conceptual synthesis in community ecologymvellend.recherche.usherbrooke.ca/vellend... · conceptual...

CONCEPTUAL SYNTHESIS IN COMMUNITY ECOLOGY

Mark VellendDepartments of Botany and Zoology, and Biodiversity Research Centre, University of British Columbia,

Vancouver, British Columbia, Canada, V6T 1Z4

e-mail: [email protected]

keywordsdispersal, drift, community ecology, population genetics, selection, speciation

abstractCommunity ecology is often perceived as a “mess,” given the seemingly vast number of processes that

can underlie the many patterns of interest, and the apparent uniqueness of each study system.However, at the most general level, patterns in the composition and diversity of species—the subjectmatter of community ecology—are influenced by only four classes of process: selection, drift, speciation,and dispersal. Selection represents deterministic fitness differences among species, drift representsstochastic changes in species abundance, speciation creates new species, and dispersal is the movementof organisms across space. All theoretical and conceptual models in community ecology can beunderstood with respect to their emphasis on these four processes. Empirical evidence exists for all ofthese processes and many of their interactions, with a predominance of studies on selection. Organizingthe material of community ecology according to this framework can clarify the essential similarities anddifferences among the many conceptual and theoretical approaches to the discipline, and it can alsoallow for the articulation of a very general theory of community dynamics: species are added tocommunities via speciation and dispersal, and the relative abundances of these species are then shapedby drift and selection, as well as ongoing dispersal, to drive community dynamics.

Introduction

COMMUNITY ECOLOGY is the studyof patterns in the diversity, abun-

dance, and composition of species in com-munities, and of the processes underlyingthese patterns. It is a difficult subject tograsp in its entirety, with the patterns ofinterest seemingly contingent on every lastdetail of environment and species interac-tions, and an unsettling morass of theoret-ical models that take a wide variety offorms. Fifteen years ago, Palmer (1994)identified 120 different hypotheses to ex-

plain the maintenance of species diversity,and the list would no doubt be even longertoday. However, despite the overwhelminglylarge number of mechanisms thought to un-derpin patterns in ecological communities,all such mechanisms involve only four dis-tinct kinds of processes: selection, drift, spe-ciation, and dispersal.

Many biologists will recognize these fourprocesses as close analogues of the “big four”in population genetics: selection, drift, mu-tation, and gene flow. Many ecologists, how-ever, might be skeptical that such a simple

The Quarterly Review of Biology, June 2010, Vol. 85, No. 2

Copyright © 2010 by The University of Chicago Press. All rights reserved.

0033-5770/2010/8502-0004$15.00

Volume 85, No. 2 June 2010THE QUARTERLY REVIEW OF BIOLOGY

183

organizational scheme is applicable to themore complex subject of community ecol-ogy. Population genetics, despite being facedwith essentially the same problem as commu-nity ecology—that is, understanding the com-position and diversity of alleles in popula-tions—is an easier subject to grasp, and Isubmit that the reason for this is not becauseof any fundamental difference in the com-plexity of the subject matter, but becauseof the coherence and simplicity of its the-oretical foundation. Every detail of thecomplex interactions between species andtheir environments that are studied byecologists can also be important agents ofnatural selection, but it is quite useful tobegin by recognizing just that: such inter-actions mostly fall under the single concep-tual umbrella of selection. Add the relativelysimpler processes of drift, gene flow, and mu-tation to the mix, and you have the ModernEvolutionary Synthesis, which remains a ro-bust, general, and widely accepted theoreticalfoundation for population genetics and micro-evolution, notwithstanding arguments aboutwhether it fully encompasses all facets of mod-ern evolutionary biology (Pigliucci 2007).

The perspective that synthesis in com-munity ecology can be achieved by orga-nizing processes into the four categories ofselection, drift, speciation, and dispersalflows directly out of a sequence of concep-tual developments that occurred over thelast half century. In the 1950s and 60s, G.Evelyn Hutchinson and Robert MacArthurushered in an era of community ecology inwhich the discourse was dominated by thedeterministic outcome of local interactionsbetween functionally distinct species andtheir environments—i.e., selection. Initialdevelopments of mathematical theory incommunity ecology had occurred decadesearlier (e.g., Lotka 1925), but, by all ac-counts, the 1960s marked the period duringwhich theoretical development in commu-nity ecology flourished (Kingsland 1995;Cooper 2003). The importance of selectiveprocesses in local communities ruled theday, and the vast body of theoretical andempirical research in this vein has beendubbed “traditional community ecology”(Lawton 1999; see also Brown 1995).

In response to the emphasis on local-scale selective processes almost to the ex-clusion of other factors, Ricklefs (1987) andothers (Ricklefs and Schluter 1993; Brown1995) argued for and successfully sparkeda shift in emphasis to a more inclusive ap-proach in community ecology, explicitlyrecognizing the importance of processesoccurring at broader spatial and temporalscales for understanding local-scale pat-terns. One key contribution here was therecognition that the composition and di-versity of species, even at a local scale, de-pend fundamentally on the compositionand diversity of the regional pool of spe-cies, which, in turn, depend on the processof speciation. Just as mutation is the ulti-mate source of genetic variation, so too isspeciation the ultimate source of the spe-cies that make up ecological communities.

The next key addition to the mix wasecological drift. Ecologists have long rec-ognized that changes in the compositionand diversity of species can have an impor-tant stochastic element (e.g., Chesson andWarner 1981). However, it was not untilHubbell (2001) imported the neutral the-ory of population genetics into ecologythat drift was incorporated into theory assomething much more than “noise” in anotherwise deterministic world. Pure ecologicaldrift happens when individuals of different spe-cies are demographically identical, which is ex-ceedingly unlikely. But drift need not be theonly active process in order to be an importantprocess, and, in many groups of species thatshow only modest functional differentia-tion, drift may indeed be quite important(McPeek and Gomulkiewicz 2005). Thefact that neutral theory was imported intoecology essentially unchanged from popu-lation genetics suggests the possibility of abroader synthesis of processes in both popula-tion genetics and community ecology, neutraland otherwise (Vellend and Geber 2005; Hu etal. 2006; Vellend and Orrock 2009).

The final key process is dispersal—the eco-logical equivalent of gene flow in populationgenetics. Dispersal has been incorporatedinto ecological theories of all kinds over thepast fifty years, but, in recent years, it hasbeen brought to the forefront in the form of

184 Volume 85THE QUARTERLY REVIEW OF BIOLOGY

the metacommunity concept (Holyoak et al.2005), which is explicitly concerned with therole of dispersal among local communities ininfluencing community patterns at multiplescales. The movement of organisms acrossspace can have a variety of important conse-quences in communities.

For each of the latter three processes—spe-ciation, drift, and dispersal—conceptual devel-opments were motivated by a perceived lack ofemphasis in the literature on the impor-tance of the process in question. Selection,in the form of deterministic interactionsamong species and between species andtheir environments, was always recognizedas important. With the additions of specia-tion, drift, and dispersal, we now have alogically complete set of process categorieswithin which all other more specific pro-cesses can be placed. I believe that organiz-ing the overwhelming number of specificecological theories for communities underthis scheme can help achieve at least twoimportant goals. First, the essential similar-ities and differences between different eco-logical models can be clarified in fairlystraightforward terms, thereby making thefull set of models easier to understand,apply, and teach to students. Second, wecan articulate a very general theory of com-munity dynamics, which may on the sur-face sound obvious and too generalized tomake any specific predictions, but may,nonetheless, serve the same critical func-tion as foundational theory in populationgenetics.

Before proceeding, I should emphasizethat I am not arguing that the parallels be-tween processes or models in population ge-netics and community ecology are perfect.For example, selection among individualsacross species can be manifested in ways thatare rare or absent within species (e.g., tro-phic or parasitic interactions), and specia-tion is a far more complicated process thanmutation. The list could go on. Rather, myargument is that we can define a similar setof four logically distinct processes in commu-nity ecology in order to provide a coherentconceptual framework for the discipline.

The rest of this paper is structured asfollows. I first specify more precisely the

motivation for conceptually organizing thematerial in community ecology, and pro-vide operational definitions of importantterms. I then illustrate, with separate sec-tions on theory and data, how the subjectmatter of community ecology can be pre-sented using the proposed organizationalframework, describing the ways in whichselection, drift, speciation, and dispersalinfluence communities. I then touch onsome of the general patterns that commu-nity ecologists have traditionally been in-terested in, and I discuss how pattern isconnected with process. Finally, I comparethe framework presented here with otherconceptual frameworks in community ecol-ogy.

Community Ecology Is a MessBased largely on empirical results, Lawton

(1999) famously called community ecology“a mess,” and ascribed this mess to the inher-ent contingency of ecological patterns onthe details of how the underlying processesor rules act. “The rules are contingent in somany ways . . . as to make the search forpatterns unworkable” (Lawton 1999:181).One source of motivation for the presentpaper is that even theoretical communityecology can be considered a mess for muchthe same reason: each and every twist addedto theoretical models seems to matter, mak-ing an overarching treatment of the subjectvery difficult. Consider the number of differ-ent models that can be constructed from thesimple Lotka-Volterra formulation of inter-actions between two species by layering onrealistic complexities, one by one. First, thereare at least three qualitatively distinct kindsof interactions (competition, predation, mu-tualism). For each of these, we can have ei-ther an implicit accounting of basal re-sources (as in the Lotka-Volterra model), orwe can add an explicit accounting in oneparticular way. That gives six different mod-els so far. We can then add spatial heteroge-neity or not (�2), temporal heterogeneity ornot (�2), stochasticity or not (�2), immigra-tion or not (�2), at least three kinds of func-tional relationships between species (e.g.,predator functional responses; �3), age/sizestructure or not (�2), a third species or not

June 2010 185SYNTHESIS IN COMMUNITY ECOLOGY

(�2), and three ways that the new speciesmay interact with one of the existing species(�3 for the models with a third species).Having barely scratched the surface of po-tentially important factors, we have 2304 dif-ferent models. Many of them would likelyyield the same predictions, but, after consol-idation, I suspect there still might be hun-dreds that differ in ecologically important ways.As Lawton (1999) put it, “the necessary contin-gent theory looks unworkably complicated” (p.180).

