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.     

Mountain metacommunities: climate and spatial connectivity shape ant diversity in a complex landscape

Understanding what drives biodiversity patterns across scales is a central goal of ecology. Both environmental gradients and spatial landscape structure have been found to be important factors influencing species distributions and community composition, and partly reflect the balance of underlying deterministic and stochastic community processes. In some systems, environmental gradients and spatial connectivity are intertwined in that steep environmental gradients serve as boundaries on species movements and impose environment‐derived complex spatial structure to metacommunities. Mountainous landscapes are prime examples of this, and recent theory has linked principles of geomorphology, environmental gradients, and spatial structure to make predictions for resulting community patterns. In this context, we examine variation in taxonomic and phylogenetic ant diversity patterns along a geographic transect spanning > 5000 m in elevational range in the Hengduan mountains of southern China. We found that environmental gradients dominate variation in both alpha and beta diversity in this landscape, with alpha diversity strongly declining with elevation and beta diversity driven by elevational differences. However, within an elevational band spatial connectivity predicts beta diversity better than geographic distance. Our findings deviate from theoretical predictions in several ways, notably alpha diversity is monotonically declining and within‐band beta diversity is invariant with increasing elevation. The discrepancies between theory and observation may be explained by differences in the Hengduan landscape from idealized fluvial landscapes, such as a lack of a mid‐elevation peak in connectivity, as well as evolutionary limits on the source pool of species available to populate metacommunities at different elevations. The latter is supported by variation in phylogenetic community structure with elevation. Our results demonstrate the power of conceptual, statistical, and theoretical frameworks that integrate the roles of environment and spatial structure in metacommunities, but that additional work is needed to bridge the gap between abstract theory and real systems.     

Integrating phylogenetic community structure with species distribution models: an example with plants of rock barrens

Approaches using phylogenetic pattern in ecological communities to deduce processes of community assembly have been criticised as disconnected from foundations in ecological mechanism, especially with respect to lack of data about abiotic and biotic niches. These criticisms can be addressed with analyses of organismal traits that underlie environmental filtering, competitive exclusion, and other candidate processes; however, the difficulty of assembling large trait databases means that such studies remain uncommon. We suggest a synthesis of phylogenetic community structure analysis and species distribution modeling that we believe can allow inference about community processes without prohibitive data requirements. We illustrate this method for angiosperm communities of rock barrens in eastern Canada. First, we analyzed phylogenetic community structure of four rock‐barren sites at three nested spatial scales (quadrat to region). For the nine most common species in our barrens, we used regional occurrence records to build species distribution models identifying environmental drivers of the nine species’ distributions. Coefficients of these models represent implicit trait data that summarize each species’ response to the environmental drivers in the model. We then tested for phylogenetic signal in these traits, to ask whether ecological forces acting on them could be generating phylogenetic community structure. We found strong phylogenetic clustering at the quadrat level, while patterns at larger scales were complex. Our distribution model suggested drought stress as the dominant driver for distributions of all the species, consistent with local correlations with soil depth, and the species’ responses to drought showed strong phylogenetic signal. The convergence of results from phylogenetic community structure and species distribution modeling suggests that barren communities are structured at the quadrat level by environmental filtering effects of moisture stress, to which species have phylogenetically patterned responses.     

Effects of neutrality and productivity on mammal richness and evolutionary history in Australia

Explaining how heterogeneous spatial patterns of species diversity emerge is one of the most fascinating questions of biogeography. One of the great challenges is revealing the mechanistic effect of environmental variables on diversity. Correlative analyses indicate that productivity is associated with taxonomic, phylogenetic, and functional diversity of communities. Surprisingly, no unifying body of theory have been developed to understand the mechanism by which spatial variation of productivity affects the fundamental processes of biodiversity. Based on widely discussed verbal models in ecology about the effect of productivity on species diversity, we developed a spatially explicit neutral model that incorporates the effect of primary productivity on community size and confronted our model's predictions with observed patterns of species richness and evolutionary history of Australian terrestrial mammals. The imposed restrictions on community size create larger populations in areas of high productivity, which increases community turnover and local speciation, and reduces extinction. The effect of productivity on community size modeled in our study causes higher accumulation of species diversity in productive regions even in the absence of niche‐based processes. However, such a simple model is not capable of reproducing spatial patterns of mammal evolutionary history in Australia, implying that more complex evolutionary mechanisms are involved. Our study demonstrates that the overall patterns of species richness can be directly explained by changes in community sizes along productivity gradients, supporting a major role of processes associated with energetic constraints in shaping diversity patterns.     

