Functional trait assembly through ecological and evolutionary time

A classic community assembly hypothesis is that all guilds must be represented before additional species from any given guild enter the community. We conceptually extend this hypothesis to continuous functional traits, refine the hypothesis with an eco-evolutionary model of interaction network community assembly, and compare the resultant continuous trait assembly rule to empirical data. Our extension of the “guild assembly rule” to continuous functional traits was rejected, in part, because the eco-evolutionary model predicted trait assembly to be characterized by the expansion of trait space and trait/species sorting within trait space. Hence, the guild rule may not be broadly applicable. A “revised” assembly rule did, however, emerge from the eco-evolutionary model: as communities assemble, the range in trait values will increase to a maximum and then remain relatively constant irrespective of further changes in species richness. This rule makes the corollary prediction that the trait range will, on average, be a saturating function of species richness. To determine if the assembly rule is at work in natural communities, we compared this corollary prediction to empirical data. Consistent with our assembly rule, trait “space” (broadly defined) commonly saturates with species richness. Our assembly rule may thus represent a general constraint placed on community assembly. In addition, taxonomic scale similarly influences the predicted and empirically observed relationship between trait “space” and richness. Empirical support for the model’s predictions suggests that studying continuous functional traits in the context of eco-evolutionary models is a powerful approach for elucidating general processes of community assembly.     

Quantifying trait selection driving community assembly: a test in herbaceous plant communities under contrasted land use regimes

Plant traits are particularly important in determining plant community structure. However, how can one identify which traits are the most important in driving community assembly? Here we propose a method 1) to quantify the direction and strength of trait selection during community assembly and 2) to obtain parsimonious lists of traits that can predict species relative abundances in plant communities. We tested our method using floristic data from 32 plots experiencing different treatments (fertilisation and grazing) in southern France. Twelve functional traits were measured on 68 species. We determined the direction and strength of selection on these 12 traits using a metric derived from a maximum entropy model (i.e. lambda). We then determined our parsimonious list of traits using a backward selection of traits based on these lambda values (for all treatments and in each treatment separately). We finally compared our method to two other methods: one based on iterative RLQ and the other based on an entropy‐based forward selection of traits. We found major differences in the direction and strength of selection across the 12 traits and treatments. From the 12 traits, plant vegetative and reproductive heights, leaf dry matter content leaf nitrogen content, specific leaf area, and leaf phosphorus content were particularly important for predicting species relative abundances when considering all treatments together. Our method yielded results similar to those produced by the entropy‐based approach but differed from those produced by the iterative RLQ, whose selected traits could not significantly predict species relative abundances. Together these results suggest that the assembly of these communities is primarily driven by a small number of key functional traits. We argue that our method provides an objective way of determining a parsimonious list of traits that together accurately predict community structure and which, despite its complementarities with entropy‐based method, offers significant advantages.     

Limitations of entropy maximization in ecology: a reply to Haegeman and Loreau

Haegeman and Loreau published a paper that is primarily a criticism of a maximum entropy model of trait-based community assembly (by Shipley et al.) and purports to show the limitations of this method in ecology. However, they misunderstood the basic purpose, logic and justification of the maximum entropy formalism and, because of this, leveled criticisms of Shipley et al. that are unfounded. Part of the confusion can be traced to sloppy presentation of the underlying approach in Shipley et al. The confusion arises because maximum entropy models are justified based on information theory and Bayesian logic while the interpretation that Haegeman and Loreau present is based on substantive empirical assumptions about microstate allocations and a combinatorial argument that do not apply to maximum entropy models and which I do not apply to my model in particular.     

