (e.g. founder ef-fects or selection) enhances introduced range performance (Daehler 2003, van Kleunenet al. 2010).

Only few studies have yet addressed the question of whether traits of successful aliensare conserved between their native and alien ranges. Most of these are based on rel-atively small databases and compare only a limited number of species; using eitherqualitative vegetative traits (e.g. growth form, nitrogen fixing, taxonomic identity; as inBradshaw 1991, Thompson et al. 1995), or only compare reproductive traits (e.g. seedsize/number, germination rates, and seedling survival; as in Hierro, Eren, Khetsuriani,Diaconu, Torok, Montesinos, Andonian, Kikodze, Janoian, Villarreal, Estanga-Mollica& Callaway 2009, Mason, Cooke, Moles & Leishman 2008). This calls for a systematic

2.2 Methods 29

evaluation of trait shifts vs. conservatism between the native and alien range of success-ful aliens at large biogeographical scales, across many species including both vegetativeand reproductive traits.

In this study we report the results from a global–scale meta–analysis aiming to quan-titatively examine changes (in uni– and multivariate spaces) on traits of conspecificsbetween their native and alien ranges. In total, our database contains 129 alien speciesfor which at least one trait was measured in both ranges. It includes species from 56plant families and covers all continents and major biomes of the world. The species in-cluded represent a range of growth forms and lineages: 116 dicot species, 8 monocots,3 Gymnosperms, and 2 Pteridophytes (ferns and fern allies). To our knowledge thiswork is the largest and most exhaustive comparison of quantitative eco–morphologicalattributes of conspecifics between their native and introduced ranges. Additionally, theuse of different alien species allowed us to extrapolate our results beyond a single aliencategory which is a much needed improvement from most works on invasion biologythat often focus only on the most spectacular plant invaders.

2.2 Methods

2.2.1 Database compilation and trait selection

Publications and online databases were located through keyword searches for referencesin Web of Science, examination of the references in these citations, and direct commu-nication with researchers. Full details of the database building process are given asAppendix A. Plant status was defined, following the definitions of Richardson, Pysek,Rejmanek, Barbour, Panetta & West (2000), as native, alien (species intentionally oraccidentally introduced as a result of human activity), naturalized (aliens that sustain vi-able populations without direct intervention by humans) or invasive (naturalized speciesthat produce large numbers of reproductively viable offspring at considerable distancesfrom parent plants).

We focused on three traits: specific leaf area (SLA in cm2 × g−−1), maximum plantheight (Hmax in m) and individual seed weight (SWT in mg). The SLA of a plantexpresses how much light capturing area it produces with each gram of leaf tissue.The SLA is negatively correlated with leaf thickness, lifespan and toughness and pos-itively correlated with mass–based measurements of leaf nitrogen content, photosyn-thetic capacity, relative growth rate, and palatability to herbivores, all of which arerelevant in plant performance (Wright et al. 2004). The Hmax is the simplest measureof stature and represents the balance between the gains from access to light, and thecosts of structural support (given the disturbance regime) and water transport (Falster& Westoby 2003). Last, SWT of a plant represents the balance between the numberand size of offspring, which is often related to the age–dependent survival probability(Moles & Westoby 2006). SWT is often negatively correlated to dispersal distance (inthe case of wind–dispersed species) and positively correlated to seedling survival prob-ability under harsh (e.g. light– or water–limited) conditions (Moles & Westoby 2006).


SLA, Hmax and SWT represent proxies for the position of a species along three inde-pendent ecological strategy–dimensions underpinned by various optimization trade–offs(Westoby et al. 2002). For instance, metrics of SLA, Hmax and SWT differentiate plantsthat invest heavily in structural support and high seedling survival (k–selected) fromthose that invest in high seed output with little energy investment in structural support(r–selected). Typically there is little correlation between SLA, Hmax and SWT amongco–occurring species and more correlation with in species. Therefore, comparisons ofSLA, Hmax and SWT between conspecifics in native versus alien ranges allowed us todetermine the magnitude of trait conservatism. We do not assert that the the used traitsare by any means the only and best traits to assess this question; they rather are a easilyaccessible subset of all possible traits adequate for this type of analysis.

The compiled database includes data for 129 different known successful alien specieswith trait information on both their native and alien ranges for at least one of thesethree traits; 55 species have information for at least two traits, and 24 species have dataon all three traits from both ranges. As traits were measured in most cases in morethan one locality on either the native or alien region (between 1 to 6 alien, and 1 to8 native communities), conspecifics were summarized as species–range–trait combina-tions. Summarizing the trait information in this way allowed us to statistically detect thebetween–ranges variation while accounting for the within–range variability.

2.2.2 Single trait comparisons

Trait conservatism of conspecifics between their native and introduced range was eval-uated using two different approaches: a mixed model linear regression framework andlog–response ratios. This allowed us to test the robustness in the observed similar-ity/dissimilarity trends.

Mixed models regressed trait values in the introduced range (alien, naturalized or in-vasive) against those in the native range, using species as a random effect. Data was nor-malized using a log10 transformation as each of the three focal traits showed a stronglyright–skewed distribution (ca. lognormal). Using log–log regressions means that the lin-earity of a proportional change in x was tested against a proportional change in y, insteadof absolute changes. Also, the slopes resulting from these regressions are scale free, andthus absolute values are compared among traits.

Regression coefficients were evaluated for two hypotheses representing either traitconservation or lability. Specifically, if traits are conserved between alien and nativeranges we expect the intercepts not to be significantly different from zero (i.e. no sig-nificant mean differentiation between ranges) and slopes not to differ from one (i.e. nochanges in the level of differentiation of a trait along the evaluated range). Alternatively,if traits are labile between ranges, we expect the intercepts to differ from zero and/or theslopes to differ from one.

As the outcomes of the regression models might be influenced by environmentalvariability or the phylogenetic relatedness, we also built regressions models that con-trolled for these factors. The effect of environmental variability was assessed using amixed effect linear mixed model where observations were grouped based on Holdridge’s

2.2 Methods 31

life–zones (e.g. a representation of broadly similar environmental-vegetation conditionsHoldridge, Grenke, Hatheway, Liang & Tosi Jr 1971) and compared using the log10–traitvalue as response variable, native/alien range as a fixed factor and species and life–zones(nested within species) as random effects. This spatial stratification was necessary sincetarget species could occur in multiple life–zones.

The influence of phylogenetic relatedness was accounted for by using the method ofphylogenetic generalized least squares – PGLS (Rohlf 2001) with a Brownian motionmodel of evolution to derive a covariance matrix. This analysis explores if potential dif-ferences in traits between the native and invasive range of species are highly aggregatedwithin certain taxonomic lineages. The phylogenetic trees were constructed using PHY-LOMATIC (Webb & Donoghue 2005) and the APG3 derived megatree R20091110 asa backbone. This tree is a strict consensus phylogeny for plants using the complete res-olution determined by the APweb (Stevens 2009). Details about the construction of theused super–tree is presented in Appendix A.

Log–response ratios were used as a measure of standardized difference in trait valuesof conspecifics between its native and introduced range. This measurement of effect sizequantifies the proportional difference in alien range relative to the native range, there-fore controlling for those differences introduced by other covariates (e.g. growth form,habitat type, life–zone or metric). The sign of the mean log–response ratio indicates thedirectional pattern of between–range differentiation (positive indicates alien range traitsare larger than native range traits while negative indicates alien range traits are smallerthan native range traits). All calculations followed Hedges, Gurevitch & Curtis (1999)formulation of mean log–response ratio and variance. Effect sizes were considered sig-nificant when 95% confidence intervals (CIs) did not overlap zero.

To examine heterogeneity among the three evaluated alien rank classes, the QB statis-tic (Hedges et al. 1999) was used to test the null hypothesis of common effect size versusdiffering effect size. The QB statistic has a χ2 distribution with degrees of freedom equalto one less than the number of classes. When QB was significant (p < 0.05) the meansof the log–response ratios for each class were examined independently.

2.2.3 Comparisons between ranges in multidimensional trait space

As traits are measured in different scales, multivariate between–ranges differences wereevaluated using standardized (mean = 0, and SD = 1) log10 transformed traits. Standard-izations were done using a global weighting procedure in which each trait was scaledrelative to a global mean and variance that was derived from a larger database withglobal coverage (as suggested by Cornwell et al. 2006). The advantage of this approachis that the standard deviation of a particular trait is equivalent worldwide.

Shifts in multidimensional trait space between native and alien species were evalu-ated using a set of 24 known alien species (14 naturalized, 10 invasive) that had informa-tion for SLA, Hmax and SWT, for both the native and introduced ranges. Between–rangedifferences in traits were evaluated using a non–parametric multivariate analysis of vari-ance – PERMANOVA (McArdle & Anderson 2001). This method simultaneously teststhe differences on multiple response variables due to factorial predictors in an ANOVA–


like fashion, on the basis of a multivariate distance measure (where we used Euclideandistance) and uses permutation methods to determine p–values. This approach is pre-ferred to a MANOVA as the used data violated the assumptions of multivariate normal-ity and homogeneity of covariance matrices (Sokal & Rohlf 1995).

To evaluate the differences in traits between ranges, a two–way crossed (orthogonal)design with species identity and range (native or alien/naturalized/invasive) as factorswas implemented. Specifically, we tested for significant differences in the species ×range interaction. To evaluate the effect of environmental conditions, comparisons weredone by restricting the randomizations to specific Holdridge’ life–zones.

2.3 Results

2.3.1 Single trait comparisons

Compared over all species, conspecifics showed a generalized tendency towards a 20%lower specific leaf area, a 3% taller statue and 9% smaller seeds in their alien region.Only SLA native vs. alien regressions (Table 2.1) showed marginally significant differ-ences between ranges (e.g. intercepts differed from zero and regression slopes differedfrom one). These trends were consistent for contrasts controlling for Holdridge’s life–zones (Table 2.1). Decomposing the variance of these models revealed an unbalancedfactor loading for all traits, with the species level contributing the most to the between–range differences (SLA 42.2%, Hmax 92.8% and SWT 99.8%). In the case of modelscontrolling for life–zone, this factor had only a marginal influence on the decomposi-tion of the variance (between 3 and 5%) while species level had the highest varianceloads (between 30 and 100%). Both of these results suggest that most of the variationin traits is observed between species and not between ranges or life–zones.

Evaluated traits were consistently similar between native–naturalized and native–invasive comparisons, even after controlling for life–zone (Table 2.1). Of the analyzedtraits, only SLA native–naturalized comparisons showed marginally significant differ-ences from the trait conservation hypothesis (i.e. intercept differs from zero and slopeis less than one). Variance decomposition analysis indicated that species provided thelargest loading to the between–range variability (10–100% for native–invasive and 47–100% for native–naturalized comparisons). In the case of life zone controlled compar-isons, a balanced distribution of variance across species and life–zones was observed,indicating that the variation in traits is due to habitat and species differences and not dueto between range dissimilarity.

Given that eco–morphological traits ( such as SLA, Hmax and SWT) are knownto strongly vary between growth forms, between–ranges differences were also evalu-ated within each group independently (e.g. woody and non woody species, Table 2.2).Woody (shrubs and trees) and non–woody species (graminoids and herbs/forbs) showeddivergent between–range patterns. From the analyzed traits, only SLA and Hmax ofwoody species were significantly different between the native and introduced ranges.

2.3 Results 33

Table 2.1 Regression coefficients from mixed–effect models (All species and Life–Zonecontrolled contrasts) and PGLS (phylogenetic least squares regressions for phylogeneticallycontrolled contrasts) comparing conspecifics trait values between their native andalien/naturalized/invasive range. Evaluated traits are specific leaf area (SLA – cm2 × g−1),maximum canopy height (Hmax – m) and individual seed size (SWT – mg). Contrast criteriaare All species, Life-Zone controlled, and Phylogenetic controlled.

Contrast criteria Compared ranges Trait N Intercept Slope R2

[95%CI] [95%CI]

SLA 67 1.06 [0.63 1.49] 0.48 [0.28 0.67] 0.996Native Vs. Alien Hmax 103 0.04 [-0.03 0.11] 0.94 [0.86 1.02] 0.998

SWT 146 0 [-0.01 0.01] 1 [0.99 1] 1SLA 51 0.95 [0.44 1.46] 0.52 [0.29 0.74] 0.996

All species Native Vs. Naturalized Hmax 81 0.04 [-0.02 0.1] 0.99 [0.92 1.06] 0.999SWT 121 0 [-0.02 0.01] 1 [0.99 1] 1SLA 18 1.36 [0.44 2.27] 0.36 [-0.05 0.78] 0.997

Native Vs. Invasive Hmax 27 0 [-0.18 0.17] 0.79 [0.57 1.01] 0.996SWT 30 0.01 [-0.01 0.03] 1 [0.99 1.02] 1

SLA 16 0.36 [-0.83 1.55] 0.8 [0.27 1.32] 0.999Native Vs. Alien Hmax 26 0.05 [-0.07 0.17] 0.92 [0.79 1.05] 1

SWT 43 0 [-0.01 0.01] 1 [1 1.01] 1SLA 12 0.39 [-0.97 1.75] 0.79 [0.19 1.39] 0.999

Life-Zone cont. Native Vs. Naturalized Hmax 23 0.01 [-0.12 0.15] 0.94 [0.8 1.07] 1SWT 38 0 [-0.01 0.01] 1 [1 1.01] 1SLA 5 -0.5 [-6.94 5.95] 1.12 [-1.69 3.92] 0.999

Native Vs. Invasive Hmax 4 0.22 [0.03 0.41] 0.95 [0.71 1.18] 1SWT 6 -0.01 [-0.02 0.01] 1 [0.99 1.01] 1

SLA 66 1.28 [0.8 1.75] 0.39 [0.22 0.56] 0.272Native Vs. Alien Hmax 98 0.01 [-0.41 0.43] 0.77 [0.66 0.88] 0.831

SWT 143 -0.01 [-0.09 0.06] 1 [0.99 1.01] 0.998SLA 51 1.19 [0.61 1.78] 0.42 [0.2 0.64] 0.286

Phylogentic cont. Native Vs. Naturalized Hmax 77 0.08 [-0.26 0.41] 0.87 [0.77 0.97] 0.907SWT 119 -0.02 [-0.1 0.06] 1 [0.99 1.01] 0.998SLA 17 1.04 [-0.3 2.38] 0.5 [-0.07 1.07] 0.133

Native Vs. Invasive Hmax 25 -0.1 [-0.62 0.41] 0.72 [0.44 1.01] 0.576SWT 28 0.01 [-0.06 0.08] 1 [0.98 1.01] 0.999

The same trend in trait differences was observed for native–invasive and native–naturalizedcomparisons.

When differences between the native and alien traits were tested within clades using aPGLS and log10 transformed traits (Table 2.1), only SLA showed significant differencesbetween ranges (i.e. intercept differed from zero and slope was less than one). Thistendency was confirmed even after accounting for differences between native and aliengrowth forms (Table 2.2).

Comparisons based on log–response ratios, showed that that plants introduced intonew ranges had lower SLA (68% of cases), higher Hmax (47% of cases) and smaller

Table2.2

Regression

coefficientsfrom

mixed-effectm

odels(A

llspecies)andP

GLS

(phylogeneticleastsquares

regressions–

forphylogeneticallycontrolled

contrasts)forspeciesofa

particulargrowth

forms.

Contrastcriteria

Com

paredranges

TraitW

oddyN

on–Woddy

NIntercept

SlopeR

2N

InterceptSlope

R2

[95%C

I][95%

CI]

[95%C

I][95%

CI]

Allspecies

Native

Vs.A

lienSL

A45

1.09[0.67

1.52]0.44

[0.240.64]

0.99620

2.26[0.72

3.8]0.02

[-0.610.65]

1H

max

590.15

[0.040.26]

0.9[0.8

1.01]0.998

39-0.14

[-0.27-0.01]

0.58[0.29

0.87]0.996

SWT

990

[-0.020.02]

1[0.99

1.01]1

390.01

[-0.010.02]

1.01[0.99

1.04]1

Native

Vs.N

aturalizedSL

A38

0.92[0.42

1.41]0.52

[0.290.75]

0.99613

2.52[0.34

4.69]-0.09

[-0.970.79]

1H

max

490.11

[-0.020.24]

0.95[0.84

1.07]0.998

29-0.19

[-0.33-0.05]

0.44[0.11

0.76]0.997

SWT

870

[-0.030.02]

1[0.98

1.01]1

280

[-0.010.02]

1.01[0.99

1.04]1

Native

Vs.Invasive

SLA

81.92

[0.653.19]

0.03[-0.59

0.65]1

80.87

[-1.393.13]

0.6[-0.34

1.55]0.997

Hm

ax12

0.28[0.05

0.52]0.73

[0.490.96]

0.99713

-0.02[-0.27

0.23]1.01

[0.361.67]

0.996SW

T15

0.01[-0.03

0.04]1.01

[0.981.03]

113

0.02[-0.02

0.06]1.01

[0.951.08]

1

Phylogenticcontrolled

Native

Vs.A

lienSL

A44

1.18[0.7

1.65]0.42

[0.230.6]

0.32920

1.17[-0.03

2.37]0.46

[-0.010.92]

0H

max

560.29

[-0.160.74]

0.79[0.64

0.93]0.822

37-0.15

[-0.60.29]

0.64[0.42

0.87]0.322

SWT

96-0.02

[-0.110.07]

1[0.99

1.01]0.998

390

[-0.080.09]

1.01[0.98

1.04]0.994

Native

Vs.N

aturalizedSL

A38

1.21[0.61

1.81]0.4

[0.170.63]

0.35313

0.9[-0.91

2.71]0.55

[-0.161.26]

0.004H

max

470.29

[-0.150.74]

0.79[0.63

0.95]0.845

27-0.16

[-0.50.19]

0.64[0.34

0.95]0.239

SWT

85-0.02

[-0.120.08]

1[0.98

1.01]0.997

280

[-0.070.07]

1[0.97

1.03]0.997

Native

Vs.Invasive

SLA

72.04

[-0.824.89]

-0.05[-1.38

1.28]0.004

80.53

[-1.252.3]

0.75[0.01

1.48]0.206

Hm

ax10

0.31[-0.12

0.75]0.68

[0.291.07]

0.70113

0.35[-0.13

0.83]1.97

[1.292.65]

0.457SW

T13

0[-0.01

0.01]1

[11]

113

0.02[-0.09

0.13]1.01

[0.941.08]

0.988

2.3 Results 35

●

●●

●

●

●

● ●

●

−0.

6−

0.4

−0.

20.

00.

20.

4

Log−

resp

onse

rat

io (

±95%

C.I)

SLA Hmax SWT SLA Hmax SWT SLA Hmax SWT

Native Vs. Alien Native Vs. Naturalized Native Vs. Invasive

Figure 2.1 Weighted mean logresponse ratios for conspecificsnative vs. alien/naturalized/invasiverange comparisons. Evaluated traitsare specific leaf area (SLA –cm2 × g1), maximum canopy height(Hmax – m) and individual seed size(SWT – mg). Logresponse ratioscalculations followed Hedges et al.(1999) formulation of meanlogresponse ratio and variance. Theeffect size is considered significant ifthe 95% condence interval does notoverlap zero. From left to right, thenumbers of records in each categorywere: 67, 103, 146, 51, 81, 121, 18,27 and 30.

SWT (18% of cases) when compared with those in the native range. Between ranges dif-ferences were significant for SLA and Hmax but not SWT (see 95% CI of log–responseratios in Fig. 2.1). Similar comparisons between native–naturalized, and native–invasiveshowed that conspecifics did not differ in SLA, Hmax or SWT between ranges (i.e. the95% CI around the mean log–response ratio overlapped zero, Fig. 2.1).

When growth form was controlled for, native–alien comparisons showed the samebetween–range similarity patterns as the complete database (Fig. 2.2). In both groups, alower SLA (69 and 70% of woody and non-woody cases respectively), higher Hmax (48and 49 % of woody and non-woody cases) and smaller SWT (11 and 36% of woodyand non-woody cases) was observed in the alien range compared to the native range;however 95%CI around the mean log–response ratio overlapped zero for Hmax of non–woody species and the SWT of woody plants. For woody and non–woody plants, com-parisons between the native–naturalized or native–invasive ranges showed different ten-dencies. The results comparing traits in native versus invasive ranges show that no traitswere significantly different between ranges (i.e. log–response ratios 95% CI overlappedzero in all cases). The log–response ratio for woody plants in the native versus natural-ized comparison was significantly positive for SLA and Hmax. Comparisons of woodyand non–woody conspecifics between native and naturalized ranges show that no traitswere significantly different between ranges (i.e. log–response ratios 95% CI overlappedzero in all cases).

There was a significant amount of heterogeneity observed between the different rangesacross the three classes of invasive ranking (SLA: Q(2) = 0.013, p < 0.01; Hmax:Q(2) = 0.063, p < 0.05; SWT: Q(2) = 0.064, p < 0.05). This heterogeneity is mainlydriven by the native–alien comparison; the differences between native and naturalized


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Native Vs. Alien Native Vs. Naturalized Native Vs. Invasive

Figure 2.2 Weightedmean log response ratiofor particular growthforms (Non–woody:graminoids andherbs/forbs; and Woody:shrubs and trees)contrasting conspecicsbetween their native andalien, naturalized orinvasive range.

or invasive plants were homogeneous (SLA: Q(1) = 0.013N.S .; Hmax: Q(1) = 0.063N.S .;SWT: Q(1) = 0.05N.S .).

2.3.2 Multivariate comparisons

The PERMANOVA comparison of alien species’ traits between native and alien rangesdid not show between–range differences (Table 2.3). The same pattern of differentiationwas observed for both native–naturalized and native–invasive comparisons (Table 2.3).Similarly, comparisons of individual growth forms between ranges showed no multi-variate differentiation for either native–alien, native–naturalized or native–invasive con-trasts (Table 2.4). Comparisons controlling for life–zones showed no differences be-tween ranges for either native–alien, native–naturalized or native–invasive comparisons(Table 2.3).

2.4 Discussion 37

Table 2.3 Conspecific PERMANOVA (F statistic and P value) based on Euclidean distancesfor the trait composition of conspecifics between its native and introduced (alien/naturalizedor invasive) range. Traits were log10 and globally standardized prior to analysis. P-values aregenerated by permutation of the raw data. Significance levels (differences to zero), aremarked with asterisks as follows: ∗p < 0.05, ∗ ∗ p < 0.01, ∗ ∗ ∗p < 0.001, and N.S.No-Significant.

Compared ranges Source F-test

Species F(40,180) = 11.28 ***Native Vs. Alien Range F(1,180) = 3.41 *

Species:Range F(40,180) = 1.23 N.S.

Species F(12,47) = 13.37 ***Native Vs. Naturalized Range F(1,47) = 0.31 N.S.


Species F(5,25) = 3.78 ***Native Vs. Invasive Range F(1,25) = 0.2 N.S.


Table 2.4 Within growth from PERMANOVAs (F statistic and P value) based on Euclideandistances for the trait composition of species between its native and introduced(alien/naturalized or invasive) range. Traits were log10 and globally standardized prior toanalysis. Significance levels as in Table 2.3.

Compared ranges Source Woody Non-Woody

Species F(20,91) = 1090.63 *** F(17,80) = 2.36 *Native Vs. Alien Range F(1,91) = 13.51 *** F(1,80) = 2.7 N.S.

Species:Range F(20,91) = 2.84 * F(17,80) = 1.02 N.S.

Species F(5,24) = 6.53 *** F(6,23) = 1.71 N.S.Native Vs. Naturalized Range F(1,24) = 2.88 N.S. F(1,23) = 0.08 N.S.

Species:Range F(5,24) = 1.2 N.S. F(6,23) = 0.43 N.S.

Species Not Calculated F(3,18) = 1.96 N.S.Native Vs. Invasive Range Not Calculated F(1,18) = 0.83 N.S.

Species:Range Not Calculated F(3,18) = 0.14 N.S.

2.4 Discussion

Our results in uni– and multivariate trait spaces show for the first time that success-ful aliens conserve their attributes once introduced to a new area. Trait conservationbetween native and introduced ranges was supported by (i) consistently similar resultsin both uni– and multidimensional analyses, (ii), log–response ratios overlapping zeroindicating no net difference in traits between ranges, and (iii) the isometric relationof traits between their native and alien, naturalized and invasive ranges, indicating thattraits are conserved along the trait spectrum. Furthermore, (iv) univariate similarities for


all species regardless of growth form and environmental conditions show similar traitmakeup between ranges. Overall, the results consistently support the trait conservationhypothesis and not the trait lability hypothesis.

Controlled comparisons indicated that traits are consistently conserved between rangeseven after accounting for the variation in environmental conditions in each range, thedisproportional representation of clades in the dataset, or particular groups showinglarge similarities between ranges. Rather, the observed between–range similarities ap-pear to occur generally across habitat types and unrelated species. Additionally, analy-sis of phylogenetically controlled regression coefficients indicated that SLA, Hmax andSWT are consistently conserved in the alien, naturalized or invasive range, supportingthe trait conservation hypothesis.

Several studies in the field of plant functional ecology have provided evidence forthe conservation of traits and proposed possible mechanisms explaining how this mightoccur (Ackerly 2009, Holt & Gaines 1992). In all these studies, trait conservation hasbeen explained as the result of either or a combination of three distinct alternative pro-cesses: habitat filtering (Kraft, Cornwell, Webb & Ackerly 2007), stabilizing selection(Ackerly 2009) and/or niche conservatism (Pearman, Guisan, Broennimann & Randin2008, Wiens, Ackerly, Allen, Anacker, Buckley, Cornell, Damschen, Jonathan Davies,Grytnes, Harrison, Hawkins, Holt, McCain & Stephens 2010). These three processes se-lect for the most adequate realizations of key traits (e.g. physiological and eco–morphological),therefore shaping the distribution of a species. Evidence of the conservation of corephysiological attributes comes from the stasis of traits across phylogenies (Ackerly &Reich 1999, Swenson & Enquist 2007), the similarity of traits of closely related co–occurring species (Knight & Ackerly 2001, Pearse & Hipp 2009), and the correlationof a species ecology with its biogeographic history (Knight & Ackerly 2001, Lord,Westoby & Leishman 1995). Building from this, it seems logical that the same processshould hold in the case of alien species, resulting in the conservation of traits betweenthe native and alien ranges.

Although the reported patterns suggest that alien species traits are consistently con-served across ranges, we do not mean to imply that aliens do not have the potentialto phenotypically or genetically adapt to conditions they encounter in their new habi-tat. We believe that conservation or lability of traits is the result of the balance be-tween long–term evolutionary inertia for the conservation of traits (e.g. core physi-ological and genetic constrains which shape the fundamental niche, as presented inAckerly 2003, Grime 2006, Webb, Ackerly, Mcpeek & Donoghue 2002) and short–term adaptation to biotic interactions and environmental stochasticity that favors traitvariation (i.e. phenotypic plasticity Ackerly 2003, Cavender-Bares, Ackerly, Baum &Bazzaz 2004). In other words, those traits that have been shown to be highly conservedover evolutionary time (e.g. wood density, seed mass, SLA, leaf life span) will be moreconserved across ranges than those that are highly influenced by biotic, ecological or en-vironmental gradients (e.g. canopy transpiration, rhizome re–sprouting, height, relativegrowth rate).

Additionally, our results do not suggest that between–range differences in the ana-lyzed traits are not possible or a likely outcome of introductions. Instead, we argue that

2.4 Discussion 39

that between–range differences will only emerge after sufficient evolutionary time haspassed which would allow the release from short–term biotic constraints (Levine, Adler& Yelenik 2004) or micro–evolutionary processes (Ackerly 2003, Pearman et al. 2008).However, given the limitations in our database, we are unable to determine the tempo-ral dimension of these patterns, as we have no information on how long the evaluatedaliens have occupied the new ranges. Further work is needed to evaluate trait shifts ofco–occurring species in native and novel ranges, as well as large–scale genetic screeningto differentiate populations.

Overall, the results presented in this work have clear implications in the predictionof successful aliens. Specifically, the observed conservation of traits between rangessupport hypotheses based on phenotypic attraction, where an alien is assumed to besuccessful in areas with environmental conditions similar to those in the native range(Daehler 2003, Thuiller, Richardson, Pysek, Midgley, Hughes & Rouget 2005).

Our results are of particular relevance for predictive frameworks aiming to identifypossibly invasive species. These frameworks use the behavior of a species in its na-tive range as a surrogate for how it will behave in the novel range in order to assessthe potential risk of invasiveness (Daehler & Carino 2000). Specifically, our results areextremely pertinent for modeling studies because they justify using a species’ native–range attributes to calibrate models of invasion (such as Rejmanek & Richardson (1996)discriminant analysis Z–scores). Accurate models are required to minimize the risk ofunnecessarily rejecting or unjustifiably accepting an introduction given the high costof missed economic opportunities and potential ecological damages. Our results em-pirically answer critical assumptions of invasion models by showing that attributes of aspecies in the native range are valid and useful proxies for how they will behave in novelranges which increases the accuracy of models screening for possibly invasive species.

In summary, the patterns reported in this work have important implications for thedevelopment of future predictive frameworks of species invasions. We suggest that theobserved pattern of trait conservatism originates from core ecological, physiological andgenetic constrains. This would have major impact in limiting or enhancing the successof an alien after being introduced to a new habitat.

3 Functional differences betweennative and alien species: aglobal–scale comparisonAlejandro Ordonez Gloriaac, Ian J. Wrightb and Han Olffa

Abstract

A prevalent question in the study of plant invasions has been whether or not invasionscan be explained on the basis of traits. Despite many attempts, a synthetic view ofmulti–trait differences between alien and native species is not yet available.

We compiled a database of three ecologically important traits (specific leaf area, typ-ical maximum canopy height, individual seed mass) for 4473 species sampled over 95communities (3784 species measured in their native range, 689 species in their intro-duced range, 207 in both ranges).

Considering each trait separately, co–occurring native and alien species significantlydiffered in their traits. These differences, although modest, were expressed in a com-bined 15% higher specific leaf area, 16% lower canopy height and 26% smaller seeds.

Using three novel multi–trait metrics of functional diversity, aliens showed signifi-cantly smaller trait ranges, larger divergences and a consistent differentiation from themedian trait combination of co–occurring natives.

We conclude that the simultaneous evaluation of multiple traits is an important noveldirection in understanding invasion success. Our results support the phenotypic diver-gence hypothesis that predicts functional trait differences contribute to the success ofalien species.

a Community and Conservation Ecology Group, University of Groningenb Department of Biological Sciences, Macquarie Universityc Correspondence author. E–mail: [email protected]

3.1 Introduction 41

3.1 Introduction

The introduction of alien plant species ranks high among major global biodiversitythreats. As a result, the ability to predict which species are likely to be successful in-vaders and have large impacts when introduced has become a priority for conservationefforts. Although many studies have quantified the extent to which native and alienspecies differ in their main characteristic traits, attempts to draw generalizations acrossthese studies have met limited success (Daehler 2003, Pysek & Richardson 2007).

In essence, two alternative approaches have been used to characterize the traits of atypical successful introduced species: i) to compare pairs of native and alien congeners,confamilials, and otherwise taxonomically and/or phylogenetically related species, ir-respective of the communities in which these occur (Burns & Winn 2006, Vila &D’Antonio 1998, Funk & Vitousek 2007, Gerlach & Rice 2003, Grotkopp, Rejmanek &Rost 2002, McDowell 2002, van Kleunen et al. 2010); or ii) multi–species approachesbased on comparisons of whole floras (Crawley et al. 1996, Hamilton et al. 2005, Lake& Leishman 2004, Lambdon et al. 2008, Thompson et al. 1995). Both approaches aim toidentify recurring trait differences between the two groups. Although most efforts haveused the first alternative (i.e., pair–wise comparisons), the best progress to date towardsa general screening system of possible invasive plants has been achieved by poolingevidence from both approaches (Grotkopp et al. 2002, Pysek & Richardson 2007, Rej-manek & Richardson 1996, Rejmanek et al. 2005, Richardson & Rejmanek 2004).

From these comparisons, two alternative hypotheses have emerged as explanationsto the success of alien species. First, several authors have argued that greater pheno-typic difference to natives increases the probability of success of an alien (Dukes 2001,Hamilton et al. 2005, Lake & Leishman 2004, Lambdon et al. 2008, Naeem, Knops,Tilman, Howe, Kennedy & Gale 2000, Pokorny, Sheley, Zabinski, Engel, Svejcar &Borkowski 2005, van Kleunen et al. 2010). This idea, ”phenotypic divergence”, is basedon the concept of limiting similarity (Abrams 1983, Hutchinson 1959, MacArthur &Levins 1967b) and proposes that an introduced species will be more successful in acommunity that lacks species that are ecologically similar to it.

Alternatively, others have argued that the opposite tendency is true. That is, the moresimilar the traits of an alien are to those of the native community, the more likely it is tosucceed in the introduced range – as the better it will be adapted to the local conditions(Daehler 2003, Prieur-Richard, Lavorel, Linhart & Dos Santos 2002, Smith & Knapp2001). This idea, ”phenotypic convergence”, is based on the concept of habitat filteringmechanisms (e.g. due to dispersal, stress and competition), which can be thought asreducing the range of successful strategies observed among coexisting species (Keddy1992, Weiher, Clarke & Keddy 1998). In theory, both of these mechanisms could operatesimultaneously in a given community, influencing one or more traits simultaneously.Both mechanisms share the idea that the success of an alien species relies on how itstraits match with those of co–occurring native species.

To date, most work considering this problem has focused on combinations of thepresence/absence of certain traits (Bradshaw, Giam, Tan, Brook & Sodhi 2008, Lamb-don et al. 2008), while quantitative traits are typically considered one at a time (Funk &

42 Functional differences between native and alien species

Vitousek (2007), Hamilton, Holzapfel & Mahall (1999), Lake & Leishman (2004) andvan Kleunen et al. (2010); but see Leishman, Haslehurst, Ares & Baruch (2007) andLeishman et al. (2010) for efforts evaluating multiple–traits). This is perhaps surprisingsince it is certain that species generally diverge along more than one niche axis at a time(e.g. resource partitioning, tolerance to abiotic stress and interactions with herbivoresand pathogens) affecting multiple quantitative traits simultaneously. Consequently, wehere suggest that a multidimensional approach to quantitative traits (matching multidi-mensional trait spaces) might be valuable for inferring the relative importance of differ-ences in attributes between aliens and co–occurring native species.

Presumably, trait differentiation among natives and aliens can arise through variousmechanisms. For example, if aliens manage to escape some of the costs faced by nativesthen, enabled via new trait combinations, they might exploit novel regions of the localniche space. One example is aliens that are not recognized as food by the resident herbi-vores, and therefore require less investment in chemical or physical defenses, allowinga great allocation to vegetative growth or reproduction (Keane & Crawley 2002).

The first aim of this study is to compare native and alien plant species in terms ofthree key traits (specific leaf area – SLA; average individual seed weight – SWT; typicalmaximum height of adults – Hmax), each representing an essentially independent axis ofecological strategy, or niche dimension (Westoby et al. 2002). Second, we aim to estab-lish whether native and alien species differ in their position within the multidimensionaltrait space generated by the three traits under consideration. Third, we assess whetherthe trait composition of co–occurring native and alien species supports either the ideaof phenotypic convergence (and thus of habitat filtering and common constraints) or theidea of phenotypic divergence (and thus of limiting similarity and empty niches).

3.2 Methods

3.2.1 Selection of traits

Each of the three traits (SLA, Hmax and SWT) represents an approximately independentaxis (or spectrum) of ecological strategic variation. These spectra are themselves un-derpinned by various trade–offs such that a wide range of trait values is typically seen,even among co–occurring species (Westoby et al. 2002, Westoby & Wright 2006).

Specific leaf area (leaf area per dry mass; SLA) indexes a species’ position along amulti–trait spectrum describing the dry mass and nutrient economics of carbon gain –the ”leaf economics spectrum” (Westoby et al. 2002, Wright et al. 2004). This spectrumruns from species with high SLA, leaf N and P concentrations, fast maximum photo-synthetic and dark respiration rates, and short leaf lifespan, to species with the oppositesuite of traits. Typically, species towards the high–SLA end of the spectrum are rela-tively fast growing and good light competitors, but tend also to be highly palatable toherbivores. Herbs, grasses and deciduous trees tend towards the high–SLA end of thisspectrum, and evergreen shrubs and trees towards the low SLA end, but there is wideoverlap between growth forms.

3.2 Methods 43

Individual seed weight (SWT) indexes a species’ position along the trait–strategydimension emerging from the trade–off between the number of seeds, and the size ofthose seeds, that can be generated for a given reproductive effort (Moles et al. 2004,Moles & Westoby 2006, Westoby et al. 2002). This resembles the classic axis of r–Kstrategies (MacArthur & Wilson 1967), where producing many small seeds generallyimproves dispersal distances (in the case of wind dispersal) and promotes longevity inthe seed bank. Thus, small–seededness may be beneficial in disturbed habitats whererandom juvenile mortality due to disturbance is high. That said, seedlings of smaller–seeded species tend to be outcompeted by those of larger–seeded species, under a varietyof environmental conditions (Westoby et al. 2002).

Typical maximum height (Hmax) of adult plants indexes a species’ position along aheight–strategy spectrum that includes the time–trajectory and pace of height growth, aswell as Hmax itself (Falster & Westoby 2003, Weiher et al. 1999, Westoby et al. 2002).Hmax represents the outcome between benefits associated with greater light interceptionof taller plants, and the higher costs of growing tall, such as greater investment in stemtissue, higher maintenance respiration costs of stem tissue, and greater risk of breakage.As a result of these trade–offs, species with a wide range of maximum heights oftenco–occur at a site (e.g. in forest with gap–phase dynamics).

3.2.2 Database compilation

A database of SLA, SWT and Hmax data for native and alien species was compiled fromboth published and unpublished sources. Papers and databases were located throughelectronic searches using relevant keywords, examination of the references in these ci-tations, and direct communication with data owners. A dataset was considered suitableif it included measurements for at least two of the traits of interest, for at least four co–occurring species (whether native, alien or both). Only measurements made under nat-ural conditions were used (greenhouse studies were discarded), so that for each dataseta location (e.g. latitude and longitude), biome, eco–region, habitat and environmentalconditions could reasonably be assigned. Further details of the data compilation processare presented in Appendix A.

Each dataset was assigned to a particular plant ”community” by placing a 25 × 25kmgrid over a distribution map of all sampled locations, and grouping together all thelocations within each grid cell. This spatial aggregation scale was selected for threereasons: (i) It is large enough to capture processes occurring at landscape, regional andbiogeographical scales, but small enough to show signals from meta–communities andlocal inter–specific interactions (Blackburn & Gaston 2002); (ii) Environmental aspectsfor each grid cell can be generally considered homogeneous (e.g., climates, overall soiltype, vegetation physiognomy), but heterogeneous in other aspects (e.g., small scaledisturbance), despite some clearly being heterogeneous (e.g., small scale disturbance);(iii) It is the area of preference for storing, evaluating and reporting information onthe distribution of native and alien species (Larsen, Holmern, Prager, Maliti & Røskaft2009).

Species traits were summarized within each community by calculating the geometric


mean of all measurements of a particular trait across all studies within the same grid.We used this approach as it allowed us to compile a dataset in which a pool of nativeand aliens are known to co–occur under broadly similar landscape and environmentalconditions. The influence of choice of grouping scale was evaluated (Appendix A) andno major evidence of a size effect was found. For each of these plant communities wefollowed Richardson, Pysek, Rejmanek, Barbour, Panetta & West (2000) definition ofalien species. That is, alien plants were defined as those whose presence at a site ispresumed due to intentional or accidental introduction as a result of human activity.

The resulting database contains 4473 species sampled over 95 communities (3784species measured in their native range, 689 species in their introduced range, 207 inboth ranges). The database covers 66 eco–regions, all continents and all major biomesof the world. The species–list includes taxa from 219 plant families, representing arange of growth forms and lineages: 3717 dicots, 514 monocots, 76 Gymnosperms, 130ferns and Fern Allies, and 37 undetermined species.

3.2.3 Individual trait comparisons

Linear mixed models were used to test whether native and alien species differed sig-nificantly in individual traits (SLA, SWT and Hmax), while simultaneously taking intoaccount the influence of taxonomic relationships and whether a given species in a givencommunity was considered as either native or alien. In these analyses the species sta-tus (native/alien) was treated as a fixed factor, while community identity and speciesidentity (nested within community) were treated as random factors. The use of commu-nity as a random factor allowed us to compare native and alien communities broadlyco–occurring under the same general landscape and environmental conditions. Addi-tionally, the use of species identity (within communities) as a random factor controlledfor the possible relatedness of native and alien species. Contrasts based on taxonomicsimilarity (i.e., congeneric/confamilial contrasts) are not presented since neither genusnor family showed a significant influence as random factors (Appendix A). Each of thethree focal traits (SLA, SWT, Hmax) showed a strongly right–skewed distribution (ca.log–normal) and thus all traits were log10–transformed for all analyses.

3.2.4 Multidimensional trait comparisons

Two analytical approaches were used to detect differences in the trait combinations ofnative and alien species. First, a discriminant analysis (Legendre & Legendre 1998)was implemented to determine which traits best differentiated between native and alienspecies. With this analysis our aim was not to determine which of the traits differed morerelative to others, but rather to establish if the evaluated traits (SLA, Hmax, SWT) couldbe used to discriminate between native and alien species in a multivariate space. Compu-tationally, discriminant analysis is similar to a multiple regression, but with group mem-bership instead of a continuous variable chosen as the response variable to be predictedfrom a set of covariates. Classification accuracy and its significance was quantified us-

3.3 Results 45

ing both the correct classification rate (CCR) and the area under the receiver–operatorcurve (AUC) (Hanley & McNeil 1982, Swets 1988).

Second, the trait composition of native and alien species was compared using a con-vex hull approach. The convex hull is the minimum convex geometry that includes allthe considered observations (Preparata & Shamos 1985) and has been recently proposedas a method to represent the volume of functional space used by a community (Cornwellet al. 2006, Villeger, Mason & Mouillot 2008). This approach, in conjunction with re–sampling techniques, allowed representing, measuring and comparing the trait variationof native and alien species in multiple dimensions, using a distribution–independent ap-proach (Cornwell et al. 2006). To avoid problems with differences in the measurementdomains of each of our traits, convex hull were calculated from standardized (mean= 0, and SD = 1) log10–transformed traits. The mean trait separation between nativeand alien species–groups within multidimensional trait space was quantified in termsof the Euclidean distance between the group centroids. Hull centroids are themselvescalculated as the mean values in each dimension using the outermost hull vertices. Addi-tionally, we used two indices of functional diversity related to convex hulls: ”functionalrichness” (i.e., convex hull volume) and ”functional divergence” (i.e., the spread of na-tive and alien traits in relation to the community–mean trait combination; Villeger et al.(2008)).

