Article

ecolottery: Simulating and assessing community assembly with environmental filtering and neutral dynamics in R

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Abstract

- We introduce the R package ecolottery dedicated to quick and efficient simulation of communities undergoing local neutral dynamics with environmentally filtered immigration from a reference species pool (spatially-implicit model). The package includes an Approximate Bayesian Computation (ABC) tool to estimate the parameters of these processes. We present the rationale of the approach and show examples of simulations and ABC analysis. - The species in the reference pool differ in their abundances and trait values. Environmental filtering weights the probability of immigration success depending on trait values, while the descendants of established immigrants undergo neutral stochastic drift. The reference pool can be defined in a flexible way as representing, e.g., the composition of a broad biogeographical region, or available dispersers around local communities. The package provides a process-based alternative to the use of randomization-based null models. - The package proposes a coalescent-based simulation algorithm that presents significant advantages over alternative algorithms. It does not require simulating community dynamics from an initial state forward in time but does still allow measurement of the influence of environmental filtering. Because of its high calculation speed, this approach allows simulating many communities within a reasonable amount of time. - Diverse patterns of taxonomic, functional and phylogenetic compositions can be generated. The package can be used to explore the outcome of ecological and evolutionary processes playing at local and regional scales, and to estimate the parameters of these processes based on observed patterns.

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... To represent the influence of regional species frequencies on local assembly through immigration dynamics, we consider a continent-island metacommunity model so that immigration pressure in communities depends on species regional frequency, which, combined with local environmental filtering, determines local species abundances (Munoz et al. 2014, Munoz et al. 2018. We attribute a trait value to each immigrant reflecting its adaptation to the local environment. ...
... We characterized the properties of local trait distributions and examined traitabundance relationships in communities over a continuum of situations from strictly neutral to strong environmental filtering (Gravel et al. 2006), and for distinct types of filtering. We simulated communities using quick and efficient coalescent-based modeling of immigration, trait-based filtering and local demography as described in Munoz et al. (2018) (Fig. 1b, top). We assessed the relative influence of three basic filtering types on the first four moments of the local trait distribution. ...
... We simulated both deterministic environmental filtering and stochastic demographic dynamics in communities related to a regional pool providing the immigrants (Fig. 1, Munoz et al. 2018). The modelling framework is individual-based: immigrant individuals are drawn from the pool, and the death and replacement dynamics of individuals is simulated within communities. ...
Article
A major objective in ecology is to determine how local species abundances relate to their functional trait values (i.e., trait-abundance relationship), under a combined influence of (i) environmental filters affecting local species performance conditionally to trait values, (ii) neutral demographic and immigration dynamics affecting abundances independently from these trait values, and (iii) varying availability and frequency of species at regional level. We examined the nature and strength of the trait-abundance relationship in 30,000 simulated communities covering a gradient of the relative importance of niche-based environmental filtering and neutral stochastic processes, with heterogeneous regional species frequencies. We explored scenarios of directional, stabilizing and disruptive filtering differently affecting the success of species in communities, depending on their relative trait values. We evaluated how the four first moments of the trait distribution in a local community (i.e. abundance-weighted mean, variance, skewness and kurtosis) were influenced by immigration, environmental filtering and neutral dynamics. Then we determined whether including constraints related to these moments in a Bayesian maximum entropy regression improved the prediction of the trait-abundance relationships. First, we found pervasive influence of regional frequencies on local species abundances, related to regular input of immigrants. Second, the first four moments of the local trait distribution were affected by environmental filtering, the shape of the response depending on the type of filtering. Third, with decreasing immigration rate, the imprint of local demographic stochasticity overrode the impact of environmental filtering on trait-abundance relationships. Lastly, accounting for the mean and variance of local trait distribution appeared sufficient to explain the trait-abundance relationships in our regression framework, although their contribution differed depending on the type of environmental filtering. Therefore, the mean and variance of trait values in communities, two pillars of trait-gradient analyses in functional ecology, can capture the key influence of environmental filtering on local trait-abundance relationships.
... Extensive process-based simulation of community dynamics has proved helpful to disentangle the respective influences of stochastic and trait-based assembly processes on diversity patterns (Jabot et al. 2008, Zurell et al. 2010, Munoz et al. 2018, Denelle et al. 2019. Indeed, community functional composition should reflect the imprint of environmental filtering (McGill et al. 2006), while taxonomic diversity should better capture the influence of stochastic immigration-extinction dynamics (Munoz et al. 2007). ...
... Indeed, community functional composition should reflect the imprint of environmental filtering (McGill et al. 2006), while taxonomic diversity should better capture the influence of stochastic immigration-extinction dynamics (Munoz et al. 2007). Comparing community composition simulated under various immigration rates and environmental filters to an observed community pattern allows to explicitly infer the contribution of these processes to community assembly (Zurell et al. 2010, Munoz et al. 2018. ...
... Here, we investigated the influence of habitat loss and fragmentation on tree community assembly in New-Caledonia's highly threatened tropical dry forest (Gillespie and Jaffré 2003), with two main purposes: 1) deciphering the respective contributions of neutral and niche-based assembly processes, and 2) identifying different tempos of their influence on diversity patterns. We characterized functional and taxonomic composition of 100 observed tree communities, and inferred plausible contributions of neutral and traitbased processes with intensive coalescent-based simulations and approximate Bayesian computation (Munoz et al. 2018). We examined how estimated parameters were related to past and present landscape structure, in terms of distance to edge, patch area and habitat amount surrounding communities. ...
Article
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The impact of rapid habitat loss and fragmentation on biodiversity is a major issue. However, we still lack an integrative understanding of how these changes influence biodiversity dynamics over time. In this study, we investigate the effects of these changes in terms of both niche-based and neutral dynamics. We hypothesize that habitat loss has delayed effects on neutral immigration-extinction dynamics, while edge effects and environmental heterogeneity in habitat patches have rapid effects on niche-based dynamics. We analyzed taxonomic and functional composition of 100 tree communities in a tropical dry forest landscape of New-Caledonia subject to habitat loss and fragmentation. We designed an original, process-based simulation framework, and performed Approximate Bayesian Computation to infer the influence of niche-based and neutral processes. Then, we performed partial regressions to evaluate the relationships between inferred parameter values of communities and landscape metrics (distance to edge, patch area, and habitat amount around communities), derived from either recent or past (65 yrs ago) aerial photographs, while controlling for the effect of soil and topography. We found that landscape structure influences both environmental filtering and immigration. Immigration rate was positively related to past habitat amount surrounding communities. In contrast, environmental filtering was mostly affected by present landscape structure and mainly influenced by edge vicinity and topography. Our results highlight that landscape changes have contrasting spatio-temporal influences on niche-based and neutral assembly dynamics. First, landscape-level habitat loss and community isolation reduce immigration and increase demographic stochasticity, resulting in slow decline of local species diversity and extinction debt. Second, recent edge creation affects environmental filtering, incurring rapid changes in community composition by favoring species with edge-adapted strategies. Our study brings new insights about temporal impacts of landscape changes on biodiversity dynamics. We stress that landscape history critically influences these dynamics and should be taken into account in conservation policies.
... (Etienne, 2007). The second null model, suggested by Munoz et al. (2018), used the I calculated parameter and the known pool of species abundances, either for the regional or local level. We calculated 4,999 sets of 16 communities in a regional and in local basis using the R function 'coalesc' from the R package 'ecolottery' (Munoz et al., 2018). ...
... The second null model, suggested by Munoz et al. (2018), used the I calculated parameter and the known pool of species abundances, either for the regional or local level. We calculated 4,999 sets of 16 communities in a regional and in local basis using the R function 'coalesc' from the R package 'ecolottery' (Munoz et al., 2018). ...
... By contrast, species associations were mainly found across species at the same sites, in accordance with the assumption that biotic interactions occur at a lower spatial scale (Munoz et al., 2018). This demonstrates the importance of spatial scales for generating null hypotheses, and future studies should therefore consider this when designing sampling strategies. ...
Article
Aim: Plant community assembly in tropical rain forest has been shown to be largely governed by stochastic processes, but as arbuscular mycorrhizal (AM) fungi display limited host preference, they may not follow the same stochastic assembly pattern. Here, we determined the relative importance of environmental and spatial drivers responsible for the community assembly process of AM fungi in two types of tropical rain forest: semideciduous rain forest and dense ombrophilous forests. Location: Atlantic rain forest in north‐eastern Brazil, South America. Taxon: Arbuscular mycorrhizal fungi (Glomeromycotina). Methods: We collected root samples from eight protected areas of Atlantic forest along a 700 km transect in north‐eastern Brazil. We measured the relative impor‐ tance of deterministic and stochastic processes by redundancy analysis (RDA) and variation partitioning in comparison with null expectations using ad hoc generated neutral communities. Furthermore, we accessed species associations from co‐occur‐ rence data, at different scales using a Bayesian approach of Hierarchical Modelling of Species Communities. Results: Overall, the extent to which stochastic and deterministic processes affected community assembly depended on the forest type and the spatial scale. Specifically, we found that abiotic and biotic predictors of AM fungal community assemblages are related to environmental homogeneity in tropical rain forests. Main conclusions: The results of the study show that dynamics in community assem‐ bly was clearly different between the two forest types, and that the difference most likely is due to differences in responses to environmental variables.