The importance of spatial scale for trait–abundance relations

The concept of community assembly through trait‐based environmental filtering has played a key role in our understanding of how communities change over space and time, however, the importance of spatial scale in the filtering process remains unclear. We propose that different environmental filters may operate at different spatial scales, and that filters at finer scales would be nested within those acting at coarser scales. We tested for the existence of spatially nested sets of trait‐based filters in a temperate native grassland by applying the recently proposed maximum entropy (MaxEnt) approach to trait‐based community assembly, which we extend through a trait selection procedure. We found that different traits were important in influencing the abundances of species at the three different spatial scales examined (micro‐habitat, habitat, landscape), supporting the idea that trait based filtering processes operating at coarse spatial scales can be quite distinct from those operating at fine scales. Despite this result, we identified several traits which were frequently related to abundance at all spatial scales. Taken together, our results support the proposition that trait‐based environmental filters at finer spatial scales are nested within those operating at coarser scales. We compared our results to those obtained using a simpler trait‐by‐trait analytical approach (correlation analysis and MaxEnt on individual traits). The capacity for MaxEnt to incorporate multiple traits simultaneously provided unique insights into the important traits at each spatial scale and presents significant advantages over existing univariate and multivariate approaches.     

Functional trait differences influence neighbourhood interactions in a hyperdiverse Amazonian forest

As distinct community assembly processes can produce similar community patterns, assessing the ecological mechanisms promoting coexistence in hyperdiverse rainforests remains a considerable challenge. We use spatially explicit neighbourhood models of tree growth to quantify how functional trait and phylogenetic similarities predict variation in growth and crowding effects for the 315 most abundant tree species in a 25‐ha lowland rainforest plot in Ecuador. We find that functional trait differences reflect variation in (1) species maximum potential growth, (2) the intensity of interspecific interactions for some species, and (3) species sensitivity to neighbours. We find that neighbours influenced tree growth in 28% of the 315 focal tree species. Neighbourhood effects are not detected in the remaining 72%, which may reflect the low statistical power to model rare taxa and/or species insensitivity to neighbours. Our results highlight the spectrum of ways in which functional trait differences can shape community dynamics in highly diverse rainforests.     

cati: an R package using functional traits to detect and quantify multi‐level community assembly processes

Community ecologists are active in describing species by their functional traits, quantifying the functional structure of plant and animal assemblages and inferring community assembly processes with null‐model analyses of trait distribution and functional diversity indices. Intraspecific variation in traits and effects of spatial scale are potentially important in these analyses. Here, we introduce the R package cati (Community Assembly by Traits: Individuals and beyond) available on CRAN, for the analysis of community assembly with functional traits. cati builds on a recent approach to community assembly that explicitly incorporates individual differences in community assembly analyses and decomposes phenotypic variations across scales and organizational levels, based on three phenotypic variance ratios, termed the T‐statistics. More generally, the cati package 1) calculates a variety of single‐trait and multi‐trait indices from interspecific and intraspecific trait measures; 2) it partitions functional trait variation among spatial and taxonomic levels; 3) it implements a palette of flexible null models for detecting non‐random patterns of functional traits. These patterns can be used to draw inferences about hypotheses of community assembly such as environmental filtering and species interactions. The basic input for cati is a data frame in which columns are traits, rows are species or individuals, and entries are the measured trait values. The cati package can also incorporate a square distance matrix into analyses, which could include phylogenetic or genetic distances among individuals or species. Users select from a variety of functional trait metrics and analyze these relative to a null model that specifies trait distributions in a regional source pool.     

The ecology of differences: assessing community assembly with trait and evolutionary distances

Species enter and persist in local communities because of their ecological fit to local conditions, and recently, ecologists have moved from measuring diversity as species richness and evenness, to using measures that reflect species ecological differences. There are two principal approaches for quantifying species ecological differences: functional (trait‐based) and phylogenetic pairwise distances between species. Both approaches have produced new ecological insights, yet at the same time methodological issues and assumptions limit them. Traits and phylogeny may provide different, and perhaps complementary, information about species' differences. To adequately test assembly hypotheses, a framework integrating the information provided by traits and phylogenies is required. We propose an intuitive measure for combining functional and phylogenetic pairwise distances, which provides a useful way to assess how functional and phylogenetic distances contribute to understanding patterns of community assembly. Here, we show that both traits and phylogeny inform community assembly patterns in alpine plant communities across an elevation gradient, because they represent complementary information. Differences in historical selection pressures have produced variation in the strength of the trait‐phylogeny correlation, and as such, integrating traits and phylogeny can enhance the ability to detect assembly patterns across habitats or environmental gradients.     