A null model approach (Gotelli & Graves 1996) was used to determine if the ob-served differences between native and aliens were different from those expected bychance alone. The use of this approach allows the comparison of functional diversityvalues among species pools with different species richness and regional spaces (Mason,Lanoiselee, Mouillot, Irz & Argillier 2007, Villeger et al. 2008). Null–communitieswere generated using a random assembly process drawing from the overall pool ofnative species with the same number of species in each draw, while maintaining theproportion of each growth form constant. The process was repeated 1000 times, eachtime determining the functional richness, divergence and divergence between centroids.Differences between the null and observed species pools were tested using a two–tailedWilcoxon signed–ranks test (Sokal & Rohlf 1995). All analyses where done using R2.10 (R Development Core Team 2009).

3.3 Results

3.3.1 Individual trait comparisons

Linear mixed–model comparisons involving the individual traits indicated that alienspecies have, on average across all species and growth forms, 15% higher SLA (t =

−5.54, p < 0.001), 16% lower Hmax (t = 2.99, p = 0.003), and 26% smaller SWT(t = 2.44, p = 0.015) than co–occurring native species. By implication, this could beinterpreted as aliens having the tendency to produce more seeds per unit reproductiveeffort (smaller SWT), have faster growth rates (at least as seedlings; via high SLA), andtake a shorter time to reach reproductive age (lower Hmax). These differences – although


modest – were significant for all three traits (Table 3.1) even after controlling for growthform as a random effect (as described in Appendix A). Trait–differences between nativeand alien species were smaller for the woody species group (shrubs and trees) than fornon–woody species (grasses and herbs/forbs), with trait differences ranging from 1.5 to5% for woody species, and between 3 to 100% for non–woody species.

Trait comparisons were also made within each growth form (Table 3.1) since weexpected patterning of trait values according to growth form, and aliens and nativesdiffered in growth form representations. Alien species had higher SLA than nativeswithin grasses and herbs (just as across all species), whereas no difference was seenwithin trees, shrubs or vines. For seed weight the group differences were deemed non–significant in all growth forms except grasses, with this difference in the same directionas for all species together (smaller seeds in aliens). A non–significant group difference inHmax was seen for all growth forms, with shifts in the opposite direction to that is seenin the all–species comparison for trees. In summary, alien and native species showedrelatively few trait differences for individual growth form comparisons. Still, there wasonly one case where the difference found was incongruent with that seen in the all–species comparison.

3.3.2 Multidimensional trait comparisons

The discriminant function analysis for all species pooled showed that all three traitscontributed to the best–fit discrimination function (Table 3.2). However, the effect ofSLA was by far the largest of the three, and that of Hmax was only marginally significant(SLA: F(1,1955) = 72.99, p < 0.001; SWT: F(1,1955) = 7.52, p = 0.006; Hmax: F(1,1955) =

3.21, p = 0.073). A model based only on SLA and SWT had a better than randompredictive ability, as both the AUC (0.67) and the correct classification rate (85.5% ofcorrect predictions) showed (where AUC and CCR values between 0 to 0.50 and 0% to50% respectively represent predictions no better than random or random guessing).

Comparisons within each growth form resulted in broadly similar predictive abil-ity: correct classification rates were all above 75%, and AUC all above 65%. Nonethe-less, examination of the discriminant function coefficients shows differences in the rel-ative discrimination power of evaluated traits between woody and non–woody species(Table 3.2), also pointing to a broad difference in the strategies of successful aliens inrelation to life history. Specifically, for non–woody species (i.e. herbs and forbs andgraminoids) SLA and Hmax (and also SWT in the case of graminoids) allowed a sig-nificant discrimination between groups. In the case of woody species (i.e. shrubs andtrees) and vines, SLA was the only variable that allowed a correct classification betweengroups.

Although the tests involving convex hulls involved all three traits, for ease of pre-sentation in Figure 3.1 we show the component set of convex hulls in 2–dimensionalcross–sections. Trait separation measurements showed significant multivariate differen-tiation between the native and alien species pools (Table 3.3). That is, distances betweennative and alien centroids were larger than expected from comparisons involving ran-domly assembled native communities. This trend was consistent for comparisons made

3.3 Results 47

Table 3.1 Comparison of mean trait values of alien and native species, considering allspecies, and species grouped by growth form. Comparisons were made using linear mixedmodels; t and P values from these analyses are given in the right-hand column (significancelevels indicated as ∗p < 0.05, ∗ ∗ p < 0.01, ∗ ∗ ∗p < 0.001, N.S. nonsignificant). Traitabbreviations: SLA – Specific Leaf Area (cm2 × g1), Hmax – Maximum Canopy height (m) andSWT – Seed weight (mg). All traits were log10 transformed before these analyses. Additionalinformation includes standard errors (SE) of trait means, the number of 25 × 25km2

communities involved in each comparison (”no. of Site”), and the number of species in eachgroup (”no. of species”).

Trait Alien Native Linear Mixed model[no. of Sites] Mean (SE) Mean (SE)

[no. of species] [no. of species]

All SLA 133.3 (1.06) 115.1 (1.04) t = 5.51 ∗ ∗∗[138] [788] [3164]Hmax 3.3 (1.14) 3.9 (1.11) t = 3.71 ∗ ∗∗[190] [647] [3562]SWT 5.6 (1.19) 7.6 (1.18) t = 2.8 ∗ ∗[190] [491] [2319]

Graminoids SLA 155.7 (1.08) 116.4 (1.09) t = 2.52∗[22] [39] [206]Hmax 0.6 (1.12) 0.6 (1.14) t = 1.18N.S .[31] [42] [295]SWT 0.4 (1.38) 0.7 (1.26) t = 2.01∗[24] [31] [198]

Herbs & forbs SLA 172.2 (1.09) 130.5 (1.07) t = 3.99 ∗ ∗∗[57] [166] [610]Hmax 0.3 (1.13) 0.3 (1.09) t = 1.75N.S .[64] [172] [652]SWT 0.7 (1.17) 0.9 (1.17) t = 0.51N.S .[61] [155] [510]

Shrubs SLA 125.3 (1.1) 114.2 (1.08) t = 1.36N.S .[36] [269] [386]Hmax 1.5 (1.12) 1.5 (1.1) t = 1.73N.S .[49] [106] [265]SWT 1.7 (1.41) 1.4 (1.4) t = 0.85N.S .[44] [67] [198]

Trees SLA 107.8 (1.09) 101.8 (1.06) t = 1.82N.S .[76] [238] [1088]Hmax 17.4 (1.08) 15.5 (1.07) t = 0.49N.S .[109] [224] [1503]SWT 31.7 (1.21) 50.8 (1.18) t = 1.55N.S .[107] [176] [889]

Vines SLA 260 (1.19) 243.6 (1.12) t = 1.43N.S .[11] [24] [74]Hmax 3.3 (1.46) 3.2 (1.38) t = 0.57N.S .[11] [25] [57]SWT 39.2 (1.39) 22.4 (1.55) t = 0.24N.S .[12] [21] [74]


Table 3.2 Summary of discriminant analyses used to determine which traits bestdifferentiated between native and alien species in multivariate trait-space, considering allspecies, and species grouped by growth form. Summary statistics shown are (from left toright) standardized classification coefficients (for Native and Alien species), results fromsignificance tests for the discrimination ability of each trait, Number of species involved ineach comparison, and classification proficiency statistics that describe the discriminationpotential of multiple trait combinations (CCR – correct classification rate, and AUC – Areaunder a receiver operator curve). CCR and AUC values were used as a significance test ofthe overall discriminant power of Native vs Alien status, based on the three traits. Traitabbreviations and significance levels follow Table 3.1.

Group Trait Classificationfunctioncoefficients

Trait Significance test Number ofspecies

CCR AUC

Native Alien Native Alien

All SLA 24 25.8 F(1,1955) = 72.99, ∗ ∗ ∗ 13032 1544 84.50% 0.67Hmax 1.8 2 F(1,1955) = 3.21,N.S .SWT 1 0.9 F(1,1955) = 7.52, ∗∗

Graminoids SLA 27.1 28.5 F(1,577) = 14.69, ∗ ∗ ∗ 893 153 80.80% 0.75Hmax 3.1 1.7 F(1,577) = 25.24, ∗ ∗ ∗SWT 1.6 1.4 F(1,577) = 0.83,N.S .

Herbs & forbs SLA 29 31.8 F(1,257) = 25.68, ∗ ∗ ∗ 2059 394 76.70% 0.69Hmax 0.4 0.6 F(1,257) = 5.54, ∗SWT 0.4 0.8 F(1,257) = 4.23, ∗

Shrubs SLA 26.1 27.9 F(1,369) = 9.21, ∗∗ 2518 354 88.30% 0.68Hmax 0.5 1.1 F(1,369) = 1.91,N.S .SWT 1 1.2 F(1,369) = 0.55,N.S .

Trees SLA 21.8 23.1 F(1,697) = 9.23, ∗∗ 6604 544 89.40% 0.61Hmax 4.6 4.6 F(1,697) = 0.001,N.S .SWT 1 0.9 F(1,697) = 1.71,N.S .

Vines SLA 31.3 34 F(1,55) = 5.23, ∗ 395 54 76.40% 0.7Hmax 1.6 1.7 F(1,55) = 0.08,N.S .SWT 5.8 6.1 F(1,55) = 0.18, ∗

within growth forms (p < 0.001 in all cases), with herbs and forbs being the most di-vergent group and shrubs the most convergent (Fig. 3.1). In general, shrubs showed thesmallest differences between groups (distributions appear to be centered similarly inboth groups); alien vines present a higher SLA; alien herbs and forbs possess a higherHmax; introduced trees differentiate from native species with both higher SLA and Hmax;and alien graminoids have both a high SLA and a low SWT in comparison to nativespecies.

Relative to the native species pool alien species showed a significant reduction inthe occupied multivariate range (56% smaller functional richness), and convex hullsclustered towards the edge of the native species trait distributions. Using a two–tailednon–parametric test, the distribution of native and alien species functional richness wassignificantly different than expected from comparing two null communities (Wilcoxon–

3.3 Results 49

All

10 100 1000

SLA (cm2*g−1)

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Figure 3.1 Minimum convex hull projections of native and alien species, showing thedifferences between these species-groups in the multidimensional trait space that they occupy,two traits at a time. Traits: specific leaf area (SLA, cm2 × g1); maximum canopy height (Hmax,cm) and individual seed size (SWT, mg). The polygons represent 2–dimensional crosssections ofthe convex hull volumes for each of the evaluated planes. Traits and axes were log10 transformedfor analysis and representation. Measurements of functional richness represent the volume ofeach convex hull; trait divergence corresponds to the distance between centers of gravity(centroids); functional divergence corresponds to relative distance of alien and native species’centroids from the community mean trait combination.

P and Observed Vs, expected ratios in Table 3.3). The same results and significancelevels were found for comparisons within growth forms.

Functional divergence measurements indicated that native and alien species differedin their average location in multivariate trait space (Table 3.3). On average, alien specieswere located 5% further away from the overall community–mean position (centroid)than were native species. Within–growth form comparisons (Table 3.3) also showedsignificant divergences between alien and native species in this regard. This suggeststhat aliens are located towards the edge of the natives’ trait distributions for most of thecompared growth forms.

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3.4 Discussion 51

3.4 Discussion

We found that alien species as a group differ in their trait composition from co–occurringnatives, for three key traits, each representing an approximately independent axis oftrait/strategy variation. Additionally we found that alien species had the tendency tooccupy regions clustered towards the edge of at least one evaluated dimension, whencompared to natives. Therefore, alien species could be considered as a biased sub-sample of species with regard to the evaluated traits, such that they tend to representgreater SLA, lower maximum height and smaller seed size. These results are in linewith two possible (related) mechanisms determining the success of alien species: (i) theidea of limiting similarity, e.g. invasive species are less likely to establish in communi-ties that are dominated by species with similar traits (Abrams 1983, Hutchinson 1959,MacArthur & Levins 1967b, van Kleunen et al. 2010); and (ii) Darwin’s naturalizationhypothesis, e.g. invading species are less likely to establish in communities with con-generics (Daehler 2001, Diez, Sullivan, Hulme, Edwards & Duncan 2008, Duncan &Williams 2002, Strauss, Webb & Salamin 2006). This means that, when compared ata community scale, the more dissimilar (functionally and/or phylogenetically) an alienspecies is to the native species community pool, the greater its chances are that it will besuccessful when introduced. We emphasize that, although the summarized patterns ofdifferentiation seem rather small, whether the analyses were univariate or multivariateit is very difficult to predict how big a trait difference should be in order to make anecological difference (e.g. in competition), as hardly any data on this are available inthe literature. In fact, the classic principle of competitive exclusion (Gause 1934) canbe interpreted such that very small but consistent trait differentiation among speciescompeting for a single resource will always lead to full competitive displacement.

The view that phenotypic divergence between native and alien species predisposes aparticular introduced species to success has also been addressed using alternative ap-proaches based on (i) history (i.e., the invasive–elsewhere principle; Muth & Pigliucci(2006), Rejmanek (1999)); (ii) taxonomy (i.e., Darwin’s naturalization hypothesis; Far-gione, Brown & Tilman (2003), Mack (2003), Strauss et al. (2006), Vivanco, Bais, Ster-mitz, Thelen & Callaway (2004)); and (iii) disturbance data (i.e., invasion of human–disturbed areas; Funk & Vitousek (2007), Leishman & Thomson (2005)). These effortshave come as a response to the problems of measuring the niche relationships betweennatives and aliens, and of identifying a series of species’ or habitat characteristics thatcould predict invasiveness. In agreement with our own study, results from studies usingthese approaches have generally suggested that whether an alien species could be suc-cessful in establishing depends on how its traits compare to those of native species inthe invaded community.

It is interesting to view these findings in relation to the evidence of aliens havinglower rates of herbivory, seed predation and pathogen attack when compared to co–occurring natives (Callaway & Aschehoug 2000, Keane & Crawley 2002, Mitchell,Agrawal, Bever, Gilbert, Hufbauer, Klironomos, Maron, Morris, Parker, Power, Seabloom,Torchin & Vazquez 2006, Richardson, Allsopp, D’Antonio, Milton & Rejmanek 2000).Consequently, one might expect alien species to be able to reallocate resources from de-


fence to growth and/or to reproduction (Blossey & Notzold 1995, Crawley et al. 1996,van Kleunen et al. 2010). Higher growth rates may be possible, via higher SLA or higherleaf mass per g plant, while increased total seed production may be possible, via lowerindividual seed mass (Westoby et al. 2002, Westoby & Wright 2006).

Could functional relatedness and the idea of limiting similarity then provide a frame-work to determine possible problematic species and threats to native communities? Withsome caution, we suggest yes –because such measures reflect the dynamics and diverseinteractions among co–occurring species, and hence capture the constraints imposed byphysiological limitations, habitat filtering and limiting similarity. In particular, the useof multidimensional metrics of functional diversity may allow discrimination betweenmechanisms causing trait convergence (i.e. habitat filtering) from those driving traitdivergence (i.e. limiting similarity). Here, comparison of all multidimensional metricsshowed a significant differentiation between native and alien species, suggesting thatthe presence of multiple closely functional equivalent species in the native pool (i.e.,species with similar trait combinations) could be a factor limiting the success of intro-duced species.

The idea of functional dissimilarity between native and aliens has been tested previ-ously using various approaches, most of which compare a single attribute between pairsof species pairs based on their taxonomic relatedness (e.g., between pairs of congenericor confamilial species). Overall, these studies show mixed results (Daehler 2003, Pysek& Richardson 2007). By contrast, the results from our present study indicate a signif-icant differentiation between groups based on a multi–site, multi–species multi–traitcomparison, which can be attributed to larger and additive differences when multipletraits are compared simultaneously and/or the role of phenotypic plasticity or evolution-ary changes in alien species attributes in those areas where they have been introduced;but the identification of the actual mechanism remains be determined. Evidence for thiswas the significant differences between multidimensional trait spaces centroids (traitdivergences) and ranges (functional richness and divergence measurements).

Two aspects of our study warrant further comment. First, our comparisons betweennative and alien species evaluate post–established population interactions only, hencemechanisms causing either an establishment failure, or trait evolution, post–introduction,cannot be tested. Second, traits in this study are assumed to be independent (that is howthey were selected), with each representing an approximately independent ecologicalstrategy dimension (Westoby et al. 2002). We believe, as Leishman et al. (2007, 2010)showed, that comparisons between traits within each ecological strategy would not showfundamentally different spectrum of variation; rather we believe that aliens will differen-tiate from natives by having trait combinations on the extreme of the evaluated ecolog-ical strategies. This difference may result from (for example) a shift in the allocation ofresources from defense to growth/reproduction, made possible by release from naturalenemies and/or a increased availability of resources (Blumenthal 2006). Alternatively,trait–shifts may be associated with an enhanced ability to take advantage of disturbance.These hypotheses remain to be evaluated as the spatial scale used to defined our ”com-munities” was to coarse and did not capture small scale inter–specific interactions northe effect of disturbance to which disturbance–adapted aliens can specialize.

3.4 Discussion 53

As this and other studies have addressed (Crawley et al. 1996, Lake & Leishman2004, Leishman & Thomson 2005, Ricciardi & Atkinson 2004, Strauss et al. 2006,Thompson et al. 1995, Williamson & Fitter 1996), a key element to understand thesuccess of alien species in their alien range is consideration of the relatedness (func-tional or phylogenetic) between the alien and natives community. We have demon-strated that alien species have a combination of traits that significantly differs fromthose of the native community where they are introduced, suggesting support for theclassic empty niches’ idea to explain invasions. Understanding the mechanisms gener-ating these patterns might then help to develop a trait–based framework for predictingthe successes/failure of aliens to establish and maintain successful populations whenintroduced to a novel region. And finally, this approach could then be used to addressthree fundamental questions in invasive biology: which species are likely to becomeinvasive; which habitats or communities are susceptible to invasion; and how can wemanage invasions once they occurred?

In conclusion, determining successful introductions will require the evaluation ofthree community attributes: the level of functional similarity between natives and aliens,as this study has done; the degree of phylogenetic relatedness between these groups;and the disturbance regime of the target community. This work focused on one of thisdimensions and determined the importance of functional differentiation as a mecha-nism associated with alien success. Our results, coupled with other recent findings in”functional trait ecology” (Fargione et al. 2003, Rejmanek et al. 2005, Ricciardi &Atkinson 2004, Strauss et al. 2006) highlight the need to take special considerationof those newly introduced aliens for which the target native community has no closefunctional similar species.

Part III

Community perspective:Biological invasions in thecontext of plant communities

4 Comparing the functionaldifferentiation of native and alienplants across spatial scalesAlejandro Ordonez Gloriaab, and Han Olffa

Abstract

By comparing the attributes of co–occurring native and alien species, researchers havetried to explain variation in introduction success. However, little attention has so farbeen paid to the relative influence of the spatial scale at which comparisons are made;preventing us from assessing potential scale-dependent aspects of alien success. Ouraim in this work is to evaluate, using a hierarchical spatially explicit framework, howmeasurements of alien–native trait differentiation are affected by the spatial scale of theanalysis.

In this study, we partition the variance in alien–native trait differences for three keyfunctional traits (specific leaf area, typical maximum canopy height, and specific seedweight) across five nested ecological scales (i.e. species within a plot, plots within anlocation, locations within a habitat, habitats within a region and differences betweenregions). For this we compiled a global database for each trait, and determine the in-fluence of each scale in standardized alien–native trait differences using a hierarchicalvariance decomposition framework.

For all traits the variation in the differences between co–occurring native and alienswas mainly explained by species differences within plots (66 to 94%), while other sclaes(e.g. plot, area, locality or region) captured the remaining variability (0 to 17%). Theseresults were consistent across alternative contrast criteria (alien to all natives in a plot,the phylogenetic closest co–occurring native or the mean of all co–occurring natives)and comparisons in multi–trait space.

Overall, the importance of differences among co–occurring alien and native speciesin traits brings substantial support to the idea that local scale community dynamicsand local niche differences ultimately shape individual invasive species distribution;while the lack of variance at larger scales (plot to region) supports the importance oftrait–based environmental filtering on invasive species success. Our results show howattention to the spatial scale of comparison helps in understanding the success or failureof alien species invasions.


58 Cross scale functional differentiation of native and alien plants

4.1 Introduction

The globalization of human activities has resulted in the intentional and un–intentionalmovement of animal and plant species to areas beyond their natural range. This hasultimately resulted in both the biotic homogenization of natural areas across the worldand irreversible changes to the functioning of various ecosystems (Mack et al. 2000).As the introductions of alien species are characterized by distinct spatial and temporaldynamics (Kuhn & Klotz 2007, Pysek & Hulme 2005), understanding the drivers ofboth the rate and magnitude of range expansion across both of these dimensions is oneof the central questions in the understanding of biological introductions.

Explanations of biogeographical/ecological patterns in the distribution of species canbe divided in to two main spatial categories: Local and regional. Local processes arethose determined by the interaction among co–occurring species (e.g. competition, pre-dation, pathogens). Regional processes on the other hand are related to abiotic hetero-geneity (leading to habitat filtering), dispersal, and evolutionary processes. In the caseof differences in biological traits of co–occurring species, the same distinction can bemade for different structuring processes across spatial scales. However, most studies todatehave focused only at one particular scale. For example, studies at local scales havefocused on the variation of traits within a species (Albert, Thuiller, Yoccoz, Soudant,Boucher, Saccone & Lavorel 2010) or among species (Moles & Westoby 2006, Wrightet al. 2004). Alternative, at regional scales the emphasis has been on the comparisonof traits across different communities (Cornwell & Ackerly 2009) or regions (Moles& Westoby 2006, Ordonez, van Bodegom, Witte, Wright, Reich & Aerts 2009, Wrightet al. 2005).

Recent studies on invasive species have shown that by evaluating processes at a singlespatial scale we are unable to distinguish the drivers and mechanisms of aliens success(Cadotte et al. 2009, Hamilton et al. 2005, Pysek & Hulme 2005, Thuiller et al. 2010).This makes the understanding of the role of spatial scale on invasion patterns a sub-ject of increased interest for both invasion biology and community ecology. Therefore,the assessment of scale–dependency of trait dissimilarity patterns becomes a topic ofgreat relevance for predicting possible invaders, given the spatial context of alternativemechanisms that may explain invasion success.

Surprisingly, to our knowledge, no study has explicitly aimed to explore trends in traitassembly across different ecologically relevant scales (although see Albert et al. (2010)and Messier, McGill & Lechowicz (2010) for relevant works). In the framework of in-vasion biology, the evaluation of the difference between native and alien across scalessimultaneously has yet to be done for a large number of species (but see Cadotte et al.(2009) and Hamilton et al. (2005) for starts in this direction). These types of analysesare of particular importance so that the processes associated to a particular predictiveframework (e.g. species invasiveness or community invasibility) are not considered out-side the relevant scale.

The identification of the spatial scale at which a particular mechanism acts has ex-plicit implications for checking the underlying assumptions of the existing theoriesof invasion success. In particular we expect that those theories based on the differ-

4.2 Methods 59

ences between species (co-occurring species should be phenotypic different to coex-ist; Hutchinson 1959) are important in understanding invasions, and are expected tomostly operate at local scales. These difference center theories (e.g. Increased compet-itive ability, biotic resistance, empty niches, novel weapons or Darwin’s naturalizationhypotheses) have a major influence at smaller scales and reflect the balance betweenthe level of saturation of the community and the trait similarity of aliens to the nativecommunity (Scheffer & van Nes 2006). Alternative, those theories explaining invasionsbased on the idea of the importance of similarity between species such as habitat filter-ing, resource–enemy release, opportunity windows or phenotypic similarity are mostlyexpected to operate at larger spatial scales, where the match between attributes andenvironmental conditions is expected to be the main factor shaping the ability of anyspecies to successfully invade once introduced . These ”similarity” based explanationsare expected to mostly operate at regional and biogeographical scales.

In this study we use a target area approach (i.e. comparing aliens to co–occurringnatives in the introduced area sensu Hamilton et al. 2005) and compared the stan-dardized differences between co–occurring aliens and native plants using a hierarchi-cal spatially explicit framework. This approach allowed us to determine to what extendtrait (di)similarity of aliens to the native community enhances its colonization potentialacross different spatial scales. Our working hypothesis is that the invasion process ischaracterized by small–scale alien–native trait differentiation due to limiting similarity,and large–scale trait convergence resulting from habitat filtering.

For this we focused on evaluating the level of variability in standardized differenti-ation (using hierarchical variance decomposition) of ecologically functional traits be-tween native and alien species co–occurring at a series of ecologically relevant scalesnested within each other. This allowed us to simultaneously evaluate the ideas of habi-tat filtering (leading to attribute similarity) and limiting similarity (leading to attributedissimilarity) at different spatial extends using a spatially explicit context.

4.2 Methods

4.2.1 Data sources and evaluated traits

Our work focused on differences in three key plant morphological traits: specific leafarea (SLA in cm2 ×g−1), maximum plant height (Hmax in m) and individual seed weight(SWT in mg); all traits are closely related to key ecological strategy dimensions of plantperformance (Westoby et al. 2002). SLA is defined as amount of fresh leaf area dividedper dry leaf mass, and provides a measure of the allocation of biomass to light harvest-ing (e.g. an index of a species position along the ”leaf economics spectrum”; Wrightet al. 2004). It strongly covaries with nitrogen and photosynthetic rate per unit mass, leaflife span and relative growth rate (Wright et al. 2004). Hmax, provides a basic measureof stature and provides an index of a species position along the height spectrum (Falster& Westoby 2003, Westoby et al. 2002). It also relates to other important ecological axesof variation representing the trade–offs between opposing costs and benefits associated


with light interception (e.g. species taller than their neighbors are able to intercept morelight in a dense vegetation), investment in stems production and maintenance (e.g. lowercosts for smaller species) and the risk of breakage/toppling (Falster & Westoby 2003).Lastly, SWT is related to the trade–offs between seed size and number, dispersal dis-tances and regeneration biology (Moles, Ackerly, Tweddle, Dickie, Smith, Leishman,Mayfield, Pitman, Wood & Westoby 2006). It also relates to the classic axis of r–Kstrategies (MacArthur & Wilson 1967), where producing many small seeds generallyimproves dispersal distances (in the case of wind dispersal) and promotes longevityin the seed bank, while producing fewer big seeds promotes establishment success insituations of low resource availability

To measure the standardized differences between co–occurring native and alien species(between group differences: BGD hereafter) we searched the literature for studies mea-suring traits for co–occurring native and alien species in natural conditions. We searchedthe ISI–Web of science for publications with either, or the combination, of importantkeywords (i.e. ”plant traits”, ”SLA”, ”LMA”, ”leaf size”, ”leaf nutrients”, ”plantheight”, ”seed size”, ”seed weight”, ”seed production”, ”plant traits”, ”LHS”, ”plantphysiology”, ”weed”, ”weeds”, ”naturalized”, ”invasive”, ”exotic”, ”noxious”, ”in-troduced”, ”alien”, ”foreign”, ”non–native”). A publication or dataset was consideredsuitable if it included measurements for any of the traits of interest (that is SLA, Hmax orSWT), for at least four native and one alien species co–occurring on a site. Only stud-ies with measurements under natural conditions were selected; greenhouse studies werediscarded. We ensured that to each study/dataset a specific local plot (with geographiccoordinates), area, region, biome, eco–region, habitat and bioclimatic conditions couldreasonably be attached.

In total, our database included 112 studies and databases, covering 5229 species(4005 with measures in the native, 1057 in the introduced and 167 on both ranges)from 261 plant families sampled over 131 communities for which information for anyof the three traits of interest was available. The species included represent a wide rangeof growth forms and lineages: 4515 dicot species, 570 monocots, 70 Gymnosperms, and74 Pteridophytes (ferns and fern allies). Further details of the data compilation processare given as Supporting Information (Appendix A).

4.2.2 Statistical comparisons

We used the log ratio [log (alien trait / native trait)] of the alien to native trait valueto measure the BGD. The use of this metric follows the recommendation of Hedgeset al. (1999) for meta–analytical analyses, and allows the identification of the directionand magnitude of the between groups standardized differentiation, while eliminating orreducing the bias and variation associated with individual studies (Hawkes 2007).

The variation in the BGD of co–occurring native and alien species was assessedacross five hierarchically nested ecological/spatial scales: i) among species within aplot, ii) plots within and location, iii) locations within a habitat (Areas), iv) habitatswithin regions and v) between regions. The selected scales have both explicit environ-mental gradients (regions, habitats and plots) and distinctive community composition

4.2 Methods 61

structures (species mixture) which allowed us to test the role of two of the mechanismsmost frequently invoked to predict alien species success: limiting similarity and habitatfiltering. Mean differences at each particular scale were estimated using the structurepresented in Table. 4.1.

A variance components analysis was used to determine the influence of each evalu-ated scale on the BGD variation. This analysis allowed us to determine the populationco–variation between each spatial scale (random factors) and the BGD (dependent vari-able). The variance components in BGD for each trait were estimated using a nestedANOVA with random effects. For this a general linear model was fitted (using a re-stricted maximum likelihood (REML) method) to the BGD variance (that is a interceptonly model), using the five evaluated ecological scales as random factors, in this in-creasing order: species/plot/locality/area/region. The variance components of a nestedANOVA represent the variances around hierarchical means as specified in Table. 4.1,and following Zar (1999), so that the variance at a particular level (e.g. plot) representsthe variability of the group means at the target scale (that is the mean BGD in a plot) inrelation to the group mean of the higher level to which they belong (e.g. the variance ofthe plot means around the mean of their locality). This allows us to evaluate the effectof each level on the level of variability in a trait BGD. Models were fitted and vari-ance components were estimated using R (version 2.10) and the nlme (Pinheiro, Bates,DebRoy, Sarkar & team 2009) and ape (Paradis, Claude & Strimmer 2004) packages.

To test the effects of spatial scale on the patterns emerging from alternative compari-son criteria, variance decomposition analyses were performed for tree alternative BGDcalculations. First, we compared each alien species to all of the co–occurring nativespecies (all pairwise comparisons within a plot, here after Alien–to–All), allowing usto test the role of limiting similarity on invasion success (e.g. the idea that functionallyrelated species can not invade due to competitive exclusion by specific native specieswith similar attributes; van Kleunen et al. 2010). Second, each alien was compared tothe phylogenetically closest co–occurring native (here after Alien–to–PhyloClose) test-ing the hypothesis that closely related species are unlikely to coexist as they likely sharesimilar attributes (e.g. as proposed by phylogenetic trait conservatism and Darwin’snaturalization hypothesis Rejmanek 1996). Thirdly, we calculated the log–ratio of eachalien in relation to the mean trait value of all co–occurring natives in a site (here afterAlien–to–Mean) to determine if successful aliens have a set of attributes novel to thenative community (e.g. Novel weapons hypothesis Callaway & Ridenour 2004). Theuse of alternative contrast criteria allowed us to address the mechanisms proposed byvarious hypotheses explaining alien success.

For the Alien–to–PhyloClose comparison, the phylogenetic relatedness of each aliento the co–occurring native species was established based a phylogeny constructed forall the evaluated species (alien and natives). The used phylogeny was build using PHY-LOMATIC (Webb & Donoghue 2005) and the APG3 derived megatree R20091110 (orAPG3 derived megatree) as a backbone. This tree is a strict consensus phylogeny forplants using the complete resolution determined by the APweb (Stevens 2009). Branchlengths of our database mega–tree were estimated using the BLADJ (Branch LengthADJustment) procedure in PHYLOCOM (Webb, Ackerly & Kembel 2008) where node

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4.3 Results 63

ages were established using the divergence times, in millions of years, estimated byWikstrom, Savolainen & Chase (2001). Details about the construction of the used super–tree is presented in Appendix A.

4.2.3 Multi–dimensional comparison

Given the importance of each of the evaluated traits and its relation to key ecologicalstrategies, we determined the level of multi–dimensional differentiation based on allthree evaluated traits and using the same three comparisons criteria as for individualtraits (Alien–to–All, Alien–to–PhyoClose and Alien–to–Mean).

Differences between alien and natives were determined using the Euclidean distancein a log10–globally standardized space. This is because traits show both a strong log–normal distribution and different ranges of variation in log10–scales. Standardizationswere done using a global weighting procedure in which each trait was scaled relativeto a global mean and variance derived from a larger database with global coverage (assuggested by Cornwell et al. 2006). The advantage to this approach is that a range ofone standard deviation of a particular trait is then the same worldwide.

4.3 Results

For all evaluated traits, alien species showed a consistent differentiation to co–occurringnatives, with aliens having higher SLA (Alien: 155±1; Native: 136±1), lower Hmax

(Alien: 2.4±1.1; Native: 2.7±1.2) and smaller SWT (Alien: 6.02±1.2; Native: 7.45±1.2).The direction of the between–groups differences was the same across scales (Fig. 4.1),but magnitude and significance of these changed with both scale of the analysis and thecomparison criteria. These results indicate how different ecological mechanisms mightbe operating at different scales and how the selected contrast criteria might influencethe observed alien–to–native (di)similarity patterns.

The partitioning of the variance for the trait differences between co–occurring na-tive and alien plants (Alien–to–All comparisons) showed an unbalanced distributionacross scales (Fig. 4.2). Variance components analysis for the three individually eval-uated traits showed similar tendencies in the scale partitioning of the variance withonly slight differences in the contribution of each scale. An important result is how thespecies scale contains almost all of the BGD; and only the area scale captured any othersignificant, although small, part of the BGD variation. This trend was consistent forAlien–to–PhyoClose and Alien–to–Mean comparisons (Fig. 4.2).

The major difference in BGD variance components analyses were between modelsbased on different comparison strategies. In particular, models comparing the averagealien to the average native in a particular location (that is mean trait for each groupacross all aliens or natives co–occurring on a plot) indicated how the area and plot scalecontained most of the BGD variation; the All category in Fig. 4.2) while models basedon contrasts of individual species (e.g. Alien–to–All or Alien–to–PhyoClose compar-isons) showed that most of the BGD is captured at the Species/Plot level.


● ●●

●

SLA

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4−

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●● ●

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●

● ●

●●

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−0.

4−

0.2

0.0

0.2

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● ● ●●

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0−

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0.0

0.5

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−1.

0−

0.5

0.0

0.5

● ● ● ●

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−1.

0−

0.5

0.0

0.5

●

● ● ●●

Hmax

−1.

0−

0.5

0.0

0.5

● ●

●●

SWT

−2.

0−

1.0

0.0

0.5

1.0

Plo

t

Loca

tion

Are

a

Reg

ion

Mean alien to mean native

●

● ●● ●

SWT

−2.

0−

1.0

0.0

0.5

1.0

Spp

Plo

t

Loca

tion

Are

a

Reg

ion

Alien to all native

●● ●

●

●

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2.0

−1.

00.

00.

51.

0

Spp

Plo

t

Loca

tion

Are

a

Reg

ion

Alien to phylogenetically closest native

●

● ●● ●

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−2.

0−

1.0

0.0

0.5

1.0

Spp

Plo

t

Loca

tion

Are

a

Reg

ion

Alien to mean native

Log−

resp

onse

ln[(

Alie

n−tr

ait)

/(N

ativ

e−tr

ait)

]

Figure 4.1 Log–response differences contrast across scales and comparison criteria for threespecies traits (Specific leaf area–SLA, typical maximum canopy height–Hmax, Specific seedWeight–SWT). Between group contrasts represent differences between i) average Alien toaverage native, ii) alien to all co-occurring natives, iii) alien to the phylogenetically closestnative and iv) alien to the mean composition of all co-occurring natives. Points represent meanlog-differentiation and whiskers represent the 95% confidence intervals.

Given that there might be a small overlap in the composition of native species be-tween plots, the same variance components analysis was performed with the speciesscale removed, so the level of discrimination between the plot and species scale couldbe determined. The results from this alternative model (Table. 4.2) were essentially thesame as the full model, with the plot level now including the variance that was originallyattributed to species in the full model.

Given that the observed BGD trends could change according to growth forms, thesame variance component analysis was done for subsets of the database. Specifically,comparisons were done for species of a particular growth form (i.e. graminoids/herbs–forbs, trees/shrubs and vines–climbers). Variance components analysis for these com-parisons (Fig. 4.3) showed the same pattern as observed for all species comparisons,

4.3 Results 65

0.0

0.4

0.8

F(1,69) = 12.909 ***

0.0

0.4

0.8

SLAF(1,111555) = 2.12 N.S.

0.0

0.4

0.8

F(1,1206) = 16.819 ***

0.0

0.4

0.8

F(1,1177) = 4.286 *

0.0

0.4

0.8

F(1,86) = 8.614 **0.

00.

40.

8Hmax

F(1,95213) = 0.946 N.S.

0.0

0.4

0.8

F(1,1139) = 2.89 N.S.

0.0

0.4

0.8

F(1,1100) = 1.91 N.S.

0.0

0.4

0.8

F(1,98) = 2.902 N.S.

0.0

0.4

0.8

SWTF(1,93830) = 1.403 N.S.

0.0

0.4

0.8

F(1,1196) = 0.001 N.S.

0.0

0.4

0.8

F(1,1154) = 0.063 N.S.

0.0

0.4

0.8

F(1,55) = 1.629 N.S.

Spp

Plo

tLo

catio

nA

rea

Reg

ion

All

0.0

0.4

0.8

MultiF(1,30940) = 429.04 ***

Spp

Plo

tLo

catio

nA

rea

Reg

ion

Alien−To−Native

0.0

0.4

0.8

F(1,629) = 62.426 ***

Spp

Plo

tLo

catio

nA

rea

Reg

ion

Alien−To−PhyloClose

0.0

0.4

0.8

F(1,598) = 202.054 ***

Spp

Plo

tLo

catio

nA

rea

Reg

ion

Alien−To−Mean

% o

f Var

ianc

e

Figure 4.2 Variance decomposition of the difference between native and aliens specific leafarea–SLA, typical maximum canopy height–Hmax, specific seed Weight–SWT and multi-traits.Loadings were calculated from full nested linear models across five scales(species/plot/location/area/region) and for three contrast criteria (as in Fig. 4.1). Bars representmean percentage load and whiskers represent the 95% confidence intervals calculated by 1000bootstrap iterations. Significance of the standardized differences was estimated using a fullnested linear models across five scales (species/plot/location/area/region) with significancelevels marked as: *** for p < 0.001; ** for p < 0.01; * for p < 0.05 and N.S: Non-significantdifferences.

with the species level (or plot scale for simplified models) containing most of the varia-tion in the BGD.

Variance components of multivariate comparisons also showed an unbalanced distri-bution across scales, whether the comparisons were based on Alien–to–All, Alien–to–PhyoClose or Alien–to–Mean contrasts (Fig. 4.2). For these, as for the individual traitcomparisons, BGD variation was mainly driven by the variability in BGD at the specieslevel, with only a minor influence of any other evaluated ecological scale. When com-parisons were made for particular growth forms, these showed the same pattern thatwas observed for all species comparisons; that is, variation in BGD was mainly at thespecies level (Fig. 4.3).


Table 4.2 Variance components of the difference between native and alien species traits(Specific leaf area–SLA, typical maximum canopy height–Hmax, Specific seed Weight–SWT)calculated from nested linear models across four scales (plot/location/area/region – specieslevel is excluded).

Paring Scale Compared TraitSLA Hmax SWT

[95%C.I.] [95%C.I.] [95%C.I.]

Alien Plot/Error 86 81 87To [86 – 87] [81 – 81] [87 – 88]

All Natives Locations 10 15 10[10 – 11] [14 – 15] [9 – 10]

Areas 2 2 1[2 – 2] [2 – 2] [0 – 1]

Region 1 2 2[1 – 2] [2 – 2] [2 – 3]


Closest Native Locations 4 14 8[4 – 4] [13 – 14] [7 – 8]

Areas 2 2 1[2 – 2] [2 – 2] [1 – 1]

Region 1 3 2[1 – 1] [3 – 3] [1 – 2]


Mean Native Locations 14 23 14[14 – 15] [23 – 24] [13 – 14]

Areas 3 2 1[3 – 3] [2 – 3] [1 – 1]

Region 4 6 4[4 – 4] [6 – 6] [3 – 4]

4.4 Discussion

We think that our results on the variance decomposition patterns provides important in-formation for both invasion ecology and basic ecological research. We emphasize threeparticular results: i) the BDG variance is consistently unbalanced across all evaluatedscales with the species scale capturing most variation in BGD; ii) The contribution oflarger spatial scales is almost negligible with BGD being undistinguishable from zeroat these scales, and iii) The three analyzed contrast criteria show always almost simi-lar variance decomposition results but differ in the significance of the between groupdifferences.

The observed uneven distribution of the BGD variance among the evaluated eco-logical scales (i.e. species, plot, location, area and region) suggests that processes at

4.4 Discussion 67

Alien−to−All

Alien−to−PhyloClose

Alien−to−Mean

Shrub/Tree SLA

Alien−to−All


Alien−to−Mean

Hmax

Alien−to−All


Alien−to−Mean

SWT

Alien−to−All


Alien−to−Mean

Region Area Location Plot Species

Multip

0.0 0.2 0.4 0.6 0.8 1.0

GrasHerb SLA

Hmax

SWT

Multip

0.0 0.2 0.4 0.6 0.8 1.0

Vine/Climber SLA

Hmax

SWT

Multip

0.0 0.2 0.4 0.6 0.8 1.0

Figure 4.3 Variance decomposition of the difference between native and alien species in a)Specific leaf area–SLA, b) typical maximum canopy height–Hmax, c) Specific seed Weight–SWTand d) multi–traits, according to growth from (i.e. Shrubs/Trees, Graminoids/Herbs–forbs andVines and climbers). Categories with no bars indicate insufficient data to perform the analysis.

each of the scales act in different directions. This could affect the observed differenti-ation patters at particular scales and the possible conclusions drawn from comparingnative and alien species. Specifically, the contributions to the BGD variance of differentscales suggest that the processes shaping the differentiation between native and alienspecies principally act at the smallest scale of analysis (species scale captures 74 to94% of the BDG). These results match the general expectations of the scale depen-dence of the processes determining the success of aliens (Hamilton et al. 2005, Kuhn& Klotz 2007, Thuiller et al. 2010). Based on this, we expect that at larger scales, boththe non–significance of and marginal influence in BGD variation indicates that at thesescales ecological pressures drive analyzed traits towards convergence. Said otherwise,as a result of habitat filtering, species in a region have similar traits irrespective whetherthey are native or an alien. Meanwhile at small scales (i.e. between plots–communitiesand/or closely related species), both limiting similarity and/or competitive exclusiondrives co–occurring species to diverge in attributes.