... Several approaches have implemented model-based inference procedures for community assembly already (Munoz et al., 2018;Pontarp, Brännström, & Petchey, 2019;van der Plas et al., 2015), paving the way to measuring the relative impact of different processes on community assembly. However, we still lack a method that integrates both phylogenetic and phenotypic information in a species-based model where the strength of the non-neutral processes can be estimated. ...
... We acknowledge that while these assembly processes are often happening simultaneously in nature, when investigating a targeted trait hypothesized to play a role in the non-neutral assembly of a particular community, the model selection inference procedure holds power to detect the most conspicuous process, if applicable. We are using both model selection approaches because, though RF has been used for model selection in other contexts, it has not been used to distinguish between community assembly models like ABC has (Munoz et al., 2018;Pontarp et al., 2019;van der Plas et al., 2015); thus, we document a comparison and collaboration of the two approaches here. ...
... While we feel CAMI will continue to make progress in advancing our understand of community ecological patterns globally, there are still many aspects of community ecological theory yet to be incorporated (Belyea & Lancaster, 1999;Weiher et al., 2011). The assembly models defined here could be made more powerful by considering other community dynamics such speciation, colonization, and extinction during the assembly process (Rosindell & Harmon, 2013), as well as co-occurring and structured non-neutral processes (Keddy & Shipley, 1989) where the relative importance of these processes can be measured (as in Munoz et al., 2018;van der Plas et al., 2015). ...
Article
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Ecologists often use dispersion metrics and statistical hypothesis testing to infer processes of community formation such as environmental filtering, competitive exclusion, and neutral species assembly. These metrics have limited power in inferring assembly models because they rely on often‐violated assumptions. Here, we adapt a model of phenotypic similarity and repulsion to simulate the process of community assembly via environmental filtering and competitive exclusion, all while parameterizing the strength of the respective ecological processes. We then use random forests and approximate Bayesian computation to distinguish between these models given the simulated data. We find that our approach is more accurate than using dispersion metrics and accounts for uncertainty in model selection. We also demonstrate that the parameter determining the strength of the assembly processes can be accurately estimated. This approach is available in the R package CAMI; Community Assembly Model Inference. We demonstrate the effectiveness of CAMI using an example of plant communities living on lava flow islands. Using an adapted model of phenotypic similarity and repulsion, we are able to simulate the process of community assembly via environmental filtering and competitive exclusion, all while parameterizing the strength of the respective assembly processes. We then use approximate model selection approaches to distinguish between assembly models and estimate the strength of non‐neutral assembly processes.
... Ecological opportunity, competition for such opportunity, and the diversification process thus affect both phylogenetic and trait patterns in emerging communities. Furthermore, theoretical studies that aim to improve our understanding, as well as our ability to estimate various assembly processes, are receiving increasing attention [10][11][12][13][14] . Several of these studies also identify competition as a major component of community assembly. ...
... The results presented here certainly suggest caution in the way community patterns are interpreted, especially if eco-evolutionary processes are suspected to be active. It will be intriguing to follow how future inference methods may develop to tackle the challenge of using functional resource trait-and phylogenetic patterns to infer interacting ecological and evolutionary assembly processes 11,12,14,25,54 . ...
Article
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It is well known that ecological and evolutionary processes act in concert while shaping biological communities. Diversification can, for example, arise through ecological opportunity and adaptive radiations and competition play an essential role in such diversification. Eco-evolutionary components of competition are thus important for our understanding of community assembly. Such understanding in turn facilitates interpretation of trait- and phylogenetic community patterns in the light of the processes that shape them. Here, I investigate the link between competition, diversification, and trait- and phylogenetic- community patterns using a trait-based model of adaptive radiations. I evaluate the paradigm that competition is an ecological process that drives large trait- and phylogenetic community distances through limiting similarity. Contrary to the common view, I identify low or in some cases counterintuitive relationships between competition and mean phylogenetic distances due to diversification late in evolutionary time and peripheral parts of niche space when competition is weak. Community patterns as a function of competition also change as diversification progresses as the relationship between competition and trait similarity among species can flip from positive to negative with time. The results thus provide novel perspectives on community assembly and emphasize the importance of acknowledging eco-evolutionary processes when interpreting community data.
... To investigate the performance of FEE in discriminating among community assembly processes, we generated artificial communities according to three different assembly processes (neutral, niche filtering, and limiting similarity), and we evaluated the capacity of FEE and some other indices to correctly diagnose the assembly processes. We used the R package "ecolottery" (Munoz et al., 2018) to create these artificial communities by simulating community dynamics from random initial compositions. We generated 10,000 independent species pools and their initial compositions in onedimensional trait space. ...
... An initial community was generated from each pool by randomly selecting 30 species, each with an initial abundance of 5 individuals. Starting from each of these 10,000 initial conditions, we used the "forward" function in the "ecolottery" R package (Munoz et al., 2018) index and the three assembly processes. The expected rank order of functional diversity among the three processes is limiting similarity > neutral assembly > niche filtering (Mouchet et al., 2010). ...
Article
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Most existing functional diversity indices focus on a single facet of functional diversity. Although these indices are useful for quantifying specific aspects of functional diversity, they often present some conceptual or practical limitations in estimating functional diversity. Here, we present a new functional extension and evenness (FEE) index that encompasses two important aspects of functional diversity. This new index is based on the straightforward notion that a community has high diversity when its species are distant from each other in trait space. The index quantifies functional diversity by evaluating the overall extension of species traits and the interspecific differences of a species assemblage in trait space. The concept of minimum spanning tree (MST) of points was adopted to obtain the essential distribution properties for a species assembly in trait space. We combined the total length of MST branches (extension) and the variation of branch lengths (evenness) into a raw FEE0 metric and then translated FEE0 to a species richness‐independent FEE index using a null model approach. We assessed the properties of FEE and used multiple approaches to evaluate its performance. The results show that the FEE index performs well in quantifying functional diversity and presents the following desired properties: (a) It allows a fair comparison of functional diversity across different species richness levels; (b) it preserves the essence of single‐facet indices while overcoming some of their limitations; (c) it standardizes comparisons among communities by taking into consideration the trait space of the shared species pool; and (d) it has the potential to distinguish among different community assembly processes. With these attributes, we suggest that the FEE index is a promising metric to inform biodiversity conservation policy and management, especially in applications at large spatial and/or temporal scales.
... Existing methods allow estimating the relative importance of spatially restricted dispersal, environmental filtering, and biotic interactions for species occurrences and abundances within local communities (Boulangeat et al., 2012;Ovaskainen et al., 2017). An important limitation of current approaches is that they either test the influence of spatially restricted dispersal versus environmental filtering, or stochasticity versus environmental filtering, but not all three processes simultaneously (but see Munoz et al., 2018 for estimating the influence of immigration rates together with stochasticity and environmental filtering). ...
... This ensured that environmental gradients were steeper than community size gradients (Figure 1a We adopted the approach of Sokol, Brown, and Barrett (2017) to build a metacommunity simulation program in R (Supporting information Appendix S2) that allowed us to simulate metacommunities that consisted of several local communities assembled with or without spatially restricted dispersal, with varying degrees of habitat connectivity (i.e., immigration rates) and with strong, intermediate, and no environmental filtering. Other spatially implicit simulation approaches allow simulating metacommunity dynamics under environmental filtering, stochastic dynamics, and immigration rates (Munoz et al., 2018). However, a strength of the simulation approach of Sokol et al. (2017) is that it is spatially explicit so that the pool of potential immigrants that can reach a community changes as the metacommunity evolves, that is, the simulated metacommunities never reach a stable equilibrium. ...
Article
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Identifying the influence of stochastic processes and of deterministic processes, such as dispersal of individuals of different species and trait‐based environmental filtering, has long been a challenge in studies of community assembly. Here, we present the Univariate Community Assembly Analysis (UniCAA) and test its ability to address three hypotheses: species occurrences within communities are (a) limited by spatially restricted dispersal; (b) environmentally filtered; or (c) the outcome of stochasticity—so that as community size decreases—species that are common outside a local community have a disproportionately higher probability of occurrence than rare species. The comparison with a null model allows assessing if the influence of each of the three processes differs from what one would expect under a purely stochastic distribution of species. We tested the framework by simulating “empirical” metacommunities under 15 scenarios that differed with respect to the strengths of spatially restricted dispersal (restricted vs. not restricted); habitat isolation (low, intermediate, and high immigration rates); and environmental filtering (strong, intermediate, and no filtering). Through these tests, we found that UniCAA rarely produced false positives for the influence of the three processes, yielding a type‐I error rate ≤5%. The type‐II error rate, that is, production of false negatives, was also acceptable and within the typical cutoff (20%). We demonstrate that the UniCAA provides a flexible framework for retrieving the processes behind community assembly and propose avenues for future developments of the framework.
... assemblage they form can be represented by coalescence, i.e., by tracing the shared co-ancestry of extant individuals backwards in time until a single common ancestor is found (Kingman, 1982). Only the ancestry of individuals observed at present is traced back, so that coalescent methods do not require simulating lineages with no extant descendants and are thereby much faster than their forward-in-time alternatives (Munoz et al., 2018). Thus, without assuming to which species each individual belongs, we simulated the genealogies of individuals in an assemblage with constant size, and modeled the effect of habitat expansion FIGURE 2 | Eco-evolutionary dynamics of individual organisms in a habitat that experienced reduction in the past. ...
... Yet we could extend our framework to consider how these same large-scale biogeographic historical processes feed back into community assembly at a local scale. This could be done for instance by integrating a subsequent step to our modeling framework in which species can potentially be filtered based on their traits (Munoz et al., 2018). ...