Incorporating intraspecific variation in tests of trait-based community assembly

Environmental filtering and niche differentiation are processes proposed to drive community assembly, generating nonrandom patterns in community trait distributions. Despite the substantial intraspecific trait variation present in plant communities, most previous studies of trait-based community assembly have used species mean trait values and therefore not accounted for intraspecific variation. Using a null model approach, I tested for environmental filtering and niche differentiation acting on three key functional traits??vegetative height, specific leaf area (SLA), and leaf dry matter content (LDMC)??in old-field plant communities. I also examined how accounting for intraspecific variation at the among-plot and individual levels affected the detection of nonrandom assembly patterns. Tests using fixed species mean trait values provided evidence of environmental filtering acting on height and SLA and niche differentiation acting on SLA. Including plot-level intraspecific variation increased the strength of these patterns, indicating an important role of intraspecific variation in community assembly. Tests using individual trait data indicated strong environmental filtering acting on all traits, but provided no evidence of niche differentiation, although these signals may have been obscured by the effects of dispersal limitation and spatial aggregation of conspecific individuals. There was also strong evidence of nonrandom assembly of individuals within single species, with the strength of environmental filtering varying among species. This study demonstrates that, while analyses using fixed species mean trait values can provide insights into community assembly processes, accounting for intraspecific variation provides a more complete view of communities and the processes driving their assembly.     

Contrasting patterns of trait‐based community assembly in lianas and trees from temperate Australia

Trait variation in plant communities is thought to be constrained by two opposing community assembly processes operating at discrete spatial scales: habitat filtering and limiting similarity between coexisting species. Filtering processes cause convergence in ecological strategy as species are excluded from unsuitable sites, whilst limiting similarity leads to the divergence of trait values between co‐occurring species in order to alleviate competition for finite resources. Levels of alpha (within‐site) and beta (among‐site) trait variation can be indicative of the strength of these community assembly processes. We used trait‐gradient analysis to explicitly compare evidence of community assembly patterns in lianas (woody vines) and trees. These two growth forms exhibit striking differences in carbon capture and regeneration strategies, yet trait‐based mechanisms that maintain their coexistence remain understudied. Using data for four functional traits – leaf mass per area, leaf nitrogen content (N_mass), leaf area and seed mass – we partitioned interspecific trait variation in lianas and trees into alpha and beta components. Our three key findings were: 1) lianas and trees exhibit divergent patterns of trait‐based habitat filtering, due to differences in the relationship between leaf size and the other three traits examined (LMA, N_mass and seed mass), 2) on average, liana species possess smaller seeds, lower LMA and higher N_mass than do trees, but there was no clear difference in leaf area between the two growth forms, and 3) soil fertility was correlated with trait variation (leaf area, seed mass) at the site‐level in trees, but not in lianas. These results provide evidence that dominant growth forms can be filtered into the same habitat on the basis of different combinations of traits. Our findings have important implications for community assembly and co‐existence theory and for more pragmatic matters such as using trait‐based principles to inform community restoration.     