The spatial or phylogenetic scale of studies comparing co–occurring natives andaliens is generally not made explicit [e.g., see Thompson et al. (1995), Williamson &Fitter (1996) and Leishman & Thomson (2005) among others; although see Cadotteet al. (2009), Diez et al. (2008), Diez, Williams, Randall, Sullivan, Hulme & Duncan(2009) and Hamilton et al. (2005) for examples of aiming to incorporate the scale ef-fect]. We think the resulting mixing up of processes at different scales is the reason


why certain studies have found a generalized tendency of trait similarity between co–occurring native and aliens (as reviewed in Daehler 2003) while others report differencesbetween these (as reviewed in van Kleunen et al. 2010). From this is clear that formu-lating the comparison of native and aliens in an explicit spatial framework, or usingmultiple scales, would help revealing and understanding both the mechanisms behindthe observed alien–native trait similarity/dissimilarity patterns; and the relation betweenBGD and the success of introduced species.

The smaller scales (plot and species) consistently explained most trait differencesbetween aliens and natives. These trend held for all comparison criteria and subsetsof the database. Within each location, invaders are on average equally differentiatedin traits from natives (Alien–to–All contrasts). However, evaluating the similarity intraits of an invader to a particular closely related co–occurring native (in functionalor phylogenetic space, as in Alien–to–PhyoClose contrasts) showed trait convergence.These two contrasting results show how considering both the spatial and phylogeneticcontext of the alien-native comparison is key to understand the possible mechanismsdetermining the success of an introduced alien in a particular community.

The second interesting result from our comparison is that the variance contributionof large ecological scales (plot–location–area–region) was consistently small, althoughwith slight changes in the contribution of each scale between comparison criteria. Whenthe BGD was evaluated at large scales, a consistent similarity in the attributes of nativeand alien species was observed. Based on both of these results, we believe that thespecies pool on a location, area or region could be considered as ”functionally redun-dant” (Clark, LaDeau & Ibanez 2004, Fonseca & Ganade 2001), the product of a self–organized trait similarity (Scheffer & van Nes 2006), and/or multiple trait combinationsof equal fitness (Marks & Lechowicz 2006).

It is also important to highlight, in the light of ecological theory, that the minimal ofinfluence of the plot–location–area–region scales and the consistency of the distributionof these differences across contrast criteria (as shown in Fig. 4.1) gives support to theidea that traits, instead of species, are what is filtered by environmental factors. Thiswould mean that the success of an alien at particular plots–areas–regions relies on ithaving the right trait combination, which allows it to occupy a particular site (e.g. beingsufficiently different or being sufficiently similar). Given this, any given species couldbe successful in colonizing a site either if it has the adequate mean trait value or haslarge trait variability (so it could achieve this trait value).

Lastly, we like to point out how the convergence of variance loading of each scale anddifferences in the significance of between group contrasts is the result of the synergisticeffect of scale dependent ecological forces and the alien–native comparison method(e.g. paring of an alien to –All, –PhyloClose or –Mean native). We suggest that theobserved variance decomposition patterns illustrate the tendency towards small–scaledifferentiation [as predicted by the limiting similarity (Hutchinson 1959) and novel traitshypotheses (Callaway & Ridenour 2004)]; but these differences can be concealed if thecontrast domain is large enough and/or if the compared pairs are functionally redundant(phylogenetically close or the same functional type). This would make processes such ashabitat filtering (Keddy 1992), niche conservatism (Wiens et al. 2010), and the balance

4.4 Discussion 69

between competition and community saturation (Scheffer & van Nes 2006) the maindrivers of traits convergence in to phenotypic clusters.

The approach used in this study is aligned with current trait–based approaches aimingto understand the evolution of species niche and traits, within the context of undefinedabiotic environmental gradients (McGill et al. 2006, Violle & Jiang 2009). This is ofparticular importance as community and invasion ecology moves to a trait–based under-standing of the link between differences in species performances, species interactions,and the processes determining community assemblies (McGill et al. 2006, Westoby &Wright 2006). Our Results shed some light in to this matter, as we show how differ-ences in mean traits and the inter–specific variability of these determines the small–scale community assembly of native and aliens, while the match in these factors withthe environment shapes the large–scale distribution of a species.

We realize that our database and analysis has limitations, specifically related to ourability to distinguish the smaller scale dynamics (e.g. the effect of alien and native traitsintra–specific variation) and the uneven coverage of different areas across the world.Nonetheless, the large taxonomical and geographical coverage of the compiled databaseallowed us to make solid generalizations on the BGD variance partitioning across dif-ferent ecological scales. Also, we believe that the observed patterns are not an artefactof sample size or of the used compilation scale, as the observed trends were consistentfor all traits, multidimensional comparisons and alternative contrast criteria.

We conclude that different spatial scales unequally contribute to the explained traitvariation between native and invasive plants, where small scale trait–based sorting ofspecies and large scale trait–driven filtering jointly drive native–alien community as-sembly.

5 The environment does notregulate differences in leaf traitsbetween aliens and nativesAlejandro Ordonez Gloriaab, and Han Olffa

Abstract

Previous studies comparing conditions of high versus low resource availability havepointed at differences in key traits that allow aliens to benefit much more from highresource availability than natives. We generalize this idea by exploring how trait dif-ferentiation between aliens and natives changes along continuous resource availabilitygradients.

We constructed a database of three leaf traits (e.g. SLA, Amass and Nmass) importantfor plant carbon capturing strategies covering 2448 native and 961 alien species over 88locations worldwide.

Using rank correlations and mixed effect linear models, the relations between traits ofaliens or natives and climatic, edaphic and human disturbance gradients were assessed.Then, we determined how the differences in traits between natives and aliens changedalong the same gradients.

On average, across all environments, aliens have higher SLA (2%), Nmass (16%) andAmass (5%) values than natives, both globally and when controlling for co–occurrence.However, these traits changed the same way in natives and aliens along the evaluatedenvironmental and disturbance gradients. Therefore, the magnitude of trait differencesbetween co–occurring aliens and natives remained the same along each of the environ-mental or disturbance gradients.

Taken together, leaf traits of aliens and natives were positively correlated with sig-nificant shifts in groups mean trait combinations along a common slope. Multi–traitcompositional differences showed no relation with any of the evaluated gradients, indi-cating how environment alone does not explain the observed performance differencesbetween plant types.

We suggest that although increased resource availability benefits plant performance,these benefits are the same for both aliens and natives. This invalidate the hypothesisthat specifically high resource availability promotes invasions by allowing aliens to out-perform natives due to differences in key traits.


5.1 Introduction 71

5.1 Introduction

Only a small fraction of all introduced organisms become invasive (Richardson & Pysek2006), making the understanding of ”why” and ”how” some introduced plants andanimals become successful invaders vital to maintaining native community biodiversityand ecosystem functioning (Srivastava & Vellend 2005). To achieve this understanding,two different methodological approaches have been used: i) a species focused approach,aiming to determine which characteristics/traits make a given species invasive; and ii)a site based approach, focused on determining which factors make a given locationsusceptible to invasions.

Results from the species based approach (mainly based on comparisons of co–occurringaliens and natives) have provided some generalizations on the attributes of successfulaliens. Specifically, analyses comparing regional and global species pools of nativesand aliens have found that aliens have faster grow rates, higher leaf nutrients con-tents and specific leaf areas, shorter life cycles, devote more resources to reproduc-tion and produce more seeds that are better dispersed and germinate faster (Grotkoppet al. 2002, Leishman et al. 2007, Leishman et al. 2010, Ordonez et al. 2010, Pysek& Richardson 2007, van Kleunen et al. 2010). Additionally, different sets of traits haveshown to confer advantages to aliens in disturbed areas (e.g. traits promoting high repro-duction rates and rapid spread), mesic–conditions (e.g. fast growth and resource acqui-sition), and high fertility (e.g. higher resource use efficiency, reduced investment in de-fenses). Together this illustrates how multiple traits contribute to the success of an alienand that the significance of individual or multiple traits is context–dependent (Moles,Gruber & Bonser 2008, Richardson & Pysek 2006, Thompson et al. 1995, Thompson& Davis 2011).

In the case of site–based approaches, both biotic (e.g. effects of herbivores or pathogens)and abiotic conditions (e.g. effects of pH or nutrient availability) have been proposed asdeterminants of the susceptibility of a community to accept new members. For exam-ple, the ”fluctuating resources theory of invasibility” (Davis, Grime & Thompson 2000)directly links the success in an area of a given alien with temporal excesses in resourceavailability. Under this framework, human disturbances promote invasions through en-hancing resource availability. (Davis et al. 2000, Mack et al. 2000, Thompson & Davis2011).

Few studies have managed to link the species and community approach due to thelack of adequate information for large number of plant species, over an equally largenumber of locations. As more distribution, trait and environmental information becomesavailable; testing the link between species and community–focused approaches has be-come easier. The most promising approach linking attributes of aliens to the suscepti-bility of a community being invaded is the use of site–based comparisons of key traitsalong large scale environmental and disturbance gradients.

The use of performance related traits (such as specific leaf area, or the maximumphotosynthetic rate per unit leaf area) is important for understanding differences in per-formance between natives and aliens. This is due to the central role of these traits inthe carbon fixation strategies of plants, one of the major axis of variation in plant eco-

72 Environment does not regulate differences in leaf traits

logical strategies. Additionally, the success of aliens is often attributed to their capacityfor fast growth, particularly when resources are not limiting (e.g. due to higher carboncapturing rates in high nutrient sites). Comparing how aliens and natives perform underhigh and low resource availability conditions thus helps us understand the mechanismsof invasions.

The relations of trait differences between aliens and natives and nutrient supply (highvs. low) have been seldom studied (for examples see Funk & Vitousek 2007, Leishman& Thomson 2005, Leishman et al. 2010, Muth & Pigliucci 2006). These studies sug-gest that specifically under high nutrient supply rates, aliens outperform natives due tocompetitive release (Davis et al. 2000) and/or due to reduced herbivory/parasitism rates(Blumenthal 2005, Blumenthal 2006, Blumenthal, Mitchell, Pysek & Jarosik 2009).Alternatively, under low resource availability aliens have been generally seen as notparticularly favored, as natives and the environment keep them better ”under control”,despite their plasticity (Richards, Bossdorf, Muth, Gurevitch & Pigliucci 2006).

The aim of this work is to explore how performance differentiation between aliens andnatives changes along continuous resource availability gradients. For this we compileda global database of continuous plant traits associated to the leaf economics spectrum,and included information on climate, soil nutrient availability, and human disturbanceregime at each site. Using this database, rank correlations and mixed effect linear modelswere used to determine the relations between traits of aliens or natives and climatic,edaphic and human disturbance gradients were assessed. Lastly, we determined howthe differences in traits between natives and aliens changed along the same gradients.

5.2 Methods

5.2.1 Database compilation and selection of traits

We focussed on three traits: specific leaf area, photosynthetic capacity and leaf nitrogencontent, Together, they describe a species’ position along the leaf economics spectrum(the balance in carbon gains and losses of leafs; Westoby et al. 2002, Wright et al. 2004).Specific leaf area (SLA cm2 × g−1) reflects the area that a plant produces per unit of leafdry–mass. Photosynthetic capacity (Amass nmol× g−1 × s−1) is a measurement of a plantpotential photosynthetic assimilation rates per unit leaf mass. Leaf nitrogen content(Nmass g× g−1 or %]) is a measurement of the resource investment in the photosyntheticmachinery and possible losses due to herbivory. Together these traits covary along aspectrum that runs from opportunistic, fast growing species susceptible to herbivorythat are characterized by high SLA, leaf N concentrations, maximum photosyntheticand dark respiration rates, and short leaf lifespan, to species with the opposite suite oftraits that are more conservative, slower growing and better able to cope with herbivoryand desiccation.

Data sets were selected using literature searches and communication with authors ofspecific papers. We searched the ISI Web of Science using both individual, all combi-nations of the following keywords:”plant traits”, ”SLA”, ”leaf nitrogen”, ”maximum

5.2 Methods 73

photosynthetic rate”, ”LMA”, ”leaf size”, ”leaf nutrients”, ”leaf economics”, ”re-source use efficiency”, ”plant traits”, ”LHS”, ”plant physiology”, ”weed”, ”weeds”,”naturalized”, ”invasive”, ”exotic”, ”noxious”, ”introduced”, ”alien”, ”foreign”, ”non–native”. Only site–based data (geographically referenced) were used so that data on cli-matic, edaphic and human disturbance conditions could be reasonably attached to eachlocality. This resulted in a dataset with 2448 native and 961 alien species with infor-mation on one or more of the selected traits across 88 locations around the world. Itencompasses most climates, soil characteristics and human disturbance regimes. Thespecies list includes taxa from 226 families, 68 orders, covering over 415 monocots,2831 dicots, 63 gymnosperms, 36 ferns and allies species.

5.2.2 Trait differentiation between native and alien species

Native and alien species where compared using two alternative approaches: i) linear(generalized least squares and mixed effects) models using the observed variables andii) site based comparisons where the native–alien contrast is captured in log–responseratios and absolute differentiation levels. Using these two approaches we determineddifferences in individual traits between plant types, the effects of individual environ-mental conditions on each group of traits, and how the differences between aliens andnatives changes along the same environmental gradient. The used linear mixed modelsdetermined how the differences between native and aliens changed across sampled sites(i.e. significance of random slopes). Our linear and mixed effects models used speciesstatus (native or alien) as a fixed factor, and in the case of mixed effects models sampledlocations were used as random effects (using a random slopes and intercepts). Mod-els were compared using a log–ratios test to determine the significance of the randomcomponents. Regressions and test were implemented using the nlme package (Pinheiroet al. 2009) in R version 2.12 (R Development Core Team 2009).

The second set of comparisons (log-ratios and Absolute differences) was used tomeasure the relative and absolute differences between co–occurring alien and nativespecies across all sampled locations. Relative differences between plants groups weremeasured using log response ratios [i.e. log (alien trait / native trait)], a tool often usedin meta–analyses (Hedges et al. 1999). This measurement expresses the proportionalityof the changes across the sampled locations. It allows the identification of the directionand magnitude of the net differentiation between natives and aliens, while eliminatingor reducing the bias and variation associated with individual studies (Hawkes 2007).Additionally, we determined the absolute differences in traits between co–occurringalien and natives [i.e. alien trait–native trait].

5.2.3 Association with the environmental conditions

We used three different groups of variables to characterize the environmental–disturbanceconditions of the sampled locations: climatic factors, edaphic factors and human influ-ence. The climate at each site was captured by: total annual precipitation (mm × yr−1),mean annual temperature (C◦), mean potential annual evapotranspiration (mm × yr−1),


daily irradiance (WH×m−2), temperature seasonality (SD × 100) and precipitation sea-sonality (CV). These variables were used to characterize the environmental conditionsthat potentially limit the resource acquisition rates via photosynthesis. All tempera-ture and precipitation measured were derived from the WorldCLIM database (Hijmans,Cameron, Parra, Jones & Jarvis 2005, http://www.worldclim.org), the mean annual po-tential evapotranspiration was obtained from the 5–arcmin FAO global agro–ecologicalassessment study (Hoogeveen 2009, http://www.fao.org/geonetwork/srv/en/main.home)and daily irradiance was estimated using ArcGIS and the 5–arcmin resolution digital el-evation model used to construct the WorldCLIM database.

The edaphic characteristics of each site was described by the available water capacity(cm×m−1), pH measured in water (pH units), total nitrogen (g× kg−1), carbon nitrogenratio (C/N), effective cation exchange capacity or total exchangeable bases (cmolc ×kg−1), bulk density (kg × dm−3), total organic carbon content (g × kg−1) and the cationexchange capacity (cmolc × kg−1). These soil characteristics were used to represent thenutrient pools and quality of the organic matter available for plants on a site (Heal,Anderson & Swift 1997). All soil parameters were obtained from the 5–arcmin ISRIC–WISE derived soil map of the world (Batjes 2006).

Last, we used the human impact index (%) as a measurement of anthropogenic dis-turbance in each of the sampled locations. This index is a regionally consistent wayto represent land transformation, due to human activity (e.g. population density, landtransformation, accessibility and electrical power infrastructure) on a global scale. Itexpresses the continuum of human influence (ranging from 0% in natural areas to 100%for completely transformed habitats) stretched across the land surface. The impact in-dex was obtained from a rasterized map in 1km resolution (Sanderson, Jaiteh, Levy,Redford, Wannebo & Woolmer 2002, http://sedac.ciesin.columbia.edu/wildareas) andrescaled to 5–arcmin for use in this study.

The association between all available trait observations and climatic, edaphic andhuman disturbance measurements were quantified using two statistical methods: spear-man rank correlations and linear mixed models. Spearman rank correlations allowedus to determine non–parametric correlations between traits and site descriptors. Lin-ear mixed models allowed us to determine the relation between traits and environ-mental conditions, after accounting for the non-independence of the observations. Inboth of these analyses, environmental and disturbance metrics were used as fixed ef-fects; for mixed models, sampled site was included as a random factor to account forthe non–independence of trait observations at a site. As all traits were approximatelylog–normally distributed (right–skewed), a log10 transformation was used to improvenormality and homogeneity of variances.

To determine if the association between traits and climatic, edaphic or human distur-bance changed between aliens and native species, relative and absolute trait differencesof co–occurring alien and native species of alien species were regressed against eachof the evaluated edaphic and human impact variables. Using a mixed effect model-ing framework, the significance of the interaction between native/alien status and en-vironmental variable (homogeneity in the relation with the environment), and of thenative/alien status (differences in native and alien mean trait across the gradient) was

5.3 Results 75

evaluated, in order to test the dependence of native–alien differences on environmentalconditions.

5.2.4 Multivariate trait: position along the leaf economics spectrum

To determine possible changes in the coordination among analyzed traits between aliensand natives, the association between all traits pair–wise contrasts were evaluated usinga standardized major axis regressions (SMA; also known as reduced major axis slopes,Sokal & Rohlf 1995). This method is preferred to classical linear regressions as both thex and y axes are subject to biological variation. The bivariate relationships of aliens andnatives (that is SMA slopes) were tested for homogeneity between groups. In those caseswhere a common slope was detected, differences between SMA regressions interceptswere compared. Last, in those cases where no differences in slopes or intercepts werefound, we tested for shifts between plants types along the common fitted slope. As forregression analysis all traits were log10 transformed for analysis. SMA regressions andtest were implemented using the SMATR package in R (Warton & Ormerod 2007).

To summarize the multivariate variation in SLA, Amass and Nmass of aliens and na-tives, a principal components analysis (PCA) was used to reduce the multi–trait vari-ation down to one main axis. This main axis (i.e. PCA–1) in this case represents themultivariate leaf economics spectrum (Wright et al. 2004) and captures the trade–offsbetween the investments of nutrients and dry mass in leaves and the rate of return interms of carbon acquisition. All traits were log10–transformed prior to the analysis. Bymeasuring the association strength between PCA–1 species scores as an additional mul-tivariate trait and climatic edaphic and human disturbance variables for alien or nativespecies, we were able to determine possible shifts along the resource acquisition axisalong these environmental and disturbance gradients.

As for individual traits, the relation between alien or native individual species PCA–1scores (as a multivariate trait) and environmental/disturbance parameters were evaluatedusing Spearman rank correlations and mixed effect models. Additionllay, the relationbetween alien–native relative and absolute differences and climatic edaphic and humandisturbance variables was evaluated.

5.3 Results

5.3.1 Trait differentiation between native and alien species

For comparisons involving all sampled individuals, without consideration of occurrencelocation, aliens showed significant higher SLA (2.1 [1.2 3.1]%), Amass (4.7 [1.7 7.6]%),and Nmass (15.6 [10.3 20.9]%). This trend was also observed in site–controlled compar-isons. For these, differences between plant types, although still significant (i.e. SLA: 2.4[1.3 3.5]%, Amass: 4.8 [1.1 8.4]% and Nmass: 13.4 [6.7 20.1]%), were slightly different(broader 95%C.I.) than for site uncontrolled contrasts. Log–likelihood comparisons ofcommunity controlled and uncontrolled models provided strong evidence of significant


●

●

●

●

Log−

resp

onse

rat

io [l

n(A

lien/

Nat

ive)

]

−0.

10.

00.

20.

4

SLA

Am

ass

Nm

ass

Mul

ti

●

●

Abs

olut

e di

ffere

nces

[Alie

n−N

ativ

e]

−10

020

4060

SLA

Am

ass

●

●

−0.

50.

00.

51.

0

Nm

ass

Mul

ti

Figure 5.1 Differencesbetween alien and native plantsspecific leaf area (SLA), foliarnitrogen per mass bases(Nmass), maximumphotosynthetic rate per massbases (Amass), and the positionin the multi–trait leaf economicsspectrum (Multi) between alienand native plants. Points markthe mean between groupdifferentiation and whiskersabove and below the pointindicate the 95% confidenceintervals. Number of contrastedcommunities: 72 SLA; 22 Amass;59 Nmass and 17 for Multi.

between sites differences in the size and direction of the alien–native dissimilarity (log–likelihood model comparisons p < 0.001 for each of the evaluated traits). Based onthis significant effect of occurrence location, the results presented hereafter refer to sitebased alien–native contrasts.

Contrast of aliens and natives co–occurring on a site indicated significant betweengroup differences for all evaluated traits, with aliens expressing higher SLA, Amass andNmass than those of co–occurring natives (Fig. 5.1). These differences were consistentfor both relative and absolute measurements of dissimilarities (Fig. 5.1 lower panel).When trait contrast controlled for growth forms (i.e. woody and non–woody species)

5.3 Results 77

●

●

●

●

Woody

Log−

resp

onse

rat

io [l

n(A

lien/

Nat

ive)

]

−0.

050.

000.

050.

100.

150.

200.

25

SLA

Am

ass

Nm

ass

Mul

ti

●

●

Abs

olut

e di

ffere

nces

[Alie

n−N

ativ

e]

−10

010

2030

SLA

Am

ass

●

●

−0.

6−

0.4

−0.

20.

00.

2

Nm

ass

Mul

ti

●

●

●

●

Non−Woody

Log−

resp

onse

rat

io [l

n(A

lien/

Nat

ive)

]

−0.

20.

00.

20.

4

SLA

Am

ass

Nm

ass

Mul

ti●

●

Abs

olut

e di

ffere

nces

[Alie

n−N

ativ

e]

−20

020

4060

8010

0

SLA

Am

ass

●

●−

2−

10

1

Nm

ass

Mul

ti

Figure 5.2 Plots for the alien–native differences in specific leaf area (SLA), foliar nitrogen permass bases (Nmass), maximum photosynthetic rate per mass bases (Amass), and the position in themulti–trait leaf economics spectrum (Multi) of the two main plant growth forms (Woody: Shrubsand Trees and Non–woody: Graminoids and Herbs/Forbs). Number of contrasted communities:47 woody and 40 non–woody SLA; 17 woody and 7 non–woody Amass; 41 woody and 25non–woody Nmass; and 12 woody and 5 non–woody for Multi.

heterogeneous results were observed for comparisons based on absolute and net differ-ences (Fig. 5.2). Absolute differences indicated, for all evaluated traits, no–significantdifferences between co–occurring aliens and natives. Log–response ratios, on the con-trary, indicated significant differences between species Nmass for both groups, and fornon–woody species also in SLA.

5.3.2 Association of traits and environmental parameters

Associations between traits of alien and natives and environmental parameters, mea-sured using Spearman rank correlation coefficients indicated a consistent and significant


change in traits of both native and alien species along climatic and edaphic gradients(Table 5.1). These association trends were confirmed by linear mixed model regres-sions analyses (Appendix D).

In the case of between alien–native differences, Spearman rank correlations indicatedno significant association to the analyzed climatic, edaphic or human disturbance factors(Table 5.2). This non–significant association between trait differences and evaluatedpredictors was confirmed by linear regressions analyses (Appendix E). These trendswere consistent for both absolute and relative differentiation and for specific growthforms. Together, these results support the idea of no changes in the association amongtraits and environmental parameters between aliens and native species.

When the used edaphic and human disturbance factors where summarized as part ofa fertility, or disturbance gradient (using PCA to determine the main axes of environ-mental variation; PCA–1 to PCA–3), traits of both native and aliens showed significantassociations with these (p < 0.001). For both alien and native species there was a shiftfrom species with low SLA, Nmass and Amass at low soil fertility and human disturbancetowards species with high SLA, Nmass and Amass at the opposite end of the soil fertilityand human disturbance gradient (Fig. 5.3). Comparisons of these relations betweennative and aliens indicated that slopes did not vary significantly, no significant differ-ences in y–intercepts were detected and there was no significant difference betweenaliens and natives position along the fertility/disturbance gradient. Together with thenon–significant association between trait differences and PCA axes of environmentalvariation, this suggests how the association between environmental conditions and en-vironmental factors is held constant regardless of the alien or native status of a givenplant.

5.3.3 Influence of climate in native and aliens multivariate trait spacedifferentiation

Principal components analysis (PCA) was used to reduce multivariate variation in SLA,Nmass and Amass down to the main axis of trait variation (i.e. PCA–1). This axis ex-plained 68% of the total trait variation among sampled species; additionally, it was pos-itively correlated SLA, Amass and Nmass (thus PCA1 can be consider to represent the leafeconomics spectrum). Comparison of leaf trait relationships among plant types showedthat SMA slopes did not vary significantly between alien and native species for neitherof the pair–wise comparisons (p ≥ 0.05 for all comparisons). After fitting a commonslope, there were no significant differences in y–intercepts between groups. Nonethe-less, significant shifts along a common SMA regression were detected between alienand native species, indicating how shifts in a trait causes shifts in associated traits (Fig.5.4). Comparisons within plant growth forms indicated that slopes did not vary signifi-cantly, no significant difference in y–intercepts were detected and there was no signifi-cant difference between aliens and natives position along the leaf economics spectrum.

When aliens and natives positions along this spectrum (i.e. the scores along PCA–1) were compared (Fig. 5.1), significant differences between these two groups were

Table5.1

Correlations

between

alienand

nativeleaftraits

andsite

climatic,edaphic

orhuman

disturbancefactors.

Association

between

variablesw

asdeterm

inedusing

spearman

rankcorrelations

(ρ).Num

berofspecies(N

Nat :N

umberof

nativespecies

andN

Ali :N

umberofA

lienspecies

)isalso

indicated.Significantassociations

arem

arkedas

with

boldcharacters.U

sedenvironm

entalvariablesw

ereeitherclim

atic[i.e.totalannualprecipitation

(mm×

yr−

1),mean

annualtem

perature(C◦),m

eanpotentialannualevapotranspiration

(mm×

yr−

1),dailyirradiance

(WH×

m−

2),temperature

seasonality(S

D×

100)andprecipitation

seasonality(C

V)],edaphic

[i.e.Available

watercapacity

(cm×

m−

1)–TAW

C,pH

measured

inw

ater(pHunits)–

PH

AQ

,Totalnitrogen(g×

kg−

1)–TO

TN,C

arbonnitrogen

ratio(C

/N)–

CN

RT,E

ffectivecation

exchangecapacity

(cmolc×

kg−

1)–E

CE

C,B

ulkdensity

(kg×

dm−

3)–B

ULK

,Totalorganiccarbon

content(g×

kg−

1)–

TOTC

andC

ationexchange

capacity(cm

olc×

kg−

1)–C

EC

S];and

human

impact(i.e.H

uman

impactindex

(%)–

HII).

PredictorSL

AA

mass

Nm

assM

ulti[N

Nat

=2100]

[NA

li=

1180][N

Nat

=329]

[NA

li=

186][N

Nat

=1265]

[NA

li=

614][N

Nat

=267]

[NA

li=

131]

Native

ρA

lienρ

Native

ρA

lienρ

Native

ρA

lienρ

Native

ρA

lienρ

HII

0-0.34

-0.027-0.046

0.0740.061

-0.188-0.041

AnnPre

0.2990.124

-0.159-0.045

-0.215-0.181

0.013-0.088

AnnT

mp

-0.086-0.243

-0.1690.09

-0.286-0.23

-0.0520.136

EvptY

r0.11

0.207-0.231

-0.105-0.217

-0.158-0.177

-0.172D

ayIrr0.068

-0.1550.001

-0.028-0.019

0.031-0.059

-0.064T

mpSeas

-0.0470.287

0.182-0.041

0.2720.151

0.013-0.087

PreSeas-0.167

-0.4070.159

0.064-0.107

-0.0770.005

-0.001TA

WC

0.16-0.002

0.014-0.068

0.150.025

-0.029-0.009

PHA

Q-0.246

0.010.334

0.1760.061

0.0170.327

0.361TO

TN

0.2960.069

0.016-0.187

0.0520.083

-0.043-0.122

CN

RT

0.233-0.09

-0.127-0.035

-0.2050.012

-0.087-0.161

EC

EC

-0.087-0.215

-0.0090.059

0.140.077

-0.0910.174

BU

LK

-0.23-0.035

-0.2040.012

-0.104-0.07

-0.0270.056

TOT

C0.269

-0.130.016

-0.1280.01

0.079-0.026

-0.118C

EC

S0.071

-0.144-0.006

-0.0060.055

0.053-0.101

0.083

Tabl

e5.

2C

orre

latio

nsbe

twee

nal

ien

and

nativ

ele

aftra

itsdi

ffere

nces

and

site

clim

atic

,eda

phic

orhu

man

dist

urba

nce

fact

ors.

Ass

ocia

tion

betw

een

varia

bles

was

dete

rmin

edus

ing

spea

rman

rank

corr

elat

ions

(ρ).

Num

bero

fspe

cies

(NN

at:

Num

bero

fnat

ive

spec

ies

and

NA

li:N

umbe

rofA

lien

spec

ies

)use

dis

also

indi

cate

d.S

igni

fican

tass

ocia

tions

are

mar

ked

asw

ithbo

ldch

arac

ters

.Use

den

viro

nmen

talv

aria

bles

asin

Tabl

e5.

1.

Pred

icto

rSL

A[N

=58

]A

mas

s[N

=20

]N

mas

s[N

=49

]M

ulti

[N=

15]

Log

–res

p.A

bs.D

iff.

Log

–res

p.A

bs.D

iff.

Log

–res

p.A

bs.D

iff.

Log

–res

p.A

bs.D

iff.

HII

-0.1

08-0

.131

-0.0

19-0

.047

-0.1

19-0

.116

0.27

20.

233

Ann

Pre

-0.0

180.

034

0.28

0.32

-0.0

74-0

.146

-0.2

63-0

.256

Ann

Tm

p0.

111

0.13

10.

077

0.14

6-0

.002

-0.0

32-0

.041

-0.1

23E

vptY

r-0

.034

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5.3 Results 81

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Figure 5.3 Correlations between alien and native leaf traits and compound measurements of soilfertility (i.e. axis of covariance between soil parameters estimated using PCA) and disturbance.Used edaphic factors where: Available water capacity (cm × m−1) – TAWC, pH measured inwater (pH units)– PHAQ, Total nitrogen (g × kg−1) – TOTN, Carbon nitrogen ratio (C/N) –CNRT, Effective cation exchange capacity (cmolc × kg−1) – ECEC, Bulk density (kg × dm−3) –BULK, Total organic carbon content (g × kg−1) – TOTC and Cation exchange capacity(cmolc × kg−1) – CECS; and human impact (Human impact index (%) – HII). For all theevaluated relations, ANOVA’s showed non–significant interaction between status (Alien orNative) and soil fertility.

observed (for both absolute and relative differences) with aliens expressing trait combi-nations that position them at the fast returns end of the leaf economics spectrum (largerPCA–1 values). This trend was also observed for associations within specific growthforms (Fig. 5.2).

Together these results support the idea that aliens and natives do not have funda-mentally different carbon capture strategies, but rather that aliens are positioned furtheralong the leaf economics spectrum towards faster growth strategies. This shift along theleaf traits trade–offs, translates in to the observed multi–trait differences between aliens


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Figure 5.4 Standardized majoraxis regression (SMA)relationships between specificleaf area (SLA), foliar nitrogen(Nmass) and photosyntheticcapacity (Amass). Black trianglesand dashed lines representaliens; grey circles and dottedline represent native species.Axes are log10 scaled

and natives co–occurring on a site and the higher SLA, Amass and Nmass values observedin aliens when compared to co–occurring natives.

Associations between the PCA–1 scores and environmental parameters (measuredusing spearman rank correlations) show no consisted associations between them (Table5.1). Linear mixed model correlation coefficients for alien and native species also showno significant association between traits and climatic, edaphic or human disturbancevariables (Appendix D). This pattern was also observed for within growth form com-parisons (r2 values ranged between 0.4 to 0.6 with p > 0.05 in all cases). In the caseof multi–trait differences between aliens and natives (measured as absolute and rela-

5.4 Discussion 83

tive differences in the position along the leaf economics spectrum), these also showednon–significant associations with either of the climatic edaphic or human disturbancevariables (Table 5.2). Together, these results provide evidence to the idea of a constantcarbon strategy between natives and aliens across different environmental conditions.

5.4 Discussion

Here we have found that alien species, as a group, differs from natives in both individ-ual traits and their positioning along the leaf economics spectrum; differences observedeven after controlling for area of co–occurrence. These trends, together with the sig-nificant variability in trait differentiation between sites (as illustrated by the significantrandom intercepts of linear mixed models) provide evidence to the context dependenceof the differentiation between natives and alien species.

The importance of the context of introduction emerges from the particular ecological–abiotic background a given species would face once introduced. We believe that ourresults support the idea of context dependence success of introductions. This meansthat, given the adequate conditions, any given species could and would be successfulwhen introduced. As a result, the success of a given introduced species is independentof area of origin, but rather, it is determined by it having a suite of traits enabling toexploit the new habitat (Thompson & Davis 2011).

Although individual or multivariate traits varied with both climatic and edaphic fac-tors in a similar way to that reported on other works (e.g. Ordonez et al. 2009, Wrightet al. 2005) the relations did not change between native and alien plants. This indicateshow regardless of the plant type and area or origin, the trait–environment associationswill converge. This is perhaps, a result of the unavoidable restrictions imposed by phys-ical, physiological and evolutionary factors.

Here we have also shown how alien species both share the same carbon assimila-tion strategies (i.e. there are constrained within the same leaf economic spectrum) andexpress significantly different leaf traits (in both absolute and relative terms) than co–occurring natives. These differences between groups, are in line with other regionaland global works comparing native and aliens leaf traits (Funk & Vitousek 2007, Gon-zalez, Kominoski, Danger, Ishida, Iwai & Rubach 2010, Gulias 2003, Leishman &Thomson 2005, Ordonez et al. 2010, Penuelas, Sardans, Llusia, Owen, Carnicer, Gi-ambelluca, Rezende, Waite & Niinemets 2010, van Kleunen et al. 2010) and the associ-ation between them (Leishman et al. 2007, Leishman et al. 2010, Penuelas et al. 2010).The observed trait differences reflect shifts along the common slope describing the axisof variation (PCA–1 multivariate differences) positioning aliens at the fast return endof the leaf economic spectrum (i.e. expressed in higher SLA, Amass and Nmass traitvalues) when compared to co–occurring natives. The reported positional differences,support the idea that under particular conditions, aliens have a higher growth capac-ity than their native counterparts (Baruch & Bilbao 1999, Burns & Winn 2006, Funk& Vitousek 2007, Gonzalez et al. 2010, Grotkopp et al. 2002, Gulias 2003, Hamiltonet al. 2005, Leishman et al. 2010).


The generality of these results across the sampled gradient of climatic, edaphic andhuman impacts supports the hypothesis that invasive organisms are able to outperformnatives in both low– and high– resource/disturbance environments. This is in line withLeishman et al. (2007) and Leishman et al. (2010) works suggesting that successfulalien species have the same resource use efficiency as co–occurring natives, and onlylocal conditions will determine the level of differentiation between groups.

An important factor to address here is how these differences relate to the climatic,edaphic and human disturbance regime aliens and native species are growing. Severalconceptual frameworks have addressed the link between alien species success and en-vironmental conditions, resource availability, disturbance, and release of enemies (e.g.Blumenthal 2005, Blumenthal 2006, Davis et al. 2000, Gonzalez et al. 2010). Wheneach trait was compared to individual environmental factors, no relation to individual ormultivariate trait differences was found. This result, both supports the idea of changesin attributes along resource and human disturbance gradients and indicate how the dif-ferentiation between these groups is kept constant along these gradients. We supposethis is because successful aliens need to express higher resource uptake, growth, and re-production output across both low and high nutrient and disturbance regimes to enablethese organisms to successfully spread into new habitats.

Based on our results, we strongly consider that alien species are successful not be-cause they have different resource acquisition strategies or lower nutrient requirements;but rather they express a suite of traits that provide them a competitive advantage fromco–occurring natives (e.g. higher specific leaf areas, shorter life cycles, devote more re-sources to reproduction and produce more seeds that are better dispersed and germinatefaster). As suggested by Thompson & Davis (2011) and Leishman et al. (2010) thisindicates how the success of any given alien is determined by both it having a suite oftraits enabling them to exploit the new environment and the biotic–abiotic–disturbancesetup it is confronted with in the introduced area.

A last factor to consider are the possible effects of changes in the population of natu-ral enemies (herbivores and/or parasites) compared with coexisting native species, givenits potential interaction with both disturbance, and resource availability (e.g. the re-source enemy release hypothesis; Blumenthal 2005). Although it could not be specif-ically tested here (due to lack of adequate information on enemies abundance or pres-ence) we strongly believe that the escape form enemies by aliens, once introduce to anew area enhances, and possibly causes, the differences between alien–native positionsalong the leaf economics spectrum. This will be especially the case for areas with highresource/disturbance rates. As suggested by Blumenthal (2005), Blumenthal (2006) andBlumenthal et al. (2009), this is the result of possible higher performance gains (mov-ing to the fast end of the resource acquisition spectrum) from enemy release in highresource/disturbance areas. As experimental evidence provides a strong support for thisidea (Blumenthal et al. 2009), there is still a need for large scale field based con–specificcomparisons, aiming to evaluate how alien spices in high resource/disturbance situationsare more strongly released from enemies than those under lower resource/disturbanceconditions.

In this work we have shown how aliens have significantly different leaf traits than

5.4 Discussion 85

co–occurring natives. Nonetheless, these two groups do not have fundamentally differ-ent carbon capture strategies, but instead all fall along the same axis of variation thatdescribes the leaf economics spectrum of plants. We have also shown that althoughindividual traits change in a predictable way with environmental conditions, trait dif-ferences (in uni– and multi–trait spaces) show no relation with climate, soil or humandisturbance.

In summary, we believe that differences between aliens and natives do not reflectthe resource supply condition in a site. Thus we consider that is the interplay betweenthe biological setup and the environmental conditions a given species face in the newenvironment, in association with the traits of the invaders, determine whether or notinvasion will be successful.

Part IV

Evolutionary perspective:Impact for predictingsuccessful aliens

6 Darwin’s naturalization conundrumrevisited: Linking phylogeneticrelatedness and trait similarityAlejandro Ordonez Gloriaab, and Han Olffa

Abstract

Two contrasting arguments have been proposed to explain the success of alien species:i) high relatedness to the native community is beneficial due to similar adaptations tothe environment; ii) low relatedness to the native community is beneficial due to lessniche overlap and less shared natural enemies.

We explored these alternatives in a large meta–analysis using both a consensus phy-logenetic tree and a database of leaf, height and seed traits of alien and native speciesco–occurring over 130 sites worldwide.

Our results show that co–occurring alien and native species are more phylogeneticallyand phenotypically similar than expected by chance. These trends are consistent forindividual growth forms and different comparison criteria (i.e. all co–occurring natives,phylogenetically closest native and average native). Additionally, our results suggestthat environmental filtering and phylogenetic trait conservatism are more important indetermining alien success than resource competition.

The results presented here oppose Darwin’s naturalization hypothesis and indicatehow measures of taxonomic relatedness and trait overlap are useful predictive tools forscreening the risk of novel species becoming invasive.


90 Darwin’s naturalization conundrum revisited

6.1 Introduction

The two main questions that have driven the research agenda of invasion ecology are:what makes a given introduced species invasive? and what makes a given communityprone to invasion? (Drake & International Council of Scientific Unions. Scientific Com-mittee on Problems of the Environment 1989). Our ability to answer these questions iskey for predicting possible invaders and preventing the ecological and economic lossesassociated with them (Mack et al. 2000).

Recent interest in merging these two questions has focused on how niche overlap (inspace and time) determines the likelihood of two species co–existing. As a result, twoalternative mechanisms have been proposed as explanations for the observed patterns ofsuccessful introductions: trait dissimilarity (e.g. aliens differ from natives and can there-fore partition and tap in to different resources) or habitat filtering (e.g. aliens and nativetraits are more similar due to relatedness and common adaptations to stress factors, suchas drought or salinity).

Perhaps one of the most promising approaches to discriminate between these twomechanisms has been the use of taxonomic (most commonly) or phylogenetic relat-edness (rarely used, but for examples see Cadotte et al. 2009, Jiang, Tan & Pu 2010,Strauss et al. 2006) as a measure of niche overlap. In invasion biology, the link betweenthe introduction success of alien species and their relatedness with native species hasbeen formalized as ”Darwin’s naturalization hypothesis” – here after DNH (Rejmanek1996). It states that closely related species will overlap more in their niches and intheir traits than less related species, making novel genera more successful in colonizingnew ranges than genera with native representatives (as argued by Violle & Jiang 2009).An alternative formulation of the role of phylogenetic relatedness and niche overlap istermed the ”Phylogenetic attraction hypothesis” – here after PAH (Strauss et al. 2006).It argues that introduced aliens that are closely related to native residents might haveimproved chances of naturalizing as they share similar pre–adaptations to the local en-vironmental conditions.

The recent increase in the amount, coverage and availability of large and detailed phy-logenies has allowed the evaluation of both DNH and PAH across regions using empiri-cal data. Nonetheless, most works on this topic have addressed these hypotheses as mu-tually exclusive rather than complementary explanations (Proches et al. 2008). This hasresulted in a mixture of patterns. For example, while some studies in continental NorthAmerica found support for DNH (Mack 1996, Rejmanek 1996, Strauss et al. 2006),others in New Zealand have provided support for PAH (Diez et al. 2008, Duncan &Williams 2002); while in Mediterranean islands an idiosyncratic relation between relat-edness and alien success was found (Lambdon & Hulme 2006, Lambdon et al. 2008).

These conflicting results only clarify that more detailed analyses are required to de-termine both how alien plant species interact with closely related natives, and the effectof this relation in the success of introduced species.

In this study we describe the phylogenetic community structure patterns of alienspecies in relation to co–occurring natives, and use it to determine the link betweenalien–native relatedness and introduction success. To achieve this we used three types

6.2 Methods 91

of data (phylogenetic, phenotypic and spatial) to determine the relation of aliens to theintroduced community. These factors are often confounding but we separate them usinga unique global database of co–occurring native and alien plants paired according totheir phylogenetic relatedness and spatial co–occurrence patterns.