From diversity indices to community assembly processes: a test with simulated data

Ecological theory suggests that spatial distribution of biodiversity is strongly driven by community assembly processes. Thus the study of diversity patterns combined with null model testing has become increasingly common to infer assembly processes from observed distributions of diversity indices. However, results in both empirical and simulation studies are inconsistent. The aim of our study is to determine with simulated data which facets of biodiversity, if any, may unravel the processes driving its spatial patterns, and to provide practical considerations about the combination of diversity indices that would produce significant and congruent signals when using null models. The study is based on simulated species’ assemblages that emerge under various landscape structures in a spatially explicit individual‐based model with contrasting, predefined assembly processes. We focus on four assembly processes (species‐sorting, mass effect, neutral dynamics and competition colonization trade‐off) and investigate the emerging species’ distributions with varied diversity indices (alpha, beta and gamma) measured at different spatial scales and for different diversity facets (taxonomic, functional and phylogenetic). We find that 1) the four assembly processes result in distinct spatial distributions of species under any landscape structure, 2) a broad range of diversity indices allows distinguishing between communities driven by different assembly processes, 3) null models provide congruent results only for a small fraction of diversity indices and 4) only a combination of these diversity indices allows identifying the correct assembly processes. Our study supports the inference of assembly processes from patterns of diversity only when different types of indices are combined. It highlights the need to combine phylogenetic, functional and taxonomic diversity indices at multiple spatial scales to effectively infer underlying assembly processes from diversity patterns by illustrating how combination of different indices might help disentangling the complex question of coexistence.     

The contribution of rare species to community phylogenetic diversity across a global network of forest plots

Niche differentiation has been proposed as an explanation for rarity in species assemblages. To test this hypothesis requires quantifying the ecological similarity of species. This similarity can potentially be estimated by using phylogenetic relatedness. In this study, we predicted that if niche differentiation does explain the co-occurrence of rare and common species, then rare species should contribute greatly to the overall community phylogenetic diversity (PD), abundance will have phylogenetic signal, and common and rare species will be phylogenetically dissimilar. We tested these predictions by developing a novel method that integrates species rank abundance distributions with phylogenetic trees and trend analyses, to examine the relative contribution of individual species to the overall community PD. We then supplement this approach with analyses of phylogenetic signal in abundances and measures of phylogenetic similarity within and between rare and common species groups. We applied this analytical approach to 15 long-term temperate and tropical forest dynamics plots from around the world. We show that the niche differentiation hypothesis is supported in six of the nine gap-dominated forests but is rejected in the six disturbance-dominated and three gap-dominated forests. We also show that the three metrics utilized in this study each provide unique but corroborating information regarding the phylogenetic distribution of rarity in communities.     

Phylogenetic community structure metrics and null models: a review with new methods and software

Competitive exclusion and habitat filtering influence community assembly, but ecologists and evolutionary biologists have not reached consensus on how to quantify patterns that would reveal the action of these processes. Currently, at least 22 α‐diversity and 10 β‐diversity metrics of community phylogenetic structure can be combined with nine null models (eight for β‐diversity metrics), providing 278 potentially distinct approaches to test for phylogenetic clustering and overdispersion. Selecting the appropriate approach for a study is daunting. First, we describe similarities among metrics and null models across variance in phylogeny size and shape, species abundance, and species richness. Second, we develop spatially explicit, individual‐based simulations of neutral, competitive exclusion, or habitat filtering community assembly, and quantify the performance (type I and II error rates) of all 278 metric and null model combinations against each assembly process. Many α‐diversity metrics and null models are at least functionally equivalent, reducing the number of truly unique metrics to 12 and the number of unique metric + null model combinations to 72. An even smaller subset of metric and null model combinations showed robust statistical performance. For α‐diversity metrics, phylogenetic diversity and mean nearest taxon distance were best able to detect habitat filtering, while mean pairwise phylogenetic distance‐based metrics were best able to detect competitive exclusion. Overall, β‐diversity metrics tended to have greater power to detect habitat filtering and competitive exclusion than α‐diversity metrics, but had higher type 1 error in some cases. Across both α‐ and β‐diversity metrics, null model selection affected type I error rates more than metric selection. A null model that maintained species richness, and approximately maintained species occurrence frequency and abundance across sites, exhibited low type I and II error rates. This regional null model simulates neutral dispersal of individuals into local communities by sampling from a regional species pool. We introduce a flexible new R package, metricTester, to facilitate robust analyses of method performance.     