Ontogenetic trait variation and metacommunity effects influence species relative abundances during tree community assembly

Predicting species abundance is one of the most fundamental pursuits of ecology. Combining the information encoded in functional traits and metacommunities provides a new perspective to predict the abundance of species in communities. We applied a community assembly via trait selection model to predict quadrat-scale species abundances using functional trait variation on ontogenetic stages and metacommunity information for over 490 plant species in a subtropical forest and a lowland tropical forest in Yunnan, China. The relative importance of trait-based selection, mass effects, and stochasticity in shaping local species abundances is evaluated using different null models. We found both mass effects and trait selection contribute to local abundance patterns. Trait selection was detectable at all studied spatial scales (0.04–1 ha), with its strength stronger at larger scales and in the subtropical forest. In contrast, the importance of stochasticity decreased with spatial scale. A significant mass effect of the metacommunity was observed at small spatial scales. Our results indicate that tree community assembly is primarily driven by ontogenetic traits and metacommunity effects. Our findings also demonstrate that including ontogenetic trait variation into predictive frameworks allows ecologists to infer ecological mechanisms operating in community assembly at the individual level.     

Plant traits,species pools and the prediction of relative abundance in plant communities: a maximum entropy approach

Questions: To what extent can Shipley et al.'s original maximum entropy model of trait‐based community assembly predict relative abundances of species over a large (3000 km²) landscape? How does variation in the species pool affect predictive ability of the model? How might the effects of missing traits be detected? How can non‐trait‐based processes be incorporated into the model? Location: Central England. Material and Methods: Using 10 traits measured on 506 plant species from 1308 1‐m² plots collected over 3000 km² in central England, we tested one aspect of Shipley et al.'s original maximum entropy model of “pure” trait‐based community assembly (S₁), and modified it to represent both a neutral (S₂) and a hybrid (S₃) scenario of community assembly at the local level. Predictive ability of the three corresponding models was determined with different species pool sizes (30, 60, 100 and 506 species). Statistical significance was tested using a distribution‐free permutation test. Results: Predictive ability was high and significantly different from random expectations in S₁. Predictive ability was low but significant in S₂. Highest predictive ability occurred when both neutral and trait‐based processes were included in the model (S₃). Increasing the pool size decreased predictive ability, but less so in S₃. Incorporating habitat affinity (to indicate missing traits) increased predictive ability. Conclusions: The measured functional traits were significantly related to species relative abundance. Our results both confirm the generality of the original model but also highlight the importance of (i) taking into account neutral processes during assembly of a plant community, and (ii) properly defining the species pool.     

Discriminating trait‐convergence and trait‐divergence assembly patterns in ecological community gradients

Question: Whereas similar ecological requirements lead to trait‐convergence assembly patterns (TCAP) of species in communities, the interactions controlling how species associate produce trait‐divergence assembly patterns (TDAP). Yet, the linking of the latter to community processes has so far only been suggested. We offer a method to elucidate TCAP and TDAP in ecological community gradients that will help fill this gap. Method: We evaluated the correlation between trait‐based described communities and ecological gradients, and using partial correlation, we separated the fractions reflecting TCAP and TDAP. The required input data matrices describe operational taxonomic units (OTUs) by traits, communities by the quantities or presence‐absence of these OTUs, and community sites by ecological variables. We defined plant functional types (PFTs) or species as community components after fuzzy weighting by the traits. The measured correlations for TCAP and TDAP were tested by permutation. The null model for TDAP preserves the trait convergence, the structure intrinsic in the fuzzy types, and community total abundances and autocorrelation. Results: We applied the method to trait‐based data from plant communities in south Brazil, one set in natural grassland experimental plots under different nitrogen and grazing levels, and another in sapling communities colonizing Araucaria forest patches of increasing size in a forest‐grassland mosaic. In these cases, depending on the traits considered, we found strong evidence of either TCAP or TDAP, or both, that was related to the environmental gradients. Conclusions: The method developed is able to reveal TCAP and TDAP that are more likely to be functional for specified ecological gradients, allowing establishment of objective hypotheses on their links to community processes.     