One important manifestation of this messis that textbook treatments of communityecology and their associated university cours-es—that is, the vehicles by which the subjectmatter is taught to students—have a struc-ture whose logic is not easy to discern. Sec-tion or chapter topics typically fall looselyunder one or more of the following head-ings: community patterns, competition, pre-dation (plus other enemy-resource interac-tions), niches, food webs, and issues of spaceand time (e.g., Putman 1994; Morin 1999;Ricklefs and Miller 1999). This is a confusinglist because it includes unlike entities—pat-terns, processes (competition, predation),concepts (niches, food webs), objects ofstudy (food webs), or a consideration that isalways important to think about (space andtime) (Vellend and Orrock 2009). In con-trast, books and courses in population genet-ics (e.g., Hartl and Clark 1997) are basedupon a structure that is easier to follow, witha consistent focus on the four processes ofselection, drift, gene flow, and mutation, andhow these processes either individually orjointly determine patterns of genetic varia-tion. In my opinion, ecology textbooks andcourses are a fairly accurate reflection of theway in which practicing community ecolo-gists have self-organized around particularresearch topics or themes, but I am not con-vinced that this is the best way to organizethe subject matter for facilitating syntheticand integrated understanding by studentsand practitioners alike. As elaborated below,selection, drift, speciation, and dispersal maynot be of equal importance in understand-ing ecological patterns, but they fully repre-sent the logically distinct categories of impor-tant processes in community ecology.

A Theory of What Is PossibleAmazingly, the foundation of theoretical

population genetics was built in the nearabsence of data on patterns of genetic vari-ation in natural populations—the very sub-ject matter of the discipline (Provine 1971).Perhaps for this reason, at least in part, atheoretical foundation was built to de-scribe a logically complete range of thebasic possible processes that could causeevolutionary change, rather than a theoryskewed towards an emphasis on those pro-cesses that are actually important in na-ture. The latter is an empirical rather thantheoretical issue. In contrast, long beforethe existence of ecological theory, patternsin nature were well-known to any keen ob-server. Allen and Hoekstra (1992) describeecology as a discipline “whose material studyis part of everyday encounters: birds, bees,trees, and rivers” (p. 1). They go on to argue,albeit in a somewhat different context, that“It is, however, a mistake to imagine that thisfamiliarity makes ecology an easy pursuit-. . .the very familiarity of ecological objectspresents the difficulties” (Allen and Hoek-stra 1992:1). I argue that this everyday fa-miliarity with ecological patterns pushedecological theory down the path of empha-sizing particular viewpoints on the pro-cesses that are actually most important innature, rather than emphasizing a logicallycomplete set of possible processes thatmust play at least some role in communitydynamics. The emphasis in ecology, there-fore, has been on pattern before process(Roughgarden 2009; Vellend and Orrock2009). Using the structure of population ge-netics theory as a guide, with details alteredwhere necessary for communities, the follow-ing presents an organizational scheme forcommunity ecology, within which all specificmodels and frameworks can be described.

definitionsTable 1 provides operational definitions

of the key terms used in this paper. Withrespect to the definition of community,there has been considerable debate inecology concerning the degree to whichecological communities are sufficiently co-


herent entities to be considered appropri-ate objects of study (reviewed in Ricklefs2008). The definition of community usedhere—that is, a group of organisms repre-senting multiple species living in a speci-fied place and time—bypasses this issue byrecognizing that properties of communi-ties are of central interest in ecology, re-gardless of their coherence and integrity.This definition of community also implic-itly embraces all scales of space and time.Studying communities in 1m2 plots or acrossentire continents requires different methods,and the relative importance of different pro-cesses likely varies across scales, but we are of-ten interested in understanding the samekinds of patterns (e.g., diversity, composition)at these different scales. This represents an ex-pansion of the purview of community ecologybeyond its traditional focus on relatively smallscales, without applying a new name to thediscipline (e.g., studies in “macroecology” of

species diversity are considered part of commu-nity ecology here).

The Four Processes of CommunityEcology: Theory

selection

Use of the term “selection” to describedeterministic fitness differences among in-dividuals of different species (Table 1) re-quires some explanation, as it is not yetcommonplace in ecology (but see Loreauand Hector 2001; Norberg et al. 2001;Shipley et al. 2006; Bell 2008). Althoughthe term is used in biology most often withrespect to evolutionary dynamics withinspecies, the definition of selection in no wayrestricts its application as such. Selection oc-curs when individuals in a population vary insome respect, and when different variantsreproduce or replicate themselves at differ-ent rates (Darwin 1859; Bell 2008; Nowak2006). In its most generalized form, the con-

TABLE 1Definitions of terms

Term Definition

Community A group of organisms representing multiple species living in a specified placeand time

Community ecology The study of patterns in the diversity, abundance, and composition of speciesin communities, and the processes underlying these patterns

Community dynamics Changes over time in the relative abundances of species in a specified area,including extinctions and species additions via dispersal or speciation

Species composition For a given community, a state defined by the abundances of all speciesSpecies relative abundance The proportion of all organisms in a given area that are of a given species;

equivalent to species frequency.Species density The number of organisms of a given species per unit of spaceCommunity size The total number of organisms in a communityCoexistence The indefinite persistence of a specified set of species in a specified areaAbsolute fitness The quantity of offspring produced by an individual organism per unit of

time, including survival of the organism itselfRelative fitness The absolute fitness of a given organism divided by the mean absolute fitness

across all individuals in the communitySpecies fitness (absolute or relative) The mean fitness (absolute or relative) across all individuals of a given

species in the community; for absolute fitness, this is equivalent to thespecies per capita population growth rate.

Selection A deterministic fitness difference between individuals of different speciesDrift Random changes in species relative abundancesNeutrality A state in which all individual organisms share identical demographic

propertiesSpeciation The creation of new speciesDispersal The movement of organisms across space


cept of selection—and, more broadly, evolu-tionary change—can be applied “based onlyon the assumption of a population of thingsthat leave descendants and have measurablephenotypes” (Rice 2008:4).

Applying the concept of selection to spe-cies in a community rather than to alleles ina species’ population requires two changesto the frame of reference. First, rather thaninvoking selection at any level higher thanthat of the individual organism, we simplydefine the “population” as containing indi-viduals of multiple species; we call this pop-ulation a community. Second, the phenotypeof interest, which may be under selection,is most often just the species identity. Thespecies identity is a categorical phenotype,assumed to have perfect heritability, ex-cept when speciation occurs, after whichnew species identities are assigned (just asmutation changes the identity of an allele).In the same way that selection may favorallele A over allele a within a species’ pop-ulation, selection may favor species X overspecies Y in a community. It is important tonote that although the concept of selectionin communities is easier to envision forspecies on the same trophic level than forspecies on different trophic levels, the dif-ference is one of degree and not kind. Forexample, a lynx and a hare are very differ-ent organisms, but selection still favorshares when lynx are declining, and it favorslynx when hares are abundant (Krebs et al.2001).

Rather than focusing only on species iden-tities, it is also possible to define each speciesby one or more traits (e.g., beak depth, leafthickness) (McGill et al. 2006) and to thenapply tools from quantitative genetics at thecommunity level (e.g., Norberg et al. 2001;Shipley et al. 2006). This opens the door tosimultaneous consideration of selection bothwithin and among species. However, to sim-plify the discussion and focus attention mostsharply at the community level, I hence-forth address selection in communities byassuming that individuals of a given specieshave the exact same phenotype (e.g., thespecies identity). Relaxing this assumptionforms the basis of a very active area ofresearch (e.g., Hughes et al. 2008), but,

before doing so, it is first necessary to establishthe basic building blocks of community ecol-ogy, with species as the fundamental categoryof accounting in the assessment of community-level phenomena.

In a community context, there are threerelevant forms of selection: (1) constant,(2) frequency- or density-dependent, and(3) spatially- or temporally-variable selec-tion. Constant selection is simple: if relativefitness is constant in space and time, inde-pendent of species’ densities but variableacross species, the species with the highestfitness will exclude all others (Figure 1A).The other forms of selection, however, aremore complicated.

Frequency- or density-dependent selection iscentral to the vast majority of theoretical mod-els with species interactions in community ecol-ogy. For simplicity, I will only use the term“density-dependent,” given that most ecologi-cal models include densities rather than fre-quencies—a key distinction from the traditionin population genetics (Lewontin 2004). Ifcommunity size is constant, density and fre-quency are equal (as in Figure 1, for simplicityof presentation). Density-dependent selectionoccurs when individual fitness in a givenspecies depends at least in part on the den-sity of that species, as well as the densitiesof other species. For two species, negativedensity-dependent selection favors specieswhen they are at low density and is thuscapable of maintaining stable coexistence(Figure 1B), whereas positive frequency-dependent selection favors species at highdensity and cannot maintain stable coexist-ence (Figure 1C). Selection can also de-pend on species densities in more complexways, possibly allowing more than one stablestate at which coexistence can be main-tained (Figure 1D), or creating repeatedoscillations in interacting species’ abun-dances (Morin 1999). A major challenge inecology is presented by the nearly limitlessvariety of configurations that the full set ofintra- and interspecific density dependen-cies can take in a species-rich community.