The MIGCLIM R package – seamless integration of dispersal constraints into projections of species distribution models

The MIGCLIM R package is a function library for the open source R software that enables the implementation of species‐specific dispersal constraints into projections of species distribution models under environmental change and/or landscape fragmentation scenarios. The model is based on a cellular automaton and the basic modeling unit is a cell that is inhabited or not. Model parameters include dispersal distance and kernel, long distance dispersal, barriers to dispersal, propagule production potential and habitat invasibility. The MIGCLIM R package has been designed to be highly flexible in the parameter values it accepts, and to offer good compatibility with existing species distribution modeling software. Possible applications include the projection of future species distributions under environmental change conditions and modeling the spread of invasive species.     

Spind: a package for computing spatially corrected accuracy measures

Using an appropriate accuracy measure is essential for assessing prediction accuracy in species distribution modelling. Therefore, model evaluation as an analytical uncertainty is a challenging problem. Although a variety of accuracy measures for the assessment of prediction errors in presence/absence models is available, there is a lack of spatial accuracy measures, i.e. measures that are sensitive to the spatial arrangement of the predictions. We present ‘spind’, a new software package (based on the R software program) that provides spatial performance measures for grid‐based models. These accuracy measures are generalized, spatially corrected versions of the classical ones, thus enabling comparisons between them. Our method for evaluation consists of the following steps: 1) incorporate additional autocorrelation until spatial autocorrelation in predictions and actuals is balanced, 2) cross‐classify predictions and adjusted actuals in a 4 × 4 contingency table, 3) use a refined weighting pattern for errors, and 4) calculate weighted Kappa, sensitivity, specificity and subsequently ROC, AUC, TSS to get spatially corrected indices. To illustrate the impact of our spatial method we present an example of simulated data as well as an example of presence/absence data of the plant species Dianthus carthusianorum across Germany. Our analysis includes a statistic for the comparison of spatial and classical (non‐spatial) indices. We find that our spatial indices tend to result in higher values than classical ones. These differences are statistically significant at medium and high autocorrelation levels. We conclude that these spatial accuracy measures may contribute to evaluate prediction errors in presence/absence models, especially in case of medium or high degree of similarity of adjacent data, i.e. aggregated (clumped) or continuous species distributions.     

Measuring biodiversity to explain community assembly: a unified approach

One of the oldest challenges in ecology is to understand the processes that underpin the composition of communities. Historically, an obvious way in which to describe community compositions has been diversity in terms of the number and abundances of species. However, the failure to reject contradictory models has led to communities now being characterized by trait and phylogenetic diversities. Our objective here is to demonstrate how species, trait and phylogenetic diversity can be combined together from large to local spatial scales to reveal the historical, deterministic and stochastic processes that impact the compositions of local communities. Research in this area has recently been advanced by the development of mathematical measures that incorporate trait dissimilarities and phylogenetic relatedness between species. However, measures of trait diversity have been developed independently of phylogenetic measures and conversely most of the phylogenetic diversity measures have been developed independently of trait diversity measures. This has led to semantic confusions particularly when classical ecological and evolutionary approaches are integrated so closely together. Consequently, we propose a unified semantic framework and demonstrate the importance of the links among species, phylogenetic and trait diversity indices. Furthermore, species, trait and phylogenetic diversity indices differ in the ways they can be used across different spatial scales. The connections between large‐scale, regional and local processes allow the consideration of historical factors in addition to local ecological deterministic or stochastic processes. Phylogenetic and trait diversity have been used in large‐scale analyses to determine how historical and/or environmental factors affect both the formation of species assemblages and patterns in species richness across latitude or elevation gradients. Both phylogenetic and trait diversity have been used at different spatial scales to identify the relative impacts of ecological deterministic processes such as environmental filtering and limiting similarity from alternative processes such as random speciation and extinction, random dispersal and ecological drift. Measures of phylogenetic diversity combine phenotypic and genetic diversity and have the potential to reveal both the ecological and historical factors that impact local communities. Consequently, we demonstrate that, when used in a comparative way, species, trait and phylogenetic structures have the potential to reveal essential details that might act simultaneously in the assembly of species communities. We highlight potential directions for future research. These might include how variation in trait and phylogenetic diversity alters with spatial distances, the role of trait and phylogenetic diversity in global‐scale gradients, the connections between traits and phylogeny, the importance of trait rarity and independent evolutionary history in community assembly, the loss of trait and phylogenetic diversity due to human impacts, and the mathematical developments of biodiversity indices including within‐species variations.     