On testing predictions of species relative abundance from maximum entropy optimisation

A randomisation test is described for assessing relative abundance predictions from the maximum entropy approach to biodiversity. The null model underlying the test randomly allocates observed abundances to species, but retains key aspects of the structure of the observed communities; site richness, species composition, and trait covariance. Three test statistics are used to explore different characteristics of the predictions. Two are based on pairwise comparisons between observed and predicted species abundances (RMSE, RMSE_Sqrt). The third statistic is novel and is based on community‐level abundance patterns, using an index calculated from the observed and predicted community entropies (E_Diff). Validation of the test to quantify type I and type II error rates showed no evidence of bias or circularity, confirming the dependencies quantified by Roxburgh and Mokany (2007) and Shipley (2007) have been fully accounted for within the null model. Application of the test to the vineyard data of Shipley et al. (2006) and to an Australian grassland dataset indicated significant departures from the null model, suggesting the integration of species trait information within the maximum entropy framework can successfully predict species abundance patterns. The paper concludes with some general comments on the use of maximum entropy in ecology, including a discussion of the mathematics underlying the Maxent optimisation algorithm and its implementation, the role of absent species in generating biased predictions, and some comments on determining the most appropriate level of data aggregation for Maxent analysis.     

植物群落构建机制研究进展

群落构建研究对于解释物种共存和物种多样性的维持是至关重要的,因此一直是生态学研究的中心论题。尽管近年来关于生态位和中性理论的验证研究已经取得了显著的成果,但对于局域群落构建机制的认识仍存在很大争议。随着统计和理论上的进步使得用功能性状和群落谱系结构解释群落构建机制变为可能,主要是通过验证共存物种的性状和谱系距离分布模式来实现。然而,谱系和功能性状不能相互替代,多种生物和非生物因子同时控制着群落构建,基于中性理论的扩散限制、基于生态位的环境过滤和竞争排斥等多个过程可能同时影响着群落的构建。所以,综合考虑多种方法和影响因素探讨植物群落的构建机制,对于预测和解释植被对干扰的响应,理解生物多样性维持机制有重要意义。试图在简要回顾群落构建理论及研究方法发展的基础上,梳理其最新研究进展,并探讨整合功能性状及群落谱系结构的研究方法,解释群落构建和物种多样性维持机制的可能途径。在结合功能性状和谱系结构研究群落构建时,除了考虑空间尺度、环境因子、植被类型外,还应该关注时间尺度、选择性状的种类和数量、性状的种内变异、以及人为干扰等因素对群落构建的影响。     

A conceptual framework for the spatial analysis of functional trait diversity

Functional trait diversity is a popular tool in modern ecology, mainly used to infer assembly processes and ecosystem functioning. Patterns of functional trait diversity are shaped by ecological processes such as environmental filtering, species interactions and dispersal that are inherently spatial, and different processes may operate at different spatial scales. Adding a spatial dimension to the analysis of functional trait diversity may thus increase our ability to infer community assembly processes and to predict change in assembly processes following disturbance or land‐use change. Richness, evenness and divergence of functional traits are commonly used indices of functional trait diversity that are known to respond differently to large‐scale filters related to environmental heterogeneity and dispersal and fine‐scale filters related to species interactions (competition). Recent developments in spatial statistics make it possible to separately quantify large‐scale patterns (variation in local means) and fine‐scale patterns (variation around local means) by decomposing overall spatial autocorrelation quantified by Moran's coefficient into its positive and negative components using Moran eigenvector maps (MEM). We thus propose to identify the spatial signature of multiple ecological processes that are potentially acting at different spatial scales by contrasting positive and negative components of spatial autocorrelation for each of the three indices of functional trait diversity. We illustrate this approach with a case study from riparian plant communities, where we test the effects of disturbance on spatial patterns of functional trait diversity. The fine‐scale pattern of all three indices was increased in the disturbed versus control habitat, suggesting an increase in local scale competition and an overall increase in unexplained variance in the post‐disturbance versus control community. Further research using simulation modeling should focus on establishing the proposed link between community assembly rules and spatial patterns of functional trait diversity to maximize our ability to infer multiple processes from spatial community structure.     