The nature of density-dependent selec-tion between pairs of species depends onthe qualitative ecological relationship be-tween them (e.g., competition, predation,


mutualism, and disease) and the quantita-tive form of this relationship. With morethan two species, indirect interactions canarise whereby fitness in one species de-pends on the density of a second species notbecause of a direct interaction, but becauseeach of the two species interacts directly with athird (Strauss 1991). Even the nature of thedirect interaction between two species can beinfluenced by other species, amplifying evenfurther the number of ways a community canbe configured. A massive edifice of theoreticalresearch has addressed the community conse-quences of different forms of density-dependent interactions among species (Morin

1999). From a given set of initial conditions,outcomes such as the exclusion of all but onespecies, the indefinite coexistence of all spe-cies, complex temporal fluctuations, or en-tirely different equilibrium patterns dependingon initial conditions are possible.

Selection, whether constant or density-dependent, may vary across space or time, withpotentially important consequences for com-munity dynamics. Most importantly, the behav-ior of such models can deviate qualitativelyfrom spatiotemporally invariant models whenthe relative fitness of different species switchesin different places or times, thereby allowingfor coexistence among species that would oth-

Figure 1. Expected Dynamics and Equilibria between Two SpeciesExamples for species A and B in a community of constant size are shown under (A) constant selection

favoring species A, (B) negative frequency-dependent selection, (C) positive frequency-dependent selection,(D) complex frequency-dependent selection, and (E) no selection. Solid and open circles indicate stable andunstable equilibria, respectively. Dotted lines indicate the difference between the fitness of species A andspecies B. Arrows indicate the change in species’ frequencies. These figures are modeled after Nowak (2006).Note that when species densities (rather than only frequencies) are of central interest, as in most models oftrophic interactions, each species density would need to be represented by a separate axis rather than along asingle axis, as in these simplified examples.


erwise not be possible (Levene 1953; Ches-son 2000). More generally, species coexist-ence always depends on trade-offs of somekind, with different species having fitnessadvantages under different sets of condi-tions, specified by some combination ofthe abiotic environment and the densitiesof the species themselves (Chesson 2000).

driftBecause birth, death, and offspring pro-

duction are inherently stochastic pro-cesses, changes in any community with afinite number of individuals will also have astochastic component. This is ecologicaldrift. If individual-level demographic pa-rameters are identical across all individualsin a closed community, drift is the onlydriver of community dynamics (i.e., thereare no deterministic changes in abun-dance; Figure 1E) and, eventually, all butone species will drift to extinction. Theprobability of each species reaching mono-dominance is equal to its initial frequency,and the rate at which this is achieved isnegatively related to community size (Fig-ure 2). As such, declines in community size(i.e., disturbance) may increase the impor-tance of drift. Importantly, drift need notact alone to have an important impact oncommunity dynamics. The interaction ofdrift with speciation and dispersal (Hub-bell 2001) will be described in subsequentsections; here, I address the interaction ofdrift and selection.

If selection is relatively strong and thecommunity size is large, selection will over-ride any effects of drift. But if selection isrelatively weak and the community size issmall, drift can override the effects of selec-tion. Between these two extremes, selectionmakes some community outcomes morelikely than others, but it does not guaranteeany particular outcome (Nowak 2006). Forexample, even with constant selection favor-ing one of two species, there is some proba-bility that the species with the higher fitnesswill drift to extinction (Figure 2).

speciationMost treatments of community ecology in-

herently exclude from their purview the ques-

tion of how the species in a given area arose inthe first place, leaving such questions to thefields of biogeography and macroevolution(Ricklefs 1987; Brown 1995). From the per-spective of understanding how species in-teractions play out in homogeneous, small-scale localities, this is entirely defensible,because the origin of the local species pooldoes not matter; what does matter is thatthe species are present locally and possessa given set of traits. But to compare com-munity patterns across different regions,and even across environmental gradientsat quite local scales, it may be important toincorporate the biogeographic and macro-evolutionary context in which the speciespool originated (Ricklefs 1987; Ricklefsand Schluter 1993; Partel 2002). We can nomore afford to exclude speciation from com-munity ecology than we can afford to excludemutation from population genetics, even ifspeciation is a far more complex process.

I deliberately focus on speciation ratherthan embracing extinction under this um-brella as well, because, with an expanded spa-tial and temporal scope of community ecology(see definitions section above), extinction isbest considered as an outcome of selection anddrift, rather than as a distinct process in and ofitself. When the last individual of a species dies,the species is extinct, and while the decline toextinction may have many specific causes, theymust either be deterministic (selection) or sto-chastic (drift). Even major geological events(e.g., glaciation) are distinguished from moresubtle environmental changes (e.g., slight acid-ification of a lake) as agents of selection bythe rate, magnitude, and spatial scale ofchange, rather than by a qualitatively distinctinfluence on communities. Such environ-mental changes may also alter the effects ofdrift via changes in community size.

I focus here on some of the simplest waysthat speciation has been incorporated into the-oretical community models, as well as someempirically-motivated conceptual models. Atlarge spatial scales, such as entire conti-nents, the rate of speciation can entermathematical models directly as a key de-terminant of community dynamics. For ex-ample, Hubbell (2001) considered a neu-tral community of fixed size in which the


speciation rate is constant, with the rate ofextinction due to drift increasing with thenumber of species because, with more species,

each species’ population must be smaller. Al-ternatively, MacArthur (1969) posited thatboth speciation and extinction rates increase

Figure 2. Frequency Dynamics of Two Species under Drift and SelectionDynamics are shown for two species, A and B, with non-overlapping generations in 10 simulated communities

of constant size, J, with (A) no fitness differential and J � 500, (B) no fitness differential and J � 50, (C) a 5%fitness advantage to species A and J � 500, and (D) a 5% fitness advantage to species A and J � 50.


with the number of species, but with theincrease decelerating for speciation and ac-celerating for extinction, thus resulting in anequilibrium number of species in the region.These models correspond to drift-speciationbalance and selection-speciation balance, re-spectively, and, in both cases, a greater rateof speciation leads to a larger species pool,all else being equal. In a model of multiplelocal communities connected by dispersalalong an environmental gradient, McPeek(2007) found that the nature of the specia-tion process influenced local species diver-sity: greater ecological similarity betweennew and existing species extended times toextinction, thereby elevating local species di-versity at any given time. More conceptual(rather than mathematical) models addressthe consequences of variation in the rate atwhich species that are adapted to particularconditions (e.g., regionally common or rareabiotic conditions) are produced. The term“species pool hypothesis” has been used todescribe this type of conceptual model (Tay-lor et al. 1990). Through its effects on theregional species pool, speciation then indi-rectly becomes a potentially important deter-minant of community dynamics and pat-terns, even at a local scale where the rate ofspeciation is negligible relative to other pro-cesses (e.g., Ricklefs and Schluter 1993; Par-tel 2002).

dispersalDispersal involves the movement of or-

ganisms across space, and, thus, its influ-ence on community dynamics depends onthe size and composition of the communi-ties where the dispersers come from and ofthose in which they disperse to (Holyoak etal. 2005). As such, the community conse-quences of dispersal can only be addressed inrelation to the action and results of other pro-cesses, selection and drift in particular. Theconstruction of theoretical community modelsaddressing the role of dispersal usually speci-fies whether organisms are distributed contin-uously across space or in discrete patches. Thelatter type of distribution will be adopted herefor the sake of simplicity and clarity.

With respect to the relative sizes of thesource and recipient communities for dispers-

ers, two kinds of models represent the ends ofa continuum. Mainland-island models assumeone-way dispersal from a source community ofeffectively infinite size (the mainland) to oneor more smaller, discrete local communi-ties (the islands, or localities). These mod-els assume that community dynamics insmall localities are sufficiently rapid rela-tive to those on the mainland, such thatthe composition of the pool of dispersers iseffectively constant. In contrast, islandmodels assume a network of small localcommunities linked by dispersal amongthem, with no distinct mainland. Such net-works of local communities may be called“metacommunities” (Holyoak et al. 2005).

Dispersal can interact with drift and specia-tion. In a mainland-island model with localdrift but no speciation or selection, dispersalincreases local species richness and causes localcommunity composition to converge with thatof the mainland. For a given level of dispersal,the number of new species introduced per unitof time will decrease as local species richnessincreases, because fewer and fewer of the dis-persers will represent new species in the local-ity. With fixed local community size, greaterspecies richness necessitates smaller popula-tion size per species, so that the rate of speciesextinction increases with species richness, atsome point equaling the rate of species intro-duction, and thus determining an equilibriumnumber of species whose identities nonethe-less change through time. This is the simplestform of the theory of island biogeography(MacArthur and Wilson 1967). In an islandmodel with local drift but no speciation or se-lection, dispersal increases local diversity bycountering drift, and causes the similarity incomposition among localities to increase(Wright 1940). Without input via speciationor dispersal from a separate metacommunity,all but one species will ultimately drift to extinc-tion. In a model with drift, speciation, and dis-persal but no selection, all community patternsare determined by the size of the local commu-nities, the size of the entire metacommunity,and the rates of speciation and dispersal (Hub-bell 2001).

Not surprisingly, the range of outcomeswhen dispersal interacts with selection is vast.The nature of selection among species in one


locality can take many different forms, and dis-persal implies multiple localities, each of whichmay represent a unique selective environment.The consequences of dispersal depend onthese details. Also, in addition to the manykinds of trade-offs in different models of pureselection, dispersal ability itself may vary amongspecies, possibly with a trade-off involving otheraspects of fitness. Enumerating all possibleways that dispersal can interact with selectionand drift is well beyond the scope of thepresent paper, but three generalized exampleswill provide us with a glimpse into how selec-tion and dispersal can interact. First, if selec-tion via competition or predation causes a spe-cies to go locally extinct, that species maynonetheless persist regionally, along with itscompetitor/predator, if it has a superior abilityto disperse to “open” sites where the supe-rior competitor/predator has gone ex-tinct due to either an absence of prey orfor other reasons (Caswell 1978; Tilman1994). Second, if selection favors differentspecies in different patches, dispersal cannonetheless maintain persistent local pop-ulations of species, even in patches wherethey are at a fitness disadvantage (Levene1953). If species vary in their mean fitnessacross patches, then very high dispersal willallow the species with the highest averagefitness to exclude all others. Finally, in amainland-island context, dispersal to theisland determines the species pool in a wayclosely analogous to the role of speciationon continents.

relating existing theories to thefour processes

Four processes—or any four items—canbe considered singly or in combination in15 different ways: each of the four alone,six pairwise combinations, four trios, andall four together. However, it is impossibleto build a theoretical community modelwith only speciation and/or dispersal with-out specifying the fate of new species ordispersers, particularly with respect to se-lection or drift. Thus, the four processescan form the basis of theoretical models in12 different ways.