Article
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Past environmental changes have shaped the evolutionary and ecological diversity of extant organisms. Specifically, climatic fluctuations have made environmental conditions alternatively common or rare over time. Accordingly, most taxa have undergone restriction of their distribution to local refugia during habitat contraction, from which they could expand when suitable habitat became more common. Assessing how past restrictions in refugia have shaped species distributions and genetic diversity has motivated much research in evolutionary biology and biogeography. But there is still lack of clear synthesis on whether and how the taxonomic, functional and phylogenetic composition of extant multispecies assemblages retains the imprint of past restriction in refugia. We devised an original eco-evolutionary model to investigate the temporal dynamics of a regional species pool inhabiting a given habitat today, and which have experienced habitat reduction in the past. The model includes three components: (i) a demographic component driving stochastic changes in population sizes and extinctions due to habitat availability, (ii) a mutation and speciation component representing how divergent genotypes emerge and define new species over time, and (iii) a trait evolution component representing how trait values have changed across descendents over time. We used this model to simulate dynamics of multispecies assemblages that occupied a restricted refugia in the past and could expand their distribution subsequently. We characterized the past restriction in refugia in terms of two parameters representing the ending time of past refugia, and the extent of habitat restriction in the refugia. We characterized extant patterns of taxonomic, functional and phylogenetic diversity depending on these parameters. We found that extant relative abundances reflect the lasting influence of more recent refugia on demographic dynamics, while phylogenetic composition reflects the influence of more ancient habitat change. Extant functional diversity depends on the interplay between diversification dynamics and trait evolution, offering new options to jointly infer current trait adaptation and past trait evolution dynamics. https://www.frontiersin.org/articles/10.3389/fevo.2021.634413/abstract
... Such models can then be compared to field data thanks to computer-intensive statistical techniques such as approximate Bayesian computation (ABC, Beaumont 2010, Jabot et al. 2013. Although several metacommunity simulators have been developed and distributed (e.g., Münkemüller & Gallien 2015, Keyel et al. 2016, Munoz et al. 2018, tailoring a spatially explicit metacommunity simulator to a specific case study to perform a genuine model-based ABC inference from metacommunity time series is still a challenge ahead. ...
Preprint
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Although metacommunity ecology has been a major field of research in the last decades, with both conceptual and empirical outputs, the analysis of the temporal dynamics of metacommunities has only emerged recently and still consists mostly of repeated static analyses. Here we propose a novel conceptual framework to assess metacommunity processes using path analyses of spatial and temporal diversity turnovers. We detail the principles and practical aspects of this framework and apply it to four datasets to illustrate its ability to decipher the respective contributions of entangled drivers of metacommunity dynamics. Empirical results support the view that metacommunity dynamics may be generally shaped by multiple ecological processes acting in concert, with environmental filtering being variable across both space and time.
... A few recent models have, however, started to give insights into functional and phylodiversity (e.g. Münkemüller & Gallien, 2015;Munoz et al., 2018). ...
Article
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The concept of biological diversity, or biodiversity, is at the core of evolutionary and ecological studies. Many indices of biodiversity have been developed in the last four decades, with species being one of the central units of these indices. However, evolutionary and ecological studies need a precise description of species' characteristics to best quantify inter‐species diversity, as species are not equivalent and exchangeable. One of the first concepts characterizing species in biodiversity studies was abundance‐based rarity. Abundance‐based rarity was then complemented by trait‐ and phylo‐based rarity, called species' trait‐based and phylogenetic originalities, respectively. Originality, which is a property of an individual species, represents a species' contribution to the overall diversity of a reference set of species. Originality can also be defined as the rarity of a species' characteristics such as the state of a functional trait, which is often assumed to be represented by the position of the species on a phylogenetic tree. We review and compare various approaches for measuring originality, rarity and diversity and demonstrate that (i) even if attempts to bridge these concepts do exist, only a few ecological and evolutionary studies have tried to combine them all in the past two decades; (ii) phylo‐ and trait‐based diversity indices can be written as a function of species rarity and originality measures in several ways; and (iii) there is a need for the joint use of these three types of indices to understand community assembly processes and species' roles in ecosystem functioning in order to protect biodiversity efficiently.
... However, the dichotomous analyses of trait similarity ignored the fact that multiple assembly processes can structure local composition simultaneously and their effects can be interactive (HilleRisLambers et al. 2012;Mayfield and Levine 2010;Shipley et al. 2012). To untangle their confounding effects, stronger evidence is necessary from trait-based researches that directly examines the relative contribution of each underlying processes ( Munoz et al. 2018;Perronne et al. 2017;van der Plas et al. 2015). ...
Article
Aims Intraspecific trait variation (ITV) has been increasingly recognized to play an important role in understanding the underlying processes influencing community assembly. However, gaps remain in our understanding of how incorporating ITV will influence the relative importance of deterministic (e.g. habitat filtering, limiting similarity) and stochastic processes in driving community assembly at different successional stages. Methods We used data for eight functional traits from 55 woody species in early (24 ha) and late (25 ha) successional temperate forest plot in northeast China. We employed an approximate Bayesian computation approach to assess the relative contribution of stochastic processes , habitat filtering and limiting similarity in driving community structure. We then compared the results with and without intraspe-cific trait variation to investigate how ITV influences the inferred importance of each process. Important Findings We found that when analyzing interspecific trait variation only (i.e. without ITV), stochastic processes were observed most frequently in driving community composition, followed by habitat filtering and limiting similarity in both forests. However, ITV analyses showed that the relative importance of both deterministic processes (habitat filtering and limiting similarity) increased in early successional forest , but remained virtually unchanged in late successional forest. Our study reveals the distinctive influence of ITV on the inference of underlying processes in a context of succession and reinforces the need to estimate ITV for making correct inferences about underlying ecological processes.
... A few recent models have, however, started to give insights into functional and phylodiversity (e.g. Münkemüller & Gallien, 2015;Munoz et al., 2018). ...
Thesis
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Humanity strongly depends on biodiversity and services it provides. To prevent the biodiversity loss and to establish sustainable relations with nature humanity has to efficently manage and protect natural resources. The problem of “what to protect” is not new but became more important than ever and could be resolved by an appropriate use of biodiversity measures. Many indices of biodiversity have been developed in the last four decades, with species being one of the central units. However, evolutionary and ecological studies need a precise description of species’ characteristics to best quantify inter-species diversity, as species are not equivalent and exchangeable. First measures taking into account species biological differences were based on species phylogenetic relations and trait values. However, many of them measure a diversity of a set of species, and does not indicate the respective contribution of each species to the diversity of the set. To find a remedy to this issue, other type of measures appeared in early 90’s, comparing species through the shared amount of characteristics, but were put aside, erroneously classified as diversity measures too. In this thesis we refer to these measures as species originality indices. A species is original if it possesses unusual trait values compared to all others in a community or if it is distantly related with other species in a community. Thus, the most original species have the greatest contribution to the diversity of that community. In this thesis we sought to demonstrate the benefits of originality metrics, particularly in conservation biology and community ecology. First we review the relation of species originality with concepts of species’ diversity and rarity and we compare their related measures. Following theoretical links between originality and diversity measures we propose a practical application of a two-step (and two-scale) originality framework to a real plant species data. Finally, we discuss main pitfalls and advantages related to species data, spatial scale of a study and the choice of an originality measure. Future studies could use originality measures with other entities than species, such as genes or habitats, and therefore broad the extent of biodiversity assessment and conservation.
... Fourth, biological filtering could be combined with spatial processes by accounting for trait-dependent differences in species dispersal capacities (Hirt et al., 2018), especially if these differences are correlated with trophic traits (Hirt et al., 2020). Overall, combining filtering approaches that consider such dispersal limitation and abiotic filtering (Munoz et al., 2018) with those that focus on trophic traits (Maureaud et al., 2020) holds promise for understanding how species trait structures drive nonrandom spatial variability in food-web structures. ...
Article
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Despite intensive research on species dissimilarity patterns across communities (i.e. β‐diversity), we still know little about their implications for variation in food‐web structures. Our analyses of 50 lake and 48 forest soil communities show that, while species dissimilarity depends on environmental and spatial gradients, these effects are only weakly propagated to the networks. Moreover, our results show that species and food‐web dissimilarities are consistently correlated, but that much of the variation in food‐web structure across spatial, environmental, and species gradients remains unexplained. Novel food‐web assembly models demonstrate the importance of biotic filtering during community assembly by (1) the availability of resources and (2) limiting similarity in species’ interactions to avoid strong niche overlap and thus competitive exclusion. This reveals a strong signature of biotic filtering processes during local community assembly, which constrains the variability in structural food‐web patterns across local communities despite substantial turnover in species composition. Our analyses of 50 lake and 48 forest soil communities show that, while species dissimilarity depends on environmental and spatial gradients, these effects are only weakly propagated to the networks. Moreover, our results show that species and food‐web dissimilarities are consistently correlated, but that much of the variation in food‐web structure across spatial, environmental, and species gradients remains unexplained. Our results also reveal a strong signature of biotic filtering processes during local community assembly, which constrains the variability in structural food‐web patterns across local communities despite substantial turnover in species composition.