吉林蛟河针阔混交林功能性状分布格局及其对地形因素的响应

森林群落的构建过程及其内在机制是生态学研究的热点问题。植物功能性状是指能够代表植物的生活史策略,反映植物对环境变化响应的一系列植物属性。通过植物功能性状的分布格局及其对环境因素的响应有助于推测群落的构建过程及其内在作用机制。以吉林蛟河21.12hm²温带针阔混交林样地为研究对象,采集并测量了样地内34种木本植物的6种不同的功能性状。以20m×20m的样方为研究单元,通过计算平均成对性状距离指数（mean pairwise trait distance;PW）和平均最近邻体性状距离指数（mean nearest neighbor trait distance;NN）来探讨群落中单个性状和综合性状的分布格局。同时结合地形因子采用回归分析探讨功能性状的分布格局对局域生境变化的响应。基于PW的结果显示：单个性状中除叶面积外,其余性状的分布格局均为聚集分布多于离散分布;基于NN的结果显示：除叶面积和最大树高外,其余性状的分布格局为聚集分布多于离散分布。此外,由6种单个性状组成的综合性状的分布格局同样为聚集分布多于离散分布。基于回归分析的结果显示：森林群落中功能性状的分布格局受到海拔、坡度和坡向等因素的显著影响,而凹凸度的影响则不显著。研究结果表明包括环境过滤和生物相互作用的非随机过程能够影响温带针阔混交林的群落构建过程,中性过程对该区域群落构建过程的影响不显著。     

VIABILITY SELECTION ON SEASONALLY POLYPHENIC TRAITS: WING MELANIN PATTERN IN WESTERN WHITE BUTTERFLIES

Wing melanin pattern varies seasonally among generations in many populations of the butterfly Pontia occidentalis, leading to distinctly different wing phenotypes during spring and summer generations. Estimates of directional selection on wing pattern can therefore quantify the imperfection of this phenotypically plastic (polyphenic) response in generating “optimal” phenotypes for each seasonal generation. Mark-release-recapture (MRR) studies were used to estimate directional selection on six wing traits in a natural population of P. occidentalis during both spring and summer weather conditions. Estimated survival and recapture probabilities varied substantially among the four MRR studies. When differences between males and females were detected, the survival and recapture probabilities were higher for males than for females. Estimated selection coefficients suggested that the direction of selection on one wing trait important for thermoregulation, melanin on the base of the dorsal hindwings (trait hb), fluctuated seasonally; there was evidence of directional selection for increased hb in the spring studies and for decreased hb in the summer studies. Such fluctuating seasonal selection on hb implies that the seasonal polyphenic response may not be sufficient to eliminate selection on this trait; the slope of the reaction-norm mapping hb onto seasonal environmental cues is too shallow, resulting in further selection on the reaction norm. Adaptive evolution of the reaction norm may be constrained by phenotypic and genetic correlations with other wing traits that experience different patterns of selection and by variable weather conditions within seasons and among years.     

Using phylogeny and functional traits for assessing community assembly along environmental gradients: A deterministic process driven by elevation