Trade-offs in community ecology: linking spatial scales and species coexistence

Trade‐offs in species performances of different ecological functions is one of the most common explanations for coexistence in communities. Despite the potential for species coexistence occurring at local or regional spatial scales, trade‐offs are typically approached at a single scale. In recent years, ecologists have increasingly provided evidence for the importance of community processes at both local and regional spatial scales. This review summarizes the theoretical predictions for the traits associated with trade‐offs under different conditions and at different spatial scales. We provide a spatial framework for understanding trade‐offs, coexistence and the supportive empirical evidence. Predictions are presented that link the patterns of diversity observed to the patterns of trade‐offs that lead to coexistence at different spatial scales. Recent evidence for the evolution of trade‐offs under different conditions is provided which explores both laboratory microcosm studies and phylogenetic tests. Examining trade‐offs within a spatial framework can provide a strong approach to understanding community structure and dynamics, while explaining patterns of species diversity.     

Untangling the assembly of littoral macroinvertebrate communities through measures of functional and phylogenetic alpha diversity

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Hierarchical and scale‐dependent effects of fishing pressure and environment on the structure and size distribution of parrotfish communities

Parrotfishes are considered to have a major influence on coral reef ecosystems through grazing the benthic biota and are also primary fishery targets in the Indo‐Pacific. Consequently, the impact of human exploitation on parrotfish communities is of prime interest. As anthropogenic and environmental factors interact across spatial scales, sampling programs designed to disentangle these are required by both ecologists and resource managers. We present a multi‐scale examination of patterns in parrotfish assemblage structure, size distribution and diversity across eight oceanic islands of Micronesia. Results indicate that correlates of assemblage structure are scale‐dependent; biogeographic distributions of species and island geomorphology hierarchically influenced community patterns across islands whereas biophysical features and anthropogenic pressure influenced community assemblage structure at the within‐island scale. Species richness and phylogenetic diversity increased with greater broad‐scale habitat diversity associated with different island geomorphologies. However, within‐island patterns of abundance and biomass varied in response to biophysical factors and levels of human influence unique to particular islands. While the effect of fishing activities on community composition and phylogenetic diversity was obscured across island types, fishing pressure was the primary correlate of mean parrotfish length at all spatial scales. Despite widespread fishery‐induced pressure on Pacific coral reefs, the structuring of parrotfish communities at broad spatial scales remains a story largely dependent on habitat. Thus, we propose better incorporation of scale‐dependent habitat effects in future assessments of overexploitation on reef fish assemblages. However, strong community‐level responses within islands necessitate an improved understanding of the phylogenetic and functional consequences of altering community structure.     

Assessing New Zealand fern diversity from spatial predictions of species assemblages