... The type and strength of trait-based community and interaction assembly processes First, the trait distributions of resource and consumer species are compared with those generated from random sampling of the regional pool to detect the type and strength of trait-based community assembly processes, such as environmental filtering or limiting similarity (Cadotte & Tucker, 2017;MacArthur & Levins, 1967;Weiher & Keddy, 1995). The strength of the trait-based community assembly process can be quantified as the standardized effect size of an appropriate metric of trait variation, such as the range or standard deviation of trait values (Kraft & Ackerly, 2010;Munoz et al., 2018). Second, the trait-based interaction assembly processes can be detected by testing for the strength of associations in traits between the trophic levels, for instance by using RLQ and fourth-corner analyses (e.g., Albrecht et al., 2018;Dehling et al., 2014;Dray et al., 2014). ...
Article
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The study of ecological networks has progressively evolved from a mostly descriptive science to one that attempts to elucidate the processes governing the emerging structure of multitrophic communities. To move forward, we propose a conceptual framework using trait-based inference of ecological processes to improve our understanding of network assembly and our ability to predict network reassembly amid global change. The framework formalizes the view that network assembly is governed by processes shaping the composition of resource and consumer communities within trophic levels and those dictating species’ interactions between trophic levels. To illustrate the framework and show its applicability, we (1) use simulations to explore network structures emerging from the interactions of these assembly processes, (2) develop a null model approach to infer the processes underlying network assembly from observational data, and (3) use the null model approach to quantify the relative influence of bottom-up (resource-driven) and top-down (consumer-driven) assembly modes on plant-frugivore networks along an elevational gradient. Simulations suggest that assembly processes governing the formation of pairwise interactions have a greater influence on network structure than those governing the composition of communities within trophic levels. Our case study further shows that the mode of network assembly along the gradient is mainly bottom-up controlled, suggesting that the filtering of plant traits has a larger effect on network structure relative to the filtering of frugivore traits. Combined with increasingly available trait and interaction data, the framework provides a timely toolbox to infer assembly processes operating within and between trophic levels and to test competing hypotheses about the assembly mode of resource-consumer networks along environmental gradients and among biogeographic regions. It is a step toward a more process-based network ecology and complete integration of multitrophic interactions in the prediction of future biodiversity.
... The index of generalism and the knowledge of the habitat spectrum of weeds should be useful for predicting the potential for immigration of weeds into cultivated fields from the surrounding habitat matrix. The probability of immigration could be weighted depending on the niche preferences and ecological generalism of weeds [46]. A perspective will be to further integrate an index of weed specialization depending on crop type [47]. ...
Article
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The definition of “arable weeds” remains contentious. Although much attention has been devoted to specialized, segetal weeds, many taxa found in arable fields also commonly occur in other habitats. The extent to which adjacent habitats are favourable to the weed flora and act as potential sources of colonisers in arable fields remains unclear. In addition, weeds form assemblages with large spatio-temporal variability, so that many taxa in weed flora are rarely observed in plot-based surveys. We thus addressed the following questions: How often do weeds occur in other habitats than arable fields? How does including field edges extend the taxonomic and ecological diversity of weeds? How does the weed flora vary across surveys at different spatial and temporal scales? We built a comprehensive dataset of weed taxa in France by compiling weed flora, lists of specialized segetal weeds, and plot-based surveys in agricultural fields, with different spatial and temporal coverages. We informed life forms, biogeographical origins and conservation status of these weeds. We also defined a broader dataset of plants occupying open habitats in France, and assessed habitat specialization of weeds and of other plant species absent from arable fields. Our results show that many arable weeds are frequently recorded in both arable fields and non-cultivated open habitats and are, on average, more generalist than species absent from arable fields. Surveys encompassing field edges included species also occurring in mesic grasslands and nitrophilous fringes, suggesting spill-over from surrounding habitats. 71.5% of the French weed flora was not captured in plot-based surveys at regional and national scales, and many rare and declining taxa were of Mediterranean origin. This result underlines the importance of implementing conservation measures for specialist plant species that are particularly reliant on arable fields as a habitat, while also pointing out biotic homogenisation of agricultural landscapes as a factor in the declining plant diversity of farmed landscapes. Our dataset provides a reference species pool for France, with associated ecological and biogeographical information.
... Numerous packages exist for simulating both neutral and niche dynamics of community assembly (Hankin, 2007;Laughlin, Joshi, van Bodegom, Bastow, & Fulé, 2012;Munoz et al., 2018;Novack-Gottshall, 2020;Taudiere & Violle, 2016). These tools massively reduce the barriers of entry for an ecologist wishing to model ecological communities and minimize time spent implementing code. ...
Article
Neutral theory proposes that some macroscopic biodiversity patterns can be explained in terms of drift, speciation and immigration, without invoking niches. There are many different varieties of neutral model, all assuming that the fitness of an individual is unrelated to its species identity. Variants that are spatially explicit provide a means for making quantitative predictions about spatial biodiversity patterns. We present software packages that make spatially explicit neutral simulations straightforward and efficient. The packages allow the user to customize both dispersal and landscape structure in a wide variety of ways. We provide a Python package pycoalescence and a functionally equivalent R package rcoalescence. In both packages, the core routines are written in C++ and make use of coalescence methods to optimize performance. We explain the technical details of the packages and give examples for their application, with a particular focus on two scenarios of ecological and evolutionary interest: a landscape with habitat fragmentation, and an archipelago of islands. Spatially explicit neutral models represent an important tool in ecology for understanding the processes of biodiversity generation and predicting outcomes at large scales. The effort required to implement these complex spatially explicit simulations efficiently has thus far been a barrier to entry. Our packages increase the accessibility of these models and encourage further investigation of the primary mechanisms underpinning biodiversity.
... Reconciling niche-based process and neutral dynamics in spatially-implicit conjecture, ecologist tried to explain the community assembly in successional patchy habitats, in that the vacant local community created by perturbation was initially colonized by the immigrants from a metacommunity under the ecological equivalence among species; then, the competitive exclutions were followed in each local community (Mouquet, Munguia, Kneitel, & Miller 2003). In stable environment, the immigrants from a metacommunity was filtered along environmental gradients, and the coexistence of species in each local community was achieved under the per capita equivalence among individuals in homogeneous environment (Jabot, Etienne, & Chave 2007;Janzen, Haegeman, & Etienne 2015;Munoz, Ramesh, & Couteron 2014;Munoz et al., 2018). In spatially-implicit conjecture; however, the regional dynamics were not predicted but usually specified by a fixed metacommunity. ...
Preprint
Reconciling niche-based process and neutral dynamics in a portion of an infinite system, the regional species pool may be already not free parameter, and the divergent ecological-evolutionary mechanisms may operate consistently. The individual-based model was implemented in the two-dimensional grid with periodic boundary condition. The model was explored using a fixed speciation rate, and a range of system sizes, dispersal rates, environmental structures and initial conditions of regional species pool. The model communities in the center of system had a fixed population size, and approximated from an area encompassing independent biogeographic units to an area packed in a biogeographic unit with open boundary conditions, and presented the three environmental structures; four humps, linear and random. Across scenarios, the number of guilds in system achieved first to a stationary state; then, the species richness converged eventually to a dynamical equilibrium through speciation-extinction balance. In simulations, the per capita ecological difference among species only contributed to the probabilities of immigration success, so the weighted lottery process was more efficient and immediate at higher dispersal rates. The increase of functional redundancy in model communities suggested that the relative role of neutral dynamics increased in an area encompassing independent biogeographic units. The variation partitioning based on canonical analysis inferred that not only the neutral dynamics among the species of single guild, but also the competition-colonization trade-off among the species of more than two guilds with similar environmental optimum and different levels of specialization operated in the spatial structures found within and among patchy habitats. Ecologist to disentangle the influence of alternative processes must shift focus from the contribution of local competitions and regional dispersals to detecting the spatio-temporal-environmental scales on which the per capita ecological difference and equivalence among species are emerged through divergent ecological-evolutionary mechanisms.
... Indeed, considering only network spatial structure, using neutral models, has provided relevant predictions of diversity patterns (Hubbell 2001, Muneepeerakul et al. 2008, Rosindell et al. 2011. Therefore, accounting with network characteristics in order to understand temporary ponds metacommunity dynamics will enhance our understanding on the pure landscape influence, improving our understanding on their functioning and providing an innovative framework for management against disturbances -e.g., wildfires among others (Estrada and Bodin 2008, Chang et al. 2013, Borthagaray et al. 2014, Sokol et al. 2015, Munoz et al. 2018 In fact, the influence of network characteristics (i.e., landscape structure) plays a key role in driving temporary ponds metacommunity dynamics due to its effect on species dispersal ability (Cañedo-Argüelles et al. 2015, Jones et al. 2015, Grainger and Gilbert 2016, Vannette and Fukami 2017, Shanafelt et al. 2018. Indeed, dispersal ability of organisms strongly determine their capacity to move through the network and consequently their landscape perception (Heino 2013, Borthagaray et al. 2015b, Hill et al. 2017b. ...
Thesis
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During the last years, there has been an increase in the number and intensity of disturbances, and their consequences related with global change, which have corroborated the already forecasted scenarios. One example are wildfires, which are expected to increase both in intensity and extension in the near future. However, although the extensive research carried out to understand wildfire impacts, there is still a lack of knowledge regarding its consequences on freshwater temporary ponds. These temporary habitats constitute small biodiversity reservoirs, holding singular and iconic fauna. Nowadays, these habitats are endangered mostly due to habitat loss. Consequently, to cope with the future climatic scenario, which predicts an increase in wildfire disturbances as well as greater habitat loss, it becomes mandatory to better comprehend and study wildfire impacts on these small biodiversity jewels.Throghout this thesis I study the Jonquera wildfire consequences on the Albera temporary ponds
... Deterministic processes modulate the success of immigrants based on how their trait values allow establishment and persistence in local environments. Altogether, stochastic and deterministic processes both influence the establishment success of immigrants and survival of their descendants in the model (Loranger et al., 2018;Munoz et al., 2018). We simulated three different outcomes of deterministic processes in ecolottery, henceforth, 'traitbased filtering'. ...