Specifically, we evaluated if the phylogenetic community patterns of alien species inrelation to co–occurring natives show an over–dispersed (as predicted by DNH) or clus-tered structure (as predicted by PAH). Additionally, to assess the possible mechanismsgenerating the observed phylogenetic structure, we examine the relationship betweentrait evolution (conservative vs. convergent) and the patterns in trait similarity (clus-tered vs. over–dispersed) of these pairs of alien and native species within communities.

6.2 Methods

6.2.1 Selection of traits and database compilation

Our analysis focuses on three traits: specific leaf area (SLA in cm2 × g−1), individualseed weight (SWT in mg) and typical maximum plant height (Hmax in cm). These de-scribe key ecological strategies related to a species’ ability to disperse, establish, acquirewater and nutrients, and photosynthesize (Westoby et al. 2002). SLA is defined as freshleaf area divided by dry leaf mass; it provides a measure of the allocation of biomassto light harvesting (i.e. an index of a species position along the ”leaf economics spec-trum”) and strongly covaries with nitrogen and photosynthetic rate per unit leaf massand leaf life span (Reich et al. 1997, Wright et al. 2004). Hmax of adult plants was usedas an index of a species position along the height spectrum as it relates to the trade–offs between opposing costs and benefits associated with light interception (e.g. tallerspecies or individuals are able to intercept more light) (Falster & Westoby 2003, West-oby et al. 2002). Last, SWT was used as a measure of the investment on seed production,and is associated with life history strategies, dispersal distances, regeneration biology,and competition–colonization trade–offs (Moles & Westoby 2006, Westoby et al. 2002).

A database of SLA, SWT and Hmax for native and alien species was compiled frompublished as well as unpublished sources. Studies reporting trait differences betweenalien and native species only under natural conditions were included in the database(greenhouse studies were discarded). Each entry has a location (e.g. latitude and longi-tude), habitat and environmental conditions assigned based on published information ora reasonable approximation. The database was built by searching the ISI–Web of Sci-ence (1945 – 2010) using relevant keywords (e.g. ”plant traits”, ”SLA”, ”LMA”, ”leafsize”, ”leaf nutrients”, ”plant height”, ”seed size”, ”seed weight”, ”seed production”,”plant traits”, ”LHS”, ”plant physiology”, ”weed”, ”weeds”, ”naturalized”, ”inva-sive”, ”exotic”, ”noxious”, ”introduced”, ”alien”, ”foreign”, ”non–native”), examin-ing the references in these publications, and communicating directly with large databasemanagers. A dataset was considered suitable if it included measurements for any of thetraits of interest, for at least four co–occurring native or alien species. A detail descrip-


tion of the database compilation procedure and the used data are provided as SupportingInformation (Appendix A).

In total, our database contains 4993 species (3824 with measures in the native, 1010in the introduced and 159 on both ranges) from 187 plant families sampled over 130communities for which information for any of the three traits of interest was avail-able. The included species represent a wide range of growth forms covering 4456 dicotspecies and 537 monocots .

Datasets were summarized into 130 spatially aggregated grids across the globe bygrouping together all the measurements within a 5km radius (here after grid-communities).Details of the communities and their distribution is presented in Appendix A. Traitswere summarized for each species within a cell by calculating the geometric mean ofall measurements of a particular attribute across all studies within the same grid. Thisscale was selected as a spatial delineation of different communities’ as it permits sum-marizing the information from different sources at a spatial scale that minimizes theeffects of methodological variability of the compiled studies. It should be noted thatthese are not communities in the classic sense but rather defined as species that co–occur in a defined, small–scale geographic area (sensu Ricklefs 2008). It is assumedthat these species are more likely to interact with each other than with species that donot locally co–occur. Additionally environmental aspects for each community can beconsider generally homogeneous (e.g. climates, overall soil type, and vegetation phys-iognomy).

In each of the plant communities, occurring species were classified using Richardson,Pysek, Rejmanek, Barbour, Panetta & West (2000) definitions of native, alien, natural-ized and invasive species. Consequently, the term ”alien” throughout this paper refersto those species whose presence at a site is due to human mediated intentional or ac-cidental introduction. This includes both naturalized (aliens that reproduce consistentlyand sustain populations over many life cycles without direct intervention by humans), aswell as invasive species (naturalized species that produce reproductive offspring, oftenin very large numbers, at considerable distances from parent plants).

6.2.2 Phylogeneny assembly

A phylogeny for all the species in the database (referred to as the database mega–tree hereafter) was built using the stand–alone version of PHYLOMATIC (Webb &Donoghue 2005). The database mega–tree was constructed using the maximally re-solved seed plant phylogeny as a backbone (APG3 derived megatree), which is an onlinephylogenetic summary that is continually updated by the Angiosperm Phylogeny Group(Stevens 2009). Branch lengths of our database mega–tree were estimated using theBLADJ (Branch Length ADJustment) procedure in PHYLOCOM (Webb et al. 2008)where node ages were established using the divergence times estimated by Wikstromet al. (2001); therefore our estimates of phylogenetic distance are in millions of years.The phylogenetic trees build from comparisons to super–trees are not fully resolved (weresolved most families to genus level) as using molecular data to determine both phy-logenetic topology and branch lengths is not possible in our study as a large number of

6.2 Methods 93

the species studies have no records in GenBank. However, implementing our method isan improvement over using only a taxonomical topology alone. A detail description ofthe phylogenetic reconstruction process is described in Appendix A.

6.2.3 Evaluating the phylogenetic community structure

For each grid-community, the phylogenetic structure of aliens in relation to the nativecounterpart was evaluated by comparing i) the degree of evolutionary conservatism oftraits (trait evolution), and ii) the level of community and trait over–dispersion (phy-logenetic structure and trait similarity). Because phylogenies, traits and co–occurrencedistances are not independent from each other, the three–way association between co–occurrence, phylogeny, and traits was assessed using a null model approach (Gotelli &Graves 1996).

Null modelsWe specified three classes of null models, where each one was iterated 1000 times. Nullmodel 1 kept both community and trait compositions constant while species were ran-domized across the phylogeny. Null model 2 randomized the trait composition whilekeeping the phylogenetic and community composition constant. A stratified shufflingwas performed for model 2, where randomizations of species traits occurred only be-tween species of the same growth form and within communities of the same habitat(specified using Holdridge’s life zones; Holdridge et al. 1971). Last, null model 3 ran-domized the spatial distribution of the species across all sampled communities, but wasconstrained to communities in the same habitat type. All randomizations were based onpresence/absence data using Gotelli (2000) independent swap algorithm because abun-dance information on each community was not available. All null model randomizationswere run for both the complete database (indicated with the sub–index a) and withineach community (indicated with the sub–index b).

Comparison criteriaTo determine the effects on the observed (di)similarity patterns between alien speciesand the native community; we analyzed the level of alien–native differentiation usingthree different comparison levels. This allowed us to evaluate how inclusiveness in thealien native comparisons (i.e. number and type of natives aliens are compared to influ-ences both phylogenetic and trait structure). First, aliens were compared to all membersof the native community (fully inclusive comparisons) to evaluate the role of similarityin alien success. Second, we compared each alien species to the average native specieswithin that community to assess if successful aliens have attributes that are novel tothe native community. Lastly, individual aliens species were compared to their closestnative relative species (based on the phylogeny) to assess if closely related species aremore likely to coexist because of shared attributes (e.g. Darwin’s naturalization hypoth-esis, Rejmanek 1996).


Analysis of trait evolutionAs shown in other studies (Cavender-Bares, Ackerly, Baum & Bazzaz 2004, Cavender-Bares, Keen & Miles 2006) the convergence or conservatism of traits can be tested bycorrelations between trait differences and phylogenetic distance between species. Usingthis approach, we correlated the pair–wise trait differences of aliens to natives (mea-sured as the Euclidean distance between log10–transformed traits) to the phylogeneticdistances (measured as the intergroup phylogenetic dissimilarity in Ma) of the samespecies pair. The level of conservatism or convergence of evaluated traits was deter-mined by comparing the observed correlation coefficients to those generated from nullmodel 1 and 2. Based on these correlations and using a two–tailed test, we determined iftraits are conserved (a positive correlation relative to the null model), convergent (a neg-ative correlation relative to the null model) or no signal is detected (correlation cannotbe distinguished from the null model).

Co–occurrence within communitiesWe examined the degree of co–occurrence of alien species and their closest phylo-genetically related native species (i.e. sister taxa) by measuring the proportional co–occurrence across sampled locations (based on presence/absence data) in relation tothe phylogenetic distance between them. We specifically aimed to determine if alienspecies are phylogenetically clustered (high phylogenetic similarity) or over–dispersed(low phylogenetic similarity) in relation to the native community. The degree of co–occurrence was tested against null models 1 and 3. Communities were classified asover–dispersed (observed association is positive relative to the null model), convergent(observed association is negative relative to the null model) or no signal (observed as-sociation cannot be distinguished from the null model).

Trait similarity within communities in relation to trait evolutionLastly, we determine the level of phenotypic similarity between co–occurring alien andnative species by measuring the correlation between alien to native pair–wise trait dif-ferences and the degree of co–occurrence of the species pair. This measurement allowedus to establish the level of phenotypic clustering or over–dispersion of alien species inrelation to co–occurring natives. Here we follow the definitions described by Cavender-Bares et al. (2006); phenotypically clustered species show high trait similarity withincommunities while over–dispersed species show low trait similarity within communi-ties.

Using pair–wise comparisons of closely related alien and native species we inves-tigated the way phenotypic similarity relates to trait evolution by measuring the levelof association between trait conservatism and trait similarity. We ranked the observedsimilarity and phylogenetic signal of each trait relative to 1000 simulations from nullmodels 1 and 2. The similarity and signal from the simulations of models 1 and 2 werecompared to observed patterns of alien trait similarity within communities. The resultsprovide clues about alien community phylogenetic structure and possible ecologicalforces giving rise to the observed phylogenetic structure of alien species.

6.3 Results 95

6.3 Results

6.3.1 Trait conservatism or convergence

Results of the analyses contrasting aliens to all natives showed evolutionary conser-vatism of all evaluated traits (Fig. 6.1). This pattern was also observed for SLA andSWT of woody species (trees and shrubs) and non–woody (herbs/forbs and graminoids)but not for Hmax, which showed no significant phylogenetic correlation. In the case ofcreeper plants (vines or lianas), none of the evaluated traits showed a trait evolutionarysignal.

The evolutionary patterns of evaluated traits in the alien–to–native comparison dif-fered. Aliens showed conservatism of SLA and SWT and convergence of Hmax to thephylogenetically closest native. On the contrary, aliens showed Hmax conservatism andrandom evolutionary patterns for SLA and SWT when compared to the mean nativecommunity trait composition.

The robustness of the phylogenetic clustering of alien traits to those in the nativecommunity was confirmed by the convergence on similar results by different null mod-els (Table 6.1). Comparisons of the observed clustering of aliens using full null model(model 1a) and a community null model (model 1b) of phylogeny randomizationsshowed that the observed patterns of trait evolution are not dependent on the scale atwhich they are defined. Additionally, shuffling the trait matrix for the full dataset (nullmodel 2a) or only within a community (null model 2b) indicated that the phylogeneticconservatism of traits within communities is not the result of environmental gradientsdriving the trait assembly process.

6.3.2 Phylogenetic Structure of Communities

Correlations between the level of co–occurrence and phylogenetic distance were morenegative than expected by chance (Table 6.2), indicating that related species co–occurredmore often than random (i.e. a significant phylogenetic clustering). These results wereconsistent to random reshuffles of the species across the phylogeny (i.e. comparisons tonull model 1a and b) or randomization of the occurrence matrix (null model 3a and b).

When the pattern of phylogenetic clustering of alien species to the native communitywere evaluated by specific growth forms, various phylogenetic trends were observed.Woody species (trees and shrubs) were the only group showing consistent communityphylogenetic clustering for all evaluated traits, while the community composition ofboth non–woody species (graminoids and herbs/forbs) and vines/climbers showed noconsistent phylogenetic pattern.

6.3.3 Trait evolution and trait similarity within communities

Fully inclusive comparisons illustrate phenotypic clustering by alien species to the na-tive community for all the evaluated traits (horizontal axis in Fig. 6.2). This pattern be-came stronger when comparing phylogenetically similar native and alien species (Fig.


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SWT

12

34


100 300 500 700

Trai

t dis

tanc

e

Phylogenetic distance (Ma)

Figure 6.1 Results of tests forconservatism or convergenceof alien species traits (specificleaf area – SLA in cm2 × gr−1;individual seed weight – SWTin mg; and typical maximumplant height – Hmax in cm) inrelation to co-occurring nativespecies. Contrast based onalien-to-all nativescomparisons.

6.2C), and weaker when comparing alien traits to the mean native traits (Fig. 6.2B).Similar comparisons by individual growth forms showed heterogeneous phylogeneticsignals for the evaluated traits (Fig. 6.2).

A comparison of trait evolution and trait similarity of aliens suggests most traits areboth phylogenetically conserved (upper regions in Fig. 6.2) and clustered (areas tothe left in Fig. 6.2). The results indicate that aliens have a tendency to occur in those

6.3 Results 97

Table 6.1 Tests for patterns of trait evolution (i.e. traits are either conserved or convergentor there is no phylogenetic signal) for datasets that vary in the community phylogeneticstructure (null model 1a–b) or the community trait composition (null model 2); for each dataset trait (Specific leaf area or SLA – cm2 × g−1; maximum average canopy height or Hmax –m; and average seed weight or SWT – mg), the null model used in the analysis, number ofalien taxa, the numbers of communities, and Pearson correlation coefficients (rho) ofobserved and expected from a null model and evolutionary pattern are given. P values(two–tailed test) are determined from null distributions of 1000 iterations. Null models arebased on randomization of the phylogeny (all species in the database null model 1a or withina community null model 1b) or the trait distance matrix (complete database null model 2a orwithin a community null model 2b).

Trait No. alien No. Rho Null model Rho (null) Obs>Sim P Evolutionarytaxa Comm. (observed) pattern

SLA 2154 90 0.094 1a 0 1000 < 0.001 Conserved[-0.001 0.001]

1b -0.001 998 0.004 Conserved[-0.003 0.001]

2a 0.001 1000 < 0.001 Conserved[0 0.002]

2b 0 999 0.002 Conserved[-0.001 0.002]

Hmax 3002 107 0.127 1a 0 1000 < 0.001 Conserved[-0.001 0.002]

1b -0.001 1000 < 0.001 Conserved[-0.002 0]

2a 0.08 1000 < 0.001 Conserved[0.08 0.081]

2b -0.001 1000 < 0.001 Conserved[-0.002 0]

SWT 2112 113 0.113 1a 0.001 1000 < 0.001 Conserved[0 0.002]

1b 0 1000 < 0.001 Conserved[-0.001 0.002]

2a 0 1000 < 0.001 Conserved[0 0.001]

2b 0.001 1000 < 0.001 Conserved[0 0.003]

areas where phylogenetically related and phenotypically similar natives already exist(i.e. support for phylogenetic clustering of aliens and native species).

Analysis of trait evolution and trait similarity by growth form (Fig. 6.2) showedheterogeneous results. The SLA of woody and the SWT of non–woody aliens specieswere phylogenetically over–dispersed, suggesting these traits are both evolutionary con-served and phenotypically over–dispersed between alien and native species in thesecommunities (as specified by locations in the upper right region of Fig. 6.2). Interest-ingly, an inverse pattern was found for the SWT of woody and the SLA of non–woody


Table 6.2 Tests for patterns of phylogenetic trait similarity between communities (i.e.communities are either over–dispersed, clustered or there is no relation), with significance ofthe associations determined by comparisons to datasets that vary in the communityphylogenetic structure (null model 1a–b) or the community species composition (null model3a –b). Variables are the same as in Table 6.1 and P values (two–tailed test) are determinedfrom null distributions of 1000 iterations. Null models are based on randomization of thephylogeny (all species in the database null model 1a or within a community null model 1b) orthe trait community matrix (complete database null model 3a or within a community nullmodel 3b).

Trait No. Rho Null model Rho (null) Obs>Sim P EvolutionaryComm. (observed) pattern

4049 133 -0.264 1a 0.001 0 < 0.001 Clustered[0 0.002]

1b -0.294 973 0.054 Weak Over-dispersion[-0.295 -0.294]

3a -0.169 0 < 0.001 Clustered[-0.17 -0.168]

3b -0.24 0 < 0.001 Clustered[-0.24 -0.24]

alien species, suggesting phylogenetic clustering of traits within the community mostlikely due to evolutionary conservatism (as specified by locations in the upper left re-gion of Fig. 6.2). Traits of aliens vines and climbers showed a random phylogeneticcomposition, suggesting that successful aliens with this growth form come from manyunrelated groups. Comparisons of alien–to–all–natives and alien–to–closest–native il-lustrate clustering of several traits by growth form (Fig. 6.2), which further supportshypotheses of phylogenetic conservatism. Altogether, the results indicate that successfulaliens tend to be phylogenetically clustered with co–occurring natives most likely dueto the evolutionary conservatism of traits and the environmental restrictions imposed tothe expressed phenotype.

6.4 Discussion

Our results indicate that alien species show phylogenetic clustering when compared toco–occurring natives and supports the predictions of the phylogenetic attraction hypoth-esis and not the predictions of Darwin’s naturalization hypothesis. On average, success-ful alien species are more closely related to co–occurring natives. Our results illustratethat alien species’ traits are more similar to those of natives than expected by chance.These trend made us consider that success of aliens that are more closely related tonatives in new habitats is probably the result of an overlap in similar traits betweenalien and native species, and perhaps their niche requirements. These results also showthat, at the scale of our analysis (5km cells), the negative relationship between phylo-

6.4 Discussion 99

Convergent

Conserved

Trai

t evo

lutio

n

Clustered Overdispersed

Trait similarity in communities

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Alien to all natives

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Figure 6.2 Conservatism of traits in relation to trait similarity within communities for particulargrowth forms (woody, non-woody and vines and climbers).

genetic distance and the co–occurrence of aliens and natives is driven by the interactionof ecological, environmental and evolutionary mechanisms.

Together, the results presented here corroborate the importance of accounting forphylogenetic relationships when examining alien invasions, and especially when pre-dicting which alien species might be successful. Our results show that by using informa-tion about phylogenetic structures we can disentangle the ecological and evolutionaryforces that account for the observed invasion patterns of alien communities. This ap-proach has gained considerable attention in invasion literature (Cadotte et al. 2009, Diezet al. 2008, Diez et al. 2009, Jiang et al. 2010, Strauss et al. 2006, Thuiller et al. 2010)as it provides a quick and easy way to screen for potential new invaders.

By examining global distribution patterns of native and alien species, we show howthe observed distribution of alien plant communities results from two interacting mech-anisms. First, alien species show evolutionary conservatism of traits, which allows themto match the environmental conditions of the new habitat and therefore occupy the newniche (Wiens et al. 2010, Wiens & Graham 2005). Second, the environmental condi-tions of the new habitat filter out unsuitable aliens, allowing only those species withtraits similar to native species to colonize the new area (Ackerly 2003, Webb, Losos &Agrawal 2006). In other words, invading species need to be able to contend with the


same environmental conditions as the native species, and it is primarily those invadingspecies that are most related to the native species that are able to do this.

The first proposed mechanisms is based on the trait (and fundamental niche) conser-vatism concept, which is one of the core principles of both DNH and PAH. To date,most tests of trait conservatism have focused on the bioclimatic requirements of aliens.Traditionally this has involved the comparisons of the realized environmental spaces ofan alien in its native and introduced range (e.g. Beaumont, Gallagher, Thuiller, Downey,Leishman & Hughes 2009, Broennimann, Treier, Muller-Scharer, Thuiller, Peterson &Guisan 2007, Peterson 2003). In contrast, our study focuses on the evolutionary simi-larity between successful alien invaders and native species by using phylogenetic andphenotypic information to better explain the observed patterns of invasion (as suggestedby McGill et al. 2006, Violle & Jiang 2009). As a whole, our results provide new evi-dence supporting the predictions of the phylogenetic attraction hypothesis.

The second proposed mechanism is based on the constraining effects of habitat filter-ing, a process often invoked to explain the patterns of community assembly (Cornwellet al. 2006, Kraft et al. 2007). Our results illustrate that habitat filtering also has a stronginfluence on the observed community phylogenetic clustering, corroborating the find-ings of others (Kraft et al. 2007, Rejmanek 2000, Richardson & Pysek 2006). Specif-ically, we show that traits are more similar between co–occurring alien and nativespecies, which supports the idea that key attributes are strongly selected by environ-mental factors (for example SLA). However, it is important to note that the observedtrait clustering could be an artifact of a similar plastic response to the environment byco–occurring species, hence inflating the possible effects/signal of habitat filtering.

There are at least two additional questions that future studies should further evaluate.First, do individual species differ in their response to environmental conditions?; andsecond, do the trade–offs between competitive interactions and community saturationaccount for the emerging patterns of self–organized trait similarity clusters?. Our re-sults strongly suggest that the observed pattern of phylogenetic clustering (at the scaleof a 5×5 km grid) is a function of both the constraining effects of phylogenetic traitconservatism and habitat filtering. Both of these factors appear to strongly influence theestablishment success of alien species. Specifically, our results suggest that the phylo-genetic clustering between alien species and the native community does not support theexpectations proposed by the DNH, but rather supports the propositions of the PAH.

Here we have show how the balance between evolutionary and ecological forces de-termines the establishment success of alien species. For example, in habitats with strongenvironmental constraints (e.g. extreme environments as desert, tundra or paramos) thepool of potentially successful species is limited. Therefore, in extreme habitats wewould expect a stronger phylogenetic clustering signal than in those areas where thehabitat conditions are not as constraining (e.g. Gonzalez et al. 2010). Therefore, analien species ability to establish in a new area is probably determined by habitat filterscoupled with the evolutionary patterns of key traits (as proposed by Cavender-Bares,Ackerly, Baum & Bazzaz 2004), and the balance between competitive interactions andcommunity saturation (Scheffer & van Nes 2006).

A last point to address here is the interplay between spatial and phylogenetic scales.

6.4 Discussion 101

It is possible that the observed patterns might be different if alternative and more in-clusive phylogenies are used (as shown by Cavender-Bares et al. 2006); this could bean avenue for follow–up studies. Furthermore, although we did not explicitly comparedifferent spatial aggregations of the data, works by Cadotte et al. (2009) and Cavender-Bares et al. (2006) have shown that the phylogenetic scale of the analysis rather thanthe scale of spatial aggregation shapes community structure. Based on their results, it islikely that at intermediate spatial scales the observed patterns of alien community struc-ture are mainly driven by how the co–occurring community is phylogenetically defined(e.g. congenerics, all species, closest or mean taxon) rather than by the spatial scale atwhich the community is specified (e.g. co–occurring on a plot, an locality a region or acontinent).

The association between alien success and their relatedness to native species hasrapidly become one of the main approaches for building predictive frameworks of speciesinvasions. Our worldwide analysis of the relation between trait similarity, phylogeneticrelatedness and the co–occurrence patterns of alien and native plants at a spatial reso-lution of 5×5 km shows that i) successful aliens are closely related to the native com-munity and ii) more similar in their traits than expected by chance. This suggests thatcombinations of phylogenetic and trait similarity indices are useful predictors to iden-tify potential alien species and susceptible communities.

7 Niche conservatism in invasiveplantsAlejandro Ordonez Gloriaab, and Han Olffa

Abstract

Explanations for the success of alien species have frequently been based on their de-gree of niche overlap with native species. In order to predict and understand futureinvasions, we thus need to know if ecological traits/requirements of aliens remain sim-ilar [niche conservatism (NC)] or change [niche lability (NL)] in their novel habitat.Here we review the evidence for either NC or NL and the importance of these conceptsfor the further development of the field of invasion biology. For this we first discussdifferent views of the niche, and their implications for NC versus NL. Building fromthis, we address three key topics relevant to this discussion: evolutionary divergencevs. convergence of traits, conservation vs. adjustment of the bioclimatic niche, and thephylogenetic stasis vs. evolution of the niche. We emphasize the importance of the useof an appropriate niche concept for the accurate description and prediction of the fate ofintroduced aliens. In a meta–analysis, we find that NC in aliens is much more commonthan NL, making the concept of NC useful in predicting future invasions. In contrast,we find traits to have the posibility of being flexible, which suggests that aliens have thepotential to change their traits in order to conserve their niche.


7.1 Introduction 103

7.1 Introduction

The prediction, which species will establish successfully after their introduction to anon–native range, has become a priority topic in conservation biology. Scientists havetherefore searched extensively for a predictive framework based on ecological mecha-nisms. A basic assumption in this line of research is the idea that aliens will expressthe same traits in both their native and introduced range. This is an important assump-tion, based on the idea of ”traits and niche conservatism” over space (their geographicrange) and time (their evolutionary dynamics). However, a critical test of this idea isnow clearly needed, especially as various a priori reasons can be thought of why itmight not hold (as discussed in Losos 2008). Here we review the direct and indirectevidence for niche and trait conservatism in invasive species.

Niche conservatism (NC hereafter) is the idea that the niche of a species is fixedover ecological time scales (Peterson, Soberon & Sanchez-Cordero 1999, Wiens &Graham 2005) only changing very slowly over long evolutionary time spans (Ackerly2003, Webb et al. 2002). This NC is an important implicit assumption in many popula-tion, community and macro ecological studies and has therefore major implications forconservation biology/ecology (Wiens & Graham 2005). Several factors causing it havebeen considered [as reviewed in Wiens et al. (2010), and Wiens & Graham (2005)] in-cluding, among others, the conservation of species–specific traits, constraints and trade–offs imposed by physiology and life history, lack of mixing between populations, ab-sence of genetic variation for necessary traits, selection favoring a consistent choice ofresources, and/or competition with species using alternative resources.

An important aspect of NC is its relevance to changes in species geographic rangesdriven by global change (e.g. the case of movement of species across dispersal barriersor due to climate change). This is an issue of particular relevance in invasion ecologyas the new performance–environment dynamics, generated from the rearrangement ofspecies distribution ranges and environmental conditions, have the potential to enhanceinvasions (Thuiller 2007, Thuiller, Richardson, Midgley & Nentwig 2007). Specifically,if species do not ”stick to their niche” during ecological time scales, the prediction ofpossible invasive species before they arrive in a new environment becomes virtuallyimpossible.

In this review we focus on three major topics concerning NC and its importancefor understanding invasive plant species dynamics. We specifically review the literatureon, and perform meta–analyses of: i) the importance of ecological traits for NC, ii)the idea of bioclimatic niche conservatism (BNC hereafter) and iii) the prevalence ofphylogenetic niche conservatism (PNC hereafter).

7.2 The starting point: an adequate niche concept

The niche is a central concept in community ecology. It provides a the baseline forunderstanding many aspects of species adaptations and interactions (Chase & Leibold2003, Hutchinson 1957, Root 1967). In order to develop a predictive framework of

104 Niche conservatism in invasive plants

species invasions based on niche dynamics, it is important to first discuss which nicheconcept(s) is most appropriate. Across the literature, many alternative definitions for”niche” have been proposed based on either the geographic distribution, the functionsperformed, the resources a species consumes, the conditions it tolerates and/or whereit is safe from enemies. Nevertheless a consistent use of those definitions is lacking.Perhaps the most commonly used of these definitions is Hutchinson’s (1957), who de-scribed the niche as a ”set of biotic and abiotic conditions in which a species is able topersist and maintain stable population sizes”. Developing from these ideas, two main(nested) niche types are currently distinguished in ecology (Chase & Leibold 2003,Pearman et al. 2008, Soberon 2007): i) the fundamental niche (or Grinnellian niche)defined as the basic conditions that allow a positive population growth rate of a partic-ular species, in absence of any other interacting species and dispersal limitation; and ii)the realized niche (or Eltonian niche) defined by the portion of the fundamental niche inwhich a species can persist, accounting for constraining effects of biological interactionswith other species such (e.g. competition or predation).

It is not easy to measure a species niche. Appropriate measures should include its’physiological tolerances, biotic interactions, and dispersal limitations. From all the avail-able methods to measure a species niche, none of them has been able to incorporate allthree elements simultaneously (Chase & Leibold 2003). As a result, some studies onlyfocus on ecological and geographical properties of species on a broad scale, excludingbiotic interactions between species (fundamental or Grinnellian niche). Meanwhile oth-ers include species–species interactions and biotic properties on the local scale (realizedor Eltonian niche). This makes the evaluation of the conservation of niches a even hardertask that already is, as one should consider not only the processes driving the conser-vation of niches but also the approach used to measure the niche and which type ofniche the selected measure refers to (i.e. fundamental vs. realized). Additionally, nichemeasurements used in most studies have are strongly scale dependent. Specifically, thefundamental niche is often studied at larger scales (e.g., in relation to climatic tolerance)while realized niche processes operate more locally, adding another layer of complexityto the problem (Pearman et al. 2008, Soberon 2007).

Also for niche conservatism to play an important role in invasion ecology, it must beclear from the beginning which type of niche is addressed in a study. This will determinehow niche overlap determines the success or failure of an introduced alien. Specifically,we propose that the understanding of the dynamics of species invasions depends on theconservatisms vs. lability of its fundamental niche (will it spread to areas with simi-lar or different environmental conditions as in its native range) and its realized nicheonce introduced (e.g. it will ecologically outperform co–occurring species in a similarway as in its native range, or not). We expect this improves the ability to predict novelspecies invasions and changes in geographic range of already introduced aliens. If thefundamental niche is conservative, then invasive species should have similar climaticpreferences in their native and introduced ranges(Wiens & Graham 2005). If the real-ized niche is conservative, then species are expected to play a similar ecological role(e.g. in the competitive hierarchy, or in relation to enemies) in their native and intro-duced ranges. It should be tested if this conservatism of the fundamental and realized

7.3 Trait conservatism as a driver of niche conservatism 105

indeed applies, or that lability is important for either of these. In the next sections, wewill explore these alternative hypotheses through meta–analyses.

7.3 Trait conservatism as a driver of niche conservatism

Niche differentiation (either fundamental or realized) between aliens and natives is themechanism most commonly invoked by the suite of hypotheses that have been proposedto explain variation in success among aliens (summarized in Table 7.1). It has beenproposed that specific community or ecosystem properties prevent alien plants frombecoming invasive (Mack et al. 2000), using explanations based on niche availability.For example, the area occupied by fundamental niches (potential habitat) for a speciescan be limited in a given landscape (Jackson & Overpeck 2000). Also, changes in thecombinations of different environmental factors that are realized in a given landscapeat a given point in time (Ackerly 2003) could allow a species to colonize previouslyunavailable areas. These explanations do not imply a change in the potential or realizedniche of the alien. They rather suggest a limitation or change in the (spatial) availabilityof these niches.

Changes in fundamental or realized niche of an alien in its new range can happenwhen it changes key functional traits. The idea of using such traits to map the nicheof species has received increased attention in recent years (McGill et al. 2006, Vi-olle & Jiang 2009). Potentially, this approach may overcome limitations of differentniche metrics, and improve the predictive and quantitative nature of community ecol-ogy. The concept is based on the assumption that some traits of species will determineunder which biotic or abiotic conditions it can persist (”response traits” sensu Lavorel &Garnier 2002). Therefore, such traits (for example thorns, salt glands, thick leaves) canbe a good proxy for the niche of a species as they tell something about the environmentalconditions where can occur, so also about where it can potentially invade.

In the case of alien species, such traits can be used to better understand the invasionprocess. For example, by comparing the attributes of the alien between its native andintroduced range, it is then possible to discriminate between niche lability vs. conser-vatism. This will in turn determine how extensive the invasion will be: will the alienoccupy/exploit a wider or another range of biotic and abiotic conditions than would beexpected from its occurrence and traits in its native range.

The majority of the studies published to date (summarized in Fig. 7.1) find that im-portant ecological traits (and possibly thus the niches of alien species) are conservedbetween their native and alien range. This supports both the idea that important ecolog-ical traits, related to a species niche, are conserved over space and evolutionary time(Travis 1989, Wiens & Graham 2005) and that natural selection favors those traitswhich maximize the survival of a species, thus inhibiting niches from changing a lot(Ackerly 2003). However, it is important to state that the stabilizing effects of selectionon ecological niches are the outcome of the trade–offs among traits, leading to alterna-tive ecological strategies or life histories, causing the preservation of equilibrium valuesof fitness–maximizing traits within a niche. This, coupled with the low genetic variation


Table 7.1 Leading in invasion biology and their relationship to niche conservatism (NC) orlability (NL).

Hypotheses NC NL References

Enemy release + (Blumenthal 2006, Colautti, Ricciardi,Grigorovich & Macisaac 2004, Darwin1866, Funk & Throop 2010, Keane &Crawley 2002, Liu & Stiling 2006, Sta-chowicz & Tilman 2005)

Evolution of increased competitive ability + (Blossey & Notzold 1995, Bossdorf, Auge,Lafuma, Rogers, Siemann & Prati 2005,Callaway & Ridenour 2004)

Biotic resistance from enemies/competitors + (Kennedy, Naeem, Howe, Knops, Tilman& Reich 2002, Levine 2000, Levine et al.2004, Macarthu.R & Levins 1967a, Maron& Vila 2001, Verhoeven, Biere, Harvey &van der Putten 2009)

New associations + (Colautti et al. 2004, Hokkanen & Pimentel1989, Verhoeven et al. 2009)

Mutualist facilitation + + (Richardson, Allsopp, D’Antonio, Milton& Rejmanek 2000)

Invasional meltdown + (Ricciardi 2001, Simberloff & Von Holle1999)

Empty niche + + (Hierro, Maron & Callaway 2005, Mwangi,Schmitz, Scherber, Roscher, Schu-macher, Scherer-Lorenzen, Weisser &Schmid 2007)

Novel weapons + (Callaway & Aschehoug 2000, Callaway &Ridenour 2004, He, Feng, Ridenour, The-len, Pollock, Diaconu & Callaway 2009, Vi-vanco et al. 2004)

Habitat filtering/ Climate matching + (Broennimann et al. 2007, Levine 2000)Darwin’s naturalization hypothesis + (Daehler 2001, Diez et al. 2008, Duncan &

Williams 2002, Jiang et al. 2010, Lambdon& Hulme 2006, Strauss et al. 2006)

Novel niches + + (MacDougall, Gilbert & Levine 2009, Mac-Dougall & Turkington 2005, Shea &Chesson 2002)

observed in some species may strongly inhibit trait evolution, which in the case of aliensrestricts spreading into new niches (Case & Taper 2000).

The link between conservation of ecological traits to the idea of niche conservatismdoes not mean that traits will always remain fixed within a species (as shown by Albertet al. (2010) and Messier et al. (2010) in a cross-scale comparison). In fact, plants arerenown for their high degree of phenotypic plasticity. In most cases, this plasticity maybe required for a species to occupy its full realized or fundamental niche. Thus, a certaindegree of plasticity in a trait can be viewed as the mechanism allowing a species to oc-

7.3 Trait conservatism as a driver of niche conservatism 107

Genetic

Height

Flower

Biomass

Leaf

Growth

Seed

Population

Defense

0% 25% 50% 75% 100%

A>N A<N A=N

Figure 7.1 Summary of the results of 34 studies comparing ecological traits of introduced plantsbetween its’ alien (A) and native (N) range. Directionally of the contrasts are presented as: Alienhigher than Native A > N; Alien smaller than Native A < N and Alien equal to Native A = N).List of references used to build the figure are presented as supplementary material (AppendixB). Each section of the bar shows percentages of significant results showing the direction of thecontrast. Used traits for each category are: Gentic, Height (Plant height, size, stem height),Flower (Flower size, flowering speed, number of flowers, petal width), Biomass (Biomass, Rootmass, Root:Shoot ratio, Shoot mass), Leaf (Leaf Area, leaf area ratio (LAR), C13, leaf chemistry(C, N, C:N), leaf number, leaf size, leaf toughness, SLA, stomata conductance, total leaf area),(Growth: Growth rate, number of shoots, number of vegetative offspring, stem Number, Tilleringrate), Seed (Fruit Mass, germination rate/speed, optimum germination temperature, reproductiveoutput, seed bank, seed mass, Seed size, seedling establishment rates, seedling survival),Population (Average age, density, maximum age, population size and proportion of youngstages), and Defense (Chemical concentration (Tannin, Hypericin, Pseudohypericin, nerolidoland viridifloral chemotypes), fruit capsule, herbivory tolerance, Trichomes).

cupy its niche (Ackerly 2003). This degree of plasticity may then be conserved betweenthe native and alien range of a plant, leading to niche conservatism.

We have shown so far that most current evidence points towards the conservatism ofkey traits in invasive plants between their native and introduced ranges (Fig. 7.1). How-ever, linking this trend to hypotheses based on the idea of alien–native trait similarity ordissimilarity will depend on the analyzed trait and the scale of the study (local, regionalor continental). Following these results on conservatism of traits, we will discuss in thenext section the conservatism of the bioclimatic niche.


7.4 Bioclimatic niche conservatism in invasive species

A large literature on species distribution models is based on the idea of the existenceof a bioclimatic niche, that is specific areas where a species encounters the climaticconditions under which it can persist (e.g. as determined by its frost or drought sensitiv-ity). These studies are often done at very large scales. Bioclimatic niches are thereforecloser to a fundamental than a realized niche. Most common definitions of the biocli-matic niche explicitly exclude local environmental conditions, such as soil properties,or biotic interactions (Wiens & Graham 2005). The conservation of this climatic–spaceacross space and time has a strong link with the idea that the fundamental niche isconserved.

This idea that bioclimatic niches are conserved over space and time (bioclimaticniche conservatism, BNC) has been intensively scrutinized in a number of studies (asreviewed in Losos 2008, Wiens et al. 2010, Wiens & Graham 2005) thanks to the in-creasing availability of easily accessible species distribution data, large scale and fineresolution climatic information and the development of new species distribution mod-eling (or SDM’s) statistical techniques. However, efforts to determine the level of BNCacross different species and groups (as summarized in Fig. 7.2 and Appendix C) haveyielded ambiguous results; with some studies showing strong support for the conser-vatism of climatic niches (Buckley, Davies, Ackerly, Kraft, Harrison, Anacker, Cor-nell, Damschen, Grytnes, Hawkins, McCain, Stephens & Wiens 2010, Roura-Pascual,Suarez, McNyset, Gomez, Pons, Touyama, Wild, Gascon & Peterson 2006, Wiens &Donoghue 2004) while others suggest that such niches are relatively labile (Broennimannet al. 2007, Losos 2008, Losos, Leal, Glor, de Queiroz, Hertz, Schettino, Lara, Jackman& Larson 2003, Stevens 2004).

In the case of invasive alien species, BNC has large implications for the predictionof successful aliens (or areas of introduction) as it provides a framework to determinewhich and where alien species can become established. An example of this the workby Thuiller et al. (2005) showing (by the use of species distribution models) a closematch between the climatic component, the ecological habitat suitability, and the cur-rent pattern of occurrence of South African invasive species in other parts of the world.A similar study on the waterthyme (Hydrilla verticillata) showed a match between theoccupied realized environments in its native (Southeast Asia and the Australo–Pacific)and its invaded distributional area in North America (Peterson 2003). Additional sup-port for BNC emerges from a study of 29 introduced reptile and amphibian species inNorth America (Wiens & Graham 2005) which found a strong relationship between na-tive and introduced geographic range limits (poleward latitudinal extents); and an earlierstudy based on several introduced bird and mammal species (Sax 2001) showing a sig-nificant correlation between native and introduced latitudinal extents. All these worksprovide support to the idea that bioclimatic niches are conserved across space, consti-tuting long–term stable constraints on the potential geographic distributions of species(Peterson et al. 1999). However, is should be noted that final conclusions on the conser-vation of the bioclimatic niche can only be drawn after sufficient time has passed sincethe introduction. Is perhaps due to this that no study to our knowledge has analyzed his-

7.4 Bioclimatic niche conservatism in invasive species 109

Native-Alien range

Native-Alien range (SDMS)

Paleo-Reconstruction

Phylogenetic Comparison

Sister taxon

Sister taxon (SDMS)

0% 25% 50% 75% 100%

NC NL

Figure 7.2 Summary of 70 studies showing direct or indirect support for or against the idea ofniche conservatism (NC) or lability (NL). List of references used to build the figure arepresented as supplementary material (Appendix C). Each section of the bar shows percentagesof significant results showing support of NC or NL. Studies were summarized according to theused methodology: Sister taxon (SDMS) comparisons of related species using speciesdistribution models (SDMS); Sister taxon performance or attributes contrast of related species;Phylogenetic Comparison attributes of related species/communities are compared to find aphylogenetic signal (clustered–overdispersed–random); Paleo–reconstruction comparisons ofthe range of current species to that of extinct relatives; Native–Alien range (SDMS) crosscomparisons of SDMS form the native and introduced range of successful aliens; andNative–Alien range comparisons of population and eco–physiological attributes between a alienand the closest related native.

torical changes in bioclimatic niches between the native and introduced range of alienspecies.

Evidence for bioclimatic niche lability has however also been found, particularly forthose species with broad environmental tolerances. Studies show that in some cases,successful alien species disperse to, and persist in areas which would be considered un-suitable for them based on their native range distribution (Losos 2008). An example ofthis is the case of the invasive spotted knapweed (Centaurea maculosa), which showeda significant range shift between its native (Europe) and its non–native (North America)distribution; indicating how invasive aliens are sometimes able to persist under differentclimatic conditions than those encountered in their native range, suggesting a labilityin their fundamental niche (Broennimann et al. 2007). This could be attributed to ei-ther genetic drift/founder effects (Muller-Scharer, Schaffner & Steinger 2004), strong


restrictions on gene flow between the native and introduced populations (Diamantidis,Carey & Papadopoulos 2008), hybridization and polyploidy (Blossey & Notzold 1995)or higher potential of rapid adaptive evolution of alien plants (Maron, Vila, Bommarco,Elmendorf & Beardsley 2004, Sexton, McKay & Sala 2002).

The occurrence of niche conservatism in many species, and lability in others, has im-portant consequences for the prediction and understanding of biological invasions. Thishas special relevance for invasive species screening systems used today (e.g. Daehler &Carino 2000, Pheloung, Williams & Halloy 1999, Reichard & Hamilton 1997, Tucker& Richardson 1995); as these are generally based on the assumption that niches andattributes are conserved across space and time.

A last point to emphasize is the need for large–scale comparisons of climatic nichesbetween native and introduced ranges, utilizing the available data from the hundreds ofintroduced animal species and thousands of introduced plants. Such studies are urgentlyneeded to assess the ability of methods based on the BNC principle to predict the spreadof invasive species.

In summary, although some studies have shown that invasive species are able tospread into novel bioclimatic niches, most of the available direct and indirect evidenceleans toward the conservation of the bioclimatic niche of introduced species. As a result,invasions of non–native environments by a species are most likely if the novel climaticconditions are similar to those the species encounters in its native range.