Table 2 relates many of the influentialand familiar theories, models, and concep-

tual frameworks in community ecology totheir emphasis on selection, drift, specia-tion, and dispersal. Briefly, the idea of spe-cies “niches” (Chase and Leibold 2003) isessentially synonymous with selection, andmany models of species interactions repre-sent different manifestations of selection.Adding demographic stochasticity to selection-based models represents a combination ofdrift and selection (e.g., Tilman 2004), asdo models proposed under the rubric of aniche-neutral reconciliation (e.g., Shipley etal. 2006; Adler et al. 2007). The species-poolhypothesis (Taylor et al. 1990) and thebroader conceptual framework, based onthe interaction between local and regionalprocesses (Ricklefs and Schluter 1993), rep-resent the interaction between speciationand selection and, to some degree, dispersal.Classic island biogeography theory(MacArthur and Wilson 1967) represents abalance between drift and dispersal, andthe full version of Hubbell’s (2001) neutraltheory represents the combined influenceof drift, dispersal, and speciation. Meta-community theory (Holyoak et al. 2005)and the many specific models that fall intothis category, such as those involving colo-nization-competition tradeoffs or “mass ef-fects,” emphasize dispersal first and fore-most, and how dispersal interacts withselection and drift.

The Four Processes of CommunityEcology: Data

A vast amount of empirical literature ad-dresses the processes underlying the dy-namics of ecological communities. Thepurpose of this section is to illustrate the kindsof evidence available from lab experiments-,field experiments, and observations of naturethat speak to the importance of various formsof selection, drift, speciation, and dispersal incommunities.

selectionCase studies of selection in ecological com-

munities number in the thousands, and mostcommunities documented in these studies ap-pear to be characterized by unique combina-tions of selective factors (Diamond and Case1986; Putman 1994; Lawton 1999; Morin


1999). Important factors that underlie the in-fluence of selection on community patternsinclude species’ responses to the abiotic envi-ronment, the disturbance regime, the types ofdirect interactions between organisms (e.g.,competition, predation, parasitism, herbivory,mutualism), the functional or behavioral re-sponses of organisms to different densities ofinteracting species, the degree of specializationin interspecific interactions, the number and

types of limiting resources (e.g., renewable ornon-renewable), and the presence and natureof indirect interactions among species (Put-man 1994; Morin 1999; Ricklefs and Miller1999). The following handful of examplesfocuses mostly on competition and trophicinteractions to illustrate the basic types ofselection (Figure 1) and the range of out-comes of selection in local communities,such as the exclusion of some species by oth-

TABLE 2Twelve combinations of selection, drift, speciation, and dispersal, and the ways in which existing ecological

theories relate to these combinations

Combination Selection Drift Speciation Dispersal Theories and modelsRepresentative

references

1 � Niche models of all kinds(e.g., resourcecompetition, predator-prey, food webs)

Tilman (1982); Chase& Leibold (2003)

2 � Neutral theory I(demographicstochasticity)

Hubbell (2001)

3 � � Niche-neutral models(any niche model withdemographicstochasticity)

Tilman (2004); Adleret al. (2007)

4 � � Historical/regionalecology I (species pooltheory, diversity ongradients, speciation-selection balance)

MacArthur (1969);Ricklefs (1987)

5 � � Neutral model II (non-spatial)

Hubbell (2001)

6 � � Metacommunities -deterministic (spatialmass effects, spatialfood webs)

Holyoak et al. (2005)

7 � � Neutral model III (islandbiogeography)

MacArthur & Wilson(1967); Hubbell(2001)

8 � � � Historical/regionalecology II

Ricklefs (1987)

9 � � � Historical/regionalecology III

Ricklefs (1987)

10 � � � Neutral model IV(spatial)

Hubbell (2001)

11 � � � Metacommunities -stochastic (colonization-competition tradeoffs,stochastic versions ofsix)

Holyoak et al. (2005)

12 � � � � The theory of ecologicalcommunities

This paper


ers, the stable coexistence of species, com-plex fluctuations in abundance over time, oralternation between different stable states. Ifocus on studies in which the outcome ofselective processes is measured as changes inthe abundances or diversity of species, ratherthan in the responses, such as individualgrowth rates or body size, of focal species,which are often measured under the as-sumption that they may have consequencesat the community level (e.g., Van Zandt andAgrawal 2004).

Species can exclude each other; whileselection in any real situation is unlikely tobe constant across all species’ densities(Figure 1A), one species may be at an ad-vantage across the full range of possible den-sities. Lab experiments have demonstratedcompetitive exclusion between species ofparamecium (Gause 1934), phytoplankton(Tilman 1977), and flour beetles (Park1948), among many others, as well as theexclusion of prey species by a predator(Gause 1934; Huffaker 1958). Similarly, fieldexperiments have revealed competitive ex-clusion—for example, between barnacle spe-cies at particular tidal depths (Connell1961), or plant species under particular re-source conditions (Tilman 1982, 1988). Inmany cases of competitive exclusion, the win-ner in competition depends on environmen-tal conditions, thus establishing the possibil-ity (in lab experiments) or existence (in fieldstudies) of spatially-variable selection. Manyspecies distribution patterns have been inter-preted as evidence of competitive exclusionbetween functionally similar species (e.g., Di-amond 1975), although it is very difficult toconfidently infer process from pattern insuch cases (Strong et al. 1984). Regardlessof the strength of direct interspecific compe-tition, past environmental change (e.g.,glacial cycles) has acted as an agent of selec-tion among species, favoring some but caus-ing others to decline, sometimes to thepoint of extinction (McKinney 1997; Wil-liams et al. 2004).

Competing species often exist in stable com-binations via negative density-dependent selec-tion. With multiple limiting resources and twophytoplankton species, Tilman (1977) foundthat one species (Asterionella formosa) was a

superior competitor for the resource mostlimiting to the other species (Si) and viceversa (Cyclotella meneghiniana, and P), result-ing in stable coexistence via negative density-dependent selection at intermediate Si/P ra-tios. Coexistence among grassland plantspecies via the same mechanism has beenfound in field experiments as well (Tilman1988). A trade-off between competitive abil-ity and colonization ability can create nega-tive density-dependent selection contribut-ing to the coexistence of protozoans androtifers in lab microcosms (Cadotte et al.2006), although field evidence for this mech-anism is more ambiguous (e.g., Levine andRees 2002). Temporally variable selection viaenvironmental fluctuations can lead to sta-ble coexistence of diatoms under variabletemperatures in the lab (Descamps-Julienand Gonzalez 2005), and also appears to bea likely explanation for the coexistence andfluctuation of grassland plants in variable cli-matic conditions in Kansas (Adler et al. 2006).Patterns of species composition are oftenclosely correlated with environmental condi-tions, with spatially-variable selection almostcertainly playing an important role (Whittaker1975).

Trophic interactions among species canlead to coexistence with fluctuations over timevia complex forms of density-dependent selec-tion. Predators and their prey can coexist overthe long term with regular cycles, both in labmicrocosms, such as those with different spe-cies of mites (Huffaker 1958) or rotifers andalgae (Fussman et al. 2000), as well as infield populations, such as snowshoe haresand lynx in the boreal forest (Krebs et al.2001). Density-dependent species interac-tions can also lead to complex, chaotic dy-namics with species persistence in aquaticlaboratory food webs (Beninca et al. 2008).

Positive and negative density-dependentselection over different ranges of species’densities can lead to switches between mul-tiple states with respect to community com-position. Changes in the initial abundancesof species in aquatic microcosms can lead tovery different and seemingly stable final spe-cies compositions (Drake 1991)—a resultthat has been found in a variety of lab andfield experiments (Schröder et al. 2005). In


natural, nonexperimental systems, a changein the abiotic environment can act as a selec-tive force that changes species composition,which, in some cases, may not be reversiblejust by returning the environmental condi-tion to its original state (Scheffer et al. 2001).In lakes, for instance, nutrient input canpush species composition towards a new sta-ble state that is not reversible unless nutri-ents are reduced to much lower levels thanthose at which the initial change took place(Dent et al. 2002).

The range of detailed mechanisms un-derlying the influence of selection on com-munities is vast. In a nutshell, almost anykind of selective interaction between spe-cies can be found in some community onearth, or can be recreated in the labora-tory. Likewise, many case studies have beenable to reject hypotheses based on partic-ular forms of selection, although such re-jections typically apply only to the systemunder study, rather than representing ageneral refutation of a hypothesis. Ecolo-gists working in different kinds of commu-nities have traditionally emphasized theimportance of particular processes (e.g.,competition among terrestrial plants vs.trophic interactions among aquatic ani-mals), although it is not clear whetherthese reflect real differences among com-munities or logistical constraints to study-ing different processes in different systems.

driftTesting for ecological drift among species

presents considerable empirical challenges.First, pure ecological drift—without any selec-tion—seems unlikely given the myriad differ-ences between species. Second, while selectionis relatively easy to detect as a consistent fitnessdifference between species across observa-tional or experimental units, the unexplainedvariance across such units cannot automaticallybe attributed to drift. This is because of theentirely plausible possibility that much of theunexplained variance is due to minor differ-ences in uncontrolled factors, such as environ-mental parameters. One can always dream upa deterministic explanation for apparent ran-domness. Indeed, the discussion sections ofmany ecological papers implicitly attribute low

values of r2 to unmeasured but deterministicfactors, rarely entertaining the possibility thatthe unexplained variation is truly random—that is, due to ecological drift. Nonetheless, in aworld of finite size, drift is a fact of life, andthere are in fact many empirical studies inwhich a compelling case can be made for driftas an important process underlying commu-nity dynamics.