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Deciphering the effect of neutral and deterministic processes on community assembly is critical to understand and predict diversity patterns. The information held in community trait distributions is commonly assumed as a signature of these processes, but empirical and modelling attempts have most often failed to untangle their confounding, sometimes opposing, impacts. Here, we simulated the assembly of trait distributions through stochastic (dispersal limitation) and/or deterministic scenarios (environmental filtering, niche differentiation). We characterized the shape of trait distributions using the skewness-kurtosis relationship. We identified commonalities in the co-variation between the skewness and the kurtosis of trait distributions with a unique signature for each simulated assembly scenario. Our findings were robust to variation in the composition of regional species pools, dispersal limitation, and environmental conditions. While ecological communities can exhibit a high degree of idiosyncrasy, identification of commonalities across multiple communities can help to unveil ecological assembly rules in real-world ecosystems.
... 8 Our model simulated biodiversity dynamics at the regional level, something unattainable with an exclusively empirical approach. Lottery and coalescent models have been particularly suitable for analysing the effects of landscape structure on biodiversity patterns here and elsewhere (Economo and Keitt 2008, Muneepeerakul et al. 2008, Borthagaray et al. 2014, Sokol et al. 2017, Munoz et al. 2018, Worm and Tittensor 2018. Moreover, our model considered trait-mediated dynamics accounting for species dispersal abilities (Louette andDe Meester 2005, Ruhí et al. 2013), and resources overlapped across them (Shipley 2010, Sokol et al. 2017. ...
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Disturbances, such as wildfires, are one of the main drivers of biodiversity dynamics , and their frequency and intensity are expected to increase due to global change. Such disturbances generate a mosaic of affected and unaffected patches that change landscape structure and, consequently, metacommunity networks. Therefore, to fully understand the consequences of such disturbances, a landscape perspective is required. In 2012, a wildfire burned 13 000 hectares in the NE Iberian Peninsula affecting a pond macroinvertebrate metacommunity. Communities were highly resilient to this disturbance, recovering after one hydroperiod. Their resilience was related to dispersal , being lower in species with weak dispersal abilities than those with strong dispersal abilities. This suggested that the metacommunity network played a major role in defining system resilience. In this context, we introduced a theoretical analysis based on this network in which we evaluated metacommunity resilience across several gradients of disturbance size and intensity incorporating species dispersal ability. Our study supports the empirical observation of a highly resilient metacommunity but also reveals that increased disturbance regimes might lead to a collapse of this resilience. Disturbance size and intensity interacted to determine the community recovery rate, which was high when both variables were low. Nevertheless, the transition from high to low resilience was sharp and depended on species dispersal. Diversity recovery was mostly driven by disturbance intensity, abruptly collapsing with its rise. This response highlighted the qualitative difference in the effect of size and intensity. These results not only illustrate the mechanisms shaping the studied metacommunity but also more generally stress the strong role of metacommunity mechanisms and landscape structure in biodiversity resilience. Finally, this study highlights the importance of using theoretical approaches rooted in empirical data to determine metacommunity dynamics and the need to preserve and build connected and heterogeneous landscapes to address future disturbance scenarios.
... The type and strength of trait-based community and interaction assembly processes First, the trait distributions of resource and consumer species are compared with those generated from random sampling of the regional pool to detect the type and strength of trait-based community assembly processes, such as environmental filtering or limiting similarity (Cadotte & Tucker, 2017;MacArthur & Levins, 1967;Weiher & Keddy, 1995). The strength of the trait-based community assembly process can be quantified as the standardized effect size of an appropriate metric of trait variation, such as the range or standard deviation of trait values (Kraft & Ackerly, 2010;Munoz et al., 2018). Second, the trait-based interaction assembly processes can be detected by testing for the strength of associations in traits between the trophic levels, for instance by using RLQ and fourth-corner analyses (e.g., Albrecht et al., 2018;Dehling et al., 2014;Dray et al., 2014). ...
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The study of ecological networks has progressively evolved from a mostly descriptive science to one that attempts to elucidate the processes governing the emerging structure of multitrophic communities. To move forward, we propose a conceptual framework using trait-based inference of ecological processes to improve our understanding of network assembly and our ability to predict network reassembly amid global change. The framework formalizes the view that network assembly is governed by processes shaping the composition of resource and consumer communities within trophic levels and those dictating species' interactions between trophic levels. To illustrate the framework and show its applicability, we (1) use simulations to explore network structures emerging from the interactions of these assembly processes, (2) develop a null model approach to infer the processes underlying network assembly from observational data, and (3) use the null model approach to quantify the relative influence of bottom-up (resource-driven) and top-down (consumer-driven) assembly modes on plant-frugivore networks along an elevational gradient. Simulations suggest that assembly processes governing the formation of pairwise interactions have a greater influence on network structure than those governing the composition of communities within trophic levels. Our case study further shows that the mode of network assembly along the gradient is mainly bottom-up controlled, suggesting that the filtering of plant traits has a larger effect on network structure relative to the filtering of frugivore traits. Combined with increasingly available trait and interaction data, the framework provides a timely toolbox to infer assembly processes operating within and between trophic levels and to test competing hypotheses about the assembly mode of resource-consumer networks along environmental gradients and among biogeographic regions. It is a step toward a more process-based network ecology and complete integration of multitrophic interactions in the prediction of future biodiversity.
... where parameter A controls the strength of environmental filtering (complete maladaptation leads to a local fitness of 1 while perfect adaptation to a local fitness of 1 + A) and parameter r controls its specificity (a relatively good local adaptation is obtained when |s s -E ij (t)| is less than r). This Gaussian-based equation is a rather standard way of modelling environmental filtering in community ecology (Gravel et al. 2006;Gilbert & Bennett 2010;Jabot 2010;M€ unkem€ uller & Gallien 2015;Sokol et al. 2017;Munoz et al. 2018). The survival of adult individuals of species s is modelled at each time step t in cell (i,j) as a Bernoulli draw with probability (1-r) 9 f s (i,j,t)/ (1 + A). ...
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Although metacommunity ecology has been a major field of research in the last decades, with both conceptual and empirical outputs, the analysis of the temporal dynamics of metacommunities has only emerged recently and still consists mostly of repeated static analyses. Here, we propose a novel analytical framework to assess metacommunity processes using path analyses of spatial and temporal diversity turnovers. We detail the principles and practical aspects of this framework and apply it to simulated datasets to illustrate its ability to decipher the respective contributions of entangled drivers of metacommunity dynamics. We then apply it to four real empirical datasets. Empirical results support the view that metacommunity dynamics may be generally shaped by multiple ecological processes acting in concert, with environmental filtering being variable across both space and time. These results reinforce our call to go beyond static analyses of metacommunities that are blind to the temporal part of environmental variability.
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Aim: Ecological specialization is defined by the variety of environments species occupy. Identifying the mechanisms that influence specialization is critical to understand patterns of species coexistence and biodiversity. However, the functional attributes that result in specialization are still unknown. Similarly, there is contrasting evidence between the degree of specialization and the local abundance of species. We investigated whether specialist and generalist plant species (i) are associated with distinct functional profiles, using core plant functional traits and strategies, (ii) show similar functional variation and (iii) perform at the local scale. Location: France. Taxon: Herbaceous plants. Methods: We analyzed the structure of a bipartite network that includes the occurrences of ~2,900 plant species at ~90,000 sites to identify ecologically consistent sets of species and sites (i.e. “modules”). This innovative approach then enabled us to define a metric of specialization, by quantifying occurrences of species at sites that belong to one or several modules. We used functional traits related to resource acquisition, competition for light and dispersal ability, as well as indices of competitive, stress-tolerance and ruderal strategies. Results: We identified five major modules in the bipartite network related to different environments and composed of species with differing functional attributes. Specialist species were less competitive and shorter, and had higher stress-tolerance and stronger resource conservation, while generalist species were taller. Generalists were also more similar to each other than specialists. In addition, specialists had higher local abundances and occurred in communities with plants of similar height. Main conclusions: We found distinctive functional signatures of specialist and generalist species in grassland communities across diverse environments at regional and community scales. By testing classic macro-ecological hypotheses, network metrics can benefit community ecology by identifying distinct ecological units at a large scale and quantifying the links developed by species.
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A central question of community ecology is to understand how the interplay between processes of the Neutral Theory (e.g., immigration and ecological drift) and niche-based processes (e.g., environmental filtering, intra- and interspecific density-dependence) shape species diversity in competitive communities. The articulation between these two categories of mechanisms can be studied through the lens of the intermediate organizational level of “functional groups” (FGs), defined as clusters of species with similar traits. Indeed, FGs stress ecological differences among species and are thus likely to unravel non-neutral interactions within communities. Here we presented a novel approach to explore how FGs affect species coexistence by comparing species and functional diversity patterns. Our framework considers the Neutral Theory as a mechanistic null hypothesis. It assesses how much the functional diversity deviates from species diversity in communities, and compares this deviation, called the “average functional deviation”, to a neutral baseline. We showed that the average functional deviation can indicate reduced negative density-dependence or environmental filtering among FGs. We validated our framework using simulations illustrating the two situations. We further analyzed tropical tree communities in Western Ghats, India. Our analysis of the average functional deviation revealed environmental filtering between deciduous and evergreen FGs along a broad rainfall gradient. By contrast, we did not find clear evidence for reduced density-dependence among FGs. We predict that applying our approach to new case studies where environmental gradients are milder and FGs are more clearly associated to resource partitioning should reveal the missing pattern of reduced density-dependence among FGs.