7.5 Phylogenetic niche conservatism and the success of introducedaliens

Phylogenetic niche conservatism (PNC) has been defined as ”the tendency of relatedspecies to retain ancestral ecological characteristic” (Wiens et al. 2010, Wiens &Graham 2005). Based on this idea, several studies have aimed to determine the relationbetween phylogenetic and ecological similarity among species, testing the hypothesisthat closely related species are more likely to be ecologically similar than phylogeneti-cally more distantly related ones. Nevertheless, as summarized in Fig. 7.2, the evidenceis not unambiguous as studies show evidence both in support of PNC (e.g. Hadly, Spaeth& Li 2009, Swenson, Enquist, Thompson & Zimmerman 2007, Webb 2000) as againstit (e.g. Losos et al. 2003, Silvertown, Dodd, Gowing, Lawson & McConway 2006).

The recent increase in interest in PNC has been the result of the better and morephylogenies for extant species, and new extensive data sets of fossil records. Addi-tionally, the invention of phylogenetic comparative methods [Phylogenetic independentcontrasts – PIC’s (Felsenstein 1985) or Phylogenetic generalized least squares –PGLS(Grafen 1992)], has facilitated the number of studies on the ”phylogenetic effect” or”phylogenetic signal” of ecological attributes (Blomberg & Garland 2002). Overall,this merging of phylogenetics and community ecology has resulted in several studiesinvoking PNC as the main mechanism explaining the responses of species to anthro-pogenic climate change, the spread of invasive species, species biogeography patterns,

7.5 Phylogenetic niche conservatism and the success of introduced aliens 111

or speciation and diversity trends across evolutionary times (Cavender-Bares, Kozak,Fine & Kembel 2009, Wiens et al. 2010, Wiens & Graham 2005).

Understanding and predicting the impact of invasive species is one of the central pil-lars of fundamental and applied ecology (Rejmanek et al. 2005, Richardson & Pysek2006). To address this, invasion ecologists have focused on understanding either whichspecies traits make introduced species more likely to become invaders (Pysek & Richardson2007, Rejmanek et al. 2005, van Kleunen et al. 2010) or why some natural communi-ties are more prone to invasion than others (Davis et al. 2000, Lambdon et al. 2008,Rejmanek 1999, Richardson, Rouget, Ralston, Cowling, Van Rensburg & Thuiller 2005).In an attempt to merge both of these approaches some works (Cadotte et al. 2009,Daehler 2001, Diez et al. 2008, Diez et al. 2009, Duncan & Williams 2002, Jianget al. 2010, Lambdon & Hulme 2006, Strauss et al. 2006, Thuiller et al. 2010) havefocused on the use of the relatedness (taxonomic or phylogenetic) between aliens andnatives as a measurement of the likelihood of invasion. This is based on the assumptionthat phylogenetic similarity can be used as a surrogate to ecological or niche similarity.Therefore, several works have used the level of similarity to the native members of acommunity as a possible predictors of invasion success; although it should be noted thatwith the exception of a few works (e.g. Cadotte et al. 2009, Jiang et al. 2010, Strausset al. 2006) the level of phylogenetic similarity has only been quantified on the basis ofclassic taxonomic classification rather than on newer phylogenies.

Based on the PNC idea, two very different hypotheses linking alien success and itsphylogenetic relatedness to the native species pool have been formulated: i) novel gen-era are expected to be more successful naturalizing in those areas where there are noclosely related natives (Darwin’s naturalization hypothesis sensu Rejmanek 1996), orii) introduced species have a higher chance to establish in areas with phylogeneticallysimilar species (phenotypic attraction hypothesis sensu Webb et al. 2002). An impor-tant assumption of both of these hypotheses is again that species niches are conservedover time, implying that closely related species tend to have more similar niches thandistantly related ones (Wiens et al. 2010). However, although closely related specieshave a tendency to occupy ecologically similar niches, those niches are never exactlyidentical to each other (Peterson et al. 1999).

As more studies address the role of PNC in the success of alien species, we believethat its ubiquity cannot be assumed blindly given the increasing amount of works thatdo not support this idea (As shown in Fig. 7.2 and reviewed by Losos 2008). For ex-ample, while some studies in continental North America support PNC (Mack 1996,Rejmanek 1996, Strauss et al. 2006), studies in New Zealand find evidence againstit (Diez et al. 2008, Duncan & Williams 2002) while again others on Mediterraneanislands have shown an idiosyncratic relation between phylogenetic relation and aliensuccess (Lambdon & Hulme 2006, Lambdon et al. 2008). A possible reason for theseheterogeneous results is that PNC strength may not be constant over different parts ofthe phylogenetic tree (Diez et al. 2009, Thuiller et al. 2010). As a result, certain groupsof species may exhibit great evolutionary lability (as reviewed by Pearman et al. 2008)while others may express evolutionary convergence of attributes (Cavender-Bares, Ack-erly, Baum & Bazzaz 2004). Based on this, it’s clear that any future ”rule of thumb”


relating introduction success to phylogenetic relatedness should explicitly provide quan-titative evidence for PNC (Blomberg, Garland & Ives 2003, Cadotte et al. 2009, Losos2008) so any possible source of deviation that could likely blur this relation could bedetermined and controlled.

A final point to address here is the difficult task of making a link between the mul-tidimensional nature of the niche with the simultaneous conservation and lability ofattributes across the phylogeny (that is, some dimensions tend to be phylogenetic under–dispersed, while others are over–dispersed). For some authors this is not a problem, asthey view the phylogenetic similarity as a conglomerate measure that merges the infor-mation of each of the dimensions defining a species niche (Strauss et al. 2006, Thuilleret al. 2010). However, it is possible that the opposite phylogenetic trends of differentniche dimensions could result in random phylogenetic patterns, making the relation be-tween phylogenetic relatedness and introduction success void, even though meaningfulecological mechanisms are currently at work.

But still it is of course true that sister species are more likely to occupy ecologi-cally similar niches than expected from random pairwise comparisons with other species(Warren, Glor & Turelli 2008). So far, evidence from several studies in this field suggestthat it is more likely for a species or a community of species to shift their range thanto evolve a new niche, thus supporting PNC (Donoghue 2008). Furthermore, it shouldbe noted that NC could not only differ across time (PNC) and space (BNC) but alsodiffers from taxa to taxa and between spatial scales of observation. Finally, we suggestthat although the level of phylogenetic similarity is a promising approach to predict suc-cessful aliens; the comparison of the patterns of phylogenetic and ecological similarityis nevertheless the most likely path to determine the ecological mechanisms that makeintroduced species naturalize.

7.6 Conclusion

Niche conservatism and its application in predicting invasions is still a much–debatedtopic in ecology with no definite answer. Evidence is found both in favor and against it.However, we conclude that most of the current evidence supports the idea of NC overspace (BNC) and time (PNC) of alien species. Nevertheless, this does imply that speciestraits are always conserved across ranges (trait conservatism). This may result from ofthe interplay between environmental filtering (resulting in the conservation of the fun-damental niche), competitive interactions (resulting in the shaping of the realized niche)and evolutionary patterns (making traits either evolutionary conserved or convergent).

One of the main consequences of the observed support for BNC and PNC for invasivespecies is that niche preferences seem mostly conserved between the native and alienranges. As a result, this suggests that the overall likelihood of evolving and adaptingto a novel niche is lower than moving to another niche with optimal or even subopti-mal conditions for survival. This seems to be consistent over evolutionary time as isshown by extensive studies on fossil records and the current distribution of many taxa.Furthermore, closely related species occupy similar niches whereas distantly related

7.6 Conclusion 113

species have different niche requirements; the outcome of this is that sister species areless likely to locally co–occur, reducing the competition between congenerics.

In general, NC is seen in many introduced taxa, but deviations from this trend are pos-sible. Unfortunately, very few studies have focussed on the evaluation of the patterns ofsimilarity or dissimilarity in the niche and/or attributes of invasive alien plants betweentheir native and their introduced range using a large number of species. As more databecome available, more studies and better comparisons should be made to determinewhether or not niches of aliens are conserved between the native and alien range, whatthe consequences are for global change phenomena for future species invasions. Thismakes multi–species comparisons over a wide set of environments an important stepforward in invasion ecology.

Part V

Synthesis and closingfeatures

8 Synthesis: are we closer tounderstanding and predictinginvasions?Alejandro Ordonez Gloriaab


118 Synthesis: are we closer to understanding and predicting invasions?

8.1 Introduction

Introduction of non–native species is one of the main drivers of global change (Vitousek,Mooney et al. 1997) causing major changes in ecosystem processes and functioning(Le Maitre, van Wilgen, Gelderblom, Bailey, Chapman & Nel 2002, Mooney & Hobbs2000, Vitousek et al. 1997, Vivrette & Muller 1977, Westbrooks 1991) in addition tosignificant economic and biodiversity losses (Pimentel, Zuniga & Morrison 2005, Sax& Gaines 2003). The importance of the problem highlights the needed for methodsthat accurately discriminate which plants, once introduced, will be successful and couldpossibly become invasive.

Invasion biologists have tried to address this problem by asking one of two importantquestions: i) which species are invasive (a species–based approach), and ii) which habi-tats are most likely to be invaded (a community–based approach). To address the firstquestion, most works have aimed to determine a broad list of traits that can be used todescribe which species will be successful in a new environment. This idea of describingthe characteristics of the ”average successful alien” builds from Baker, Stebbins & In-ternational Union of Biological Sciences’s (1965) description of the ”ideal weed” (e.g.plants with ruderal strategies). Although, due to the idiosyncrasy of the invasion pro-cess, some authors believed that such a list was not possible (e.g. Alpert & Simms 2002,Roy 1990); later works, inspired by Rejmanek’s (1996) ”Theory of seed plant invasive-ness” have shown (by the use of multi–species comparisons) that successful aliens doappear to have some traits in common (e.g. Cadotte & Lovett-Doust 2001, Goodwin,McAllister & Fahrig 1999, Hamilton et al. 2005, Lake & Leishman 2004, Ordonezet al. 2010, Pysek & Richardson 2007, van Kleunen et al. 2010).

Efforts to answer the second question have yielded descriptions of the character-istics that make a given area intrinsically vulnerable to invasions. Some of the pro-posed characteristics are low site diversity (Elton 2000, Levine et al. 2004, Maron &Vila 2001); availability of empty niches (Elton 2000, Hierro et al. 2005); release fromnatural enemies (Colautti et al. 2004, Darwin 1866, Torchin & Mitchell 2004); intro-duction of novel weapons to the target area (Callaway & Aschehoug 2000, Callaway& Ridenour 2004); high resource availability (Blumenthal 2005, Davis et al. 2000) andhigh disturbance frequency (Lozon & MacIsaac 1997).

It’s clear that each of these approaches provide complementary answers to the ”whatdrives invasions” question. Therefore, any progress towards a general theory of plantinvasiveness can only been achieved by pooling evidence from both the species in-vasiveness and community invasibility approach. Some efforts to make this link (e.g.theory of seed plant invasiveness Rejmanek (1996); fluctuating resources theory of in-vasibility ?; niche opportunity: Shea & Chesson (2002); or state factor models Bar-ney & Whitlow (2008) among others) have aimed to explicitly linking the relation be-tween the characteristics/traits of a given aliens and the ecological–resource–enemy–evolutionary–environmental setup an alien species will face on a particular location.This dissertation is based on this perspective; aiming to address by the use of a globalscale multi–species, target area, native–alien comparison approach, how autoecological,evolutionary and environmental factors affects invasions success.

8.2 Attributes of success: What traits tell us about invasions? 119

8.2 Attributes of success: What traits tell us about invasions?

To date, most works aiming to determine a link between traits and invasion have fo-cused their efforts on profiling the ”average successful alien” (Table 8.1). Although,some generalizations have been found (e.g. aliens have faster grow rates, higher leafnutrients contents and specific leaf areas, shorter life cycles, devote more resources toreproduction and produce more seeds that are better dispersed and germinate faster) itis clear that any benefit yield from expressing a given attribute (or set of them) wouldbe contingent on the biological–evolutionary–abiotic setup a species faces.

Ecological and physiological literature has shown how fitness and performance ofa given species is determined by both its’ traits, and the functional and evolution-ary relation to the community it is embedded in (Lavorel & Garnier 2002, Marks &Lechowicz 2006, Marks 2007, Tilman 1982). This link between traits–performance–fitness provides a methodological framework to compare alien and native species world-wide. This is clearly the case for the group of traits used in this dissertation (i.e. Specificleaf area, photosynthetic capacity, leaf nitrogen content, individual seed weight, and typ-ical maximum height), given their influence on resource acquisition, growth, herbivoryrisk, r–K strategy, reproductive output, light competition, risk of breakage and respira-tion costs (Falster & Westoby 2003, Moles & Westoby 2006, Moles et al. 2009, Westobyet al. 2002, Wright et al. 2004). Furthermore, each of these traits is linked to a particularecological strategy (i.e. Leaf economics, seed mass-seed output trade-off, and canopyheight, as proposed in Westoby et al. 2002, Westoby & Wright 2006) representing howa species secure carbon profit during vegetative growth, ensure gene transmission intothe future and interacts with both the environment and other co–occurring species.

This work has shown how alien species, as a group, differ in individual traits (Chapter 3and 4) each one representing an approximately independent axis of trait/strategy varia-tion. These differences also hold for comparisons based on the multivariate trait compo-sition (SLA–Hmax –SWT 3D or 2D spaces, Chapter 3) and their positioning along the”leaf economics spectrum” (Chapter 5). Aliens location in both uni– and multivariatetrait–space, indicated how non–natives had the tendency to occupy regions clusteredtowards the edge of at least one of the evaluated dimension, when compared to natives(Chapter 3 and 5). Therefore, alien species could be considered as a biased subsampleof species with regard to the evaluated traits, such that they tend to express greater leaftraits (SLA, Nmass, Amass, as shown in Chapter 3 and 5), lower maximum height or/andsmaller seed size (as shown in Chapter 3 and 4). These results indicate that the ob-served trend of global differentiation relate to one (or both) of two possible mechanismsdetermining the success of alien species: i) the idea of limiting similarity, so that alienspecies are less likely to establish in communities that are dominated by species withsimilar traits (Abrams 1983, Hutchinson 1959); and ii) phenotypic attraction hypothe-sis, so that alien species are more likely to establish in communities with congenerics(Daehler (2001) and Diez et al. (2009); and tested in Chapter 6)

When aliens where compared to natives co–occurring in the same area, both a sig-nificant alien–native trait differentiation on individual traits and multi–trait composi-tion was detected (as illustrated by the significant random intercepts of linear mixed

Table8.1

Synthesis

ofresultsfrom

comparative

andcongeneric

studieson

traitsprom

otinginvasiveness

inplant.Traits

notaddressed

ina

particularstudy(M

ulti–speciescom

parativeorcongeneric/confam

ilialparing)areindicated

byem

ptycells.

Tablebased

onreferences

compiled

inP

ysek&

Richardson

(2007).

Group

oftraitsTrait

Multi–speciescom

parativestudies

Congeneric–C

onfamilialstudies

Morphological

Biom

assA

mbiguous

PlantheightProm

otesinvasiveness

Promotes

invasivenessV

egetativespatialgrow

thProm

otesinvasiveness

Promotes

invasivenessL

eafnumber

Am

biguousL

eafmorphology,canopy

structureA

mbiguous

PhysiologicalPhotosynthetic

rate/capacityProm

otesinvasiveness

Water,N

andP

useeffi

ciencyProm

otesinvasiveness

Chlorophyllcontents

Lim

itedinfo

LeafN

contentsL

imited

infoL

eaflongevityL

imited

infoTissue

constructioncosts

Lim

itedinfo

Specificleafarea

Promotes

invasivenessProm

otesinvasiveness

Leafarea

ratioProm

otesinvasiveness

TotalleafareaA

mbiguous

Seedlingrelative

growth

rateA

mbiguous

Promotes

invasivenessG

rowth

rate,allocationto

growth

Promotes

invasiveness

Reproductive

Self-compatibility

No

patternL

imited

infoB

reedingsystem

Some

typesare

relatedPollen

qualityL

imited

infoPollen

vectorN

opattern

Time

offlowering

Early

/longerflowering

Early

/longerflowering

Generation

time

Lim

itedinfo

FecundityProm

otesinvasiveness

Propagulesize

Promotes

invasivenessL

imited

infoD

ispersalmode

andeffi

ciencyA

mbiguous

Promotes

invasivenessSeed

releaseL

imited

infoG

ermination

abilityProm

otesinvasiveness

Seedlingsurvivaland

establishment

Promotes

invasivenessSeed

dormancy

/bank/longevity

/sizeL

imited

infoProm

otesinvasiveness

8.2 Attributes of success: What traits tell us about invasions? 121

models Chapter 2, 4 and 5). Together, these results indicate a context dependenceon alien–native performance differences, and how opposite and balancing mechanismmight act at different spatial scales. Specifically, evaluating the effect of scale on thesedifferences showed a consistently unbalanced distribution across a scale gradient rang-ing from species to regions. These comparisons suggest that the process causing traitdifferentiation (i.e. limiting similarity) mainly acts at the smallest scale of analysis (74to 94% of the trait differentiation variability is captured at the species level, as shown inChapter 4). Comparisons at larger scales capture only a marginal fraction of the vari-ability in trait differences (0 to 17%); indicating how at these scales ecological factorsdrive analyzed traits towards convergence (i.e. phenotypic attraction). From this is clearthat according to scale of analysis, evaluated attributes could show either patterns ofdivergence (e.g. plot–community scales) or convergence (e.g. areas–biomes–regions).

When focusing only at a community scale, the more dissimilar (functionally and/orphylogenetically) an alien species is to the native species community pool, the greaterits chances are that it will be successful when introduced (as shown in Chapter 3, 4and 5; and reviewed by Diez et al. 2009, Pysek & Richardson 2007, van Kleunenet al. 2010). We emphasize that, although the summarized patterns of differentiation (inuni– or multivariate trait spaces) seem rather small in absolute (15 to 26% Chapter 3)or relative terms (2 to 16% Chapter 4 and 5); it is very difficult to predict how big atrait difference should be in order to be of ecological relevance (e.g. in competition),as hardly any data on this are available in the literature. In fact, the classic principleof competitive exclusion (Gause 1934) can be interpreted such that very small but con-sistent trait differentiation among species, competing for a single resource, will alwayslead to full competitive displacement.

The idea of functional dissimilarity between aliens and natives has been tested previ-ously by focusing on how a particular attribute of an alien species differs from those ofco–occurring natives (as discussed in the introduction and summarized in Table 8.1).When comparing the findings from these works amongst them, and with those of thisdissertation, is clear that any discrepancy will emerge from the differences in the spatialand/or phylogenetic scale of the comparisons. This indicate how formulating the alien–native comparison in an explicit scale context (spatial and taxonomic/phylogenetic) isessential for revealing and understanding both the mechanisms behind the observedalien–native trait similarity/dissimilarity patterns, and the relation between these differ-ences and the success of an introduced species.

Lastly, the comparison criteria might also play an important role on the observed traitconvergence–divergence patterns (as discussed in the introduction and Chapter 6). Forexample, in the case of comparison with a native community pool (multi–species con-trasts as presented in Table 8.1) aliens are expected to show trait differentiation, dueto niche filing, competitive exclusion and limiting similarity. On the contrary, compar-isons within a similar growth form, functional group or between closely related species(experimental paring of species based on functional, phylogenetic or taxonomic simi-larity, as presented in Table 8.1) traits of aliens would tend towards convergence withthe compared species of group.

It seems counterintuitive that successful aliens are dissimilar to most natives, but


similar to closely related natives (in a functional or phylogenetic space). This apparentparadox can be explained (as discussed in Chapter 6 and by Scheffer & van Nes 2006),by a balance between niche filing–adequacy mechanism. In un–invaded conditions,species are spread out in a trait/niche space (as assumed by limiting similarity andniche partitioning theory), making the intermediate positions between native speciesopen niches; and obviously the best places for new invaders. However, if the intro-duced non–native is very similar in a functional space (or in a community were residentspecies traits/niches are closely packed), the areas between species traits/niches are un-suitable locations (MacArthur & Levins 1967b, Scheffer & van Nes 2006), making theinvasion of areas close to the native–pair a more viable option. The balance betweenthese two forces would then lead to the observed pattern of alien species occurrencein a given community. Specifically, areas between natives in a given area can onlybe invaded by highly competitive species (the so called super invaders; as discussedin Daehler 2003, Richardson & Pysek 2006). Whereas the areas between functionallyclose species are relative windows of opportunity where even relatively weak aliens canbe successful if they are functionally similar to those natives. A point to emphasize hereis that this balance can be easily broken by the random introduction of certain species(with unusual high competitive ability) and intrinsic native–native and alien–native dif-ferences in overall competitive power.

8.3 Possible mechanisms responsible for aliens’ traitdifferentiation/similarity

As an alien species is introduced to a new region/habitat, it must overcome a set of envi-ronmental and biological barriers (e.g. seed germination, seedling establishment, phys-iological tolerances, demographic stochasticity, and biotic interactions) all of which re-strict its’ demographical and physiological success (Pysek & Richardson 2007, Richard-son & Pysek 2006). In addition, it is almost inevitable that introduced plant populationswill loose most of its natural enemies (specialist), mutualism and competitors; while atthe same time establish new interactions with those species occurring in the new area(Levine et al. 2004, Mitchell et al. 2006, Mitchell & Power 2003, Rejmanek et al. 2005).From this perspective, trait differentiation from the existing native species poll wouldallow aliens to succeed in their introduced range by reducing possible competitive inter-actions with the native community. Meanwhile, similarity to natives would allow aliensto overcome the restrictions imposed by environmental factors (Fig. 8.1). Resultingform this balance, trait segregation between co–occurring native and aliens (as pointedout in Chapter 3, 4, and 5) would trigger dissimilarities in performance, competitiveability, and growth–reproduction dimensions, between introduced and all native plantson a site. Meanwhile, trait similarity at larger scales (as pointed out in Chapter 4) wouldbe the result of habitat filtering and niche conservatism (Chapter 7).

The emerging question is then, how aliens manage to obtain these differences intraits?. Several possible explanations/mechanism have been proposed to answer thisquestion. These range from phenotypic plasticity, mutation–hybridizations–polyploidy

8.3 Possible mechanisms responsible for aliens’ trait differentiation/similarity 123

Trai

ts o

f the

alie

nBi

otic

-abi

otic

com

mun

ity fe

atur

es

Community invasibilityPropagule pressure

Biotic resistance hypothesisInvasion meltdown

Enemy releaseHabitat filtering

Empty nicheMutualist facilitation

Species invasivenessTens Rule, Residence time, Taxonomic affiliation

Darwin’s naturalization hypothesisPhenotypic plasticity and evolution

Long-distance dispersalNovel weapons

Species-Com

munity invasibility

Theory of seed plant invasivenessT

heory of fluctuating resourcesEvolution of increased com

petitive ability

Introduction

Climatic suitability

Trait similaritydissimilarity

Escape from predators

new weapons Bio-

geog

raph

ic (

Reg

iona

l)

Envi

ronm

enta

l (Lo

cal)

Perf

orm

ance

(Si

te)

Her

bivo

ry-P

aras

itism

(Si

te)

Figure 8.1 The ”alien introduction continuum” conceptualizes the various barriers that a plantmust overcome to establish a viable in a new environment (figure is adapted from Richardson &Pysek (2006)). Understanding of the dynamics of plant invasions requires insights on traits ofthe plant (elements of species invasiveness) and features of the environment (components ofcommunity invasibility), but neither aspect can be fully evaluated without reference to the other.A predictive framework for invasion biology should be a holistic combination of these factors inaddition to consider the spatial and phylogenetic scale of the contrast.

or the fact that aliens have the same extreme values in their home range (this last oneevaluated in Chapter 2). Supported on evidence coming both from the results presentedin this dissertation, and those of related fields [e.g. theories of trait/functional diver-sity evolution Ackerly (2003), resource competition theory Tilman (1982) and growthrate hypotheses Elser, Acharya, Kyle, Cotner, Makino, Markow, Watts, Hobbie, Fagan,Schade, Hood & Sterner (2003)] some of the possible mechanisms generating the ob-served trends in alien species traits are now discussed. First, lets’ focus on the role ofphenotypic plasticity, niche conservatisms and ecological filtering as factors triggeringthe observed changes on individual axis of the trait space (as done in Chapter 2, 4 and7); and second on the importance of changes in (or escape from) the factors constrainingthe trade offs between correlated traits (as assessed in Chapter 7 and 5).

Perhaps, the most likely mechanisms causing the observed patterns of trait adaptationin aliens is a combination of niche conservatism (as evaluated in Chapter 2 and 7) andphenotypic plasticity (Ackerly 2003). For non–natives, trait variation by phenotypicplasticity, would allow adjustments in their expressed traits, so that there is a bettermatch between performance and environment (hence a conservation of their fundamen-


tal niche). This process could be favoured by the escape (or strength reduction) from aseries of constraining costs known to limit the levels of trait variation (e.g. herbivory–parasitism, close competition with co–evolved plants, or investment in defence mech-anisms). This can potentially reduce the strength of selection (Donohue 2003), or/andalter the strength of ecological interactions (mainly predation and intense competition)within their new community.

Studies assessing the role of phenotypic plasticity on invasion success have indi-cated a higher plasticity of alien species when compared to natives (as reviewed byDaehler 2003). From them it could be concluded that aliens often have a wider physi-ological responses (Pattison, Goldstein & Ares 1998, Williams & Black 1994), biggerchanges in biomass allocation patterns in response to different environmental condi-tions (Baruch & Bilbao 1999, Simoes & Baruch 1991, Yamashita, Ishida, Kushima& Tanaka 2000) and/or larger variation in patters of germination (Hierro et al. 2009).Probably this mechanism is what allows non–natives to establish and prevail, while con-serving their niche and possibly their mean trait value. Nonetheless, it is important topoint that this does not imply an a priori performance advantage of aliens over natives,just a change in certain attributes related to plant performance. Furthermore, it is clearthe necessity to couple this phenotypic variation with the level of genetic variation inorder to assess the possible responses of an alien species to environmental changes overtime or space.

In addition to phenotypic plasticity, anthropogenic selection resulting from inten-tional or unintentional introductions is also a key factor determining the level of alienstrait variation, selection and change (Alpert 2006, Thuiller, Richardson, Rouget, Proches& Wilson 2006). In the case of intentionally introduced species, most of them have beenselected for their usefulness to humans with a special interest in species with horticul-tural and/or agronomic uses. This screening process has also aimed to select certaintraits within these species. Specifically species or genotypes with fast growth, high re-source efficiency, faster generation times, high reproductive output, or high resistance topathogens have been usually selected for human use (Alpert 2006, Thuiller et al. 2006).Unintentional introductions also impose a set of filters to the introduced community.These filters select a non–randomly set of traits which increase the probability that analien can be transported along with commercial goods, human belongings, or transportvessels. Most of these characteristics (e.g. high propagule number, dispersal by animals,parasitism on intentionally introduced organisms, tolerance of extreme conditions) arehighly correlated to human activity or human modified habitats (Alpert 2006, Leishman& Thomson 2005, Leishman et al. 2010) enhancing their probability of establishmentsuccess in human intervened areas. For either of these cases (i.e. intentional or uninten-tional introductions) successful aliens would most likely express the same attributes inboth its native and introduced region, or just vary within its’ natural range of phenotypicplasticity.

These factors (i.e. phenotypic plasticity, niche conservatisms and human selection ofattributes) could potentially drive alien species attributes to represent states at the edgesof previously described global domains of trait distribution (Falster & Westoby 2003,Moles et al. 2006, Moles & Westoby 2006, Wright et al. 2004). This use of areas at

8.3 Possible mechanisms responsible for aliens’ trait differentiation/similarity 125

the extremes of the trait domain was observed in our results (Chapter 3, 4 and 5)as indicated by the location and skewness of the observed alien mean trait values anddistribution, which significantly differed when compared to the native community. Thislinks to the mechanism discussed next, the escape of biophysical costs.

Phenotypic plasticity and anthropogenic selection might enhance or direct the pat-terns of trait variation. The effects of ”biophysical costs” (or in the case of aliens es-cape from them) would then constrain trait variability by establishing a space of viabletraits–combinations (or ”trait envelope). As discussed in the introduction, a multidi-mensional trait spectrum is limited by a set of biophysical costs (e.g. physical proper-ties of the tissue, biotic milieu, environmental factors, disturbance regimes, etc.) andevolutionary processes (e.g. trait coevolution) that creates what could be considered acommunity ”trait envelope” (Fig. 8.2). This represents (as presented in Fig. 8.2) thebalance between the possible advantages and disadvantages of being in one end or theother of an ecological strategy. All else being equal, the trait space from alien colonizersshould be restricted by the same factors (trade–offs, evolutionary and physiological con-strains) that limit natives (as shown in Chapter 5 and by Leishman et al. 2007, Leish-man et al. 2010). But as predation pressures are reduced, due to aliens escape frompredators–parasites, non–natives can then occupy spaces far from the native species’physiological–cost effective optima. As a result, the new alien population would expe-rience strong selection for shifts on more than one trait axis, due to the coordinationspecifying an ecological strategy (that is a movement along the strategy axis; as shownin Chapter 5 and schematized in Fig. 8.2).

Some of the major hypothesis explaining the advantage of aliens over native species,such as the enemy release hypothesis (Colautti et al. 2004, Torchin & Mitchell 2004),novel weapons (Callaway & Aschehoug 2000, Callaway & Ridenour 2004), invasionmeltdown (Richardson, Allsopp, D’Antonio, Milton & Rejmanek 2000, Sax, Stachow-icz & Gaines 2005, Simberloff & Von Holle 1999) or the empty niche (Elton 2000, Hi-erro et al. 2005), etc. are related to the escape from one or more ”biophysical costs”.Therefore, understanding the consequences of these factors on the trait variation ofaliens would be useful for determining both the causes and consequences of escapingthe limitations imposed to traits variation.

Is clear that large mixture of mechanisms may underlie invasion success (Levine,Vila, D’Antonio, Dukes, Grigulis & Lavorel 2003), and the ones proposed here are onlybased on theoretical backgrounds or indirect evidence from studies in the field of traitevolution/differentiation. But as suggested by the evidence summarized in this disser-tation and other similar studies (e.g. Crawley et al. 1996, Gonzalez et al. 2010, Lake& Leishman 2004, Leishman & Thomson 2005, Ricciardi & Atkinson 2004, Scharfy,Funk, Venterink & Gusewell 2011, Strauss et al. 2006, Thompson et al. 1995, van Kle-unen et al. 2010, Williamson & Fitter 1996), a key element to understand the successof non–natives in their introduced range is considering the functional or phylogeneticrelatedness between the alien and native community, and its relation to differences inplant performance.


Trait combinationnot competitive or viable

Trait combination not possible due tobiophysical constrains and costs

For example: physical properties of the tissue, biotic milieu, environmental factors, disturbance regimes

NativeAlien

Native

Alien

Trait - A

Trai

t -

B

Figure 8.2 Shift between alien and native plants along an ecological strategy. Due to theevolutionary and physiological constrains imposed to both individual traits and its trade-offswith related attributes (which define the ecological spectrum of interests), alien and nativespecies are expected to fall within the same ecological strategy (no changes in the relationsbetween related traits). We show how aliens have trait combinations shifted towards the extremeof the native trait envelope define by the ecological strategy.

8.4 From patterns to mechanisms: Linking traitconvergence–divergence to hypothesis explaining aliensuccess

Various hypotheses have been proposed to explain which species would be success-ful once introduced. These are based on how differences or similarities in life historyattributes determine both the demographic success (e.g. long–term and large–scale pos-itive or stable population growth) and the ecological impact of an introduced species.Methodological approaches used to determine both of these aspects could be grouped aseither focusing on either the characteristics of invaders (e.g. Kolar & Lodge 2001, Pysek& Richardson 2007, van Kleunen et al. 2010); properties of the invaded community(e.g. Blumenthal 2005, Davis et al. 2000, Hufbauer & Torchin 2007, Keane & Crawley2002, Shea & Chesson 2002); or evolutionary processes (e.g. Diez et al. 2008, Dun-can & Williams 2002, Ellstrand & Schierenbeck 2000, Maron, Vila & Arnason 2004,Rejmanek 1996, Strauss et al. 2006, Thuiller et al. 2010). The goal of this section is toestablish a link between the patterns of traits (dis)similarity reported in this dissertation,

8.4 From patterns to mechanisms 127

and some of the most accepted species, community and evolutionary based hypothesesused to explaining alien species success.

8.4.1 Species based hypothesis

As discussed previously, efforts to determine the attributes of successful aliens has yieldnumerous generalizations on the question ”what makes an alien successful?”; and mul-tiple hypotheses aiming to explain these patterns (reviewed by Sax & Brown (2000),Hierro et al. (2005), Mitchell et al. (2006) and Hufbauer & Torchin (2007), and summa-rized as species hypotheses in Table 8.1). Species based hypotheses suggest that aliensare either inherently superior than natives (e.g. inherent superiority and novel weaponshypotheses); or that aliens are only successful in areas where they are sufficiently dif-ferent to the native community, so that they avoid competition (e.g. empty niche andenemy release hypotheses). In the first case, this means a generalized differentiationbetween plant groups, especially in axes of ecological variation related to competi-tion, reproduction and/or growth (as shown in Chapter 2 for multivariate trait com-position and in Chapter 5 for individual leaf traits). Other works have also addressedthis conception of generalized superiority of aliens, based on measures of competition(Callaway & Aschehoug 2000, Sax & Brown 2000) or defense mechanisms (Callaway& Ridenour 2004, Vivanco et al. 2004). Nevertheless, is clear that this is only a first or-der approach to understand the success of aliens, given that a particular differentiationin attributes is not advantageous under all situations (having a 10% larger leaf, does nothave the same implication in a desert than in a tropical rain forest).

The results presented in Chapter 3 and 5, support the idea of inherently superiorof an alien when compared to co–occurring natives. Of particular interest are thosefinds relating to traits associated with carbon capture strategies (i.e. traits of the ”leafeconomics spectrum” compared in Chapter 5). These indicate how alien species aresuccessful not because they have different resource acquisition strategies or lower nutri-ent requirements than natives. Rather, it seams that the suite of traits expressed by thesespecies provides them with a competitive advantage from co–occurring natives (e.g.higher specific leaf areas, shorter life cycles, devote more resources to reproductionand produce more seeds that are better dispersed and germinate faster). Nonetheless,the large variability of alien–native differences across sampled locations suggests howsite conditions are what ultimately determine the level of differentiation between thesegroups (as shown Chapter 3, 4 and 5 by a significant effect of sites in trait compar-isons). As a result any performance advantage of an alien with respect of co–occurringnatives is site specific.

The idea of site–specific advantageous trait combinations was supported by boththe significant, and positive relation, of leaf traits and resource availability gradients(Chapter 5) and the scale dependence of the differentiation between natives an alienspecies (Chapter 4). Although it was not possible to address the effect of changes inthe biotic–milieu (composition of direct competitors, herbivores and parasites) due tolack of adequate information; it was hypothesized that the escape from enemies byaliens, once introduce to a new area, enhances and possibly causes the differences


between alien–native species. This will be especially the case for areas with high re-source/disturbance rates, as suggested by Blumenthal (2005), due to possible higherperformance gains (moving to the fast end of the resource acquisition spectrum) fromenemy release in high resource/disturbance areas. It is clear that there is a need forlarge scale field based conspecific comparisons, aiming to evaluate how alien speciesin high resource/disturbance situations are more strongly released from enemies thanthose under lower resource/disturbance conditions.

8.4.2 Community based hypotheses

The species assembly in a given plant community can be perceived as the result ofthe interaction between the conditions of the area in which a species arrive (such asresources, climate and disturbance), when they arrive (time of introduction and sub-sequent re–introductions), and how these interact with both its’ environment and eachother (balance between competition–herbivory–parasitism). Species introductions fit inthis scheme, as new colonizers face the same constrains as natives do for establishingsuitable populations in to particular communities (Fig. 8.2). Based on these principles,several hypotheses have been proposed to explain alien species success (e.g. biotic re-sistance hypothesis, fluctuating resources, and the resource–enemy release hypothesis,as discussed in Chapter 1). These ideas focus on the attributes of the community wherea given alien species is introduced, aiming to determine how these factors relate to thelikelihood of that location being invaded. In this dissertation two alternative hypotheseslinking community properties to aliens success were considered: the biotic resistanceand the resource–enemy release hypothesis.

The biotic resistance hypothesis, is one of the oldest principles in invasion ecology(Elton 2000). It’s based on the idea that communities’ with high species diversity areless likely to be invaded. Most studies testing this hypothesis have focus on how alienswill interact with resident species (mainly competition) and the level of saturation ofthe recipient community (availability of niches). However, the results from these com-parisons have been inconclusive, showing both positive and negative relations betweendiversity and probability of alien success (as reviewed in Levine et al. 2004, Sax &Gaines 2003, Shea & Chesson 2002). This discrepancy has been usually attributed tothe scale dependence of diversity patterns (Sax & Gaines 2003, Sax et al. 2005).

Alongside the scale dependence of this relation, an alternative explanation of thisdiscrepancy is the effect of diversity on the balance between resource supply and avail-ability in a site. As experimental studies have shown (Fukami 2001, Levin 2000), thenumber of species using the available resources determine the resource availability (i.e.density of unused resources as nutrients and water) of a location, and it in turn would de-termine the possibility of successful introductions (resource opportunities as describedin Shea & Chesson 2002). For example, diverse communities will contain species witha grater range of traits, thus making the use of resources more efficiently (proposed bythe resource use complementarity hypothesis Loreau & Hector (2001) and discussedin Chapter 3). As a result of this, a limited supply of resources would be availablefor aliens to tap in (i.e. a reduced resource availability). The same effect could also be

8.4 From patterns to mechanisms 129

caused if these diverse communities contain species with traits that allow them to useresources either more efficiently or at a faster rate, as proposed by the sampling effecthypothesis (Tilman 1999), so that the reduction in the resource supply poll is reducedto suboptimal levels for aliens.

An alternative view on the effect of available resources and alien success is theresource–enemy release hypothesis. This idea, originally proposed by Davis et al. (2000)and adapted by Blumenthal (2005), builds from the association between alien speciessuccess and environmental conditions, resource availability , disturbance, and releaseof enemies. The principle of this hypothesis is that a plant community with unusedresources (such as water, nutrients, space or light) will be more susceptible to introduc-tions (as tested in Chapter 5). The pool of unused resources will be then determined bythe balance between the supply and uptake of these by the resident native community.As conditions (climatic and nutrient availability) are not fixed over time, fluctuation inthe resource availability will create windows of opportunity for invasions (as reviewedby Davis et al. 2000). Additionally, the scape from predators and/or parasites couldaffect the benefits of higher available resources synergistically. This synergy betweenbiotic and abiotic factors is centred on how changes in predation–parasite pleasures or’escape opportunities” (that is low level or low efficiency of natural enemies to whichaliens might be susceptible) might provide a greater benefit for species adapted to high–resource conditions (Blumenthal 2005). This is typically the case of plants growing inresource rich areas, where they are typically fast growing, and not well defended againstenemies.

Test of these ideas in Chapter 5 showed how performance of native and alien plantsis associated to resource availability gradients. Evidence for this was the significant re-lation between alien and native traits (and position along the carbon–strategy spectrum)and gradients of soil fertility and disturbance (Chapter 5). This, in combination with theconsistent carbon strategy of aliens and natives along the same global resource and dis-turbance gradients (Leishman et al. 2007, Leishman et al. 2010), indicate how given theadequate conditions, any given species could and would be successful when introduced.As a result, the success of a given introduced species is then not dependent of area oforigin; but rather, it is determined by it having a suite of traits enabling to exploit thenew habitat and the biotic–abiotic–disturbance setup it’s confronted with (Thompson &Davis 2011).

8.4.3 Evolutionary based hypotheses

Several works have recently addressed the link between evolutionary patterns and aliensuccess (e.g. Agrawal & Kotanen 2003, Cadotte et al. 2009, Jiang et al. 2010, Mack2003, Proches et al. 2008, Thuiller et al. 2010). These pick up on Baker et al. (1965)work addressing the potentially critical role of evolution in the success of colonizingspecies, although important progress has been made, understanding of the evolutionarydimension of this problem remains rudimentary. This is perhaps due to the challengesof both in understanding when and how evolution plays a role in the success of alienspecies. Additionally, determining a way to measure and interpret patterns emerging


from these evolutionary processes has also proven to be challenging. Irrespective ofthese problems, the known impact of evolutionary processes on the fitness of introducedindividuals makes the evaluation of this dimension necessary for predicting successfulintroductions.

The influence of evolutionary process on aliens’ success might be in from of compet-itive advantages when compared to co–occurring natives (addressed in Chapter 4 and6), or performance differences between the introduced and native range (addressed inChapter 2). In this dissertation, two of the most important theories linking the level ofsimilarity in attributes and the success of aliens (e.g. evolution of increased competitiveability and Darwin’s naturalization hypothesis) were examined.

The evolution of increased competitive ability proposes that in the new area, changesin the selection pressures (due to founder effects, genetic bottle necks, hybridization,genotypic plasticity, etc.) will drive changes in performance attributes. A particular caseof this is the investment in costly defenses against enemies, which would no longerenhance fitness if aliens escape from natural enemies in the new area. Results frommeta–analyses in this dissertation (Chapter 2 and Chapter 7) consistently supportedthe trait conservation hypothesis and not the evolution of increased competitive abilityhypothesis. It’s shown in Chapter 2, how traits of con–specifics, closely linked to keyecological strategies of plant performance, are consistently similar between the nativeand introduced range. This pattern was also observed for other studies (as summarizedin Chapter 7). Together this would suggest that traits are conserved along the trait spec-trum, as no differences in evaluated attributes of non–natives was detected between theirnative and alien, naturalized and invasive ranges.

Although the analyzed attributes in this dissertation show a consistent conservationacross space, it is not implied that aliens do not have the potential to phenotypicallyor genetically adapt to the new conditions they might encounter in their new habitat(as we explain in Chapter 2). It’s considered that traits on a site are the result of thebalance between long–term evolutionary inertia pushing towards the conservation oftraits (Rejmanek 1996), and short–term adaptation to biotic interactions, environmentalstochasticity and phenotypic plasticity that favours trait variation [such as core phys-iological and genetic constrains which shape the fundamental niche, as presented inGrime (2006) and Webb et al. (2002)]. In other words, those traits that have been shownto be highly conserved over evolutionary time (e.g. wood density, seed mass, SLA, leaflife span) will be more conserved across ranges than those that are highly influencedby biotic, ecological or environmental gradients (e.g. canopy transpiration, rhizome re–sprouting, height, relative growth rate).