Experiments by Thomas Park (1948) andcolleagues (Mertz et al. 1976) with Triboliumflour beetles demonstrated a competitive ad-vantage of one or another species dependingupon conditions of temperature and humid-ity, but they also discovered conditions un-der which the outcome was indeterminate.Sometimes T. castaneum wins and sometimesT. confusum wins, despite seemingly identicalconditions across replicate microcosms. Ithas been suggested that differences in thegenetic composition of populations can pro-vide a selective explanation for the seeminglyindeterminate results (Lerner and Dempster1962), but, ultimately, it appears that underparticular conditions the two species are suf-ficiently close to competitive equivalencythat ecological drift does indeed play an im-portant role in the outcome of competition(Mertz et al. 1976). More recently, densitymanipulation experiments with Enallagmadamselflies strongly suggested ecologicalequivalence between two species, with no ob-vious advantage to either species at low rela-tive abundance, but strong sensitivity of de-mography to total density across the twospecies (Siepielski et al. 2010).

I know of few other examples where con-clusive evidence has been found that driftdoes indeed play a dominant role in com-munity dynamics, but a number of studieshave reported seeming competitive equiv-alence between species under particularconditions, in organisms ranging from vas-cular plants (Goldberg and Werner 1983)to salamanders (Fauth et al. 1990). Hub-bell (2001, 2005) has vigorously advancedthe hypothesis that many tropical tree spe-cies are effectively ecological equivalents,with their community dynamics determinedby drift and dispersal in the short term, alongwith speciation in the long term. Some trop-ical tree species show clear evidence of


ecological differences in traits, such as atrade-off between survival versus growth ratein gaps (Hubbell 2005) and environment-dependent fitness (John et al. 2007), thussuggesting an important role for selection incommunity dynamics. However, hundreds ofco-occurring species of any particular ecolog-ical “type” still remain, indicating a potentiallyimportant role for drift, even though it isclearly not the only important process at workin tropical forests. In many data sets, speciescomposition is strongly related to environmen-tal conditions (indicative of selection), butvariation in the compositional similaritybetween sites is also related to spatial prox-imity independent of environment, andthis is an indirect indication of drift (Cot-tenie 2005). For species engaged in tro-phic interactions, the concept of pure neu-trality does not apply, although changes inpredator and prey abundances almost cer-tainly have an important stochastic compo-nent in many cases (Chesson 1978).

speciationSpeciation is obviously an important deter-

minant of the number and types of speciesfound in large regions, such as entire conti-nents, as well as on isolated islands (MacArthur1969; Losos and Schluter 2000; Ricklefs 2008).Although the distinction of discrete spatialscales is largely arbitrary (Ricklefs and Schluter1993), the present discussion focuses on cir-cumstances under which speciation exerts animportant influence on community patterns atcomparatively small scales.

Speciation appears to be critical to our un-derstanding of at least two kinds of species di-versity patterns. First, why do equal-sized areasunder very similar environmental condi-tions but in different geographical regionscontain different numbers of species?These have been dubbed “diversity anom-alies” (Ricklefs 2008). For example, acrossa range of scales, equal-area portions ofeastern Asia contain about twice the num-ber of plant species as in eastern NorthAmerica, despite similar environmentalconditions and strong taxonomic affilia-tions between the two regions (Ricklefs etal. 2004). Increased opportunity for specia-tion in eastern Asia due to greater physi-

ographic heterogeneity appears to be animportant contributor to this pattern(Qian and Ricklefs 2000). More generally,many studies report linear increases in lo-cal species richness with increasing re-gional species richness (Srivastava 1999),thus suggesting an important influence onlocal diversity of processes, such as specia-tion and dispersal, that determine the re-gional species pool.

The second kind of species diversity patternfor which speciation can be a key underlyingprocess is the relationship between species di-versity and local environmental gradients(Ricklefs 2004). Such patterns are widespread(Rosenzweig 1995), and, before assessing theunderlying processes at work here, it is impor-tant to consider that the species in lower diver-sity areas may not just be a subset of the speciesin higher diversity areas. For example, whilethe number of species per unit of area maychange with elevation up a mountainside, onemust take into account that there are differentsets of species living at the base and at the topof the mountain (Whittaker 1975). If we takethe regional species pool as a given and assumethat all species have been able to reach differ-ent areas, selection must be an important pro-cess underlying the composition-environmentrelationship. However, why should we find dif-ferent numbers of species at different eleva-tions or different levels of productivity? Forproductivity gradients in plants, for instance,one selection-based explanation is that highproductivity fosters dominance by fast-growingspecies, thereby limiting species diversity undersuch conditions (Grime 1973). But again, whyshould there be relatively few species capableof exploiting high productivity conditions or,more generally, any particular set of conditions(Aarssen and Schamp 2002)?

One potentially important part of the an-swer is that different sets of environmentalconditions have been represented to variabledegrees over time, such that speciation hasproduced many species that are adapted tocommon, widespread conditions, but farfewer that are adapted to rarer conditions(Taylor et al. 1990). For example, in regionswhere relatively high soil pH has predomi-nated, plant species diversity tends to be pos-itively correlated with pH, whereas in regions


where relatively low soil pH has predomi-nated, the opposite is true (Partel 2002).Even if different habitats have been equallyavailable over time, current species richnessmight be greatest in conditions under whicha particular group of organisms initiallyevolved and, therefore, where diversity hashad more time to accumulate via speciation.For example, Wiens et al. (2007) found sim-ilar rates of diversification at different eleva-tions for a clade of tropical salamanders, butthey noted that mid-elevation habitats werecolonized earliest in the evolution of theclade, thus helping explain a mid-elevationpeak in species richness patterns. In sum-mary, although selection is a key determi-nant of compositional change along gradi-ents, speciation is likely a critical processcontributing to many diversity-environmentrelationships (Ricklefs 2004).

dispersalDispersal can have manifold consequences

for community patterns at multiple spatialscales. First, much like speciation, dispersalis a key contributor to the regional speciespool and, consequently, the various com-munity consequences that it entails (Rick-lefs and Schluter 1993).

From the local habitat perspective, acommon empirical result is that increasing dis-persal into the locality increases species diver-sity. For areas undergoing primary succession,such as Krakatau following its volcanic erup-tion, dispersal is required in order to establisha community and increase diversity (Whittakeret al. 1989). In the field, experimental dispersalvia seed addition into established plant com-munities often results in increased speciesdiversity (Turnbull et al. 2000), and the prox-imity of an island or habitat patch to potentialsources of dispersers often correlates positivelywith local species diversity in a wide range oforganisms (e.g., MacArthur and Wilson 1967).For amphibians in a network of ponds, forinstance, increased connectivity positively influ-enced species turnover, suggesting that dis-persal can affect not only species compositionand diversity, but their temporal rates ofchange as well (Werner et al. 2007a).

Since species vary in their propensity fordispersal, the proximity of a locality to poten-

tial source habitats can also influence speciescomposition, with distant localities contain-ing a preponderance of good dispersers(e.g., Kadmon and Pulliam 1993). With vari-ation in local species composition created bydispersal, either related to locality isolationor stochastic variation, density-dependent se-lection via species interactions can furthermagnify local variation in species composi-tion, as in freshwater communities of zoo-plankton and their insect or fish predators(Shurin 2001).

Dispersal can interact with selection ordrift to influence community patterns atthe regional scale as well as at the localscale. In an experimental metacommunityof protozoans and rotifers, local speciesrichness was maximal at intermediate ratesof dispersal (Cadotte 2006a). The shiftfrom low to moderate dispersal increasesthe rate of addition of new species to local-ities and allows competitively inferior spe-cies to find temporary refuges, whereas theshift from moderate to high dispersal al-lows superior competitors to dominateacross the metacommunity. In the same ex-periment, compositional variability amonglocalities was maintained to the greatest de-gree with low to moderate dispersal, thusmaximizing richness across the entire meta-community (Cadotte 2006a). A meta-analysisof similar experiments found that local diver-sity was generally maximized at intermediatedispersal rates in animal communities, but,at the highest dispersal rates in plants, therewas either a negative effect on regional di-versity or no effect was observed at all (Ca-dotte 2006b). For the pond amphibiansmentioned above, species turnover wasstrongly influenced by both connectivity andenvironmental factors, thus suggesting animportant interaction between dispersal andselection (Werner et al. 2007a,b).

The body of research on the communityconsequences of dispersal and its interac-tion with selection is still comparativelysmall. As with selection, it seems likely that anytheoretically plausible effect of dispersal oncommunity dynamics will be found in someexperimental or natural community, while atthe same time, many hypotheses concerning


the consequences of dispersal will be rejectedin particular systems.

General Patterns and the Pattern-Process Relationship

In this paper, I have argued for a concep-tual organization of community ecologybased on the recognition of four fundamen-tal classes of process. However, research di-rections in community ecology have seldombegun by starting first from principles andthen asking what patterns in nature we ex-pect to see based on the action of elementaryprocesses. More often, patterns are observedin nature, after which explanations are sought.Patterns that have received considerable atten-tion include the distribution of species’ relativeabundances; the relationship between speciesdiversity and area, latitude, elevation, produc-tivity, disturbance, or spatial heterogeneity; therelationship between local and regional speciesdiversity; patterns in connectance, as well asother properties, of food webs; and temporalchanges in species composition during succes-sion (Diamond and Case 1986; Rosenzweig1995; Morin 1999; Ricklefs and Miller 1999).