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pez is an R package that permits measurement, modelling, and simulation of phylogenetic structure in ecological data. pez contains the first implementation of many methods in R, and aggregates existing data structures and methods into a single, coherent package. pez is released under the GPL v3 open-source license, available on the Internet from CRAN (http://cran.r-project.org). The package is under active development, and the authors welcome contributions (see http://github.com/willpearse/pez). William D. Pearse; will.pearse@gmail.com. © The Author (2015). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.
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Despite being recognized as a promoter of diversity and a condition for local coexistence decades ago, the importance of intraspecific variance has been neglected over time in community ecology. Recently, there has been a new emphasis on intraspecific variability. Indeed, recent developments in trait-based community ecology have underlined the need to integrate variation at both the intraspecific as well as interspecific level. We introduce new T-statistics ('T' for trait), based on the comparison of intraspecific and interspecific variances of functional traits across organizational levels, to operationally incorporate intraspecific variability into community ecology theory. We show that a focus on the distribution of traits at local and regional scales combined with original analytical tools can provide unique insights into the primary forces structuring communities.
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Natural populations consist of phenotypically diverse individuals that exhibit variation in their demographic parameters and intra- and inter-specific interactions. Recent experimental work indicates that such variation can have significant ecological effects. However, ecological models typically disregard this variation and focus instead on trait means and total population density. Under what situations is this simplification appropriate? Why might intraspecific variation alter ecological dynamics? In this review we synthesize recent theory and identify six general mechanisms by which trait variation changes the outcome of ecological interactions. These mechanisms include several direct effects of trait variation per se and indirect effects arising from the role of genetic variation in trait evolution.
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Ecological models suggest that high diversity can be generated by purely niche-based, purely neutral or by a mixture of niche-based and neutral ecological processes. Here, we compare the degree to which four contrasting hypotheses for coexistence, ranging from niche-based to neutral, explain species richness along a body mass niche axis. We derive predictions from these hypotheses and confront them with species body-mass patterns in a highly sampled marine phytoplankton community. We find that these patterns are consistent only with a mechanism that combines niche and neutral processes, such as the emergent neutrality mechanism. In this work, we provide the first empirical evidence that a niche-neutral model can explain niche space occupancy pattern in a natural species-rich community. We suggest this class of model may be a useful hypothesis for the generation and maintenance of species diversity in other size-structured communities.
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Environmental filtering, where the environment selects against certain species, is thought to be a major mechanism structuring communities. However, recent criticisms cast doubt on our ability to accurately infer filtering because competition can give rise to patterns identical to those caused by environmental filtering. While experiments can distinguish mechanisms, observational patterns are especially problematic. The environment determines community composition not only directly via survival, but also by influencing competition. If species population growth rates covary with environmental gradients, then outcomes of competitive exclusion will also vary with the environment. Here, we argue that observational studies remain valuable, but inferences about the importance of the environment cannot rely on compositional data alone, and that species abundances, population growth, or traits must be correlated with the environment.
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The distribution of abundance amongst species with similar ways of life is a classical problem in ecology. The unified neutral theory of biodiversity, due to Hubbell, states that observed population dynamics may be explained on the assumption of per capita equivalence amongst individuals. One can thus dispense with differences between species, and differences between abundant and rare species: all individuals behave alike in respect of their probabilities of reproducing and death. It is a striking fact that such a parsimonious theory results in a non-trivial dominancediversity curve (that is, the simultaneous existence of both abundant and rare species) and even more striking that the theory predicts abundance curves that match observations across a wide range of ecologies. This paper introduces the untb package of R routines, for numerical simulation of ecological drift under the unified neutral theory. A range of visualization, analytical, and simulation tools are provided in the package and these are presented with examples in the paper.
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The quest for ‘assembly rules’, i.e. the processes shaping the species composition of communities, is a central issue in community ecology. Nevertheless, so far there is no general agreement on a framework to detect assembly rules in real life data: several key elements are still missing or heavily disputed, including the choice of the appropriate test statistic (e.g. functional diversity index) and randomization strategy for each major assembly process.Simulation studies based on artificial communities can help to explore the usefulness of different approaches in detecting assembly rules. Nevertheless, the currently dominant approach to simulate artificial communities (i.e. selecting species from a pool based solely on trait values) oversimplifies the complex processes involved in community assembly and thus fails to produce realistic patterns. Consequently, its value for testing methodologies is seriously limited.In this study we implemented a flexible, individual-based algorithm simulating real-life community processes (individuals are born, survive, compete for resources, reproduce and die), to generate artificial species composition data. With the help of this algorithm, we estimated the type I error rates and the statistical power of five different diversity indices (FRic, Rao's quadratic entropy, FEve, the variance of functional distances, and the variance of nearest neighbor distances) in combination with three randomization strategies (randomization of trait values in the whole dataset, within plots and within the range of trait values occurring in each plot) for detecting two underlying assembly processes (habitat filtering and limiting similarity). We also tested the influence of all adjustable simulation parameters on the simulation results in a sensitivity analysis framework.The results of the sensitivity analysis show that the individual-based simulation framework proposed here can be used for creating artificial community data with realistic pattern of trait values. Based on the results, Rao's quadratic entropy performed best for detecting both habitat filtering (trait convergence) and limiting similarity (trait divergence). Functional richness may also be suitable for detect traiting convergence. Functional evenness and variance of nearest neighbor distances, however, should not be used for finding assembly rules.This article is protected by copyright. All rights reserved.
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The desire to predict the consequences of global environmental change has been the driver towards more realistic models embracing the variability and uncertainties inherent in ecology. Statistical ecology has gelled over the past decade as a discipline that moves away from describing patterns towards modelling the ecological processes that generate these patterns. Following the fourth International Statistical Ecology Conference (1–4 July 2014) in Montpellier, France, we analyse current trends in statistical ecology. Important advances in the analysis of individual movement, and in the modelling of population dynamics and species distributions, are made possible by the increasing use of hierarchical and hidden process models. Exciting research perspectives include the development of methods to interpret citizen science data and of efficient, flexible computational algorithms for model fitting. Statistical ecology has come of age: it now provides a general and mathematically rigorous framework linking ecological theory and empirical data.
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1.One of the most pervasive concepts in the study of community assembly is the metaphor of the environmental filter, which refers to abiotic factors that prevent the establishment or persistence of species in a particular location. The metaphor has its origins in the study of community change during succession and in plant community dynamics, though it has gained considerable attention recently as part of a surge of interest in functional trait and phylogenetic based approaches to the study of communities.2.While the filtering metaphor has clear utility in some circumstances, it has been challenging to reconcile the environmental filtering concept with recent developments in ecological theory related to species coexistence. These advances suggest that the evidence used in many studies to assess environmental filtering is insufficient to distinguish filtering from the outcome of biotic interactions.3.We re-examine the environmental filtering metaphor from the perspective of coexistence theory. In an effort to move the discussion forward, we present a simple framework for considering the role of the environment in shaping community membership, review the literature to document the evidence typically used in environmental filtering studies, and highlight research challenges to address in coming years.4.The current usage of the environmental filtering term in empirical studies likely overstates the role abiotic tolerances play in shaping community structure. We recommend that the term “environmental filtering” only be used to refer to cases where the abiotic environment prevents establishment or persistence in the absence of biotic interactions, though only 15% of the studies in our review presented such evidence. Finally, we urge community ecologists to consider additional mechanisms aside from environmental filtering by which the abiotic environment can shape community pattern.This article is protected by copyright. All rights reserved.
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Understanding the regional dynamics of plant communities is crucial for predicting the response of plant diversity to habitat fragmentation. However, for fragmented landscapes the importance of regional processes, such as seed dispersal among isolated habitat patches, has been controversially debated. Due to the stochasticity and rarity of among-patch dispersal and colonization events, we still lack a quantitative understanding of the consequences of these processes at the landscape-scale. In this study, we used extensive field data from a fragmented, semi-arid landscape in Israel to parameterize a multi-species incidence-function model. This model simulates species occupancy pattern based on patch areas and habitat configuration and explicitly considers the locations and the shapes of habitat patches for the derivation of patch connectivity. We implemented an approximate Bayesian computation approach for parameter inference and uncertainty assessment. We tested which of the three types of regional dynamics – the metacommunity, the mainland-island, or the island communities type – best represents the community dynamics in the study area and applied the simulation model to estimate the extinction debt in the investigated landscape. We found that the regional dynamics in the patch-matrix study landscape is best represented as a system of highly isolated ‘island’ communities with low rates of propagule exchange among habitat patches and consequently low colonization rates in local communities. Accordingly, the extinction rates in the local communities are the main drivers of community dynamics. Our findings indicate that the landscape carries a significant extinction debt and in model projections 33–60% of all species went extinct within 1000 yr. Our study demonstrates that the combination of dynamic simulation models with field data provides a promising approach for understanding regional community dynamics and for projecting community responses to habitat fragmentation. The approach bears the potential for efficient tests of conservation activities aimed at mitigating future losses of biodiversity.