Darwin’s naturalization hypothesis on the other hand, links evolutionary dynamicsto the level of similarity between aliens and co–occurring natives. It states that closelyrelated species will overlap more in their niches (and therefore in their traits) than lessrelated species (Rejmanek 1996, Thuiller et al. 2010). As a result novel genera wouldbe more successful in colonizing new ranges than genera with native representatives.An alternative formulation of the role of phylogenetic relatedness and niche overlap istermed the phylogenetic attraction hypothesis (Webb et al. 2002). It argues that intro-

8.5 Final conclusions 131

duced aliens that are closely related to native residents might have improved chances ofnaturalizing as they share similar pre–adaptations to the local environmental conditions.

Analyses presented in Chapter 2 and 7 indicate that alien species showed, when com-pared to co–occurring natives, a tendency to phylogenetic clustering (i.e. closely relatedspecies co–occurring on a site), therefore supporting the predictions of the phylogeneticattraction hypothesis. This similarity was consistent also for comparisons controllingfor spatial scale (Chapter 4). The evidence presented in this dissertation provides strongsupport for the importance of evolutionary patterns and the need to account for phylo-genetic relationships when examining alien invasions, especially when the goal of thestudy is to predict which alien species might be successful.

By examining global distribution patterns of native and alien species traits, this workhas shown how the observed distribution of alien plant communities is the likely re-sults from two mechanisms. First, alien species showing an evolutionary conservationof traits, restricting them to areas that match the environmental conditions of their na-tive habitat (for reviews and meta-analysis of this topic see Cahill Jr, Kembel, Lamb &Keddy 2008, Pysek & Richardson 2007). Second, the environmental conditions of thenew habitat would filter out unsuitable aliens, therefore allowing only those species withtraits similar to native species to colonize (Wiens et al. 2010, Wiens & Graham 2005).

8.5 Final conclusions: where do we stand and where does the roadahead lead to?

Invasion biology research agenda has reached an exciting point. The combined effortof large numbers of individual case and community studies has allowed the produc-tion of several testable hypothesis while setting the ground for theoretical advancement.Additionally, the study of introductions has provided a unique, but unfortunate, op-portunity to address the possible ecological and evolutionary mechanisms behind bothspecies distribution and community assembly patterns (Callaway & Maron 2006, Shea& Chesson 2002). The scientific importance of this reaches far beyond the field on in-vasion biology.

In this work it has been shown, in a fairly robust way, that alien species have a combi-nation of traits that significantly differs from those of the native community where theyare introduced, hence supporting the classic empty niches’ idea to explain invasions.Meanwhile, the attributes of these successful aliens show no significant change betweenranges, indicating that the observed pattern of trait conservatism between ranges orig-inates from core ecological, physiological and genetic constrains. These trends wereconsistent when the dissimilarities between plant types were evaluated in a commu-nity context (comparison of co–occurring aliens and natives) and when the spatial scaleof this community context (i.e. how a community is defined) was taken in to consid-eration. Together, the evidence presented here very clearly indicates how the role ofplant traits in the colonization process of aliens is to a very large extent context specific(biogeographical–environmental–evolutionary). As a result, traits that might confer an


advantage in a given community might be neutral or even detrimental in different con-ditions.

The road ahead for invasion biology should be paved on all the available biogeo-graphical, environmental and evolutionary information, and should aim to link life his-tory, community characteristics and evolutionary processes. For this some key factorsmust be carefully considered:

Appropriate spatial scale: Ecological and evolutionary mechanisms act at particularscales. This makes the use of multi–scale contrast the best approach to evaluate theinfluence of all possible mechanisms driving introduction success.

Appropriate phylogenetic scale: Framing the comparison between aliens and nativesin an adequate context is relevant. To which species or group of these are aliens con-trasted; also the phylogenetic background of the community they are embedded is im-portant to determine the possible mechanism driving the observed patterns.

Appropriate measure of (dis)similarity: Both functional and phylogenetic informa-tion should be considered in the quantification of the dissimilarity between aliens andnatives.

The work presented here is a contribution to the long lasting quest for understand-ing the causes and mechanisms behind the species invasiveness–community invasibilitycontinuum. This dissertation aimed to link three separate lines of evidence that havereceived considerable attention independently (species invasiveness, community invasi-bility and evolutionary patterns). It is clear that if the ultimate goal is to predict invasionrisks (by a species or of an area) these three dimensions must be accounted simultane-ously

9 SummaryAlejandro Ordonez Gloriaab

The globalization of human activities has resulted in the intentional and un–intentionalmovement of animal and plant species to areas beyond their natural range. This hasultimately resulted in both the biotic homogenization of natural areas across the worldand irreversible changes to the functioning of various ecosystems. Given that both ofthese changes pose a significant threats to indigenous flora and natural ecosystems,understanding the why, when and how of biological introductions is crucial. Because ofthis, one of the main goals of invasion biologists and community ecologists has beendetermining what makes a given species invasive or a community prone to invasions.

In an effort to reach this goal, biological introductions have been addressed using twoalternative perspectives: a species–based (asking, which species are invasive?); and acommunity–based (asking, which habitats are most likely to be invaded?). Each of theseperspectives provides complementary answers to the ”what drives invasions” question.Therefore, any progress towards a general theory of plant invasiveness can only beenachieved by pooling evidence from both perspectives.

Several approaches have been used to answer these questions (e.g. population dy-namics, invasive history, human use, trade intensity); but so far, the use of functionaltraits has proven to be the most promising. This is due to the importance of certaintraits (e.g. carbon capture, reproductive effort or light competition) in determining plantperformance, and hence their success. Describing the invasion process in terms of keyattributes, and especially those related to performance and metabolic homeostasis, hasallowed scientists to formulate some of the most accepted hypotheses explaining alienssuccess (e.g. evolution of competitive ability, novel weapons, new niches, Darwin’snaturalization hypothesis). In these hypotheses, as in classical community ecology, thesuccess of a colonizing alien is considered to be result of the influence on plant per-formance of environmental gradients (a species’ expected performance is a functionof both its fundamental niche and functional traits) and biotic interactions (changes inspecies optimal performance due to biotic interactions that shape a species fundamentalniche).

This dissertation addresses the invasiveness/invasibility question by exploring globalpatters of trait (dis)similarity between co–occurring alien and native plants. In order todo so, two questions were asked: Can aliens success be explain by alien and nativespecies trait (dis)similarity?; and, are the observed (dis)similarity patterns a productof evolution?. To answer these questions I first evaluated the relationship between na-tive and alien plants performance related traits, aiming to determine the existence of

134 Summary

a pattern of trait (dis)similarity between both groups. Second, I assessed the observednative–alien trait (dis)similarity patterns in relation to the ecological setup (commu-nity phylogenetic composition, scale and resource availability) of the introduced area.Lastly, I examined the role of evolutionary dynamics as the mechanisms generating theobserved trait (dis)similarity patters.

The first approach used in this dissertation is to determine the traits of successfulinvaders. Previous studies on the subject have yielded interesting results. Specifically,aliens have been found to have faster growth rates, higher concentrations of leaf nutri-ents and specific leaf areas, shorter life cycles, devote more resources to reproductionand produce more seeds that are better dispersed and germinate faster. Nonetheless, ex-pressing any of these attributes would give an advantage only on particular situations(e.g. having a large leaf area does not have the same implications in a desert than in atropical rain forest). Additionally, the biological context (traits of co–occurring species)also plays a major role on the advantages of particular traits.

In this dissertation both factors were considered by comparing aliens and native com-munities on particular locations (Chapter 3, 4, and 5). Evidence for inherently supe-riority of aliens when compared to co–occurring natives was observed. It is importantto emphasize that, although the summarized patterns of differentiation (in uni– or mul-tivariate trait spaces) seem rather small in absolute (15 to 26% Chapter 3) or reltivetermsa (2 to 16% Chapter 4, and 5); it is very difficult to predict how big a trait dif-ference should be in order to be of ecological relevance (e.g. in competition). Thesedifferences in traits representing an approximately independent axis of trait/strategyvariation also hold for comparisons based on the multivariate trait composition (SLA–Hmax–SWT axis in 3D or 2D spaces, Chapter 3) and their positioning along the ”leafeconomics spectrum” (Chapter 5). Analysis of the position of aliens in this multivari-ate trait–space revealed that non–natives trait values are clustered towards the edge of atleast one of the evaluated dimension, when compared to natives (Chapter 3 and 5). Thissuggests that the suites of traits expressed by aliens provides them with a competitiveadvantage over co–occurring natives. Nonetheless, the large variability of alien–nativedifferences across sampled locations indicate that site conditions ultimately determinethe level of differentiation between these groups (as shown in Chapter 3, 4, and 5 by asignificant effect of site in trait comparisons). In conclusion, any performance advantageof an alien with respect of co–occurring natives is site specific.

When the comparisons between aliens and natives were done within a similar growthform, functional group or between closely related species (experimental paring of speciesbased on functional, phylogenetic or taxonomic similarity) traits of aliens were found toconverge natives (as shown in Chapter 4, 6 and 7). This convergence (in a functional orphylogenetic space, Chapter 4 and Chapter 6) seems counterintuitive when comparedto the dissimilarity of aliens to most natives (Chapter 3 and 5). A possible explanationfor this is the balance between the availability of new niches to be invaded (interme-diate positions between native species niches) and constraints imposed by functionalsimilarity (intermediate positions become the worst places in the ”fitness landscape”).As a result of this balance, those areas between natives in a given area can only beinvaded by highly competitive species); whereas the areas between functionally close

Summary 135

species are relative windows of opportunity where even relatively weak aliens can besuccessful if they are functionally similar to those natives.

The second dimension evaluated in this dissertation is the relation between commu-nity conditions and alien success. Several hypotheses aim to determine how commu-nity factors relate to the likelihood of at location being invaded (e.g. biotic resistancehypothesis, fluctuating resources, and the resource–enemy release hypothesis). In thiswork two of these alternative hypotheses, linking community properties to alien suc-cess, were evaluated within the framework of ecological traits: the biotic resistance andthe resource–enemy release hypothesis. Both of these hypotheses can be related to theidea of ”resource opportunities” (i.e. the net result of the effects of all the organisms ina system and the supply of the resource) and how these define the conditions promotinginvasions.

The biotic resistance hypothesis is one of the oldest principles in invasion ecology,and is based on the idea that communities with a high species diversity are less likely tobe invaded. This is often explained by the lower resource availability thought to occur inmore diverse communities. The resource–enemy release hypothesis is also based on theidea that a plant community with unused resources (such as water, nutrients, space orlight) will be more susceptible to introductions. In this case, fluctuations in the resourceavailability (due to stochastic variations in resource use or supply) will create windowsof opportunity for invasions.

Test of this ideas using leaf traits important for plant carbon capturing strategies(SLA, Amass and Nmass), showed how performance of native and alien plants is asso-ciated to resource availability gradients (Chapter 5). The evidence for this was the sig-nificant relation between alien and native traits (and position along the carbon–strategyspectrum) and gradients of soil fertility and disturbance (Chapter 5). However, my com-parison of the difference in traits and carbon capture strategies of co–occurring alien andnatives showed no relation to environmental and disturbance gradients. Based on theseresults, I proposed that although higher resource availability benefits plant performance,these benefits are the same for both aliens and natives. This invalidates the hypothesisthat especially high resource availability promotes invasions by allowing aliens to out-perform natives due to differences in key traits that matter only under those conditions.

It’s possible that synergy between the biological setup and the environmental condi-tions is what determines whether or not an invasion will be successful. Although thiscouldn’t be specifically tested in this dissertation (due to lack of adequate informationon the abundance or presence of enemies), it is possible that the escape form enemiesby aliens, once introduce to a new area causes the differences between alien–nativepositions along the ”leaf economics spectrum”. This will be especially the case for ar-eas with high resource/disturbance rates. As experimental evidence provides a strongsupport for this idea, there is still a need for large scale field based con–specific com-parisons, aiming to evaluate how alien species in high resource/disturbance situationsare more strongly released from enemies than those under lower resource/disturbanceconditions.

The third dimension evaluated in this dissertation is the relation between evolutionaryprocess, and the mechanisms determining the success of colonizing species. Although

136 Summary

most of research on the mechanisms underlying biological invasions has focused onthe ecological explanations, several works have recently addressed the link betweenevolutionary patterns and alien success. These efforts have generally assumed two typesof associations between evolutionary and niche divergence/convergence patters: i) thedegree of phylogenetic relatedness translates in to niche overlap, and ii) the niche of aspecies is fixed over ecological time scales. Together, these two associations are at thebase of many population, community and macro ecological studies, and therefore hasmajor implications for conservation biology/ecology.

The role of evolution on the success of colonization success of alien species has beenformalized in several evolutionary hypotheses to explain invader success. In this disser-tation, two of the most important theories making this linking were examined: evolutionof increased competitive ability (Chapter 2 and 7) and Darwin’s naturalization hypoth-esis (Chapter 2, 4 and 7). In both of these hypotheses, the influence of evolutionaryprocess on aliens’ success might be in the form of competitive advantages when com-pared to co–occurring natives ( Chapter 4 and 7), or performance differences betweenthe introduced and native range (Chapter 2).

My tests of the evolution of increased competitive ability hypothesis (i.e. changesbetween ranges, Chapter 2) showed how traits of con–specifics are consistently simi-lar between the native and introduced range. These similarities were observed at bothuni– and multidimensional trait spaces. This would suggest that traits are conservedalong the trait spectrum, are little subject to evolutionary change. However, I do notimply that aliens do not have the potential to phenotypically or genetically adapt to thenew conditions they might encounter in their new habitat in any trait (as discussed inChapter 2). But I suggest that those traits that have been shown to be highly conservedover evolutionary time (e.g. wood density, seed mass, SLA, leaf life span) will be moreconserved across ranges than those that are highly influenced by biotic, ecological or en-vironmental gradients (e.g. canopy transpiration, rhizome re–sprouting, height, relativegrowth rate).

Based on the phylogenetic conservation of niches idea, Darwin’s naturalization hy-pothesis was evaluated by comparing the relation between co–occurrence, phylogeneticrelatedness and trait similarity of alien and native plants (Chapter 6). Additionally thelevel of spatial variability on these relations (Chapter 4) was also assessed. Results formthese two evaluations indicated that alien species show phylogenetic clustering (traitsof co–occurring species are more similar than expected by chance) when comparedto co–occurring natives. These trends are consistent for individual growth forms anddifferent comparison criteria (i.e. all co–occurring natives, phylogenetically closest na-tive and average native, Chapter 6); and when comparisons controlled for spatial scale(Chapter 4). This provides strong support for the importance of incorporating evolu-tionary patterns and the need to account for phylogenetic relationships when examiningalien invasions, especially when the goal of the study is to predict which alien speciesmight be successful.

This dissertation aimed to link three separate lines of evidence (species invasiveness,community invasibility and evolutionary patterns) that have received considerable at-tention independently. It is clear that if the ultimate goal is to predict invasion risks in

Summary 137

the future (by a species or of an area) these three dimensions must be jointly accounted.The work presented here is a contribution to the long lasting quest for understanding thecauses and mechanisms behind the species invasiveness–community invasibility contin-uum.

In conclusion, I suggest that determining successful introductions will require theevaluation of three community attributes: the level of functional similarity between na-tives and aliens; the degree of phylogenetic relatedness between these groups; and theresource availability–disturbance regime of the target community.

10 SamenvattingAlejandro Ordonez Gloriaab

De globalisering van menselijke activiteiten heeft geleid tot opzettelijke en de onopzettelijkeverspreiding van dier- en plantensoorten buiten hun natuurlijke verspreidingsgebied. Ditheeft uiteindelijk geresulteerd in zowel biotische homogenisering van de natuurlijke ge-bieden over de hele wereld en onomkeerbare veranderingen in het functioneren van deverschillende ecosystemen. Gezien het feit dat beide van deze veranderingen een be-langrijke bedreiging voor inheemse flora en de natuurlijke ecosystemen is, is het vancruciaal belang om het waarom, wanneer en hoe van biologische introducties te begri-jpen. Om deze reden, is een van de belangrijkste doelen van ecologen het bepalen watplantsoorten invasief maakt en wat een plantgemeenschap gevoelig maakt voor invasies.

twee alternatieve perspectieven bekeken: een soort gerichte aanpak (welke soortenzijn invasief?), en een plantgemeenschap gerichte aanpak (welke habitatten wordenhet meest waarschijnlijk geinvadeerd door uitheemse plantsoorten?). Elk van deze per-spectieven biedt aanvullende antwoorden op de vraag ”wat drijft biologische invasies”.Daarom kan iedere vooruitgang op weg naar een algemene theorie van plantinvasiviteitalleen worden behaald door het samenbrengen van gegevens uit beide perspectieven.

Verschillende benaderingen zijn gebruikt om deze vragen te beantwoorden(bijvoorbeeldde populatiedynamiek, invasie geschiedenis, antropogeen gebruik, handel intensiteit),maar tot nu toe is bewezen dat het gebruik maken van functionele eigenschappen vanplanten een van de meest belovende benaderingen is. Dit is te wijten aan het belang vanbepaalde eigenschappen (bijvoorbeeld koolstofvastlegging, reproductieve inspanning oflicht competitie) bij het bepalen van plant prestatie, en daarmee hun succes. Door hetbeschrijven van het invasie proces in termen van de belangrijkste eigenschappen, vooraldie betrekking hebben op de prestatie en metabole homeostase, is het voor wetenschap-pers mogelijk een aantal van de meest geaccepteerde hypotheses te formuleren die hetsucces van uitheemse soorten uitlegt (bijvoorbeeld de evolutie van concurrerend vermo-gen, nieuwe wapens, nieuwe niches, Darwins naturalisatie hypothese). In deze hypothe-sen wordt het succes van een koloniserende uitheemse plant beschouwd als gevolg vande invloed op de plant prestatie over omgevingsgradinten (de verwachte prestaties vaneen soort is een functie van zowel de fundamentele niche en functionele eigenschappen)en biotische interacties (veranderingen in de optimale prestaties van de soort te wijtenaan biotische interacties die de fundamentele niche vormt).

Dit proefschrift behandelt de invasiviteit/invasibiliteit vraag door het verkennen vande wereldwijde patronen van eigenschappen (on)gelijkenis tussen uitheemse en in-heemse planten die samen voorkomen. Om dit te doen, zijn twee vragen gesteld: Kan

Samenvatting 139

het succes van een uitheemse soort verklaart worden door de eigenschappen (on)gelijkenistussen uitheemse en inheemse soorten, en, zijn de waargenomen patronen van (on)gelijkeniseen product van evolutie?. Om deze vragen te beantwoorden heb ik allereerst de relatietussen inheemse en uitheemse plant prestaties gerelateerde eigenschappen gevalueerdom het bestaan van een patroon van eigenschappen (on)gelijkenis tussen beide groepente bepalen. Ten tweede, heb ik de inheemse en uitheemse eigenschappen (on)gelijkenispatronen beoordeeld in relatie tot de ecologische setup (fylogenetische samenstellingvan de plant gemeenschap, omvang en beschikbaarheid van resources) van het ge-bied waar ze zijn ingevoerd. Tot slot heb ik onderzocht wat de rol is van evolution-aire dynamiek als mechanisme van de waargenomen patronen van de eigenschappen(on)gelijkenis.

De eerste aanpak in dit proefschrift is het bepalen van de eigenschappen van suc-cesvolle uitheemse planten. Voorafgaande studies hebben interessante resultaten opgeleverd.Zij vonden dat uitheemse invasieve soorten de volgende eigenschappen hebben: snelleregroei, een hoger percentage voedingsstoffen in het blad en hoger specifieke blad opper-vlak, kortere levenscycli, meer middelen besteden aan de voortplanting, meer en beterverspreide zaden en snellere ontkieming. Toch uiten zich deze eigenschappen alleenals een voordeel in bepaalde situaties (bijvoorbeeld, een groot bladoppervlak in eenwoestijn heeft minder voordelen dan in een tropisch regenwoud). Daarnaast speelt ookde biologische context (eigenschappen van gelijktijdig optredende soorten) een belan-grijke rol in de voordelen van bepaalde eigenschappen.

In dit proefschrift zijn beide factoren onderzocht door het vergelijken van uitheemseen inheemse plantgemeenschappen op specifieke locaties (hoofdstuk 3, 4 en 5). Be-wijs voor inherent superioriteit van uitheemse soorten in vergelijking met gelijktijdigoptredende inheemse soorten werd waargenomen. Het is belangrijk om te benadrukkendat, hoewel de samengevatte patronen van differentiatie (in uni–of multivariate eigen-schappen ruimtes/landschappen) eerder klein lijkt in absolute (15 tot 26 % hoofdstuk3) of relatieve termen (2 tot 16 % hoofdstuk 4 en 5); het is moeilijk te voorspellen hoegroot een het verschil in eigenschap dient te worden om van de ecologische relevantie tezijn (bv. in de competitie). Deze verschillen in eigenschappen representeren min of meereen onafhankelijke as van eigenschappen/strategie variatie die ook geldt voor vergeli-jkingen op basis van de multivariate eigenschap samenstelling (SLA–Hmax–SWT 3D-of 2D-ruimtes, hoofdstuk 3) en hun positionering langs de ”blad economische spec-trum” (hoofdstuk 5). Analyse van de positie van uitheemse soorten in deze multivari-ate eigenschap–ruimte bleek dat niet-inheemse geclusterd in eigenschap waarden naarde rand van ten minste een van de gevalueerde dimensie, in vergelijking met inheemsesoorten (hoofdstuk 3 en 5). Dit suggereert dat de suites van eigenschappen die dooruitheemse soorten hen voorziet van een competitief voordeel uit gelijktijdig optredendeinheemse soorten. Toch geeft de grote variabiliteit van uitheemse–inheemse verschillentussen de bemonsterde locaties aan dat omstandigheden ter plaatse uiteindelijk de matevan differentiatie tussen deze groepen bepaalt (zoals aangetoond in hoofdstuk 3, 4en 5 door een significant effect van locaties in eigenschappen vergelijkingen). Samen-vattend, ieder prestatievoordeel van een uitheemse plant is ten aanzien van gelijktijdigoptredende inheemse soorten locatie specifiek.

140 Samenvatting

Vergelijkingen tussen uitheemse en inheemse planten binnen een gelijke groei vorm,functionele groep of tussen nauw verwante soorten (experimentele paring van de soortenop basis van functionele, fylogenetische of taxonomische gelijkenis) bleken eigenschap-pen van uitheemse en inheemse te convergeren (zoals in hoofdstuk 4, 6 en 7) .Deze convergentie (in een functionele of fylogenetische ruimte, hoofdstuk 4 en hoofd-stuk 6) lijkt contra-intutief in vergelijking met de ongelijkheid van uitheemse voor demeeste inheemse (hoofdstuk 3 en 5). Een mogelijke verklaring hiervoor is de bal-ans tussen de beschikbaarheid van nieuwe niches (standen tussen de inheemse soortenniches) en beperkingen opgelegd door functionele gelijkenis (tussenposities uitgegroeidtot de slechtste plaatsen in de ”fitness landschap”). Als gevolg van dit evenwicht, kanin een bepaald gebied lokale plantpopulatie alleen worden geinvadeerd door sterk con-currerende soorten), en dat de gebieden tussen functioneel vlak soorten zijn relatievewindows of opportunity waar zelfs relatief zwakke uitheemse succesvol kunnen zijn alsze zijn functioneel vergelijkbaar die inheemse.

De tweede dimensie die in dit proefschrift is gevalueerd is de relatie tussen de plant-gemeenschap voorwaarden en het succes van uitheemse plant. Verschillende hypothesenhebben tot doel om te bepalen hoe de plant gemeenschap factoren betrekking hebbenop de waarschijnlijkheid van invasies van uitheemse planten (bijv. biotische weerstandhypothese, fluctuerende middelen en de middelen–vijand release hypothese). hier hebik twee van deze alternatieve hypothesen, waarin plantgemeenschap eigenschappengekoppeld wordt aan het invasie succes van uitheemse soorten, werden gevalueerd inhet kader van de ecologische kenmerken: de biotische weerstand en de bron–vijand re-lease hypothese. Beide hypotheses kan worden gerelateerd aan het idee van ”resourcekansen” (dwz het netto resultaat van de gevolgen van alle organismen in een systeemen de levering van de middelen) en hoe deze de voorwaarden te bevorderen invasies tedefiniren.

De biotische weerstand hypothese is een van de oudste beginselen invasie ecologie,en is gebaseerd op het idee dat de plantgemeenschappen met een grote verscheidenheidaan soorten minder kans heeft om te worden geinvadeerd. Dit wordt vaak verklaard doorde lagere beschikbaarheid van resources bij meer diverse gemeenschappen. De bron–vijand release hypothese is ook gebaseerd op de gedachte dat een plant gemeenschapmet niet-gebruikte middelen (zoals water, voedingsstoffen, ruimte of licht) meer vatbaarzal zijn voor introducties. In dit geval zal fluctuaties in de beschikbaarheid van middelen(als gevolg van stochastische variaties in het gebruik van hulpbronnen of de levering)windows of opportunity creren voor invasies.

Het testen van deze ideen met behulp van blad eigenschappen die belangrijk zijnvoor de vastlegging van plantaardige koolstof (SLA, Amass Nmass), liet zien hoe deprestaties van inheemse en uitheemse planten is gekoppeld aan de beschikbaarheid vanresourcegradinten (hoofdstuk 5). Het bewijs hiervoor was de belangrijke relatie tussenuitheemse en inheemse planteigenschappen (en de positie langs de koolstof–strategiespectrum) en gradienten van de vruchtbaarheid van de bodem en verstoring (hoofdstuk5) . Echter, mijn vergelijking van het verschil in eigenschappen en koolstofvastleggingstrategien van gelijktijdig optredende uitheemse en inheemse soorten vertoonde geenrelatie tot het milieu en de verstoring van gradinten. Op basis van deze resultaten heb ik

Samenvatting 141

voorgesteld dat, hoewel een hogere beschikbaarheid van hulpbronnen voordelen heeftdoor plant prestaties, deze voordelen gelijk zijn voor zowel de uitheemse en inheemsesoorten. Dit ontkracht de hypothese dat vooral een hoge beschikbaarheid van resourcesinvasies bevordert doordat uitheemse beter te presteren dan inheemse als gevolg vanverschillen in de belangrijkste eigenschappen die kwestie alleen onder deze voorwaar-den.

De rol van de evolutie op het succes van de kolonisatie succes van uitheemse soortenis geformaliseerd in verschillende evolutionaire. In dit proefschrift werden twee vande belangrijkste theorien die de koppeling tussen kolonisatie succes en evolutie onder-zocht: de evolutie van de toegenomen concurrentie vermogen (hoofdstuk 2 en ??) enDarwin’s naturalisatie hypothese (hoofdstuk 2, 4 en 7). In beide hypothesen, zou deinvloed van de evolutionaire proces op uitheemse ’succes in de vorm van competitievevoordelen in vergelijking met gelijktijdig optredende inheemse soorten (hoofdstuk 4en 7), of prestaties verschillen tussen de ingevoerde en de oorspronkelijke verspreid-ingsgebied (hoofdstuk 2).

Mijn tests van de evolutie van de toegenomen concurrerend vermogen hypothese(dwz veranderingen tussen de reeksen, hoofdstuk 2) liet zien hoe eigenschappen vancon–specifics consequent vergelijkbaar zijn tussen de inheemse en uitheemse bereik.Deze overeenkomsten werden waargenomen bij zowel uni–en multidimensionale eigen-schap ruimten. Dit zou suggereren dat eigenschappen die bewaard zijn gebleven langsde eigenschap spectrum, weinig onderhevig zijn aan evolutionaire verandering. Ik sug-gereer niet dat uitheemse planten niet de potentie hbeen om zich fenotypisch of genetischaan te passen aan de nieuwe voorwaarden in hun nieuwe habitat in elke eigenschap(zoals besproken in hoofdstuk 2). Maar ik stel voor dat die eigenschappen waarvanis aangetoond dat ze in hoge mate behouden zijn over evolutionaire tijd (bijvoorbeeldhoutdichtheid, zaad massa, SLA, blad levensduur) zal meer worden bewaard over eenafstand dan die sterk worden benvloed door biotische, ecologische of milieu-gradinten(bijv. luifel transpiratie, rizoom opnieuw–kiemen, hoogte, de relatieve groei).

Gebaseerd op de fylogenetische instandhouding van het niches idee, was Darwin’snaturalisatie hypothese beoordeeld door vergelijking van de relatie tussen samen voorkomen,fylogenetische verwantschap en gelijkenis in eigenschappen van uitheemse en inheemseplanten (hoofdstuk 6). Daarnaast is het het niveau van de ruimtelijke variabiliteit opdeze betrekkingen ((hoofdstuk 4) beoordeeld. Resultaten vormen deze twee evaluatiesaangegeven dat uitheemse soorten fylogenetische clustering (kenmerken van co-show.voorkomende soorten zijn meer vergelijkbare dan verwacht door toeval) in vergelijkingmet gelijktijdig optredende inheemse soorten. Deze trends zijn consistent voor individu-ele groei vormen en verschillende vergelijking criteria (dat wil zeggen alle gelijktijdigoptredende inheemse soorten, die fylogenetisch dichtst inheemse en de gemiddelde na-tive, hoofdstuk 6); en wanneer vergelijkingen gecontroleerd voor ruimtelijke schaal(hoofdstuk 4). Dit zorgt voor sterke steun voor de belang van de integratie evolutionairepatronen en de noodzaak om rekening te houden fylogenetische relaties bij het onder-zoek van buitenaardse invasies, vooral wanneer het doel van de studie is te voorspellenwelke uitheemse soorten kunnen succesvol zijn.

Dit proefschrift richt zich op drie verschillende lijnen van bewijs (soorten invasiviteit,

142 Samenvatting

gemeenschap invasibiliteit en evolutionaire patronen) die elke onafhankelijk van elkaarveel aandacht hebben ontavangen. Het is duidelijk dat als uiteindelijke doel om een in-vasie risico’s in de toekomst te voorspellen (door een soort of van een gebied) deze driedimensies gezamenlijk moeten worden bekeken. De hier gepresenteerde werk is een bi-jdrage aan de langdurige zoektocht naar het begrijpen van de oorzaken en mechanismenachter de soort invasiefplantgemeenschap invasibiliteit continum.

Tot slot stel ik voor dat de bepaling van succesvolle introducties zal de evaluatie vande drie communautaire attributen nodig: het niveau van de functionele overeenkomsttussen inheemse en uitheemse; de mate van fylogenetische verwantschap tussen dezegroepen, en de beschikbaarheid van hulpbronnen–verstoring regime van de doelgroep.an fylogenetische verwantschap tussen deze groepen, en de beschikbaarheid van hulpbronnen–verstoring regime van de doelgroep.

11 Acknowledgments

First I would like to thank to my supervisor, Prof. Han Olff, for his careful guidanceduring my study years and the freedom he gave to me during my MSc and PhD years.Also, I would like to thank him for the opportunity to enroll as a Ph.D. student in the”Ubbo Emmius” program at University of Groningen after my MSc.

I should thank many more people, a very long list i have to admit, but with out adoubt is clear that both my mother (Evlyn) and my father (Carlos) are right on the topof the list. They teachings, encouragement and unconditional support trough out my lifeare the main reason why this document came to be. Also, I have to thank my sister,Margarita, for being my family anchor and coming to understand my constant radiosilence.

To Suzanne, for being by my side, pointing out the importance of my achievements,being so cool with my constant coming and goings up and down between Amsterdamand Groningen, understanding of my obsession with order; my need to run 7km everyday, even when we are on holidays; my compulsive cleaning, cleaning and cleaning;being so cool about me being totally clueless about especial dates; understanding myfascination with electronic music; my obsession with Apple; my idea that cycling ev-erywhere, even when I had one drink to much, is better than taking the tram; my needfor having several credit cards; my compulsive folding behavior; that I brush my teethmore than 3 times a day; my love for Coca-Cola; the fact that wake up way to early onthe weekends and my idea that expiration dates ”are just a suggestion”.

To my Top–MSc friends, particularly to Marloes Poortvliet, Nina Bhola and IvanPuga, also to Ronald Schokker and Lucile Nouis (the honorary Top-MSc’s), thanksguys for making the last six years in Groningen not such a painful experience.

Also I have to give spatial thanks to all my childhood friends (Fabio, Mauricio, Omar,Javier, Nani and Claudia) for keeping me grounded and preventing me from becominga ”Science nerd”. Thanks you guys for your constant reminder that I will be a ”doctor”but not of the proper kind, that always kept things in perspective. Also, I have to saythanks to my Amsterdam crew (Jose, Catalina, Ana Maria, Eimar, Ellen, Jen, Rowan,Maria, Robert, Lex and Lucas) for all the great moments we shared together during mytime there, for keeping it real, not taking me to seriously, and especially for keep askingme, So, this thesis of yours, what it is going to be good for?.

I particularly thank the past and current members of the Community and Conser-vation Ecology Group at the University of Groningen. To all of you, thanks all thelunch discussions, our relaxed literature discussion group, all formal and informal cof-

144 Acknowledgments

fee brakes, our conversations on quantum computers, gigantic squids, food form all overthe world, conventional, unconventional and simply weird science, gender equality, theweirdness of the ”Dutch” and many otter R-rated topics. Especially, I have to acknowl-edge (again) Nina Bhola for surviving the task of sharing an office with me for the lastsix years; I will certainly miss our constant ”fighting”, teasing and you asking me to ”fixyou a cup of expresso”. Also, I have to give many thanks to Jasper Ruifrok for goingout of his way and properly translating my ”google translated” Samenvatting.

It is clear that this work could not have been done with out the collaboration of manypersons and groups that kindly decided to share their data. Particularly I would like tothank Ian J. Wright (Macquarie University – Sydney) for introducing me to the fieldof trait ecology and big databases. Thanks to him I managed to put together most ofthe data used in this dissertation. Also this work could not have been done with out thedata contributions of the LEDA project, the Millennium seed database (Kew Botanicalgarden), the NCEAS Neo–tropics working group and the Comparative Ecology Groupfrom Macquarie University.

As this dissertation came together, the discussions and comments form a number ofpeople have made this dissertation a better one. Particular I would like to acknowledgeIan J. Wright, Rampal Etienne, Prof. Jan Bakker, Ciska Veen, Verena Cordlandwehr,Grant Hopcraft, Ingolf Khn Marc Cadotte and Wim Van der Putten for comments andideas on one or several of the chapters in this dissertation.

Lastly, or perhaps above all, is clear that this dissertation is built on the legacy of someof the greatest ecologist (Darwin, Elton, Hutchinson and MacArthur among others); ifthis work has any impact is only thanks to them.

12 Curriculum vitae

12.1 Personal information

Name: Alejandro Ordoez GloriaAddress: Department of Geography and Center for Climatic Research. University ofWisconsin- Madison [Madison, WI 53706]Professional profile: Biologist with emphasis in modeling, macro ecology, communityecology and natural resource management, with experience in ecological modeling, ad-vanced statistics and database management and analysis.

12.2 Education and training

BSc form the Pontificia Universidad Javeriana (Bogota Colombia)Specialization in Natural Resources Management, Universidad de los Andes (BogotaColombia)MSc (Cum laude) form the University of Groningen (Groningen Netherlands)PhD form the University of Groningen (Groningen Netherlands)PostSoc- Department of Geography and Center for Climatic ResearchUniversity of Wisconsin- Madison (Current)

12.3 Work experience

June of 2011 - current: Post Doctoral Fellow Center for climatic research. University ofWisconsin- MadisonSeptember of 2007 June of 2011: PhD student University of groningenSeptember of 2007 - October of 2008: Researcher ECOGRID projectNovember of 2006 May of 2007: Visiting exchange scholar ARC-NZ Research net-work for Variegation Function [Macquarie University Sydney Australia]January of 2003 June of 2005: Operations Manager Prodycon Laboratories S.A. [BogotColombia]January of 2002 March of 2002: Intern Universidad de Murcia [Universidad de Murcia

146 Curriculum vitae

Spain]January of 2002 March of 2002: Teacher assistant Universidad de Murcia [Universidadde Murcia Spain]June of 2000 July of 2001: Teacher Assistant Pontificia Universidad Javeriana [Pontif-icia Universidad Javeriana Colombia]January of 1999 December of 1999: Field Biologist Prodycon Laboratories S.A. [BogotColombia]

12.4 Publications

Ordonez, A., Wright, I.J. & Olff, H. (2010) Functional differences between native andalien species: a global-scale comparison. Functional Ecology, 24, 1353-1361.Ordez A, Garca MD, Fagua G. 2008 Evaluation of efficiency of Schoenly trap for col-lecting adult sarcosaprophagous dipterans. J Med Entomol. 45(3):522-32.

12.5 Conferences, congress and presentations

2011 Netherlands Annual Ecology Meeting (NERN) [Within-species changes in traitsbetween the native and introduced range of alien plants: a global scale comparison]2011 International Biogeography society 5th Biennial Conference [Spatial and habitatcomponents of native-alien functional differentiation]2010 Ecological Society of America (ESA) [Niches Vs. Phylogenies: dissecting simi-larity patterns of species invasions]2010 9th international Meeting on Vegetation Databases [Trait similarity between alienplants and the native vegetation: Darwin’s naturalization conundrum revisited.]2009 Ecological Society of America (ESA) [Contrasting exotics native and introducedrange trait combination: a test to the trait preservation hypothesis]2009 International Biogeography society 4rd Biennial Conference [Comparison of traitstrategies of co-occurring native and exotic plants: implications for predicting success-ful introductions]2008 Society for Conservation GIS 11Th Annual Conference [Effects of populationvariability on the accuracy of detection probability estimates]2007 International Biogeography society 3rd Biennial Conference [Exploring Patternsof Functional Diversity In African Termites]2007 International Biogeography society 3rd Biennial Conference [Exploring Patternsof Functional Diversity In African Termites]2006 Macroecological Tools for Global Change Research [Effect of climate change onSouthern Africa termites]2006 GRC 2006: Metabolic Basis of Ecology [Savanna Termites In A Changing Cli-mate]

12.5 Conferences, congress and presentations 147

2004 XXII International Congress Of Entomology [Sarcosaprophagous Fauna Associ-ated with Decay Rabbit Colleted with the Modified Schoenly Trap]2004 XXXI Colombian National Congress Of Entomology. [Comparison of the adultsarcosaprphagous diptera collected with the modified Schoenly trap Vs. the TraditionalMethodology. (Awarded the Francisco Galician Luis Prize , 2005 Version Best under-graduate thesis project)]2004 XXXI Colombian National Congress Of Entomology. Bogot Colombia [Evalu-ation of the succession the sarcosaprophagopus fauna associated to rabbit carcasses inTenjo (Cundinamarca Colombia) using Baited Schoenly traps]2004 XXXI Colombian National Congress Of Entomology. Bogot Colombia [Deter-mination of the effectiveness of the modified Schoenly trap to collect adult sarcos-aprophagous insects]2004 Second Meeting of the European Association for Forensic Entomology [Effective-ness of the Modified Schoenly Trap For Collecting Sarcosaprophagous fauna]2003 XXXVIII Colombian National Congress of Biological Sciences [Structure andComposition of the Vegetation of the Natural Reserve Lagoon of the Tabacal (La VegaCundinamarca Colombia)]

Appendix A Description of the protocolused to build the trait database

A.1 Data set compilation.

A.1.1 Information gathering

Data were compiled from both published and unpublished sources. Papers and databaseswere located through electronic searches using keywords (e.g. plant traits’, SLA’, LMA’,leaf size’, leaf nutrients’, plant height’, seed size’, seed weight’, seed production’, planttraits’, LHS’, plant physiology’), examination of the references in the selected works,and direct communication with researchers.

A data set was considered suitable when it contained data for at least one of the traitsof interest (i.e. Specific leaf area – SLA, maximum possible canopy height – Hmaxand individual seed weight – SWT) for at least four species co–occurring in the field(these species could be either native, aliens or a combination of both). We aimed to in-clude information from native and alien species growing just in natural or semi–naturalenvironments, for which we could reasonably attach information on location (latitude,longitude), biome, eco–region, habitat and environmental conditions. Highly artificialvegetation types such as forestry plantations and crop fields were not included. Studieswhere plant attributes were measured from manipulated sites (e.g. watering, fertiliza-tion, density manipulation or application of insecticides/herbicides) glasshouses, exper-imental fields or plots, agricultural environments and gardens, were also excluded.

An additional literature–search was performed to identify additional data for plantspecies in their introduced range. This search, added to the used keywords terms such asweed(s)’, naturalized’, invasive’, exotic’, noxious’, introduced’, alien’, foreign’,’ non–native’. The search targeted species that had been transported by humans from theirnatural range to a new area (specifically a between continents transport).

Species names were checked and standardized based on the International Plant NamesIndex (http://www.ipni.org/), Taxon Scrubber (Boyle 2004), and the Angiosperm Phy-logeny Website (Stevens 2009). Growth form data for each species (e.g. tree, shrub,herb/forbs, graminoids, vine, fern or fern ally) was obtained from a wide range ofsources, including floras and Internet databases.

A.1.2 Trait measurements

For measurements of SLA, leaf nitrogen and photosynthetic capacity, mean values werecalculated for each species at a site if several measurements were reported. Data for

A.2 Community assignment and data summary. 149

leaves closer to their ’peak” physiological stage were used where there was a choice (i.e.prior to significant age– or light–related decline in nutrient contents and photosyntheticcapacity; sun–leaf data used in preference to shade–leaf data).

Seed weight data were assumed to describe seed dry mass, unless otherwise stated.Where data for fresh mass were reported only, dry mass was estimated following Moleset al. (2006): [dry mass = (0.92 × fresh mass) 0.94; R2 = 0.97, n = 418 species]. Noattempt was made to convert diaspora mass into seed mass, given that there is no cleardistinction on what different authors call a ’seed”. Nonetheless, seed mass was usedrather than diaspora mass wherever there was a possibility to do so. Additionally, fora number of native or alien species, seed mass values were obtained from either theseed mass data set of Kew Gardens Seed Information database (Liu, Eastwood, Flynn,Turner & Stuppy 2008), the LEDA trait database (Knevel, Bekker, Kunzmann, Stadler,Thomson, Knevel, Bekker, Kunzmann, Stadler & Thomson 2005), Moles & Westoby(2006) or Mason et al. (2008).

Height data were summarized by site, so that an estimate of the maximum potentialheight could be determined. Here, only fully–grown and reproductively–active specieswere used. In the case of vines and lianas, Hmax data referred to the maximum stemlength. If the study reported several heights for a site, values were summarized using themean height of a species on a site. For a number of native species, Hmax values wereobtained from local and regional floras or the LEDA trait database.

A.2 Community assignment and data summary.