Community assembly processes is the primary focus of community ecology. Using phylogenetic‐based and functional trait‐based methods jointly to explore these processes along environmental gradients are useful ways to explain the change of assembly mechanisms under changing world. Our study combined these methods to test assembly processes in wide range gradients of elevation and other habitat environmental factors. We collected our data at 40 plots in Taibai Mountain, China, with more than 2,300 m altitude difference in study area and then measured traits and environmental factors. Variance partitioning was used to distinguish the main environment factors leading to phylogeny and traits change among 40 plots. Principal component analysis (PCA) was applied to colligate other environment factors. Community assembly patterns along environmental gradients based on phylogenetic and functional methods were studied for exploring assembly mechanisms. Phylogenetic signal was calculated for each community along environmental gradients in order to detect the variation of trait performance on phylogeny. Elevation showed a better explanatory power than other environment factors for phylogenetic and most traits’ variance. Phylogenetic and several functional structure clustered at high elevation while some conserved traits overdispersed. Convergent tendency which might be caused by filtering or competition along elevation was detected based on functional traits. Leaf dry matter content (LDMC) and leaf nitrogen content along PCA 1 axis showed conflicting patterns comparing to patterns showed on elevation. LDMC exhibited the strongest phylogenetic signal. Only the phylogenetic signal of maximum plant height showed explicable change along environmental gradients. Synthesis. Elevation is the best environment factors for predicting phylogeny and traits change. Plant's phylogenetic and some functional structures show environmental filtering in alpine region while it shows different assembly processes in middle‐ and low‐altitude region by different trait/phylogeny. The results highlight deterministic processes dominate community assembly in large‐scale environmental gradients. Performance of phylogeny and traits along gradients may be independent with each other. The novel method for calculating functional structure which we used in this study and the focus of phylogenetic signal change along gradients may provide more useful ways to detect community assembly mechanisms.     

Trait response in communities to environmental change: effect of interspecific competition and trait covariance structure

The response of ecological communities to environmental disturbances depends not just on the number of species they contain but also on the functional diversity of the constituent species; greater variation in the tolerance of species to different environmental disturbances is generally thought to confer greater resistance to the community. Here, I investigate how the functional diversity of communities changes with environmental disturbances. Specifically, I assume that there is variation in traits among species that confer tolerance or sensitivity to environmental disturbances. When a disturbance occurs, variation in species tolerances causes changes in the relative abundances of species, which in turn changes the average tolerance of the community. For example, if tolerance to an environmental disturbance is conferred by large body size, then the environmental disturbance should be expected to increase the average body size of individuals in the community. Despite this expectation, ecological interactions among species can affect the average community response. For example, if larger species are also strong competitors with each other, then this might reduce the increase in average body size in the community, because interspecific competition limits the grow in population density of large bodied species. Similarly, when disturbances affect multiple traits, the covariance in the distribution of trait values among species may restrict the response of any one trait; if two traits provide tolerance to the same disturbance but negatively covary among species, then the response of one trait will limit the response of the other trait at the community level. Using a Lotka–Volterra model for competitive communities, I derive general formulae that generate explicit predictions about the changes in average trait values in a community subject to environmental disturbances. These formulae demonstrate that competition can impede the change in average community trait values. However, the impediment is not considerable in comparison to the predominant factors of trait variances and species selection effects when species with the most similar trait values also experience the greatest interspecific competition. Similarly, negative covariances among different traits that confer resistance to the same environmental disturbance will impede their responses. I illustrate these results using phytoplankton data from a whole-lake experiment in which manipulation to the zooplankton community created a disturbance to the phytoplankton that changed the selective consumption of large vs. small phytoplankton.     

Patterns and Processes of Microbial Community Assembly

SUMMARY

Recent research has expanded our understanding of microbial community assembly. However, the field of community ecology is inaccessible to many microbial ecologists because of inconsistent and often confusing terminology as well as unnecessarily polarizing debates. Thus, we review recent literature on microbial community assembly, using the framework of Vellend (Q. Rev. Biol. 85:183–206, 2010) in an effort to synthesize and unify these contributions. We begin by discussing patterns in microbial biogeography and then describe four basic processes (diversification, dispersal, selection, and drift) that contribute to community assembly. We also discuss different combinations of these processes and where and when they may be most important for shaping microbial communities. The spatial and temporal scales of microbial community assembly are also discussed in relation to assembly processes. Throughout this review paper, we highlight differences between microbes and macroorganisms and generate hypotheses describing how these differences may be important for community assembly. We end by discussing the implications of microbial assembly processes for ecosystem function and biodiversity.