The utility of explicit spatial predictions for biodiversity assessment is investigated with New Zealand fern flora. Distributions of 43 species were modelled from climatic and landform variables and predicted across New Zealand using generalised additive models (GAM). An original package of functions called generalised regression analysis and spatial prediction (GRASP) was developed to perform the analyses. On average, for the 43 models, the contributions of environmental variables indicate that mean annual temperature is the most important factor at this broad regional scale. Both annual solar radiation and its seasonality had higher correlations than temperature seasonality. Measures of water availability such as ratio of rainfall to potential evapotranspiration, air saturation deficit and soil water deficit presented significant contributions. Lithology was a better predictor than slope and drainage. These results are similar to those obtained from analyses of the distributions of New Zealand tree species and are consistent with the hypothesis that both tree and fern diversity are highest on sites conducive to high productivity. In order to identify hotspots of fern diversity, spatial predictions of individual species were summed up. The resulting map gave a very similar result to the direct prediction of their corresponding richness (number of species by plot out of 43 spp.). As a consequence, and where individual species models were not all available, the number of species within different species assemblages was directly modelled. Predicted richness hotspots of total species (out of 122 spp.), selected species (out of 43 and 21 spp.) and common species (out of 23 spp.) present very similar spatial patterns and are highly correlated. Richness of uncommon species (out of 39 spp.) was also accurately predicted, but presented a different spatial pattern. The number of rare species (out of 60 spp.) was not correctly modelled. Even though the lack of data for rare species clearly limits the application of this approach, fern community composition of more common species can be partially reconstructed from individual species predictions. This case study offers therefore a consistent approach not only for biodiversity hotspots identification, but also for setting targets to biodiversity assessment and restoration programs.     

Integrating correlation between traits improves spatial predictions of plant functional composition

Functional trait composition is increasingly recognized as key to better understand and predict community responses to environmental gradients. Predictive approaches traditionally model the weighted mean trait values of communities (CWMs) as a function of environmental gradients. However, most approaches treat traits as independent regardless of known tradeoffs between them, which could lead to spurious predictions. To address this issue, we suggest jointly modeling a suit of functional traits along environmental gradients while accounting for relationships between traits. We use generalized additive mixed effect models to predict the functional composition of alpine grasslands in the Guisane Valley (France). We demonstrate that, compared to traditional approaches, joint trait models explain considerable amounts of variation in CWMs, yield less uncertainty in trait CWM predictions and provide more realistic spatial projections when extrapolating to novel environmental conditions. Modeling traits and their co‐variation jointly is an alternative and superior approach to predicting traits independently. Additionally, compared to a ‘predict first, assemble later’ approach that estimates trait CWMs post hoc based on stacked species distribution models, our ‘assemble first, predict later’ approach directly models trait‐responses along environmental gradients, and does not require data and models on species’ distributions, but only mean functional trait values per community plot. This highlights the great potential of joint trait modeling approaches in large‐scale mapping applications, such as spatial projections of the functional composition of vegetation and associated ecosystem services as a response to contemporary global change.     

How do different aspects of biodiversity change through time? A case study on an Australian bird community

The study of ecological communities through time can reveal fundamental ecological processes and is key to understanding how natural and human pressures will affect biodiversity. Most studies of ecological communities through time consider only one or a few summary measures (e.g. species richness, total abundance), which might neglect important aspects of community structure or function. We studied temporal variation in several measures of species diversity, size diversity, and species composition in an intensively sampled bird community to determine whether different biodiversity measures change synchronously. We used a novel function regression model, which supports the study of diversity measures that are distributions (e.g. species abundance distributions) alongside measures that are scalar values (e.g. species richness). Most diversity measures changed predictably within years, but inter‐annual changes in size diversity and species composition were not reflected in species diversity. Within and among years, there was considerable variation in distributional measures that was not captured in scalar measures. Predictable variation within years probably was related to seasonal variation in weather patterns or food availability, but variation in size diversity among years probably resulted from stochastic changes in species composition. These results suggest that species and size diversity may be decoupled, and that inferences on scalar diversity measures might not reflect fundamental changes to community structure or function. Our method supports the inclusion of size‐based measures and distributional measures in ecological analyses, and broader uptake of our approach is likely to provide new insight into the processes structuring ecological communities, and inform the links between structure and function in ecological communities.     