A major source of debate in communityecology is the fact that most such patterns havemultiple explanations. As such, finding a par-ticular pattern in a given system often revealsvery little about the important processes atwork in that system. Species-area relationshipsprovide an illustrative example. According tothe theory of island biogeography, large islandscontain larger populations of component spe-cies, so the rate of extinction due to drift islower than on smaller islands, thus leading toa greater number of species on large ver-sus small islands (MacArthur and Wilson1967). It is also possible that larger islandsprovide a bigger target for dispersing or-ganisms, such that the rate of immigration,and therefore species richness, is greateron large islands as compared to small ones(Gilpin and Diamond 1976). The environ-mental heterogeneity of an island also tends toscale positively with island area, such that spa-tially variable selection allows more species tocoexist on large rather than small islands(Whittaker and Fernandez-Palacios 2007). Fi-nally, opportunities for speciation may begreater on large islands, thereby contributing

to positive species-area relationships (Lososand Schluter 2000). Thus, drift, dispersal, se-lection, and speciation can all explain or con-tribute to the species-area relationship. Similararguments pertain to other common commu-nity patterns.

As such, perhaps the greatest challenge incommunity ecology is drawing the link be-tween process and pattern. Community ecol-ogists have, in fact, risen impressively to thischallenge, by developing a suite of experi-mental and observational methods to teaseapart the workings of particular communi-ties in particular places, often providing crit-ical guidance to applied management efforts(Simberloff 2004). It is, therefore, fairlystraightforward to study processes at rela-tively small scales, or to document broad-scale community patterns. The “mess” stemsfrom our inability to make general state-ments about process-pattern connections(Lawton 1999; Simberoff 2004). Thus, thereis a kind of black box in community ecology,within which lie the innumerable ways to getfrom process to pattern (Figure 3), and it isdisconcerting to many that when we peerinto the box, what we see seems to be funda-mentally system-specific. Lawton (1999)takes this as a lesson that local experimentalstudies are no longer a fruitful avenue forpursuing generalities in ecology. Alterna-tively, it could be taken as a lesson that seek-ing generalities of the form “pattern X has abroadly applicable explanation in simpletheory Y” or “process Q is always the key to

Figure 3. The Black Box of CommunityEcology

Community ecology has a straightforward set ofprocesses that have created some general patterns innature, but there are innumerable ways to get fromprocess to pattern.


understanding community patterns” isbound to fail in community ecology. Gener-alities of the form “community patterns canbe understood as the outcome of interactingprocesses A, B, and C” seem more likely tohold. This paper is about defining the ABC’sof community ecology in the simplest possi-ble, logically complete way.

Existing Organizational Frameworksin Community Ecology

A number of different frameworks havebeen put forth aimed at the conceptual orga-nization of community ecology, or at least ma-jor parts of community ecology, with which thepresent framework can be compared. Ecologyhas a long history of debates centered aroundwhether or not populations and communitiesreach some kind of equilibrium state—that is,a “balance of nature” (Kingsland 1995). Theconceptual framework presented here is silenton this issue—and, indeed, on any issueregarding what has most often actually hap-pened in nature—but is focused on conceptu-ally organizing the processes that can influencewhat happens in communities, whether theyare at equilibrium or not.

At least three fairly recent conceptual frame-works have gained popularity in the contem-porary literature: equalizing vs. stabilizingmechanisms of coexistence (Chesson 2000),local vs. regional controls on community struc-ture (Ricklefs and Schluter 1993), and themetacommunity concept (Holyoak et al.2005). With respect to models of species coex-istence, Chesson (2000) recognized two funda-mental classes of mechanism: those that equal-ize fitness differences, thereby slowingcompetitive exclusion and possibly enhancingdrift, and those that stabilize coexistence vianegative density dependent selection. Thisframework is reflected in many of the recentefforts at synthesis under the rubric of niche-neutral reconciliation (e.g., Shipley et al. 2006;Adler et al. 2007), and has proven very useful,but its domain is restricted to competitive co-existence and is focused almost entirely on lo-cal selection and drift.

The emphasis on historical and regionalprocesses (Ricklefs and Schluter 1993) wasdeveloped to underscore the importance ofprocesses occurring at broader spatial and

temporal scales than are typically consideredin traditional community ecology—namely,speciation and long-range dispersal. Theframework presented here shares much incommon with the perspective of Ricklefs andSchluter (1993). The graphical representa-tion of their perspective shows regional di-versity determined by input via biotal inter-change and species production, and outputvia mass extinction; local diversity is deter-mined by input via habitat selection and out-put via stochastic extinction, competitive ex-clusion, and predatory exclusion (Figure30.1 in Ricklefs and Schluter 1993:351). Thisperspective is quite similar to a common typeof graphical model that shows a local com-munity as the outcome of a series of filters,including dispersal, the abiotic environment,and biotic interactions (e.g., Morin 1999).The conceptual framework presented heretakes these a step further by recognizing fourdistinct classes of process, within which allothers fall and which thereby allows for amore comprehensive and logically completeframework. For example, biotal interchangeand habitat selection (as used by Ricklefs andSchluter) both fall under dispersal, and com-petition and predation are only two of manydeterministic factors that can exclude spe-cies, all of which fall under selection.

The metacommunity framework explic-itly encompasses drift, selection, and dis-persal (Holyoak et al. 2005). Speciation isnot explicitly excluded, but is, for the mostpart, absent from this framework. Withinthe metacommunity framework, four per-spectives are recognized: neutrality, patchdynamics, species sorting, and mass effects.These correspond loosely to theoreticalconstructs or formalisms around whichpracticing ecologists have self-organized,but, in my opinion, they do not representfundamental, logically distinct classes ofecological process. Mass effects, for exam-ple, include species sorting, and patchdynamics models can be neutral. Themetacommunity perspective also excludesfrom its purview community dynamics thatdo not involve dispersal as a key compo-nent. For these reasons, the present frame-work is distinct from the metacommunity


perspective, although metacommunity mod-els fit comfortably within it.

In addition to these three conceptualframeworks specifically focused on communityecology, two highly influential theoreticalframeworks that cut across sub-fields of biol-ogy, but with some connections to communityecology, are worth mentioning: the metabolictheory of ecology (Brown et al. 2004) and eco-logical stoichiometry (Sterner and Elser 2002).In simple terms, these two approaches explorethe consequences of considering organisms es-sentially as physical entities that process energyoptimally given their size (metabolic theory),or that interact with their environment basedlargely on their chemical composition (stoichi-ometry). In my opinion, these frameworksare most powerful in aiding our under-standing of the functioning of individualorganisms or the fluxes of energy andchemicals in whole ecosystems. The contri-butions of these frameworks to communityecology, such as predictions concerning theeffect of temperature on species diversity (met-abolic theory) or of plant-herbivore interac-tions (stoichiometry), fall comfortably withinthe present framework, usually as mechanismsunderlying selection.

implicationsThe first goal of this paper was to orga-

nize the material of community ecology ina logically consistent way in order to clarifythe similarities and differences among var-ious conceptual constructs in the disci-pline. One motivation was the commoncriticism that ecologists tend to repeatedlyreinvent the wheel: we claim ideas as newthat are only subtly distinct, or not distinctat all, from ideas put forth long ago (Law-ton 1991; Graham and Dayton 2002; Be-lovsky et al. 2004). There are likely manyreasons for this, but one important reason,at least in community ecology, may be thelack of a coherent framework within whichparticular perspectives or theories can bedescribed and related. As such, a plethoraof terms, each of which sounds new anddifferent, is often used to communicatemuch the same thing—such as niche pro-cesses, species interactions, or species sort-ing all being used to describe selection. It

does not matter whether selection is thebest term for deterministic fitness differ-ences among species, but it is critical torecognize that different mechanisms un-derlying selection, such as competition orpredation, share more in common withone another than either does with drift,dispersal, or speciation.

Recognizing how different theoreticaltraditions in community ecology relate toone another based on fundamental, logi-cally distinct categories of process can po-tentially prevent students from concludingfrom a Web of Science search that researchon species sorting or metacommunitiesgoes back no more than 15–20 years. Wemight also make more modest—and, I be-lieve, realistic—assessments of the degreeto which popular areas of research trulyrepresent new paradigms or, more likely,incremental advances on previous work.Placing ecological ideas in their full histor-ical context can curtail wheel reinventionand thus help to advance and expand eco-logical understanding in the long term(Graham and Dayton 2002).

My hope is that the present framework willbe useful to practicing community ecologistsas a way to place their research in a process-based context. I also think that this concep-tual framework can potentially be of greatuse in teaching and communicating the sub-ject matter of community ecology to abroader audience. As argued in the intro-duction, the traditional presentation of com-munity ecology can be confusing becausethe common threads among topics such asfood webs, competitive coexistence, and is-land biogeography are quite difficult to dis-cern. The essential similarities and differ-ences among these theoretical traditions canbe seen quite clearly in the present frame-work (Table 2). The core subject matter incommunity ecology need not change, but Ibelieve there can be great benefit to shiftingthe emphasis away from an organizationalstructure based on the useful lines of inquirycarved out by researchers, to one based onthe fundamental processes that underliecommunity dynamics and patterns.

The second goal of this paper was to artic-ulate a general theory of community ecol-


ogy. Such a theory might seem so general-ized as to be of little use, but the utility of theModern Synthesis in evolutionary biology—warts and all (Pigliucci 2007)—suggests oth-erwise. In essence, the Modern Synthesis canbe summarized as positing that genetic vari-ation is created in populations via mutationand immigration, and is then shaped by driftand natural selection to drive evolutionarychange (Kutschera and Niklas 2004). Thefact that the all-important mechanism of he-redity was essentially unknown until the re-discovery of Mendel made the constructionof the Modern Synthesis a profound scien-tific achievement in a way that cannot bematched in community ecology, where the

important rule of heredity is decidedly facile:elephants give rise to elephants and daffodilsto daffodils. However, on its own, the Mod-ern Synthesis makes no predictions aboutexactly how processes will interact to deter-mine evolutionary change in any particularsituation; rather, it simply establishes the fun-damental set of processes that may be atwork.