Each dataset was assigned to a particular plant community by placing a 25 × 25km(Chapter 3) or a 5 × 5 km (Chapter 4, 6 and 5) mesh over a distribution map of allsampled locations, and grouping together all the locations within the same grid. Speciestraits were summarized within each community by calculating the geometric mean ofall measurements of a particular attribute across all studies within the same grid. Weused this approach as it allowed us to compile a global data set based on pools of nativeand aliens known to co–occur in given areas. Additionally, the use of a these communityaggregations provided an area large enough to compile studies in a similar region, butsmall enough to ensure a sufficient level of habitat and environmental homogeneity.For each of these plant communities we followed the Richardson, Pysek, Rejmanek,Barbour, Panetta & West (2000) definition of naturalized and invasive alien species.That is, alien plants were defined as those whose presence at a site is due to intentionalor accidental introduction as a result of human activity.

The effect of grouping scale on the native–alien trait similarity was evaluated usinga regression framework describing the association between differences in trait values ofco–occurring native–alien species and the size of the grouping grid (Fig. A.1). Signifi-cance of this association was evaluated based on the regression coefficients significance(slopes, elevations and Pearson correlation coefficient rho).

A consistent tendency of aliens to show higher SLA, lower Hmax and smaller SWT,when compared to co–occurring natives, was recorded across all the evaluated grid sizes

150 Description of the protocol used to build the trait database

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0 km x0 km

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100 km x100 km

Figure A.1 Relationships between the mean difference in traits of co–occurring alien and nativespecies (y–axis) and size of the grouping scale (x–axis). Calculated regressions are, from top tobottom, differences in A) log10 specific leaf area (log10 SLA), B) log10 maximum canopy height(log10 Hmax) and C) log10 individual seed size (log10 SWT). Horizontal dashed lines indicate nodifferences between groups (y=0), and solid lines represent the relation of traits and groupingscale. 95% confidence intervals for slopes, and Pearson correlation coefficients (rho), are shownfor each regression. P values (* p < 0.05, ** p < 0.01, *** p < 0.001, and N.S. Non–significant)refer to the null hypothesis that the traits would have a correlation of zero. Points are thesummary, for all grids at a particular spatial aggregation, of the differences betweenco–occurring native and alien species log10 transformed in traits.

(Fig. A.1), differences in log–transformed trait values (95% CIs) ranging, for SLAbetween 0.052 and 0.058, for Hmax between –0.059 and –0.041, for SWT between –0.13 and –0.099. The association between grouping grid size and trait differences wassignificant for SLA and SWT (Fig. A.1). For these traits, regression slopes were one(1) fold smaller than regression intercepts. This very small effect of grouping grid sizeallowed us to disregard its influence on the observed patterns.

A.3 Mixed effect models specification 151

log10( SLA ) ~ Native.Exotic

Den

sity

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model residuals

Histogram of model residuals

Figure A.2 Model residualshistograms from lineal mixedeffect models using log10

transformed traits.

A.3 Mixed effect models specification

Each of the three focal traits (SLA, SWT, Hmax) showed a strongly right–skewed distri-bution (ca. log–normal), making assumptions of linearity and additivity not reasonablefor raw data (Shapiro–Wilk test SLA: W = 0.757, p ≤ 0.001; Hmax: W = 0.835, p ≤0.001; SWT: W = 0.46, p ≤ 0.001). All traits were log10–transformed for all analy-ses so trait distributions approximated normality (Shapiro–Wilk test log10(S LA) : W =

0.985, p = 0.108; log10(Hmax) : W = 0.963, p ≤ 0.001; log10(S WT ) : W = 0.978, p =

0.003); this was confirmed by plotting the residuals from log10 transformed models(Fig. A.2).

Additionally, to avoid problems with differences in measurement scales between dif-ferent variables, multi–trait tests were done using traits standardized (mean = 0, and SD= 1) log10–transformed trait values. Standardization was done using a global weightingprocedure in which each trait is scaled relative to the global mean and variance for thattrait derived from recently compiled global data sets for plant traits (Brown 1997, Leish-man et al. 1995, Leishman et al. 2000, Liu et al. 2008, Mason et al. 2008, Moles


et al. 2006, Moles & Westoby 2006, Moles et al. 2009, Ordonez et al. 2010, Wrightet al. 2004). The advantage to this approach is that a range of one standard deviation ofa particular trait would then be the same whether measured in the Tropics, Europe orAustralia. All traits were analyzed using a linear mixed model, implemented in R 2.10(R Development Core Team 2009) using the nlme package (Pinheiro et al. 2009). Wespecified the model in a hierarchical form where the evaluated trait (i.e. SLA, Hmax orSWT) was specified as the response variable, plant type (native or alien) was treated asa fixed factor. Community identity (25 × 25 km2 or 5 × 5 km2 geographical grid thespecies were sampled) and species identity (taxonomic identity of the specified species)nested within community were treated as random factors. Both community and speciesidentity were treated as random factors since they are a random selection of all the pos-sible grids (25 × 25 km2 or 5 × 5 km2) in the world, and the sampled species are justa random selection of all the possible species within each community. The specifiedfunctional form of the model was:

Trait ˜ Native/Alien + (1 + Native/Alien | Community/Species)

Analysis of the regression coefficients showed significant differences between nativeand alien species for all the evaluated traits. Given that growth forms were sampled ap-proximately randomly in each grid, the effect of its inclusion in the analysis as a randomeffect was evaluated (nested within community above the level of species), showing sig-nificant differences between native and alien species (SLA: t = −4.6, p ≤ 0.001; Hmax:t = −0.85, p = 0.422; SWT: t = 2.34, p = 0.019) and no significant gain in the powerof the model (Log–likelihood test p < 0.005).

Since the sets of native and alien species compared were chosen via a random se-lection of locations having both native and alien species with trait information, it is ofinterest to quantify how much of the trait variance in the dataset can be attributed tocommunity identity, to species identity (within community), and to random error. De-composition of the variance components (Fig. A.1) showed that 44 to 67 % of traitvariation was between native and alien species within a community, 28 to 48 % be-tween species within a community, and 4 to 8 % of the variation was between specieswithin native and alien status, within communities Additionally, the role of taxonomicaffiliation (e.g. genus and family) was evaluated by including them as random factors(nested within community, a level above species identity). The significance of includingthis taxonomic affiliation on the evaluation of trait differences between native and alienspecies was quantified using likelihood–ratio tests. The functional form of these modelswere:

Full Model: Trait ˜ Native/Alien + (1 + Native/Alien | Community/Native–Alien/Family/Genus/Species)

Reduced Model: Trait ˜ Native/Alien + (1 + Native/Alien |Community/Native–Alien/Species)

Analysis of variance components (Fig. A.2) indicated that the major component oftrait variance was variance between–sites (30 to 50% of native vs. alien variation). Each

A.4 Phylogeny assembly 153

Table A.1 Variance components from a linear mixed model comparing the differences inSLA Hmax and SWT between native and alien species

SLA Hmax SWTVar % Var % Var %

Sampled Community 0.060 49.9 % 0.462 67.3 % 0.703 43.9 %Species status (Native/Alien) 0.055 45.6 % 0.191 27.8 % 0.769 48.1 %Residual 0.005 4.5 % 0.034 4.9 % 0.128 8.0 %

Table A.2 Variance components from a linear mixed model evaluating the differences inSLA, Hmax and SWT between native and alien species. The model included the fulltaxonomic identity structure (i.e. family/genus/species).

SLA Hmax SWTVar % Var % Var %

Sampled Community 0.040 41.71 % 0.350 51.84 % 0.514 30.29 %Family 0.013 14.05 % 0.181 26.87 % 0.529 31.14 %Genus 0.014 15.22 % 0.072 10.67 % 0.448 26.38 %Species 0.024 25.13 % 0.056 8.26 % 0.153 9.02 %Residual 0.004 3.89 % 0.016 2.36 % 0.054 3.17 %

of the taxonomic levels evaluated (family, genus, species) had a smaller, but approxi-mately similarly–sized influence on the between–groups differences. Likelihood–ratiotests showed that including other sources of taxonomic affiliation (Family or genus)as random effects, and the related influence on the model variance and the covariancewith the other random effect, does not increase the ability to determine the differencesbetween native and alien species.

A.4 Phylogeny assembly

A phylogeny for all the species in the database (referred to as the database mega–tree hereafter) was built using the stand–alone version of PHYLOMATIC (Webb &Donoghue 2005). The database mega–tree was constructed using the maximally re-solved seed plant phylogeny as a backbone (APG3 derived megatree), which is an onlinephylogenetic summary that is continually updated by the Angiosperm Phylogeny Group(Stevens 2009). Branch lengths of our database mega–tree were estimated using theBLADJ (Branch Length ADJustment) procedure in PHYLOCOM (Webb et al. 2008)where node ages were established using the divergence times estimated by Wikstromet al. (Wikstrom et al. 2001); therefore our estimates of phylogenetic distance are inmillions of years.

The phylogenetic trees build from comparisons to super–trees are not fully resolvedbecause using molecular data to determine both phylogenetic topology and branch


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Figure A.3 Spatial location of locations with data for either or the analyzed traits.

lengths is not available for all the species included in our study, there is a lack of re-solved phylogenies for many seed plant families and genera, and the use of sister speciesas a solution for this cold potentially bias the results. As a result of this, in our PHY-LOMATIC trees proportion of the generic and species relationships within clades wereuncertain. Large unresolved clades by PHYLOMATIC (i.e., Poales, Malpighales andPinaceae) were further resolved using recently published phylogenies (Davis, Webb,Wurdack, Jaramillo & Donoghue 2005, Gernandt, Lopez, Garcia & Liston 2005, Salamin,Hodkinson & Savolainen 2002, Wang, Tank & Sang 2000). The remaining unresolvedclades in the phylogeny were treated as soft” polytomies. This provides some limita-tions, but implementing this method is an improvement over using only a PHYLO-MATIC tree, a taxonomic or a phylogenetic topology alone.

A.5 Habitat and environmental coverage

In total, our database included 544 studies and databases, covering 1016 locations. Thedatabase covers 22 ecoregions, all continents and all major biomes of the world (Fig.A.3). In total, the complete database encompasses 10644 species (7520 with measures inthe native, 2613 in the introduced and 511 on both ranges) from 82 orders and 365 plantfamilies sampled over 1016 communities for which information for any of the traits ofinterest was available. The species included represent a wide range of growth forms andlineages: 8799 dicot species, 1454 monocots, 172 Gymnosperms, 182 Pteridophytes(ferns and fern allies), and 2 undetermined species.

The total number of species studies and locations might vary for each chapter, ac-cording to the used traits, the comparison criteria (alien–to–alien or alien–to–native)and the scale of the aggregation. For example, in Chapter 2 comparisons are madebetween aliens in both its native and alien range (129 Alien species were compared); inChapter 3 comparisons where made for alien and natives co-occurring at 25 × 25km2

A.5 Habitat and environmental coverage 155

grids (a total of 4473 species were evaluated), and in Chapter 5 comparisons wheremade for leaf traits only of alien and natives co-occurring at 5 × 5km2 grids (a total of2248 species were evaluated).

Appendix B Summary of studiesdetermining the conservation oftraits between the native and alienrange

Class

TraitA>N

A=N

A<N

Sppand

Study

Defence

Defence

chemicals

(Tannin)X

Sapiumsebiferum

(Siemann

&R

ogers2001)

Defence

Fruitcapsule(protection)

XSilene

latifolia(B

lair&W

olfe2004)

Defence

Herbivory

toleranceX

SolidagoC

anadensis(van

Kleunen

&Schm

id2003)

Defence

Hypericin

concentrationX

Hypericum

perforatum(M

aron,Vila

&A

rnason2004)

Defence

nerolidol:viridifloralchemotypes

XM

elaleucaquinquenervia

(Franks,Pratt,Dray

&Sim

ms

2008)D

efencePseudohypericin

concentrationX

Hypericum

perforatum(M

aron,Vila

&A

rnason2004)

Defence

Trichomes

XSilene

latifolia(B

lair&W

olfe2004)

Genetic

Genetic

variabilityX

Hypericum

perforatum(M

aron,V

ila,B

omm

arco,E

lmendorf

&B

eardsley2004)

Grow

thB

asalArea

(size)X

Sapiumsebiferum

(Siemann

&R

ogers2001)

Grow

thB

iomas

XL

epidiumdraba

(Cripps,

Hinz,

McK

enney,Price

&Schw

arzlander2009)

Grow

thB

iomass

XA

lliariapetiolata

(Bossdorf,Prati,A

uge&

Schmid

2004)G

rowth

Biom

assX

Carduus

nutans,D

igitalispurpurea,

Echium

vulgareand

Senecioja-

cobaea(W

illis,Mem

mott&

Forrester2000)G

rowth

Biom

assX

Lythrumsalicaria

(Willis

&B

lossey1999)

Grow

thB

iomass

XM


(Franksetal.2008)

Grow

thB

iomass

XPhalaris

arundinacea(L

avergne&

Molofsky

2007)G

rowth

Grow

thrate

XM


(Franksetal.2008)

Grow

thG

rowth

rateX

SolidagoC

anadensis(van

Kleunen

&Schm

id2003)

Grow

thG

rowth

ratesX

Lythrumsalicaria

(Willis

&B

lossey1999)

Grow

thG

rowth

ratesX

Rhododendron

ponticum(E

rfmeier&

Bruelheide

2005)G

rowth

Grow

thrates

XSilene

latifolia(B

lair&W

olfe2004)

Grow

thL

eaf:stemratio

XM


(Franksetal.2008)

Grow

thPlantheight

X(Pritchard

1960,Craw

ley1987,Fow

leret

al.1996,Rees

andPaynter

1997,Buckley

etal.2003,Grosholtz

andR

uiz2003)

Grow

thPlantheight

XA

lliariapetiolata

(Bossdorfetal.2004)

Grow

thPlantheight

XE

schscholziacalifornica

(Leger&

Rice

2007)G

rowth

PlantheightX

Hypericum

perforatum(M

aron,V

ila,B

omm

arco,E

lmendorf

&B

eardsley2004)

Grow

thPlantheight

XLythrum

salicaria(W

illis&

Blossey

1999)G

rowth

PlantheightX

Multiple

speciesin

California

(Thebaud

&Sim

berloff

2001)G

rowth

PlantheightX

SolidagoC

anadensis(van

Kleunen

&Schm

id2003)

Grow

thPlantheight

XSolidago

gigantea(M

eyer,Clare

&W

eber2005)

Cla

ssTr

ait

A>

NA

=N

A<

NSp

pan

dSt

udy

Gro

wth

Roo

tmas

sX

Lyth

rum

salic

aria

(Will

is&

Blo

ssey

1999

)G

row

thR

ootw

eigh

tX

Esc

hsch

olzi

aca

lifor

nica

(Leg

er&

Ric

e20

07)

Gro

wth

Roo

t:Sho

trat

ioX

Car

duus

nuta

ns,

Dig

italis

purp

urea

,E

chiu

mvu

lgar

ean

dSe

neci

oja

-co

baea

(Will

iset

al.2

000)

Gro

wth

Roo

t:Sho

trat

ioX

Lep

idiu

mdr

aba

(Cri

pps

etal

.200

9)G

row

thR

oot:S

hotr

atio

XLy

thru

msa

licar

ia(W

illis

&B

loss

ey19

99)

Gro

wth

Roo

t/sho

otra

tioX

Hyp

eric

umpe

rfor

atum

(Mar

on,E

lmen

dorf

&V

ila20

07)

Gro

wth

Shoo

tmas

sX

Car

duus

nuta

ns,

Dig

italis

purp

urea

,E

chiu

mvu

lgar

ean

dSe

neci

oja

-co

baea

(Will

iset

al.2

000)

Gro

wth

Shoo

twei

ght

XE

schs

chol

zia

calif

orni

ca(L

eger

&R

ice

2007

)G

row

thSi

zeX

Car

duus

nuta

ns,

Dig

italis

purp

urea

,E

chiu

mvu

lgar

ean

dSe

neci

oja

-co

baea

(Will

iset

al.2

000)

Gro

wth

Stam

ennu

mbe

rX

Esc

hsch

olzi

aca

lifor

nica

(Leg

er&

Ric

e20

07)

Gro

wth

Stem

heig

htX

Phal

aris

arun

dina

cea

(Lav

ergn

e&

Mol

ofsk

y20

07)

Gro

wth

Tille

ring

rate

(Gro

wth

)X

Phal

aris

arun

dina

cea

(Lav

ergn

e&

Mol

ofsk

y20

07)

Gro

wth

Vig

orX

Acr

optil

onre

pens

(Hin

z&

Schw

arzl

aend

er20

04)

Gro

wth

Vig

orX

Cyt

isus

scop

ariu

s(P

aynt

er,D

owne

y&

Shep

pard

2003

)G

row

thV

igor

XH

elio

trop

ium

euro

paeu

m(S

hepp

ard,

Bru

n&

Lew

is19

96)

Gro

wth

Vig

orX

Hel

iotr

opiu

meu

ropa

eum

(She

ppar

det

al.1

996)

Gro

wth

Vig

orX

Lyth

rum

salic

aria

(Bas

tlova

-Han

zely

ova

2001

)G

row

thV

igor

XLy

thru

msa

licar

ia(E

cker

t,M

anic

acci

&B

arre

tt19

96)

Gro

wth

Vig

orX

Mel

aleu

caqu

inqu

ener

via

(Van

,Ray

amaj

hi&

Cen

ter2

001)

Gro

wth

Vig

orX

Mim

osa

pigr

a(L

onsd

ale

&Se

gura

1987

)G

row

thV

igor

XR

hodo

dend

ron

pont

icum

(Erf

mei

er&

Bru

elhe

ide

2004

)G

row

thV

igor

XSe

neci

oin

aequ

iden

s(P

rati

&B

ossd

orf2

002)

Gro

wth

Vig

orX

Solid

ago

giga

ntea

n(J

akob

s,W

eber

&E

dwar

ds20

04)

Popu

latio

nA

vera

geag

eX

Rho

dode

ndro

npo

ntic

um(E

rfm

eier

&B

ruel

heid

e20

04)

Popu

latio

nD

ensi

tyX

Acr

optil

onre

pens

(Hin

z&

Schw

arzl

aend

er20

04)

Popu

latio

nD

ensi

tyX

Car

duus

nuta

ns(W

oodb

urn

&Sh

eppa

rd19

96)

Popu

latio

nD

ensi

tyX

Cyt

isus

scop

ariu

s(P

aynt

eret

al.2

003)

Popu

latio

nD

ensi

tyX

Gen

ista

mon

spes

sula

na(H

inz

&Sc

hwar

zlae

nder

2004

)Po

pula

tion

Den

sity

XH

elio

trop

ium

euro

paeu

m(S

hepp

ard

etal

.199

6)Po

pula

tion

Den

sity

XL

epid

ium

drab

a(H

inz

&Sc

hwar

zlae

nder

2004

)

Class

TraitA>N

A=N

A<N

Sppand

Study

PopulationD

ensityX

Lythrumsalicaria1,(B

astlova-Hanzelyova

2001)Population

Density

XM


(Van

etal.2001)Population

Density

XM

imosa

pigra(L

onsdale&

Segura1987)

PopulationD

ensityX

Rhododendron

ponticum(E

rfmeier&

Bruelheide

2004)Population

Density

XSolidago

gigantean(Jakobs


Maxim

umage

XC

ytisusscoparius

(Paynteretal.2003)Population

Maxim

umage

XG

enistam

onspessulana(H

inz&

Schwarzlaender2004)

PopulationPopulation

sizeX

Lythrumsalicaria

(Eckertetal.1996)

PopulationPopulation

sizeX

Senecioinaequidens

(Prati&B

ossdorf2002)Population

Populationsize

XSolidago

gigantean(Jakobs


Proportionofyoung

stagesX

Cytisus

scoparius(Paynteretal.2003)

PopulationProportion

ofyoungstages

XG

enistam

onspessulana(H

inz&

Schwarzlaender2004)

PopulationProportion

ofyoungstages

XM


(Van


Seedlingestablishm

entratesX

Echium

plantagineum(G

rigulis,Sheppard,Ash

&G

roves2001)

PopulationSeedling

establishmentrates

XR

hododendronponticum

(Erfm

eier&B

ruelheide2004)

PopulationSeedling

survivalX

Cytisus

scoparius(Sheppard,H

odge,Paynter&R

ees2002)

PopulationSeedling

survivalX

Echium

plantagineum(G

rigulisetal.2001)

Reproduction

Flowersize

XSilene

latifolia(B

lair&W

olfe2004)

Reproduction

Flowering

speedX

Eschscholzia

californica(L

eger&R

ice2007)

Reproduction

FruitMass

XLythrum

salicaria(W

illis&

Blossey

1999)R

eproductionG

ermination

orreproductiveperiod

XA

cacialongifolia

(Weiss

&M

ilton1984)

Reproduction

Germ

inationorreproductive

periodX

Acroptilon

repens(H

inz&

Schwarzlaender2004)

Reproduction

Germ


periodX

Carduus

nutans(W

oodburn&

Sheppard1996)

Reproduction

Germ


periodX

Chrysanthem

oidesm

onilifera(W

eiss&

Milton

1984)R

eproductionG

ermination

rateX

Centaurea

solstitialis(H

ierroetal.2009)

Reproduction

Germ

inationrate

XPhalaris

arundinacea(L

avergne&

Molofsky

2007)R

eproductionG

ermination

rateX

Rhododendron

ponticum(E

rfmeier&

Bruelheide

2005)R

eproductionG

ermination

speedX

Eschscholzia

californica(L

eger&R

ice2007)

Reproduction

Germ

inationspeed

XPhalaris

arundinacea(L

avergne&

Molofsky

2007)R

eproductionG

ermination

velocityX

Rhododendron

ponticum(E

rfmeier&

Bruelheide

2005)

Cla

ssTr

ait

A>

NA

=N

A<

NSp

pan

dSt

udy

Rep

rodu

ctio

nG

erm

inat

ion

Vel

ocity

XSi

lene

latif

olia

(Bla

ir&

Wol

fe20

04)

Rep

rodu

ctio

nIn

flore

scen

cebi

omas

sX

Solid

ago

Can

aden

sis

(van

Kle

unen

&Sc

hmid

2003

)R

epro

duct

ion

Inflo

resc

ence

mas

sX

Car

duus

nuta

ns,

Dig

italis

purp

urea

,E

chiu

mvu

lgar

ean

dSe

neci

oja

-co

baea

(Will

iset

al.2

000)

Rep

rodu

ctio

nN

umbe

roffl

ower

sX

Esc

hsch

olzi

aca

lifor

nica

(Leg

er&

Ric

e20

07)

Rep

rodu

ctio

nN

umbe

roffl

ower

sX

Sile

nela

tifol

ia(B

lair

&W

olfe

2004

)R

epro

duct

ion

Num

bero

flea

fsX

Sile

nela

tifol

ia(B

lair

&W

olfe

2004

)R

epro

duct

ion

Num

bero

fsho

ots

XL

epid

ium

drab

a(C

ripp

set

al.2

009)

Rep

rodu

ctio

nN

umbe

rofv

eget

ativ

eoff

spri

ngX

Solid

ago

Can

aden

sis

(van

Kle

unen

&Sc

hmid

2003

)R

epro

duct

ion

Opt

imum

germ

inat

ion

tem

pera

ture

XR

hodo

dend

ron

pont

icum

(Erf

mei

er&

Bru

elhe

ide

2005

)R

epro

duct

ion

Peta

lwid

thX

Esc

hsch

olzi

aca

lifor

nica

(Leg

er&

Ric

e20

07)

Rep

rodu

ctio

nR

epro

duct

ive

outp

utX

Aca

cia

long

ifol

ia(W

eiss

&M

ilton

1984

)R

epro

duct

ion

Rep

rodu

ctiv

eou

tput

XC

ardu

usnu

tans

(Woo

dbur

n&

Shep

pard

1996

)R

epro

duct

ion

Rep

rodu

ctiv

eou

tput

XC

hrys

anth

emoi

des

mon

ilife

ra(W

eiss

&M

ilton

1984

)R

epro

duct

ion

Rep

rodu

ctiv

eou

tput

XE

chiu

mpl

anta

gine

um(G

rigu

liset

al.2

001)

Rep

rodu

ctio

nR

epro

duct

ive

outp

utX

Gen

ista

mon

spes

sula

na(H

inz

&Sc

hwar

zlae

nder

2004

)R

epro

duct

ion

Rep

rodu

ctiv

eou

tput

XH

elio

trop

ium

euro

paeu

m(S

hepp

ard

etal

.199

6)R

epro

duct

ion

Rep

rodu

ctiv

eou

tput

XLy

thru

msa

licar

ia(E

cker

teta

l.19

96)

Rep

rodu

ctio

nR

epro

duct

ive

outp

utX

Mel

aleu

caqu

inqu

ener

via

(Van

etal

.200

1)R

epro

duct

ion

Rep

rodu

ctiv

eou

tput

XM

imos

api

gra

(Lon

sdal

e&

Segu

ra19

87)

Rep

rodu

ctio

nR

epro

duct

ive

outp

utX

Rho

dode

ndro

npo

ntic

um(E

rfm

eier

&B

ruel

heid

e20

04)

Rep

rodu

ctio

nR

epro

duct

ive

outp

utX

Sene

cio

inae

quid

ens

(Pra

ti&

Bos

sdor

f200

2)R

epro

duct

ion

Rep

rodu

ctiv

eou

tput

XSo

lidag

ogi

gant

ean

(Jak

obs

etal

.200

4)R

epro

duct

ion

Seed

bank

XA

caci

alo

ngif

olia

(Wei

ss&

Milt

on19

84)

Rep

rodu

ctio

nSe

edba

nkX

Car

duus

nuta

ns(W

oodb

urn

&Sh

eppa

rd19

96)

Rep

rodu

ctio

nSe

edba

nkX

Chr

ysan

them

oide

sm

onili

fera

(Wei

ss&

Milt

on19

84)

Rep

rodu

ctio

nSe

edba

nkX

Gen

ista

mon

spes

sula

na(H

inz

&Sc

hwar

zlae

nder

2004

)R

epro

duct

ion

Seed

bank

XH

elio

trop

ium

euro

paeu

m(S

hepp

ard

etal

.199

6)R

epro

duct

ion

Seed

bank

XM

imos

api

gra

(Lon

sdal

e&

Segu

ra19

87)

Rep

rodu

ctio

nSe

edbi

omas

s(S

iliqu

e)X

Alli

aria

petio

lata

(Bos

sdor

feta

l.20

04)

Rep

rodu

ctio

nSe

edca

psul

epr

oduc

tion

(pro

tect

ion)

XH

yper

icum

perf

orat

um(M

aron

,Vila

&A

rnas

on20

04)

Class

TraitA>N

A=N

A<N

Sppand

Study

Reproduction

Seedm

assX

Multiple

speciesw

orldw

ide(D

aws,H

all,Flynn&

Pritchard2007)

Reproduction

Seedm

assX

Multiple

speciesw

orldw

ide(M

asonetal.2008)

Reproduction

Seednum

berX

Hypericum

perforatum(M

aron,V

ila,B

omm

arco,E

lmendorf

&B

eardsley2004)

Reproduction

Seednum

ber(Silique)X

Alliaria

petiolata(B

ossdorfetal.2004)R

eproductionSeed

productionX

Multiple

speciesw

orldw

ide(M

asonetal.2008)

Reproduction

Seedproduction

XSapium

sebiferum(Siem

ann&

Rogers

2001)R

eproductionSeed

sizeX

Cytisus

scoparius(B

uckley,D

owney,

Fowler,H

ill,M

emm

ot,N

oram-

buena,Pitcairn,Shaw,Sheppard,W

inks,Wittenberg

&R

ees2003)

Reproduction

Seedsize

XE

schscholziacalifornica

(Leger&

Rice

2007)R

eproductionSeed

sizeX

Silenelatifolia

(Blair&

Wolfe

2004)R

eproductionSeed

sizeX

Ulex

europaeus(B

uckleyetal.2003)

Reproduction

Seedsperflow

erX

Eschscholzia

californica(L

eger&R

ice2007)

Resource

Leafarea

XH

ypericumperforatum

(Maron,

Vila,

Bom

marco,

Elm

endorf&

Beardsley

2004)R

esourceL

eafArea

XSolidago

Canadensis

(vanK

leunen&

Schmid

2003)R

esourceL

eafarearatio

(LA

R).

XH

ypericumperforatum

(Maron

etal.2007)R

esourceL

eafC13

XH

ypericumperforatum

(Maron

etal.2007)R

esourceL

eafcarbonX

Hypericum

perforatum(M

aronetal.2007)

Resource

Leafchem

istry(C

:N)

XSapium

sebiferum(Siem

ann&

Rogers

2001)R

esourceL

eafhairdensityX

Melaleuca

quinquenervia(Franks

etal.2008)R

esourceL

eafNitogen

XH

ypericumperforatum

(Maron

etal.2007)R

esourceL

eafnumber

XR

esourceL

eafsizeX

Lepidium

draba(C

rippsetal.2009)

Resource

Leafsize

XSilene

latifolia(B

lair&W

olfe2004)

Resource

Leaftoughness

XM


(Franksetal.2008)

Resource

SLA

XH

ypericumperforatum

(Maron

etal.2007)R

esourceSL

AX

Melaleuca

quinquenervia(Franks

etal.2008)R

esourceSL

AX

SolidagoC

anadensis(van

Kleunen

&Schm

id2003)

Resource

Stomata

conductanceX

SolidagoC

anadensis(van

Kleunen

&Schm

id2003)

Resource

Totalleafarea,X

Hypericum

perforatum(M

aronetal.2007)

Appendix C Summary studies showingdirect or indirect support for oragainst the idea of (bioclimatic orphylogenetic) niche conservatism(NC) or lability (NL) in natural andinvaded communities

SppN

CN

LSum

mary

Com

parisontype

Reff

12chaparral

shrubsform

theC

aliforniafloristic

regionX

Absence

ofchange

incurrentC

aliforniachaparralplants

speciessuggests

thatancestors

ofchaparral

taxahad

alreadyacquired

appropriatetraits

thatcon-

tributedto

theirsuccessunderM

editerranean-typeclim

ates.

PhylogeneticC

ompari-

son(A

ckerly2004)

Californian

Ceanothus

speciesX

Within-com

munity

niche(a

niche)difference

evolvedearly

inthe

divergenceoftw

om

ajorsubcladesw

ithinC

eanothus,whereas

macrohabitataffi

nityorcli-

matic

tolerances(b

niche)diversifiedlaterw

ithineach

ofthesubclades.

PhylogeneticC

ompari-

son(A

ckerly,Schw

ilk&

Webb

2006)

Hieracium

aurantiacum,

Hi-

eraciumm

urorum,

Hieracium

pilosella

XInvasive

populationsofH

ieraciumspecies

canoccurin

areasw

ithdifferentcli-

matic

conditionsthan

experiencedin

theirnativeranges.

Native-A

lienrange

(SDM

S)(B

eaumontetal.2009)

142land

birdsoccurring

inE

asternG

ermany

XD

ietaryniche

breadthacross

landbirds

occurringin

Eastern

Germ

anyshow

edphylogenetic

conservatism:abouthalf

ofthe

variationin

dietaryniche

breadthacross

speciesw

asdue

tovariation

between

families

andgenera.

PhylogeneticC

ompari-

son(B

ohning-Gaese

&O

berrath1999)

Centaurea

maculosa

XT

hereis

astrong

andsignificant

shiftof

theobserved

climatic

nichebetw

eennative

(Europe)

andnon-native

(North-A

merica)

rangesof

theSpotted

Knap-

weed

(Centaurea

maculosa).R

esultsindicate

thatinvasivespecies

canoccupy

climatically

distinctnichespaces

following

itsintroduction

intoa

newarea.

Native-A

lienrange

(SDM

S)(B

roennimann

etal.2007)

World

mam

mals

XV

ariabilityin

climate

richnessrelationship

between

clades,regionsand

time

periodsis

expectedunder

ascenario

inw

hichenvironm

entalnichesare

evolu-tionarily

conservedand

cladesdifferin

theirgeographicalandclim

aticorigins.

PhylogeneticC

ompari-

son(B

uckleyetal.2010)

17Floridian

oakspecies

XL

ackofa

relationship,ornegativerelationship,betw

eenphylogenetic

andeco-

logicalsimilarity

nicheoverlap

andhabitatuse

inFlorida

oaksSistertaxon

(Cavender-B

ares,K

ita-jim

a&

Bazzaz

2004)17

Floridianoak

speciesX

Lack

ofarelationship,ornegative

relationship,between

phylogeneticand

eco-logicalsim

ilarityniche

overlapand

habitatusein

Floridaoaks

PhylogeneticC

ompari-

son(C

avender-Bares,

Kita-

jima

&B

azzaz2004)

Three

lineagesof

floridaO

uer-cus,Pinus,orIlex,

XSpecies

interactionsam

ongclose

relativesinfluence

comm

unitystructure

andshow

thatnicheconservatism

isincreasinglyevidentascom

munitiesare

definedto

includegreater

phylogeneticdiversity.

As

thespatial

scaleis

increasedto

encompass

greaterenvironm

entalheterogeneity;

nicheconservatism

emerges

asthe

dominantpattern

PhylogeneticC

ompari-

son(C

avender-Bares

etal.

2006)

Woody

vegetationof

10w

ettropical

forestsin

northeasternC

ostaR

ica.

XL

egaciesofbothphylogenetic

historyand

forestdisturbancestructure

thedistri-

butionofreproductive

traitsw

ithinand

among

tropicalwetforestcom

munities.

PhylogeneticC

ompari-

son(C

hazdon,C

areaga,W

ebb&

Vargas

2003)

Spp

NC

NL

Sum

mar

yC

ompa

riso

nty

peR

eff

Nor

thA

mer

ican

rept

iles

and

amph

ibia

nsX

Neo

trop

ical

rept

iles

and

amph

ibia

nsin

trod

uced

inSo

uthe

rnFl

orid

ado

notc

ol-

oniz

ete

mpe

rate

regi

ons

due

toco

nser

vatio

nof

thei

rFun

dam

enta

lnic

heN

ativ

e-A

lien

rang

e(C

onan

t197

5,St

ebbi

ns20

03)

Zap

rion

usin

dian

usX

Com

pari

ngm

odel

sbu

ildfo

rth

ena

tive

rang

es(A

fric

a)of

show

eda

quic

kex

-pa

nsio

nin

todi

ffer

ente

nvir

onm

ents

inth

ein

vade

dar

eas

(Am

eric

aan

dIn

dia)

,su

gges

ting

clim

atic

nich

esh

ifts

,pri

mar

ilyin

Indi

a.

Nat

ive-

Alie

nra

nge

(SD

MS)

(da

Mat

a,Ti

don,

Cor

tes,

De

Mar

co&

Din

iz-F

ilho

2010

)M

arm

ota

(Mam

mal

ia:

Rod

en-

tia)

XSi

gnifi

cant

corr

elat

ion

betw

een

clim

ate

and

phyl

ogen

etic

dist

ance

indi

catin

gth

atcl

osel

yre

late

dsp

ecie

sof

mar

mot

ste

ndto

stay

insi

mila

renv

iron

men

ts.

Sist

erta

xon

(Dav

is20

05)

79sp

ecie

sof

mam

mal

sX

Impo

rtan

tpar

toft

heva

riat

ion

ofm

amm

albo

dym

ass

isre

late

dto

the

com

mon

influ

ence

ofph

ylog

eny

and

popu

latio

nde

nsity

.The

port

ion

ofth

eph

ylog

enet

icva

riat

ion

ofa

trai

ttha

tmay

bere

late

dto

ecol

ogy

isca

lled

phyl

ogen

etic

nich

eco

nser

vatis

m.

Phyl

ogen

etic

Com

pari

-so

n(D

esde

vise

s,L

eg-

endr

e,A

zouz

i&

Mor

and

2003

)

Rev

iew

XIn

vasi

vepl

ants

have

evol

ved

new

ecol

ogic

alst

rate

gies

(e.g

.rep

rodu

ctio

nan

ddi

sper

sal)

inth

eiri

ntro

duce

dra

nge,

poss

ibly

asa

resu

ltof

adap

tive

evol

utio

nN

ativ

e-A

lien

rang

e(D

ietz

&E

dwar

ds20

06)

140

mam

mal

spec

ies

inE

urop

eX

Rel

ated

spec

ies

wer

eno

tsim

ilar

inth

eir

clim

ate

nich

e,pe

rhap

sdu

eto

stro

ngin

ters

peci

ficco

mpe

titiv

eco

nstr

aint

onth

ere

aliz

edni

che,

rath

erth

ana

rapi

dev

olut

ion

ofth

efu

ndam

enta

lnic

he.

Sist

erta

xon

(Dor

man

n,G

ru-

ber,

Win

ter

&H

errm

ann

2010

)So

leno

psis

invi

cta

XN

ativ

era

nge

occu

rren

ces

unde

r-pr

edic

ted

the

inva

sive

pote

ntia

lof

fire

ants

,w

here

asoc

curr

ence

data

from

the

US

over

-pre

dict

edth

eso

uthe

rnbo

unda

ryof

the

nativ

era

nge.

Seco

ndly

,int

rodu

ced

fire

ants

initi

ally

esta

blis

hed

inen

viro

n-m

ents

sim

ilar

toth

ose

inth

eir

nativ

era

nge,

buts

ubse

quen

tlyin

vade

dha

rshe

ren

viro

nmen

ts.

Nat

ive-

Alie

nra

nge

(SD

MS)

(Fitz

patr

ick,

Wel

tzin

,Sa

nder

s&

Dun

n20

07)

Rev

iew

XO

ver

26st

udie

s,no

tal

lch

arac

ters

that

are

pote

ntia

lsu

rrog

ates

for

ecol

ogic

alva

riat

ion

(e.g

.mor

phol

ogic

alan

dph

ysio

logi

calc

hara

cter

s,la

titud

e);e

xhib

ited

are

latio

nshi

pbe

twee

nec

olog

ical

sim

ilari

tyan

dph

ylog

enet

icre

late

dnes

s.

Phyl

ogen

etic

Com

pari

-so

n(F

reck

leto

n,H

arve

y&

Page

l200

2)

fung

alpa

thog

ens

ofpl

ant

leav

esin

atr

opic

alra

info

rest

XT

helik

elih

ood

that

apa

thog

enca

nin

fect

two

plan

tspe

cies

decr

ease

sco

ntin

u-ou

sly

with

phyl

ogen

etic

dist

ance

betw

een

the

plan

ts,e

ven

toan

cien

tevo

lutio

n-ar

ydi

stan

ces.

Phyl

ogen

etic

Com

pari

-so

n(G

ilber

t&W

ebb

2007

)

Ecu

ador

ian

frog

sfo

rmth

eD

en-

drob

atid

aefa

mily

XC

onsi

sten

tpat

tern

that

man

yre

late

dta

xaor

node

sex

isti

ndi

stin

cten

viro

nmen

-ta

lspa

cesu

ppor

ting

the

idea

that

diff

eren

tials

elec

tion

likel

ypl

ayed

anim

por-

tant

role

insp

ecie

sdi

ffer

entia

tion

offr

ogs

inth

eA

ndes

Sist

erta

xon

(SD

MS)

(Gra

ham

,R

on,

San-

tos,

Schn

eide

r&

Mor

itz20

04)

SppN

CN

LSum

mary

Com

parisontype

Reff

63N

orthA

merican

mam

malian

generaX

Realized

niche(m

easuredas

rangesize)ofm

amm

aliangenera

andfam

iliesw

asconstantoverthe

lastglacialinterglacialtransition.Paleo-R

ecostruction(H

adlyetal.2009)

11sunfishes

(Centrarchidae)

from890

lakesX

After

statisticallyrem

ovingthe

environmental

effects,phylogeneticrepulsion

was

apparent,with

closelyrelated

sunfishesless

likelyto

co-occur.Phylogenetic

Com

pari-son

(Helm

us,Savage,

Diebel,

Maxted

&Ives

2007)Fagus

speciesin

Europe

andnorth

Am

ericaX

The

physiologicalcharacteristics

determining

thespecies’

distributionsare

presumably

evolutionarilyconservative,

havingpersisted

throughrepeated

orbitally-forcedcycles

ofmigration

sincethe

original(mid-Tertiary)separation

ofEuropean

andN

orthA

merican

temperate

forests

Paleo-Recostruction

(Huntley,

Bartlein

&Prentice

1989)

Allliving

FelidsX

Based

onphylogeny,

closerelatives

infelids,

oftendiffer

greatlyin

climatic

requirements

PhylogeneticC

ompari-

son(Johnson,

Eizirik,

Pecon-Slattery,M

ur-phy,

Antunes,

Teeling&

O’B

rien2006)

Review

XE

videncesupporting

thehypothesis

thatthereis

adynam

icinterplay

between

ecologyand

evolutionw

ithincom

munities

(Johnson&

Stinchcombe

2007)43

Malagasy

Primates

XL

ittlerelationship

between

thephylogenetic

distanceofM

alagasyprim

atesand

theirrainfall

andtem

peratureniche

space,i.e.,closelyrelated

speciestend

tooccupy

differentclimatic

niches.

PhylogeneticC

ompari-

son(K

amilar

&M

uldoon2010)

World

wide

comparison

of1287

speciesX

Asignificant

phylogeneticsignals

implies

thatboth

thecontingencies

ofevo-

lutionaryhistory

andsom

edegree

ofenvironm

entalconvergence

haveled

toa

comm

onsetof

rulesthatconstrain

thepartitioning

ofnutrients

among

plantorgans.

PhylogeneticC

ompari-

son(K

erkhoff,Fagan,E

lser&

Enquist2006)

15species

ofC

ubanlizards

ofthe

Anolis

sagreigroupX

Com

parisonofsisterspeciesofthe

genusAnolis(based

onenvironm

entalnichem

odelling)foundno

generalrelationshipbetw

eenphylogenetic

andniche

sim-

ilarity.

PhylogeneticC

ompari-

son(K

nouft,Losos,G

lor&

Kolbe

2006)

15species

ofC

ubanlizards

ofthe

Anolis

sagreigroupX

Com

parisonofsisterspeciesofthe

genusAnolis(based

onenvironm

entalnichem

odelling)foundno

generalrelationshipbetw

eenphylogenetic

andniche

sim-

ilarity.

Sistertaxon(K

nouftetal.2006)

18Salam

anderspecies

thegenus

Desm

ognathusX

Strongcorrelation

between

morphology

andm

icrohabitatecologyindependent

ofphylogeneticeffects

andsuggestthatecom

orphologicalchangesare

concen-trated

earlyin

theradiation

ofDesm

ognathus.