戴云山物种多样性与系统发育多样性海拔梯度分布格局及驱动因子

生物多样性的海拔分布格局是生态学研究的热点。海拔作为综合性因子驱动着植物群落的物种、系统发育与功能多样性的空间分布。以戴云山南坡900-1600 m森林植物群落为研究对象,探讨物种多样性、系统发育指数与环境驱动因子的相互关系以及环境因子在群落构建与多样性维持中的重要意义。结果表明：（1）森林植物群落的系统发育多样性与物种多样性沿海拔均呈现中间高度膨胀格局。（2）物种多样性Margalef指数、Shannon-Wiener指数与系统发育多样性指数呈显著正相关,表明物种多样性越高,系统发育多样性也越高。Shannon-Wiener指数与物种多样性指数（Margalef、Pielou、Simpson指数）、系统发育多样性及系统发育结构都存在显著相关性,一定程度上Shannon-Wiener指数可以代替其他指数。Pielou指数、Simpson指数、Shannon-Wiener指数与系统发育结构NRI （Net relatedness index）指数、NTI （Net nearest taxa index）指数存在显著正相关,表明群落优势度、均匀度与系统发育结构相关性较强。（3）土壤全磷含量是影响系统发育多样性和物种多样性的主要驱动因子,土壤含水量是影响Shannon-Wiener、Pielou、Simpson指数的最显著因子,海拔是影响群落系统发育结构的主要因素。海拔是影响系统发育结构变化的主要环境因子,而土壤因子是影响物种多样性与系统发育多样性的主要因素,进一步验证了物种多样性与系统发育多样性的高度相关,结果旨在揭示物种群落空间分布规律。     

Evolutionary processes,dispersal limitation and climatic history shape current diversity patterns of European dragonflies

We investigated the effects of contemporary and historical factors on the spatial variation of European dragonfly diversity. Specifically, we tested to what extent patterns of endemism and phylogenetic diversity of European dragonfly assemblages are structured by 1) phylogenetic conservatism of thermal adaptations and 2) differences in the ability of post‐glacial recolonization by species adapted to running waters (lotic) and still waters (lentic). We investigated patterns of dragonfly diversity using digital distribution maps and a phylogeny of 122 European dragonfly species, which we constructed by combining taxonomic and molecular data. We calculated total taxonomic distinctiveness and mean pairwise distances across 4192 50 × 50 km equal‐area grid cells as measures of phylogenetic diversity. We compared species richness with corrected weighted endemism and standardized effect sizes of mean pairwise distances or residuals of total taxonomic distinctiveness to identify areas with higher or lower phylogenetic diversity than expected by chance. Broken‐line regression was used to detect breakpoints in diversity–latitude relationships. Dragonfly species richness peaked in central Europe, whereas endemism and phylogenetic diversity decreased from warm areas in the south‐west to cold areas in the north‐east and with an increasing proportion of lentic species. Except for species richness, all measures of diversity were consistently higher in formerly unglaciated areas south of the 0°C isotherm during the Last Glacial Maximum than in formerly glaciated areas. These results indicate that the distributions of dragonfly species in Europe were shaped by both phylogenetic conservatism of thermal adaptations and differences between lentic and lotic species in the ability of post‐glacial recolonization/dispersal in concert with the climatic history of the continent. The complex diversity patterns of European dragonflies provide an example of how integrating climatic and evolutionary history with contemporary ecological data can improve our understanding of the processes driving the geographical variation of biological diversity.     

Environmentally and behaviourally mediated co‐occurrence of functional traits in bird communities of tropical forest fragments

Two major theories of community assembly – based on the assumption of ‘limiting similarity’ or ‘habitat filtering’, respectively – predict contrasting patterns in the spatial arrangement of functional traits. Previous analyses have made progress in testing these predictions and identifying underlying processes, but have also pointed to theoretical as well as methodological shortcomings. Here we applied a recently developed methodology for spatially explicit analysis of phylogenetic meta‐community structure to study the pattern of co‐occurrence of functional traits in Afrotropical and Neotropical bird species inhabiting forest fragments. Focusing separately on locomotory, dietary, and dispersal traits, we tested whether environmental filtering causes spatial clustering, or competition leads to spatial segregation as predicted by limiting similarity theory. We detected significant segregation of species co‐occurrences in African fragments, but not in the Neotropical ones. Interspecific competition had a higher impact on trait co‐occurrence than filter effects, yet no single functional trait was able to explain the observed degree of spatial segregation among species. Despite high regional variability spanning from spatial segregation to aggregation, we found a consistent tendency for a clustered spatial patterning of functional traits among communities in fragmented landscapes, particularly in non‐territorial species. Overall, we show that behavioural effects, such as territoriality, and environmental effects, such as the area of forest remnants or properties of the landscape matrix in which they are embedded, can strongly affect the pattern of trait co‐occurrence. Our findings suggest that trait‐based analyses of community structure should include behavioural and environmental covariates, and we here provide an appropriate method for linking functional traits, species ecology and environmental conditions to clarify the drivers underlying spatial patterns of species co‐occurrence.