We can likewise articulate a very generaltheory of community ecology: species areadded to communities via speciation anddispersal, and the relative abundances ofthese species are then shaped by drift andselection, as well as ongoing dispersal, todrive community dynamics (Figure 4). The

Figure 4. The Theory of Community EcologySelection, drift, speciation, and dispersal interact to determine community dynamics across spatial scales.

The delineation of discrete spatial scales is arbitrary, and used only for clarity of presentation. Figure modifiedfrom Vellend and Orrock (2009).


precise way in which these processes inter-act to determine community dynamics var-ies tremendously from case to case, just asthe processes that determine evolutionarychange interact in ways that vary tremen-dously in each case. Stating a general theoryof community ecology in this way echoes theperspective of Ricklefs and Schluter (1993),and I believe that recognizing this perspec-tive as the community ecology counterpartto the evolutionary Modern Synthesis high-lights an important sense in which commu-nity ecology already has a general theoreticalframework that is every bit as robust as thatof population genetics. The oft-cited recalci-trance of community ecology to generallyapplicable theory (e.g., Lawton 1999) seemslike a fair assessment if the goal is to be able

to make general predictions about how par-ticular processes have shaped real ecologi-cal communities. If the goal is to makegeneral statements about the fundamentalprocesses that can underlie community dy-namics and the possible ways in whichthese can interact, then community ecol-ogy appears to be in excellent shape.

acknowledgmentsValuable feedback and insights on the topic of thismanuscript or on the manuscript itself were provided byJ. Goheen, C. Harley, R. Holt, J. Levine, J. Losos, J.Orrock, R. Ricklefs, J. Roughgarden, J. Shurin, D. Sriv-astava, M. Whitlock, A. Agrawal, J. Wiens, the UBC Com-munity Ecology class of 2008, and two anonymous re-viewers. This work was supported by the NaturalSciences and Engineering Research Council, Canada.

REFERENCES

Aarssen L. W., Schamp B. S. 2002. Predicting distri-butions of species richness and species size in re-gional floras: applying the species pool hypothesisto the habitat templet model. Perspectives in PlantEcology, Evolution and Systematics 5:3–12.

Adler P. B., HilleRisLambers J., Kyriakidis P. C., GuanQ., Levine J. M. 2006. Climate variability has astabilizing effect on coexistence of prairie grasses.Proceedings of the National Academy of Sciences USA103(34):12793–12798.

Adler P. B., HilleRisLambers J., Levine J. M. 2007. Aniche for neutrality. Ecology Letters 10:95–104.

Allen T. F. H., Hoekstra T. W. 1992. Toward a UnifiedEcology. New York: Columbia University Press.

Bell G. 2008. Selection: The Mechanism of Evolution. Ox-ford (UK): Oxford University Press.

Belovsky G. E., Botkin D. B., Crowl T. A., CumminsK. W., Franklin J. F., Hunter M. L., Jr., Joern A.,Lindenmayer D. B., MacMahon J. A., Margules C. R.,Scott J. M. 2004. Ten suggestions to strengthen thescience of ecology. BioScience 54(4):345–351.

Beninca E., Huisman J., Heerkloss R., Jöhnk K. D.,Branco P., Van Nes E. H., Scheffer M., Ellner S. P.2008. Chaos in a long-term experiment with aplankton community. Nature 451(7180):822–825.

Brown J. H. 1995. Macroecology. Chicago (IL): ChicagoUniversity Press.

Brown J. H., Gillooly J. F., Allen A. P., Savage V. M.,West G. B. 2004. Toward a metabolic theory ofecology. Ecology 85(7):1771–1789.

Cadotte M. W. 2006a. Metacommunity influences oncommunity richness at multiple spatial scales: amicrocosm experiment. Ecology 87(4):1008–1016.

Cadotte M. W. 2006b. Dispersal and species diversity: ameta-analysis. American Naturalist 167(6):913–924.

Cadotte M. W., Mai D. V., Jantz S., Collins M. D., KeeleM., Drake J. A. 2006. On testing the competition-colonization tradeoff in a multispecies assemblage.American Naturalist 168(5):704–709.

Caswell H. 1978. Predator mediated coexistence: anonequilibrium model. American Naturalist 112:127–154.

Chase J. M., Leibold M. A. 2003. Ecological Niches:Linking Classical and Contemporary Approaches. Chi-cago (IL): University of Chicago Press.

Chesson P. 1978. Predator-prey theory and variability.Annual Review of Ecology and Systematics 9:323–347.

Chesson P. 2000. Mechanisms of maintenance of spe-cies diversity. Annual Review of Ecology and System-atics 31:343–366.

Chesson P. L., Warner R. R. 1981. Environmental vari-ability promotes species coexistence in lottery com-petitive systems. American Naturalist 117:923–943.

Connell J. H. 1961. The influence of interspecific compe-tition and other factors on the distribution of the bar-nacle Chthamalus stellatus. Ecology 42:710–723.

Cooper G. J. 2003. The Science of the Struggle for Existence:On the Foundations of Ecology. Cambridge (UK): Cam-bridge University Press.

Cottenie K. 2005. Integrating environmental and spa-tial processes in ecological community dynamics.Ecology Letters 8:1175–1182.

Darwin C. 1859. On the Origin of Species by Means ofNatural Selection, or the Preservation of Favoured Racesin the Struggle for Life. London (UK): John Murray.

Dent C. L., Cumming G. S., Carpenter S. R. 2002.Multiple states in river and lake ecosystems. Philo-


sophical Transactions of the Royal Society of London,Series B 357(1421):635–645.

Descamps-Julien B., Gonzalez A. 2005. Stable coexist-ence in a fluctuating environment: an experimen-tal demonstration. Ecology 86(10):2815–2824.

Diamond J. M. 1975. Assembly of species communi-ties. Pages 342–444 in Ecology and Evolution of Com-munities, edited by M. L. Cody and J. M. Diamond.Cambridge (MA): Harvard University Press.

Diamond J. M., Case T. J. 1986. Community Ecology.New York: Harper and Row.

Drake J. A. 1991. Community-assembly mechanics andthe structure of an experimental species ensemble.American Naturalist 137(1):1–26.

Fauth J. E., Resetarits W. J., Jr., Wilbur H. M. 1990.Interactions between larval salamanders: a case ofcompetitive equality. Oikos 58:91–99.

Fussmann G. F., Ellner S. P., Shertzer K. W., HairstonN. G., Jr. 2000. Crossing the Hopf bifurcation in alive predator-prey system. Science 290(5495):1358–1360.

Gause G. F. 1934. The Struggle for Existence. Baltimore(MD): Williams and Wilkins Company.

Gilpin M. E., Diamond J. M. 1976. Calculation of immigra-tion and extinction curves from the species-area-distance relation. Proceedings of the National Academy ofSciences USA 73(11):4130–4314.

Goldberg D. E., Werner P. A. 1983. Equivalence ofcompetitors in plant communities: a null hypoth-esis and a field experimental approach. AmericanJournal of Botany 70:1098–1104.

Graham M. H., Dayton P. K. 2002. On the evolution ofecological ideas: paradigms and scientific progress.Ecology 83:1481–1489.

Grime J. P. 1973. Competitive exclusion in herba-ceous vegetation. Nature 242:344–347.

Hartl D. L., Clark A. G. 1997. Principles of PopulationGenetics. Third Edition. Sunderland (MA): SinauerAssociates.

Holyoak M., Leibold M. A., Holt R. D. 2005. Metacom-munities: Spatial Dynamics and Ecological Communi-ties. Chicago (IL): University of Chicago Press.

Hubbell S. P. 2001. The Unified Neutral Theory of Bioge-ography and Biodiversity. Princeton (NJ): PrincetonUniversity Press.

Hubbell S. P. 2005. Neutral theory in communityecology and the hypothesis of functional equiva-lence. Functional Ecology 19:166–172.

Huffaker C. B. 1958. Experimental studies on preda-tion: dispersion factors and predator-prey oscilla-tions. Hilgardia 27:343–383.

Hughes A. R., Inouye B. D., Johnson M. T. J., Under-wood N., Vellend M. 2008. Ecological consequencesof genetic diversity. Ecology Letters 11(6):609–623.

Hu X.-S., He F., Hubbell S. P. 2006. Neutral theory inmacroecology and population genetics. Oikos 113(3):548–556.

John R., Dalling J. W., Harms K. E., Yavitt J. B., Stal-lard R. F., Mirabello M., Hubbell S. P., Valencia R.,Navarrete H., Vallejo M., Foster R. B. 2007. Soilnutrients influence spatial distributions of tropicaltree species. Proceedings of the National Academy ofSciences USA 104(2):864–869.

Kadmon R., Pulliam H. R. 1993. Island biogeography:effect of geographical isolation on species compo-sition. Ecology 74(4):977–981.

Kingsland S. E. 1995. Modeling Nature: Episodes in theHistory of Population Ecology. Second Edition. Chi-cago (IL): University of Chicago Press.

Krebs C. J., Boonstra R., Boutin S., Sinclair A. R. E.2001. What drives the 10-years cycle of snowshoehares? BioScience 51(1):25–35.

Kutschera U., Niklas K. J. 2004. The modern theory ofbiological evolution: an expanded synthesis. Natur-wissenschaften 91:255–276.

Lawton J. H. 1991. Warbling in different ways. Oikos60:273–274.