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Understanding the forces that influence natural variation within and among populations has been a major objective of evolutionary biologists for decades. Motivated by the growth in computational power and data complexity, modern approaches to this question make intensive use of ...
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Understanding how local species assembly depends on the regional biogeographic and environmental context is a challenging task in community ecology. In spatially implicit neutral models, a single immigration parameter, I(k), represents the flux of immigrants from a regional pool that compete with local offspring for establishment in communities. This flux counterbalances the effect of local stochastic extinctions to maintain local species diversity. If some species within the regional pool are not adapted to the local environment (habitat filtering), the migrant flux is reduced beyond that of the neutral model, such that habitat filtering influences the value of I(k) in non-neutral situations. Here, we propose a novel model in which immigrants from the regional pool are filtered according to their habitat preferences and the local environment, while taxa potentially retain habitat preferences from their ancestors (niche conservatism). Using both analytical reasoning and simulations, we demonstrate that I(k) is expected to be constant when estimated based on the community composition at several taxonomic levels, not only under neutral assumptions but also when habitat filtering occurs, unless there is substantial niche conservatism. In the latter case, I(k) is expected to decrease when estimated based on the composition at species to genus and family levels, thus allowing a signature of niche conservatism to be detected by simply comparing I(k) estimates across taxonomic levels. We applied this approach to three rainforest datasets from South India and Central America and found no significant signature of niche conservatism when I(k) was compared across taxonomic levels, except at the family level in South India. We further observed more limited immigration in South Indian forests, supporting the hypothesis of a greater impact of habitat filtering and heterogeneity there than in Central America. Our results highlight the relevance of studying variations of I(k) in space and across taxonomic levels to test hypotheses about the ecological and evolutionary drivers of biodiversity patterns.
Article
In this paper, we provide a brief review of the well-known methods of reducing spatially structured population models to mean-field models. First, we discuss the terminology of mean-field approximation which is used in the ecological modelling literature and show that the various existing interpretations of the mean-field concept can imply different meanings. Then we classify and compare various methods of reducing spatially explicit models to mean-field models: spatial moment approximation, aggregation techniques and the mean-field limit of IBMs. We emphasize the importance of spatial scales in the reduction of spatially explicit models and briefly consider the inverse problem of scaling up local ecological interactions from microscales to macroscales. Then we discuss the current challenges and limitations for construction of mean-field population models. We emphasize the need for developing mixed methods based on a combination of various reduction techniques to cope with the spatio-temporal complexity of real ecosystems including processes taking place on multiple time and space scales. Finally, we argue that the construction of analytically tractable mean-field models is becoming a key issue to provide an insight into the major mechanisms of ecosystem functioning. We complete this review by introducing the contributions to the current special issue of Ecological Complexity.
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Neutral community models have shown that limited migration can have a pervasive influence on the taxonomic composition of local communities even when all individuals are assumed of equivalent ecological fitness. Notably, the spatially implicit neutral theory yields a single parameter I for the immigration-drift equilibrium in a local community. In the case of plants, seed dispersal is considered as a defining moment of the immigration process and has attracted empirical and theoretical work. In this paper, we consider a version of the immigration parameter I depending on dispersal limitation from the neighbourhood of a community. Seed dispersal distance is alternatively modelled using a distribution that decreases quickly in the tails (thin-tailed Gaussian kernel) and another that enhances the chance of dispersal events over very long distances (heavily fat-tailed Cauchy kernel). Our analysis highlights two contrasting situations, where I is either mainly sensitive to community size (related to ecological drift) under the heavily fat-tailed kernel or mainly sensitive to dispersal distance under the thin-tailed kernel. We review dispersal distances of rainforest trees from field studies and assess the consistency between published estimates of I based on spatially-implicit models and the predictions of the kernel-based model in tropical forest plots. Most estimates of I were derived from large plots (10-50 ha) and were too large to be accounted for by a Cauchy kernel. Conversely, a fraction of the estimates based on multiple smaller plots (1 ha) appeared too small to be consistent with reported ranges of dispersal distances in tropical forests. Very large estimates may reflect within-plot habitat heterogeneity or estimation problems, while the smallest estimates likely imply other factors inhibiting migration beyond dispersal limitation. Our study underscores the need for interpreting I as an integrative index of migration limitation which, besides the limited seed dispersal, possibly includes habitat filtering or fragmentation.
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Ecologists have long grappled with the problem of scaling up from tractable, small-scale observations and experiments to the prediction of large-scale patterns. Although there are multiple approaches to this formidable task, there is a common underpinning in the formulation, testing, and use of mechanistic response functions to describe how phenomena interact across scales. Here, we review the principles of response functions to illustrate how they provide a means to guide research, extrapolate beyond measured data, and simplify our conceptual grasp of reality. We illustrate these principles with examples of mechanistic approaches ranging from explorations of the ecological niche, random walks, and macrophysiology to theories dealing with scale transition, self-organization, and the prediction of extremes.
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Resolving contingencies in community ecology requires comparative studies of local communities along broad-scale environmental gradients and in different biogeographic regions. However, comparisons of local ecological processes among regions require a synthetic understanding of how the species pool of potential community members influences the structure of ecological communities. Here, we outline an integrative approach for quantifying local ecological processes while explicitly accounting for species pool influences. Specifically, we highlight the utility of combining geographically replicated local studies, null models of community structure, and ecologically explicit definitions of the species pool as a means to compare predominant ecological processes among regions. By uniting concepts and tools from community ecology and macroecology, this approach might facilitate synthesis and resolve many perceived ecological contingencies.
Book
Plant community ecology has traditionally taken a taxonomical approach based on population dynamics. This book contrasts such an approach with a trait-based approach. After reviewing these two approaches, it then explains how models based on the Maximum Entropy Formalism can be used to predict the relative abundance of different species from a potential species pool. Following this it shows how the trait constraints, upon which the model is based, are necessary consequences of natural selection and population dynamics. The final sections of the book extend the discussion to macroecological patterns of species abundance and concludes with some outstanding unresolved questions. Written for advanced undergraduates, graduates and researchers in plant ecology, Bill Shipley demonstrates how a trait-based approach, can explain how the principle of natural selection and quantitative genetics can be combined with maximum entropy methods to explain and predict the structure of plant communities.
Article
Although the structure and composition of plant communities is known to influence the functioning of ecosystems, there is as yet no agreement as to how these should be described from a functional perspective. We tested the biomass ratio hypothesis, which postulates that ecosystem properties should depend on species traits and on species contribution to the total biomass of the community, in a successional sere following vineyard abandonment in the Mediterranean region of France. Ecosystem-specific net primary productivity, litter decomposition rate, and total soil carbon and nitrogen varied significantly with field age, and correlated with community-aggregated (i.e., weighed according to the relative abundance of species) functional leaf traits. The three easily measurable traits tested, specific leaf area, leaf dry matter content, and nitrogen concentration, provide a simple means to scale up from organ to ecosystem functioning in complex plant communities. We propose that they be called ''functional markers,'' and be used to assess the impacts of community changes on ecosystem properties induced, in particular, by global change drivers.
Article
Community assembly processes are thought to shape the mean, spread, and spacing of functional trait values within communities. Two broad categories of assembly processes have been proposed: first, a habitat filter that restricts the range of viable strategies and second, a partitioning of microsites and/or resources that leads to a limit to the similarity of coexisting species. The strength of both processes may be dependent on conditions at a particular site and may change along an abiotic gradient. We sampled environmental variables and plant communities in 44 plots across the varied topography of a coastal California landscape. We characterized 14 leaf, stem, and root traits for 54 woody plant species, including detailed intraspecific data for two traits with the goal of understanding the connection between traits and assembly processes in a variety of environmental conditions. We examined the within-community mean, range, variance, kurtosis, and other measures of spacing of trait values. In this landscape, there was a topographically mediated gradient in water availability. Across this gradient we observed strong shifts in both the plot-level mean trait values and the variation in trait values within communities. Trends in trait means with the environment were due largely to species turnover, with intraspecific shifts playing a smaller role. Traits associated with a vertical partitioning of light showed a greater range and variance on the wet soils, while nitrogen per area, which is associated with water use efficiency, showed a greater spread on the dry soils. We found strong nonrandom patterns in the trait distributions consistent with expectations based on trait-mediated community assembly. There was a significant reduction in the range of six out of 11 leaf and stem functional trait values relative to a null model. For specific leaf area (SLA) we found a significant even spacing of trait values relative to the null model. For seed size we found a more platykurtic distribution than expected. These results suggest that both a habitat filter and a limit to the similarity of coexisting species can simultaneously shape the distribution of traits and the assembly of local plant communities.
Article
Species diversity and genetic diversity remain the nearly exclusive domains of community ecology and population genetics, respectively, despite repeated recognition in the literature over the past 30 years of close parallels between these two levels of diversity. Species diversity within communities and genetic diversity within populations are hypothesized to co-vary in space or time because of locality characteristics that influence the two levels of diversity via parallel processes, or because of direct effects of one level of diversity on the other via several different mechanisms. Here, we draw on a wide range of studies in ecology and evolution to examine the theoretical underpinnings of these hypotheses, review relevant empirical literature, and outline an agenda for future research. The plausibility of species diversity–genetic diversity relationships is supported by a variety of theoretical and empirical studies, and several recent studies provide direct, though preliminary support. Focusing on potential connections between species diversity and genetic diversity complements other approaches to synthesis at the ecology–evolution interface, and should contribute to conceptual unification of biodiversity research at the levels of genes and species.