Sistertaxon(K

ozak,Larson,B

onett&

Harm

on2005)

Spp

NC

NL

Sum

mar

yC

ompa

riso

nty

peR

eff

18Sa

lam

ande

rsp

ecie

sth

ege

nus

Des

mog

nath

usX

Stro

ngco

rrel

atio

nbe

twee

nm

orph

olog

yan

dm

icro

habi

tate

colo

gyin

depe

nden

tof

phyl

ogen

etic

effec

tsan

dsu

gges

ttha

teco

mor

phol

ogic

alch

ange

sar

eco

ncen

-tr

ated

earl

yin

the

radi

atio

nof

Des

mog

nath

us.

Phyl

ogen

etic

Com

pari

-so

n(K

ozak

etal

.200

5)

Sim

ulat

ion

XC

lose

lyre

late

dsp

ecie

sar

eec

olog

ical

lydi

verg

ent,

and

that

envi

ronm

enta

lfilte

r-in

gis

resp

onsi

ble

fort

hepr

esen

ceof

dist

antly

rela

ted,

bute

colo

gica

llysi

mila

r,sp

ecie

sw

ithin

aco

mm

unity

Phyl

ogen

etic

Com

pari

-so

n(K

raft

etal

.200

7)

Five

sym

patr

ictu

rtle

spec

ies

(Gra

ptem

ysps

eudo

geog

raph

-ic

a,G

rapt

emys

ouac

hite

nsis

,A

palo

nem

utic

a,Tr

ache

-m

yssc

ript

aan

dPs

eude

mys

conc

inna

)

XPh

ylog

eny

isof

grea

teri

mpo

rtan

cein

stru

ctur

ing

reso

urce

use

inK

entu

cky

Lak

etu

rtle

than

inte

rspe

cific

com

petit

ion

Phyl

ogen

etic

Com

pari

-so

n(L

inde

man

2000

)

55of

58sp

ecie

sof

Cub

anA

no-

lisliz

ards

XIn

trop

ical

lizar

dco

mm

uniti

esw

here

spec

iesh

ave

alo

ngev

olut

iona

ryhi

stor

yof

ecol

ogic

alin

tera

ctio

n,ev

olut

iona

rydi

verg

ence

over

com

esni

che

cons

erva

tism

.Si

ster

taxo

n(L

osos

etal

.200

3)

55of

58sp

ecie

sof

Cub

anA

no-

lisliz

ards

XIn

trop

ical

lizar

dco

mm

uniti

esw

here

spec

iesh

ave

alo

ngev

olut

iona

ryhi

stor

yof

ecol

ogic

alin

tera

ctio

n,ev

olut

iona

rydi

verg

ence

over

com

esni

che

cons

erva

tism

.Ph

ylog

enet

icC

ompa

ri-

son

(Los

oset

al.2

003)

Mam

mal

spec

ies

acro

ssth

elo

wer

48st

ates

ofth

eU

nite

dSt

ates

.

XE

colo

gica

lni

ches

repr

esen

tlo

ng-t

erm

stab

leco

nstr

aint

son

the

dist

ribu

tiona

lpo

tent

ialo

fspe

cies

assu

gges

ted

byth

eco

nsis

tent

trac

kof

suita

ble

clim

ate

pro-

files

thro

ugho

utth

edr

astic

clim

ate

chan

geev

ents

that

mar

ked

the

end

ofth

ePl

eist

ocen

egl

acia

tions

.

Nat

ive-

Alie

nra

nge

(SD

MS)

(Mar

tınez

-Mey

er,

Tow

nsen

dPe

ters

on&

Har

grov

e20

04)

Mam

mal

spec

ies

acro

ssth

elo

wer

48st

ates

ofth

eU

nite

dSt

ates

.

XE

colo

gica

lni

ches

repr

esen

tlo

ng-t

erm

stab

leco

nstr

aint

son

the

dist

ribu

tiona

lpo

tent

ialo

fspe

cies

assu

gges

ted

byth

eco

nsis

tent

trac

kof

suita

ble

clim

ate

pro-

files

thro

ugho

utth

edr

astic

clim

ate

chan

geev

ents

that

mar

ked

the

end

ofth

ePl

eist

ocen

egl

acia

tions

.

Pale

o-R

ecos

truc

tion

(Mar

tınez

-Mey

eret

al.

2004

)

Nor

thA

mer

ican

angi

ospe

rms

XA

llsp

ecie

ste

sted

show

edge

nera

lco

nser

vatis

min

ecol

ogic

alch

arac

teri

stic

sov

erth

ecl

imat

ech

ange

sas

soci

ated

with

the

Plei

stoc

ene-

to-R

ecen

ttra

nsiti

on.

Sist

erta

xon

(SD

MS)

(Mar

tınez

-Mey

er&

Pete

rson

2006

)N

orth

Am

eric

anan

gios

perm

sX

All

spec

ies

test

edsh

owed

gene

ral

cons

erva

tism

inec

olog

ical

char

acte

rist

ics

over

the

clim

ate

chan

ges

asso

ciat

edw

ithth

ePl

eist

ocen

e-to

-Rec

entt

rans

ition

.Pa

leo-

Rec

ostr

uctio

n(M

artın

ez-M

eyer

&Pe

ters

on20

06)

Era

gros

tisle

hman

nian

aX

Nat

ive

and

alie

nra

nge

base

dm

odel

ssh

owed

stro

ngag

reem

entf

orth

ear

eaen

-co

mpa

ssed

byth

epr

esen

cepo

ints

inth

ein

vade

dra

nge,

and

offer

edin

sigh

tint

oth

eov

erla

ppin

gbu

tsl

ight

lydi

ffer

ent

ecol

ogic

alni

che

occu

pied

byth

ein

tro-

duce

dgr

ass

inth

ein

vade

dra

nge.

Nat

ive-

Alie

nra

nge

(SD

MS)

(Mau

-Cri

mm

ins,

Schu

ssm

an&

Gei

ger2

006)

SppN

CN

LSum

mary

Com

parisontype

Reff

Aphelocom

aultram

arinaX

There

islittle

evidencefor

nichedivergence

among

Mexican

Jay(A

.ultrama-

rina)lineagesin

theprocess

ofspeciation.Incontrast,A

phelocoma

speciesthat

existinpartialsym

patryin

some

regionsshow

evidenceforniche

divergence.

Sistertaxon(M

ccormack,

Zellm

er&

Know

les2010)

FleasX

Num

berofhosts,butnottheirtaxonomic

identity,isconserved

infleas

Sistertaxon(M

ouillot,R

.K

rasnov,I.Shenbrot,J.G

aston&

Poulin2006)

Helm

inthparasites

XTaxonom

icidentity

andnotthe

numberofhosts,is

conservedin

helminth

para-sites

Sistertaxon(M

ouillotetal.2006)

Review

XC

ompilation

ofrecent

applicationof

speciesdistribution

models

(SDM

s)and

phylogeneticm

ethodsto

analysisof

nichecharacteristics

hasprovided

insightto

nichedynam

ics.These

showsupportforN

icheconservatism

PhylogeneticC

ompari-

son(Pearm

anetal.2008)

Review

XC

ompilation

ofrecent

applicationof

speciesdistribution

models

(SDM

s)and

phylogeneticm

ethodsto

analysisof

nichecharacteristics

hasprovided

insightto

nichedynam

ics.These

showsupportforN

icheconservatism

Sistertaxon(SD

MS)

(Pearman

etal.2008)

21sistertaxon

pairsofbirds,11

sistertaxon

pairsof

mam

mals,

and5

sistertaxon

pairsof

but-terflies

XSister

taxonpairs

showniche

conservatismover

severalmillion

yearsof

inde-pendentevolution

butlittleconservatism

attheleveloffam

ilies.Sistertaxon

(Petersonetal.1999)

Bubulcus

ibis,C

arpodacusm

exicanus,A

noplophoraglabripennis

andA

noplophoram

alasiaca

XU

singspecies

distributionm

odelingthe

useof

nativerange

buildm

odelaccu-rately

predictedthe

invasionrange

ofevaluatedspecies

Native-A

lienrange

(SDM

S)(Peterson

&V

ieglais2001)

Hydrilla

verticillataX

Waterthym

e(H

ydrillaverticillata)

environmentalrequirem

entsshow

eda

closem

atchbetw

eenits

native(SoutheastA

siaand

theA

ustralo-Pacific)and

itsin-

vadeddistributionalarea

inN

orthA

merica

Native-A

lienrange

(SDM

S)(Peterson

2003)

Solenopsisinvicta

XT

hedifference

inpredictive

abilitiesappears

tocentre

onthe

complexity

oftheenvironm

entalvariablesinvolved.These

resultsemphasize

importantinfluences

ofenvironmentaldata

setsonthe

generalityand

abilityofecologicalniche

mod-

elsto

anticipatenovelphenom

ena,andoffer

asim

plerexplanation

forthe

lackof

predictiveability

among

nativeand

invadeddistributionalareas

thanthatof

nicheshifts.

Native-A

lienrange

(SDM

S)(Peterson

&N

akazawa

2008)

Schiffornisturdina

XR

econstructionsofneotropicsPleistoceneL

astGlacialM

aximum

reconstructedusing

nichem

odelssignificantlyrelate

topreviousidentified

phylogroupspoint-ing

tothe

conservationofthe

speciesniche

Paleo-Recostruction

(Peterson&

Nyari2008)

Spp

NC

NL

Sum

mar

yC

ompa

riso

nty

peR

eff

Schi

ffor

nis

turd

ina

XR

econ

stru

ctio

nsof

neot

ropi

csPl

eist

ocen

eL

astG

laci

alM

axim

umre

cons

truc

ted

usin

gni

che

mod

elss

igni

fican

tlyre

late

topr

evio

usid

entifi

edph

ylog

roup

spoi

nt-

ing

toth

eco

nser

vatio

nof

the

spec

ies

nich

e

Sist

erta

xon

(SD

MS)

(Pet

erso

n&

Nya

ri20

08)

Hig

her

plan

tsfr

omce

ntra

lE

u-ro

peX

Usi

ngbo

tha

phyl

ogen

etic

(deg

ree

ofre

tent

ion

ofni

ches

acro

ssth

eph

ylog

eny)

and

taxo

nom

ic(v

aria

nce

amon

gsp

ecie

sex

plai

ned

athi

gher

taxo

nom

icle

vels

)sh

owed

ate

nden

cyof

clea

rnic

heco

nser

vatis

m

Phyl

ogen

etic

Com

pari

-so

n(P

rinz

ing,

Dur

ka,K

lotz

&B

rand

l200

1)

Aph

eloc

oma

jays

XL

ack

ofa

rela

tions

hip,

orne

gativ

ere

latio

nshi

p,be

twee

nph

ylog

enet

ican

dec

o-lo

gica

lsi

mila

rity

base

don

pred

ictio

nsba

sed

onen

viro

nmen

tal

nich

ede

ter-

min

edus

ing

Geo

grap

hic

Info

rmat

ion

Syst

em(G

IS)o

fAph

eloc

oma

jays

Phyl

ogen

etic

Com

pari

-so

n(R

ice,

Mar

tinez

-Mey

er&

Pete

rson

2003

)

Aph

eloc

oma

jays

XL

ack

ofa

rela

tions

hip,

orne

gativ

ere

latio

nshi

p,be

twee

nph

ylog

enet

ican

dec

o-lo

gica

lsi

mila

rity

base

don

pred

ictio

nsba

sed

onen

viro

nmen

tal

nich

ede

ter-

min

edus

ing

Geo

grap

hic

Info

rmat

ion

Syst

em(G

IS)o

fAph

eloc

oma

jays

Sist

erta

xon

(SD

MS)

(Ric

eet

al.2

003)

Her

bace

ous

pere

nnia

lin

Asi

aan

dea

ster

nN

orth

Am

eric

aX

Sign

ifica

ntco

rrel

atio

nin

area

ofge

ogra

phic

alra

nge

ofdi

sjun

ctta

xasu

gges

tsev

olut

iona

ryst

asis

oftr

aits

rela

ted

toec

olog

ical

dist

ribu

tion

over

peri

ods

ofat

leas

t10

mill

ion

and

poss

ibly

mor

eth

an30

mill

ion

yr.

Pale

o-R

ecos

truc

tion

(Ric

klef

s&

Lat

ham

1992

)

Wor

ldan

gios

perm

sX

Man

yfa

mili

esof

flow

erin

gpl

ants

are

limite

dto

the

trop

ics,

with

out

asi

ngle

mem

bert

hath

asbe

enab

leto

cros

sin

tote

mpe

rate

area

sSi

ster

taxo

n(R

ickl

efs

&R

enne

r199

4)W

orld

angi

ospe

rms

XM

any

fam

ilies

offlo

wer

ing

plan

tsar

elim

ited

toth

etr

opic

s,w

ithou

ta

sing

lem

embe

rtha

thas

been

able

tocr

oss

into

tem

pera

tear

eas

Phyl

ogen

etic

Com

pari

-so

n(R

ickl

efs

&R

enne

r199

4)R

evie

wX

The

corr

elat

ion

betw

een

dive

rsity

and

envi

ronm

ent

may

refle

ct,

perh

aps

toa

larg

eex

tent

,the

hist

ory

ofra

pid

ecol

ogic

aldi

vers

ifica

tion

ofpl

ants

from

pri-

mar

ilyw

ettr

opic

alor

igin

s.

Sist

erta

xon

(Ric

klef

s20

05)

Rev

iew

XT

heco

rrel

atio

nbe

twee

ndi

vers

ityan

den

viro

nmen

tm

ayre

flect

,pe

rhap

sto

ala

rge

exte

nt,t

hehi

stor

yof

rapi

dec

olog

ical

dive

rsifi

catio

nof

plan

tsfr

ompr

i-m

arily

wet

trop

ical

orig

ins.

Phyl

ogen

etic

Com

pari

-so

n(R

ickl

efs

2005

)

SppN

CN

LSum

mary

Com

parisontype

Reff

Hem

idactylusturcicus

XC

omparison

ofthe

nativeand

invasiverange

distributionm

odelsindicate

thatthe

degreeofconservatism

ofnichesin

H.turcicus

largelyvaries

among

predic-tors

andvariable

setsapplied.

Native-A

lienrange

(SDM

S)(R

odder&

Lotters

2009)

Linepithem

ahum

ileX

Behaviouraland

ecologicalcharacteristics(derived

fromecologicalniche

mod-

els)oftheargentine

ant(Linepithem

ahum

ile)areconserved

between

theintro-

ducedand

nativeranges.

Native-A

lienrange

(SDM

S)(R

oura-Pascualet

al.2006)

fossilGinkgo

XE

xamination

offossil

Ginkgo,

forexam

ple,indicates

thattrees

inthis

genushave

utilizeddisturbed

streamside

andlevee

environments,w

hereit

occurredw

itha

consistentsetofotherplants,sincethe

lateC

retaceous

PhylogeneticC

ompari-

son(R

oyer,Hickey

&W

ing2003)

Catharus

ustulatusX

Bioclim

aticanalyses

stronglysupportthe

hypothesisthatpopulations

expand-ing

outoftheeastinto

previouslyglaciated

areasin

thew

estwere

undergoinga

naturalextensionoftheirrange

bytracking

thechanges

inclim

aticconditions.

Paleo-Recostruction

(Ruegg,

Hijm

ans&

Moritz

2006)

Globaldatasetofexotic

speciesof

birds,m

amm

als,fishes

andplants

XSignificant(butw

eak)correlationbetw

eennative

andintroduced

latitudinalex-tents.

Native-A

lienrange

(SDM

S)(Sax

2001)

English

meadow

plantspeciesX

Coexisting

[plant]congenersare

oftenas

ecologicallydifferentfrom

eachother

asthey

arefrom

unrelatedm

embers

ofthesam

ecom

munities).M

olecularphy-logenetic

analysisshowsno

correlationbetw

eenthe

ecologicalandevolutionary

distancesinα

niches.At

localor

regionalscales

certainshow

edevolutionary

conservatism.

Sistertaxon(Silvertow

netal.2006,

Silvertown

etal.2006)

Cape

floristicregion

Tetrariaclade

XE

valuationof11

existingvegetation

surveysshow

edevidence

forphylogeneticoverdispersion

andtraitconservatism

fortheevaluated

cladein

theC

apeFloris-

ticR

egion

PhylogeneticC

ompari-

son(Slingsby

&V

erboom2006)

9N

ewW

orldbatfam

ilies.X

Ecologicaland

evolutionarydifferences

among

highertaxonom

icunits,partic-

ularlythose

differencesinvolving

life-historytraits,predispose

taxato

exhibitdifferentpatterns

ofdiversityalong

environmentalgradients

Native-A

lienrange

(Stevens2004)

tropicalforestsX

Com

paringthe

phylogeneticstructure

ofa

localassemblage

toa

speciespool

drawn

fromincreasingly

largergeographicscales

resultsin

anincreased

signalofphylogenetic

clustering.

PhylogeneticC

ompari-

son(Sw

enson,E

nquist,Pither,

Thom

pson&

Zim

merm

an2006)

tropicalforestcomm

unitiesX

The

degreeofphylogenetic

relatednessacross

two

fundamentalscaling

dimen-

sions(plant

sizeand

neighborhoodsize)

shows

thatphylogenetic

nichecon-

servatismis

likelyw

idespread;indicatingthatclosely

relatedspecies

arem

orefunctionally

similarthan

distantlyrelated

species.

PhylogeneticC

ompari-

son(Sw

ensonetal.2007)

Spp

NC

NL

Sum

mar

yC

ompa

riso

nty

peR

eff

96pl

ants

ende

mic

toSo

uth

Afr

ica

and

inva

sive

else

whe

reX

Inva

sive

Sout

hA

fric

ansp

ecie

scl

imat

ic,e

colo

gica

l,an

dha

bita

tpre

fere

nces

are

sim

ilar

betw

een

thei

rna

tive

(Sou

thA

fric

an)

and

intr

oduc

edra

nges

(sev

eral

Med

iterr

anea

nre

gion

sw

orld

wid

e).

Nat

ive-

Alie

nra

nge

(SD

MS)

(Thu

iller

etal

.200

5)

19A

maz

onia

nliz

ards

XC

ompa

riso

nof

diet

ary

over

laps

with

phyl

ogen

etic

sim

ilari

ties

indi

cate

sth

atm

uch

ofth

eva

riat

ion

indi

etar

ysi

mila

rity

inth

isas

sem

blag

eis

asso

ciat

edw

ithph

ylog

enet

icsi

mila

rity

Phyl

ogen

etic

Com

pari

-so

n(V

itt,

Zan

i&

Esp

osito

1999

)

15sp

ecie

sof

Cub

anliz

ards

ofth

eA

nolis

sagr

eigr

oup

XE

nvir

onm

enta

lni

che

over

lap

iscl

osel

ytie

dto

geog

raph

icov

erla

p,bu

tno

tto

phyl

ogen

etic

dist

ance

s,su

gges

ting

that

nich

eco

nser

vatis

mha

sno

tcon

stra

ined

loca

lcom

mun

ities

inth

isgr

oup

toco

nsis

tofc

lose

lyre

late

dsp

ecie

s.

Phyl

ogen

etic

Com

pari

-so

n(W

arre

net

al.2

008)

Rev

iew

XL

ack

ofph

ylog

enet

icsi

gnal

may

bepr

imar

ilyan

isla

ndph

enom

enon

beca

use

insu

lars

ettin

gsar

ere

now

ned

fort

heir

adap

tive

radi

atio

nsPh

ylog

enet

icC

ompa

ri-

son

(Web

bet

al.2

002)

Rev

iew

XE

vide

nce

form

vari

ous

stud

ies

show

ing

the

cons

erva

tion

ofni

ches

Phyl

ogen

etic

Com

pari

-so

n(W

ebb,

Los

os&

Agr

awal

2006

)Tr

eesp

ecie

sof

Bor

nean

rain

fore

sts

XSe

edlin

gsu

rviv

alw

asne

gativ

ely

rela

ted

toth

ede

gree

ofph

ylog

enet

icsi

mi-

lari

tyam

ong

near

byhe

tero

spec

icpl

ants

,pre

sum

ably

beca

use

ofa

rela

tions

hip

betw

een

phyl

ogen

etic

and

ecol

ogic

alsi

mila

rity

Phyl

ogen

etic

Com

pari

-so

n(W

ebb,

Gilb

ert

&D

onog

hue

2006

)

Her

bivo

reca

terp

illar

s(L

epi-

dopt

era)

,be

etle

s(C

oleo

pter

a),

and

gras

shop

pers

and

rela

-tiv

es(o

rtho

pter

oids

)in

aN

ewG

uine

ara

info

rest

XC

ater

pilla

rsp

ecie

ssh

owed

sign

ifica

ntph

ylog

enet

iccl

uste

ring

with

resp

ect

toho

stpl

anta

ssoc

iatio

ns,s

omew

hatm

ore

soth

anfo

rbee

tles

oror

thop

tero

ids.

Phyl

ogen

etic

Com

pari

-so

n(W

eibl

en,

Web

b,N

ovot

ny,

Bas

set

&M

iller

2006

)

Alli

aria

petio

lata

XT

heob

tain

edcl

imat

icm

odel

ofth

era

nge

ofA

.pet

iola

tash

ows

cons

ider

able

cong

ruen

cies

with

itsm

appe

d,na

tive

Eur

asia

nra

nge.

Nat

ive-

Alie

nra

nge

(SD

MS)

(Wel

k,Sc

hube

rt&

Hoff

man

n20

02)

Rev

iew

XA

bsen

ceof

mig

ratio

nfr

omtr

opic

into

tem

pera

tere

gion

sas

aco

nseq

uenc

eof

nich

ere

stri

ctio

ns,n

odu

eto

disp

ersa

llim

itatio

nsor

shor

tevo

lutio

nary

time.

Nat

ive-

Alie

nra

nge

(Wie

ns&

Don

oghu

e20

04)

124

hylid

spec

ies

XT

hest

udy

illus

trat

esho

wtw

oge

nera

lpr

inci

ples

(nic

heco

nser

vatis

man

dth

etim

e-fo

r-sp

ecia

tion

effec

t)m

ayhe

lpex

plai

nth

ela

titud

inal

dive

rsity

grad

ient

asw

ella

sm

any

othe

rdi-

vers

itypa

ttern

sac

ross

taxa

and

regi

ons.

Phyl

ogen

etic

Com

pari

-so

n(W

iens

,G

raha

m,

Moe

n,Sm

ith&

Ree

der2

006)

SppN

CN

LSum

mary

Com

parisontype

Reff

124hylid

speciesX

The

studyillustrates

howtw

ogeneral

principles(niche

conservatismand

thetim

e-for-speciationeffect)m

ayhelp

explainthe

latitudinaldiversitygradientas

wellas

many

otherdi-versitypatterns

acrosstaxa

andregions.

PhylogeneticC

ompari-

son(W

iensetal.2006)

Cyclam

enspecies

(Myrsi-

naceaefam

ily)X

Phylogeneticstructure

forsom

eclim

aticcharacteristics,

andshow

thatm

ostC

yclamen

havedistinct

climatic

niches,w

iththe

exceptionof

severalw

ide-ranging,geographically

expansive,species.

Sistertaxon(SD

MS)

(Yesson

&C

ulham2006)

Cyclam

enspecies

(Myrsi-

naceaefam

ily)X

Phylogeneticstructure

forsom

eclim

aticcharacteristics,

andshow

thatm

ostC

yclamen

havedistinct

climatic

niches,w

iththe

exceptionof

severalw

ide-ranging,geographically

expansive,species.

PhylogeneticC

ompari-

son(Y

esson&

Culham

2006)

184squam

atelizard

speciesin

12fam

iliesfrom

4continents

XA

ncienteventsin

squamate

cladogenesis,ratherthan

present-daycom

petition,caused

dietaryshifts

inm

ajorcladessuch

thatsome

lizardclades

gainedaccess

tonew

resources,which

inturn

ledto

much

ofthebiodiversity

observedtoday.

PhylogeneticC

ompari-

sonPhylogenetic

Com

pari-son

Appendix D Correlations between leaftraits (for native, alien anddifference between them) andclimatic, edaphic and humandisturbance parameters.

Correlations between leaf traits and climatic, edaphic and human disturbance 173

Figure D.1 Correlations between evaluated alien and native leaf traits and climatic (Total Annualprecipitation (mm × yr−1)– AnnPre, Mean annual temperature (C◦) – AnnTmp, Potential annualevapotranspiration (mm × yr−1)– EvptYr, Daily irradiance (WH × m−2) – DayIrr, TemperatureSeasonality (SD *100)– TmpSeas and Precipitation seasonality (CV) – PreSeas), edaphic(Available water capacity (cm × m−1) – TAWC, pH measured in water (pH units)– PHAQ, Totalnitrogen (g × kg−1) – TOTN, Carbon nitrogen ratio (C/N) – CNRT, Effective cation exchangecapacity (cmolc × kg−1) – ECEC, Bulk density (kg × dm−3) – BULK, Total organic carboncontent (g × kg−1) – TOTC and Cation exchange capacity (cmolc × kg−1) – CECS) and humanimpact (Human impact index (%) – HII) measurements for all sampled locations.

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Human impact (%)

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2.4

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AnnPre

Total Annual Precipitation (mm*yr−1)

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AnnTmp

Mean Annual temperature (oC)

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2.4

2.8

EvptYr

Potential Evapotraspiration (mm)

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Yearly Irradiance (J*m−2)

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DayIrr

Dayly Irradiance (J*m−2)

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Temperature seasonality (SD *100)

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Precipitation seasonality (CV)

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2.8

TAWC

Available water capacity (cm m−1)

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5.0 6.0 7.0 8.0

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2.0

2.4

2.8

PHAQ

pH measured in Water

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1.6

2.0

2.4

2.8

TOTN

Total Nitrogen (gN kg−1)

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2.0

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2.8

CNRT

C/N Ratio

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2.4

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ECEC

Effective cation exchange capacity (cmolc kg−1)

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1.6

2.0

2.4

2.8

BULK

Bulk density (kg dm−3)

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2.8

TOTC

Organic carbon content (gC kg−1)

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5 10 15 20 25 30

1.6

2.0

2.4

2.8

CECS

NA

log1

0(SL

A) [c

m2

x g−

1]

SLA

Covariate

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HII

Human impact (%)

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DayIrr


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PreSeas


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TAWC


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PHAQ


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TOTN


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1.4

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CNRT

C/N Ratio

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ECEC


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2.2

BULK


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TOTC


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1.4

1.8

2.2

CECS

NA

Log1

0(Am

ass)

[nm

ol x

g−1

x s−1

]

Amass

Covariate

174 Correlations between leaf traits and climatic, edaphic and human disturbance

Figure D.2 Continued...

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HII

Human impact (%)

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PHAQ


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C/N Ratio

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CECS

NA

Log1

0(Nm

ass)

(%)

Nmass

Covariate

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Human impact (%)

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AnnPre


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YrIrrd


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DayIrr


!

!

!

!

!

!

!! !

!

!

!

!

!

!

!!

!

!

!

0 4000 8000 12000

−20

1

TmpSeas


!

!

!

!

!

!

!! !

!

!

!

!

!

!

!!

!

!

!

20 40 60 80

−20

1

PreSeas


!

!

!

!

!

!

!! !

!

!

!

!

!

!

!!

!

!

!

5 10 15 20

−20

1

TAWC


!

!

!

!

!

!

! !!

!

!

!

!

!

!

!!

!

!

!

5.0 6.0 7.0 8.0

−20

1

PHAQ


!

!

!

!

!

!

! !!

!

!

!

!

!

!

!!

!

!

!

0.5 1.0 1.5 2.0 2.5

−20

1

TOTN


!

!

!

!

!

!

! !!

!

!

!

!

!

!

!!

!

!

!

9.5 10.5 11.5

−20

1

CNRT

C/N Ratio

!

!

!

!

!

!

!!!

!

!

!

!

!

!

!!

!

!

!

5 10 15 20 25 30

−20

1

ECEC


!

!

!

!

!

!

! !!

!

!

!

!

!

!

!!

!

!

!

0.8 1.0 1.2 1.4

−20

1

BULK


!

!

!

!

!

!

! !!

!

!

!

!

!

!

!!

!

!

!

10 20 30 40 50

−20

1

TOTC


!

!

!

!

!

!

! !!

!

!

!

!

!

!

!!

!

!

!

5 10 15 20 25 30−2

01

CECS

NA

PC−1

pos

Possition in the leaf economics spectrum

Covariate

Appendix E Correlations between leaftraits (for native, alien anddifference between them) andclimatic, edaphic and humandisturbance parameters.


Figure E.1 Correlations between alien and native leaf trait differences (absolute and relative) andclimatic (Total Annual precipitation (mm × yr−1)– AnnPre, Mean annual temperature (C◦) –AnnTmp, Potential annual evapotranspiration (mm × yr−1)– EvptYr, Daily irradiance(WH × m−2) – DayIrr, Temperature Seasonality (SD *100)– TmpSeas and Precipitationseasonality (CV) – PreSeas), edaphic (Available water capacity (cm × m−1) – TAWC, pHmeasured in water (pH units)– PHAQ, Total nitrogen (g × kg−1) – TOTN, Carbon nitrogen ratio(C/N) – CNRT, Effective cation exchange capacity (cmolc × kg−1) – ECEC, Bulk density(kg × dm−3) – BULK, Total organic carbon content (g × kg−1) – TOTC and Cation exchangecapacity (cmolc × kg−1) – CECS) and human impact (Human impact index (%) – HII)measurements for all sampled locations.

SLA

Covariates

log−

resp

onse

ratio

[ln(

A/N)

]

−0.4−0.2

0.00.20.40.6

−3 −2 −1 0 1 2

!

!

! !

!

!

!!

!!!

!

!

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!!!

!!

!!!

!

AnnPre

−3 −2 −1 0 1 2

!

!

!

!

!!!!

!

!

!

!

!

!!

!

!

!

!

!

!!

!

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!

!

!

!!

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!

!!

! !!

!

!

!

!

!!

!

!

!

!

!

!!

!

!

!

!

!

!

!

AnnTmp

−2 −1 0 1

!!!

!

!

!

!

!

!

!

!

!

!!!

!!

!!!

!

!

!

!!

!

!

!!

! !!

!

!

!

!

!

!

!

!

!

! !!

! !

!!!

!

!

!

!!

!

!

!!

BULK

−1 0 1 2 3

!

!!!

!!

! !!

!

!

!

!!

!

!

!!! ! !

!

!

!

!

!

!

!

!

!

! !!

! !

!!!

!

!

!

!!

!

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!!

!!!

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!

CECS−1 0 1 2 3 4

!!

!

!

!

!!

!

!

!!

!!!

!

!

!

!

!

!

!

!

!

!!!

!!

!!!

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! !

!

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!!

!!!

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! !

!

CNRT

−2 −1 0 1 2 3

!

!!

! !!

!

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!!

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!

!!! ! !

!

!

!

!

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!!!

!!

!!!

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!!

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!!

! !!

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! !

DayIrr

−1 0 1 2 3 4

!

!

!!

!

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!

!!

!!!

!

!

!

!

!!

!

!

!

!

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!!

!

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!!

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!

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!!

! !!

!

!

!

!

!!

!

!

!

!

!

!!

!

!

!

!

ECEC

−2 −1 0 1 2

−0.4−0.20.00.20.40.6!

!

!

!

!

!

!

!

!

!!!

!!

!!!

!

!

!

!!

!

!

!!

!!!

!

!

!

!

!

!

!

!

!

! !!

!!

!!!

!

!

!

! !

!

!

!!

! !!

EvptYr

−0.4−0.2

0.00.20.40.6

−2 −1 0 1 2 3

!

!

!!

!

!

!

!

!

!

!!

!

!

!

!!

!!!

!

!

!

!

!!

!

!

!

!

!

!!

!

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!

!

!

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!!

!

!

!

!!

! !!

!

!

!

!

!!

!

!

!

HII

−1 0 1 2

!

!

!

!

!

!!!

!!

! !!

!

!

!

!!

!

!

!!

! !!

!

!

!

!

!

!

!

!

!

!!!

! !

!!!

!

!

!

!!

!

!

!!

! !!

!

!

!

!

PHAQ

−2 −1 0 1 2

!

!

!!

!! !

!

!

!

!

!

!

!

!

!

!!!

!!

!!!

!

!

!

!!

!

!

!!

!! !

!

!

!

!

!

!

!

!

!

! !!

!!

!!!

!

!

!

!!

PreSeas

−2 −1 0 1 2 3

!!

!!!

!

!

!

!

!!

!

!

!

!

!

!!

!

!

!

!

!

!

!!

!

!

!

!!

! !!

!

!

!

!

!!

!

!

!

!

!

!!

!

!

!

!

!

!

!!

!

!

!

TAWC−2 −1 0 1 2 3

!

!

!

!

!

!

!!

!

!

!

!!

!!!

!

!

!

!

!!

!

!

!

!

!

!!

!

!

!

!

!

!

!!

!

!

!

!!!!

!

!

!

!

!

!!

!

!

!

!

!

!!

TmpSeas

−1 0 1 2 3

!

!

!

!

!

!!

!

!

!

!

!

!!

!

!

!

!

!

!

!!

!

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!

!!

!!!

!

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!

!

!!

!

!

!

!

!

!!

!

!

!

!

!

!

!!

!

!

!

!!

!!

TOTC

−1 0 1 2 3

!

!

!

!

!

!!

!

!

!

!

!

!

!!

!

!

!

!!

!!!

!

!

!

!

!!

!

!

!

!

!

!!

!

!

!

!

!

!

!!

!

!

!

!!!!

!

!

!

!

!

!!

TOTN

−2 −1 0 1 2

−0.4−0.20.00.20.40.6

!

!

!!

!

!

!

!

!

!!

!

!

!

!

!

!

!!

!

!

!

!!! !

!

!

!

!

!

!!

!

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!

!

!

!!

!

!

!

!

!

!

!!

!

!

!

!!

! !!

!

!

YrIrrd

SLA

Covariates

Abso

lute

diff

erec

nes

[A−N

]

−50

0

50

100

−3 −2 −1 0 1 2

!

!

!!

!

!

!!

!!

!

!

!

!

!

!

!

!

!

!

!!

!

!!

!!

!

!

!

!

!!!

!

!!

!!

!

!

!

!

!

!

!

!

!

!

!!

!

!!

!!

!

!

AnnPre

−3 −2 −1 0 1 2

!

!

!

!

!

!

!!!

!

!

!

!

!!!

!

!

!

!

!!

!

!!

!!

!

!!

!

!

!

!

!

! !!

!

!

!

!

!!

!

!

!

!

!

!!

!

!!

!!

!

!

AnnTmp

−2 −1 0 1

!!!

!

!

!

!

!

!

!

!

!

!!!

!!

!!!

!

!

!

!!

!

!

!!

!!

!

!

!

!

!

!

!

!

!

!

!!

!

!!

!!

!

!

!

!

!!!

!

!!

BULK

−1 0 1 2 3

!

!!

!

!!

!!

!

!

!

!

!!!

!

!!!

!!

!

!

!

!

!

!

!

!

!

!!

!

!!

!!

!

!

!

!

!!

!

!

!!

!!!

!

!

!

!

!

!

!

!

CECS−1 0 1 2 3 4

!!

!

!

!

!!

!

!

!!

!!

!

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!

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!

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!

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!

!

!!

!

!!

!!

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!

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!!!

!

!!

!!!

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!

!

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!

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!

!

!!

!

!!

!

CNRT

−2 −1 0 1 2 3

!

!!

!!

!

!

!

!

!!!

!

!!!

!!

!

!

!

!

!

!

!

!

!

!!

!

!!

!!

!

!

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!

!!

!

!

!!

!!

!

!

!

!

!

!

!

!

!

!

!!

DayIrr

−1 0 1 2 3 4

!

!

!!

!

!

!

!

!

!!!

!

!

!

!

!!!

!

!

!

!

!!

!

!!

!!

!

!!

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!

!

!

!

! !!

!

!

!

!

!!

!

!

!

!

!

!!

!

!!

!

ECEC

−2 −1 0 1 2

−50

0

50

100

!

!

!

!

!

!

!

!

!

!!

!

!!

!!!

!

!

!

!!

!

!

!!

!!

!

!

!

!

!

!

!

!

!

!

!!

!

!!

!!

!

!

!

!

!!

!

!

!!

!!

!

EvptYr

−50

0

50

100

−2 −1 0 1 2 3

!

!

!!

!

!!

!!

!

!!

!

!

!

!

!

!!!

!

!

!

!

!!!

!

!

!

!

!!

!

!!

!!

!

!!

!

!

!

!

!

! !!

!

!

!

!

!!

!

!

!

HII

−1 0 1 2

!

!

!

!

!

!!

!

!!

!!

!

!

!

!

!!

!

!

!!

!!

!

!

!

!

!

!

!

!

!

!

!!

!

!!

!!

!

!

!

!

!!!

!

!!

!!

!

!

!

!

!

PHAQ

−2 −1 0 1 2

!

!

!!

!!

!

!

!

!

!

!

!

!

!

!

!!!

!!

!!

!

!

!

!

!!

!

!

!!

!!

!

!

!

!

!

!

!

!

!

!

!!

!

!!

!!!

!

!

!

!!

PreSeas

−2 −1 0 1 2 3

!

!

!!!

!

!

!

!

!!

!

!

!

!

!

!!

!

!!

!!

!

!!

!

!

!

!

!

! !!

!

!

!

!

!!

!

!

!

!

!

!!

!

!!

!!

!

!!

!

!

!

TAWC−2 −1 0 1 2 3

!

!!

!!

!

!!

!

!

!

!

!

!!!

!

!

!

!

!!

!

!

!

!

!

!!

!

!!

!!

!

!!

!

!

!

!

!

!!!

!

!

!

!

!!

!

!

!

!

!

!!

TmpSeas

−1 0 1 2 3

!

!

!

!

!

!!

!

!

!

!

!

!!

!

!!

!!

!

!!

!

!

!

!

!

! !!

!

!

!

!

!!

!

!

!

!

!

!!

!

!!

!!

!

!!

!

!

!

!

!

!!

TOTC

−1 0 1 2 3

!

!

!

!

!

!!

!

!!

!!

!

!!

!

!

!

!

!

!!!

!

!

!

!

!!

!

!

!

!

!

!!

!

!!

!!

!

!!

!

!

!

!

!

!!!

!

!

!

!

!!

TOTN

−2 −1 0 1 2

−50

0

50

100

!

!

!!

!

!

!

!

!

!!

!

!!

!!

!

!!

!

!

!

!

!

! !!

!

!

!

!

!!

!

!

!

!

!

!!

!

!!

!!

!

!!

!

!

!

!

!

! !!

!

!

YrIrrd


Figure E.2 Continued...Amass

Covariates

log−

resp

onse

ratio

[ln(

A/N)

]

0.0

0.5

−1.0−0.5 0.0 0.5 1.0

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

AnnPre

−1 0 1 2 3

!

!!!

!

!

!!!

!

!

! !!

!

!

! !!

!

AnnTmp

−1 0 1 2

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

BULK

−1 0 1

!!

!

!

!

! !

!

!

!

!!

!

!

!

!!

!

!

!

CECS−1 0 1 2

!

!

!

!

! !

!

!

!

! !

!

!

!

!!

!

!

!

!

CNRT

−1 0 1

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

DayIrr

−1 0 1 2

!

!

!

!

!!

!

!

!

!!

!

!

!

!!

!

!

!

!

ECEC

−1 0 1 2

0.0

0.5!

!

!!

!

!

!

! !

!

!

!

!!

!

!

!

!!

!

EvptYr

0.0

0.5

−2 −1 0 1

!

!!

!

!

!

!!

!

!

!

!!

!

!

!

!!

!

!

HII

−1.0 0.0 0.5 1.0 1.5

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

PHAQ

−2 −1 0 1 2

!

!

!

!!

!

!

!

!!

!

!

!

! !

!

!

!

!!

PreSeas

−1.0 0.0 0.5 1.0 1.5

!

!

!

!!

!

!

!

!!

!

!

!

!!

!

!

!

!!

TAWC−2 −1 0 1 2 3

!

!

!!!

!

!

!!!

!

!

!!!

!

!

!!!

TmpSeas

−2 −1 0 1

!!

!

!

! !!

!

!

!!!

!

!

!!!

!

!

!

TOTC

−1 0 1 2

!

!

!

! !!

!

!

!!!

!

!

!!!

!

!

!!

TOTN

−1 0 1 2 3

0.0

0.5!

!

!!

!

!

!

!!

!

!

!

!!

!

!

!

!!

!

YrIrrd

Amass

Covariates

Abso

lute

diff

erec

nes

[A−N

]

−50

0

50

100

150

−1.0−0.5 0.0 0.5 1.0

!!

!

!

!

!!

!

!

!

!!

!

!

!

!!

!

!

!

AnnPre

−1 0 1 2 3

!

!!!

!

!

!!

!

!

!

!!!

!

!

!!

!

!

AnnTmp

−1 0 1 2

!

!

!

!!

!

!

!

!!

!

!

!

!!

!

!

!

!!

BULK

−1 0 1

!!

!

!!

! !

!

!!

!!

!

!!

!!

!

!!

CECS−1 0 1 2

!

!

!!

! !

!

!!

! !

!

!!

!!

!

!!

!

CNRT

−1 0 1

!

!!

!

!

!

!!

!

!

!

!!

!

!

!

!!

!

!

DayIrr

−1 0 1 2

!!

!

!

!

!!

!

!

!

!!

!

!

!

!!

!

!

!

ECEC

−1 0 1 2

−50

0

50

100

150

!!

!!

!

!!

! !

!

!!

!!

!

!!

!!

!

EvptYr

−50

0

50

100

150

−2 −1 0 1

!

!

!!

!

!

!

!!

!

!

!

!!

!

!

!

!!

!

HII

−1.0 0.0 0.5 1.0 1.5

!

!

!!

!

!

!

!!

!

!

!

!!

!

!

!

!!

!

PHAQ

−2 −1 0 1 2

!

!!

!!

!

!!

!!

!

!!

! !

!

!!

!!

PreSeas

−1.0 0.0 0.5 1.0 1.5

!

!

!

!

!!

!

!

!

!!

!

!

!

!!

!

!

!

!

TAWC−2 −1 0 1 2 3

!

!

!!

!

!

!

!!

!

!

!

!!

!

!

!

!!

!

TmpSeas

−2 −1 0 1

!!

!

!

!!

!

!

!

!!

!

!

!

!!!

!

!

!

TOTC

−1 0 1 2

!

!

!

!!

!

!

!

!!!

!

!

!!

!

!

!

!!

TOTN

−1 0 1 2 3

−50

0

50

100

150

!

!

!

!!

!

!

!

!!

!

!

!

!!

!

!

!

!!

YrIrrd


Figure E.3 Continued...Nmass

Covariates

log−

resp

onse

ratio

[ln(

A/N)

]

−0.4−0.2

0.00.20.40.6

−4 −3 −2 −1 0 1 2

!! !!

!

!!!

!

!

!

!

!

! !

!

!

!

!!

!

!

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