Lawton J. H. 1999. Are there general laws in ecology?Oikos 84(2):177–192.

Lerner I. M., Dempster E. R. 1962. Indeterminism ininterspecific competition. Proceedings of the NationalAcademy of Sciences USA 48(5):821–826.

Levene H. 1953. Genetic equilibrium when morethan one ecological niche is available. AmericanNaturalist 87:331–333.

Levine J. M., Rees M. 2002. Coexistence and relativeabundance in annual plant communities: the rolesof competition and colonization. American Naturalist160:452–467.

Lewontin R. 2004. The problems of population ge-netics. Pages 5–23 in Evolutionary Genetics: from Mol-ecules to Morphology, edited by R. S. Singh and C. B.Krimbas. Cambridge (UK): Cambridge UniversityPress.

Loreau M., Hector A. 2001. Partitioning selection andcomplementarity in biodiversity experiments. Na-ture 412(6842):72–76.

Losos J. B., Schluter D. 2000. Analysis of an evolutionaryspecies-area relationship. Nature 408(6814):847–850.

Lotka A. J. 1925. Elements of Physical Biology. Baltimore(MD): Williams and Wilkins.

MacArthur R. H. 1969. Patterns of communities inthe tropics. Biological Journal of the Linnean Society1(1–2):19–30.

MacArthur R. H., Wilson E. O. 1967. The Theory ofIsland Biogeography. Princeton (NJ): Princeton Uni-versity Press.

McGill B. J., Enquist B. J., Weiher E., Westoby M.2006. Rebuilding community ecology from func-tional traits. Trends in Ecology and Evolution 21(4):178–185.

McKinney M. L. 1997. Extinction vulnerability andselectivity: combining ecological and paleontolog-


ical views. Annual Review of Ecology and Systematics28:495–516.

McPeek M. A. 2007. The macroevolutionary conse-quences of ecological differences among species.Paleontology 50:111–129.

McPeek M. A., Gomulkiewicz R. 2005. Assemblingand depleting species richness in metacommuni-ties: insights from ecology, population geneticsand macroevolution. Pages 355–373 in Metacom-munities: Spatial Dynamics and Ecological Communi-ties, edited by M. Holyoak et al. Chicago (IL):University of Chicago Press.

Mertz D. B., Cawthon D. A., Park T. 1976. An exper-imental analysis of competitive indeterminacy inTribolium. Proceedings of the National Academy of Sci-ences USA 73(4):1368–1372.

Morin P. J. 1999. Community Ecology. Oxford (UK) andMalden (MA): Blackwell.

Norberg J., Swaney D. P., Dushoff J., Lin J., Casagrandi R.,Levin S. A. 2001. Phenotypic diversity and ecosystemfunctioning in changing environments: a theoreticalframework. Proceedings of the National Academy of SciencesUSA 98(20):11376–11381.

Nowak M. A. 2006. Evolutionary Dynamics: Exploring theEquations of Life. Cambridge (MA): Belknap Pressof Harvard University Press.

Palmer M. W. 1994. Variation in species richness:towards a unification of hypotheses. Folia Geobo-tanica et Phytotaxonomica 29:511–530.

Park T. 1948. Experimental studies of interspeciescompetition. I. Competition between populationsof the flour beetles, Tribolium confusum Duval andTribolium castaneum Herbst. Ecological Monographs18(2):265–308.

Partel M. 2002. Local plant diversity patterns andevolutionary history at the regional scale. Ecology83(9):2361–2366.

Pigliucci M. 2007. Do we need an extended evolution-ary synthesis? Evolution 61(2):2743–2749.

Provine W. B. 1971. The Origins of Theoretical PopulationGenetics. Chicago (IL): University of Chicago Press.

Putman R. J. 1994. Community Ecology. New York: Chap-man and Hall.

Qian H., Ricklefs R. E. 2000. Large-scale processesand the Asian bias in species diversity of temperateplants. Nature 407(6801):180–182.

Rice S. H. 2008. A stochastic version of the Priceequation reveals the interplay of deterministic andstochastic processes in evolution. BMC Evolution-ary Biology 8:262.

Ricklefs R. E. 1987. Community diversity: relative roles oflocal and regional processes. Science 235(4785):167–171.

Ricklefs R. E. 2004. A comprehensive framework forglobal patterns in biodiversity. Ecology Letters 7:1–15.

Ricklefs R. E. 2008. Disintegration of the ecologicalcommunity. American Naturalist 172:741–750.

Ricklefs R. E., Miller G. L. 1999. Ecology. Fourth Edi-tion. New York: W.H. Freeman.

Ricklefs R. E., Qian H., White P. S. 2004. The regioneffect on mesoscale plant species richness betweeneastern Asia and eastern North America. Ecography27:129–136.

Ricklefs R. E., Schluter D. 1993. Species Diversity inEcological Communities: Historical and GeographicalPerspectives. Chicago (IL): University of ChicagoPress.

Rosenzweig M. L. 1995. Species Diversity in Space and Time.Cambridge (UK): Cambridge University Press.

Roughgarden J. 2009. Is there a general theory ofcommunity ecology? Biology and Philosophy 24(4):521–529.

Scheffer M., Carpenter S., Foley J. A., Folke C., WalkerB. 2001. Catastrophic shifts in ecosystems. Nature413:591–596.

Schröder A., Persson L., De Roos A. M. 2005. Directexperimental evidence for alternative stable states:a review. Oikos 110(1):3–19.

Shipley B., Vile D., Garnier E. 2006. From plant traitsto plant communities: a statistical mechanistic ap-proach to biodiversity. Science 314(5800):812–814.

Shurin J. B. 2001. Interactive effects of predation anddispersal on zooplankton communities. Ecology 82:3404–3416.

Siepielski A. M., Hung K.-L., Bein E. E., McPeek M. A.2010. Experimental evidence for neutral commu-nity dynamics governing and insect assemblage.Ecology 91:847–857.

Simberloff D. 2004. Community ecology: is it time tomove on? American Naturalist 163:787–799.

Srivastava D. S. 1999. Using local-regional richnessplots to test for species saturation: pitfalls andpotentials. Journal of Animal Ecology 68:1–17.

Sterner R. W., Elser J. J., Vitousek P. 2002. EcologicalStoichiometry: The Biology of Elements from Molecules to theBiosphere. Princeton (NJ): Princeton University Press.

Strauss S. Y. 1991. Indirect effects in community ecol-ogy: their definition, study and importance. Trendsin Ecology and Evolution 6(7):206–210.

Strong D. R., Simberloff D., Abele L. G., Thistle A. B.1984. Ecological Communities: Conceptual Issues and theEvidence. Princeton (NJ): Princeton University Press.

Taylor D. R., Aarssen L. W., Loehle C. 1990. On therelationship between r/K selection and environ-mental carrying capacity: a new habitat templetfor plant life history strategies. Oikos 58:239–250.

Tilman D. 1977. Resource competition between plank-ton algae: an experimental and theoretical ap-proach. Ecology 58(2):338–348.

Tilman D. 1982. Resource Competition and CommunityStructure. Princeton (NJ): Princeton University Press.

Tilman D. 1988. Plant Strategies and the Dynamics andStructure of Plant Communities. Princeton (NJ):Princeton University Press.


Tilman D. 1994. Competition and biodiversity in spa-tially structured habitats. Ecology 75(1):2–16.

Tilman D. 2004. Niche tradeoffs, neutrality, and com-munity structure: a stochastic theory of resourcecompetition, invasion, and community assembly.Proceedings of the National Academy of Sciences USA101(30):10854–10861.

Turnbull L. A., Crawley M., Rees M. 2000. Are plantpopulations seed-limited? A review of seed sowingexperiments. Oikos 88(2):225–238.

Van Zandt P. A., Agrawal A. A. 2004. Specificity of inducedplant responses to specialist herbivores of the commonmilkweed Asclepias syriaca. Oikos 104(2):401–409.

Vellend M., Geber M. A. 2005. Connections betweenspecies diversity and genetic diversity. Ecology Let-ters 8:767–781.

Vellend M., Orrock J. L. 2009. Genetic and ecologicalmodels of diversity: lessons across disciplines. Pages439–461 in The Theory of Island Biogeography Revisited,edited by J. B. Losos and R. E. Ricklefs. Princeton(NJ): Princeton University Press.

Werner E. E., Skelly D. K., Relyea R. A., Yurewicz K. L.2007b. Amphibian species richness across environ-mental gradients. Oikos 116(10):1697–1712.

Werner E. E., Yurewicz K. L., Skelly D. K., Relyea R. A.2007a. Turnover in an amphibian metacommu-

nity: the role of local and regional factors. Oikos116:1713–1725.

Whittaker R. H. 1975. Communities and Ecosystems. NewYork: MacMillan Company.

Whittaker R. J., Bush M. B., Richards K. 1989. Plantrecolonization and vegetation succession on theKrakatau Islands, Indonesia. Ecological Monographs59(2):59–123.

Whittaker R. J., Fernandez-Palacios J. M. 2007. IslandBiogeography: Ecology, Evolution and Conservation.Second Edition. Oxford (UK): Oxford UniversityPress.

Wiens J. J., Parra-Olea G., Garcıa-Parıs M., Wake D. B.2007. Phylogenetic history underlies elevationalbiodiversity patterns in tropical salamanders. Pro-ceedings of the Royal Society of London, Series B 274:919–928.

Williams J. W., Shuman B. N., Webb T, III, BartleinP. J., Leduc P. L. 2004. Late Quaternary vegetationdynamics in North America: scaling from taxa tobiomes. Ecological Monographs 74(2):309–334.

Wright S. 1940. Breeding structure of populations inrelation to speciation. American Naturalist 74:232–248.

Associate Editor: Anurag Agrawal


conceptual synthesis in community ecologymvellend.recherche.usherbrooke.ca/vellend... · conceptual...

Documents