Article
Current neutral theory in community ecology views local biodiversity as a result of the interplay between speciation, extinction and immigration. Simulations and a mean-field approximation have been used to study this neutral theory. As simulations have limitations of convergence and the mean-field approximation ignores dependencies between species’ abundances when applied to species-abundance data, there is still no final conclusion whether the neutral theory or the traditional lognormal model describes community structure best. We present a novel analytical framework, based on the genealogy of individuals in the local community, to overcome the problems of previous approaches, and show, using Bayesian statistics, that the lognormal model provides a slightly better fit to the species-abundance distribution of a much-discussed tropical tree community. A key feature of our approach is that it shows the tight link between genetic and species diversity, which creates important perspectives to future integration of evolutionary and community ecological theory.
Article
It is widely believed that the neutral theory of biodiversity cannot be used for parameter inference if the assumption of neutrality is not met. The goal of this work is to extend this neutral framework to quantify the intensity of recruitment limitation (limited dispersal plus environmental filtering) in natural species assemblages. We model several local communities as part of a larger metacommunity, and we assume that neutrality holds in each local community, but not in the metacommunity. The immigration rate m does not only reflect dispersal limitation into a given local community, but also the intensity of environmental filtering. We develop a novel statistical method to infer the immigration parameter m in each local community. Using simulated datasets, we show that m indeed depends on both dispersal limitation and on the intensity of environmental filtering. We then apply this method to a network of tropical tree plots in central Panama. Inferred recruitment rates m were positively correlated with the fraction of trees dispersed by mammals, and with annual rainfall, possibly due to a weaker environmental filtering as rainfall increases. Finally, m, as estimated from trees greater than 1 cm trunk diameter, were significantly larger than an estimation based on trees greater than 10 cm trunk diameter. This suggests a cumulative effect of environmental filtering upon trees throughout their ontogeny.
Article
Neutral models in ecology have attracted much attention in recent literature. They can provide considerable insight into the roles of non-species-specific factors (e.g. stochasticity, dispersal, speciation) on community dynamics but often require intensive simulations, particularly in spatial settings. Here, we clearly explain existing techniques for modelling spatially explicit neutral processes in ecology using coalescence. Furthermore, we present several novel extensions to these methods including procedures for dealing with system boundaries which enable improved investigation of the effects of dispersal. We also present a semi-analytical algorithm that calculates the expected species richness in a sample, for any speciation rate. By eliminating the effect of stochasticity in the speciation process, we reduce the variance in estimates of species richness. Our benchmarks show that the combination of existing coalescence theory and our extensions produces higher quality results in vastly shorter time scales than previously possible: years of simulation time are reduced to minutes. As an example application, we find parameters for a spatially explicit neutral model to approximate the species richness of a tropical forest dataset.
Article
1. There is a limit to the similarity (and hence to the number) of competing species which can coexist. The total number of species is proportional to the total range of the environment divided by the niche breadth of the species. The number is reduced by unequal abundance of resources but increased by adding to the dimensionality of the niche. Niche breadth is increased with increased environmental uncertainty and with decreased productivity. 2. There is a different evolutionary limit, L, to the similarity of two coexisting species such that a) If two species are more similar than L, a third intermediate species will converge toward the nearer of the pair. b) If two species are more different than L, a third intermediate species will diverge from either toward a phenotype intermediate between the two.
Article
. Assembly rules provide one possible unifying framework for community ecology. Given a species pool, and measured traits for each species, the objective is to specify which traits (and therefore which subset of species) will occur in a particular environment. Because the problem primarily involves traits and environments, answers should be generalizable to systems with very different taxonomic composition. In this context, the environment functions like a filter (or sieve) removing all species lacking specified combinations of traits. In this way, assembly rules are a community level analogue of natural selection. Response rules follow a similar process except that they transform a vector of species abundances to a new vector using the same information. Examples already exist from a range of habitats, scales, and kinds of organisms.
Article
Plant communities have traditionally been viewed as either a random collection of individuals or as organismal entities. For most ecologists however, neither perspective provides a modern comprehensive view of plant communities, but we have yet to formalize the view that we currently hold. Here, we assert that an explicit re-consideration of formal community theory must incorporate interactions that have recently been prominent in plant ecology, namely facilitation and indirect effects among competitors. These interactions do not support the traditional individualistic perspective. We believe that rejecting strict individualistic theory will allow ecologists to better explain variation occurring at different spatial scales, synthesize more general predictive theories of community dynamics, and develop models for community-level responses to global change. Here, we introduce the concept of the integrated community (IC) which proposes that range from highly natural plant communities individualistic to highly interdependent depending on synergism among: (i) stochastic processes, (ii) the abiotic tolerances of species, (iii) positive and negative interactions among plants, and (iv) indirect interactions within and between trophic levels. All of these processes are well accepted by plant ecologists, but no single theory has sought to integrate these different processes into our concept of communities.
Article
Limiting similarity means that there is some maximum level of similarity (ie. similar use of a set of resources that are in short supply) between competing species short of complete identity (complete overlap) that will allow these species to coexist. The 1st part of this review discusses a proposed general limit, and suggests that such does not exist. The 2nd part looks at cases where there appear to be no limits to similarity and argues that there actually are limits if similarity is appropriately defined. The 3rd part discusses factors that may affect the limit in specific cases. The 4th part examines field observations relevant to theories of limiting similarity and considers the use of the theory in explaining patterns in nature.-P.J.Jarvis
Article
Ecology Letters (2011) 14: 816–827 Statistical models are the traditional choice to test scientific theories when observations, processes or boundary conditions are subject to stochasticity. Many important systems in ecology and biology, however, are difficult to capture with statistical models. Stochastic simulation models offer an alternative, but they were hitherto associated with a major disadvantage: their likelihood functions can usually not be calculated explicitly, and thus it is difficult to couple them to well-established statistical theory such as maximum likelihood and Bayesian statistics. A number of new methods, among them Approximate Bayesian Computing and Pattern-Oriented Modelling, bypass this limitation. These methods share three main principles: aggregation of simulated and observed data via summary statistics, likelihood approximation based on the summary statistics, and efficient sampling. We discuss principles as well as advantages and caveats of these methods, and demonstrate their potential for integrating stochastic simulation models into a unified framework for statistical modelling.
Article
Understanding the forces that influence natural variation within and among populations has been a major objective of evolutionary biologists for decades. Motivated by the growth in computational power and data complexity, modern approaches to this question make intensive use of simulation methods. Approximate Bayesian Computation (ABC) is one of these methods. Here we review the foundations of ABC, its recent algorithmic developments, and its applications in evolutionary biology and ecology. We argue that the use of ABC should incorporate all aspects of Bayesian data analysis: formulation, fitting, and improvement of a model. ABC can be a powerful tool to make inferences with complex models if these principles are carefully applied.
Article
I present a model of stochastic community dynamics in which death occurs randomly in the community, propagules disperse randomly from a regional pool, and recruitment of new individuals of a species is proportional to the species local abundance multiplied by its local competitive ability. The competitive ability of a species is assumed to be determined by a function of one trait of the species, and I call this function the environmental filtering function. I show that information on local species abundances in a network of plots, together with trait data for each species, enables the inference of both the immigration rate and the environmental filtering function in each plot. I further study how the diversity patterns produced by this model deviate from the neutral predictions, and how this deviation depends on the characteristics of the environmental filtering function. I show that this inference framework is more powerful at detecting trait-based environmental filtering than existing statistical approaches based on trait distributions, and discuss how the predictions of this model could be used to assess environmental heterogeneity in a plot, to detect functionally meaningful trade-offs among species traits, and to test the assumption that there exists a simple relationship between species traits and local competitive ability.
Article
Patterns of phylogenetic relatedness within communities have been widely used to infer the importance of different ecological and evolutionary processes during community assembly, but little is known about the relative ability of community phylogenetics methods and null models to detect the signature of processes such as dispersal, competition and filtering under different models of trait evolution. Using a metacommunity simulation incorporating quantitative models of trait evolution and community assembly, I assessed the performance of different tests that have been used to measure community phylogenetic structure. All tests were sensitive to the relative phylogenetic signal in species metacommunity abundances and traits; methods that were most sensitive to the effects of niche-based processes on community structure were also more likely to find non-random patterns of community phylogenetic structure under dispersal assembly. When used with a null model that maintained species occurrence frequency in random communities, several metrics could detect niche-based assembly when there was strong phylogenetic signal in species traits, when multiple traits were involved in community assembly, and in the presence of environmental heterogeneity. Interpretations of the causes of community phylogenetic structure should be modified to account for the influence of dispersal.
Article
In this essay, I argue that the seemingly indestructible concept of the community as a local, interacting assemblage of species has hindered progress toward understanding species richness at local to regional scales. I suggest that the distributions of species within a region reveal more about the processes that generate diversity patterns than does the co-occurrence of species at any given point. The local community is an epiphenomenon that has relatively little explanatory power in ecology and evolutionary biology. Local coexistence cannot provide insight into the ecogeographic distributions of species within a region, from which local assemblages of species derive, nor can local communities be used to test hypotheses concerning the origin, maintenance, and regulation of species richness, either locally or regionally. Ecologists are moving toward a community concept based on interactions between populations over a continuum of spatial and temporal scales within entire regions, including the population and evolutionary processes that produce new species.