Competitive interactions change the pattern of species co‐occurrences under neutral dispersal

Non‐random patterns of species segregation and aggregation within ecological communities are often interpreted as evidence for interspecific interactions. However, it is unclear whether theoretical models can predict such patterns and how environmental factors may modify the effects of species interactions on species co‐occurrence. Here we extend a spatially explicit neutral model by including competitive effects on birth and death probabilities to assess whether competition alone is able to produce non‐random patterns of species co‐occurrence. We show that transitive and intransitive competitive hierarchies alone (in the absence of environmental heterogeneity) are indeed able to generate non‐random patterns with commonly used metrics and null models. Moreover, even weak levels of intransitive competition can increase local species richness. However, there is no simple rule or consistent directional change towards aggregation or segregation caused by competitive interactions. Instead, the spatial pattern depends on both the type of species interaction and the strength of dispersal. We conclude that co‐occurrence analysis alone may not able to identify the underlying processes that generate the patterns.     

Species partitioning in a temperate mountain chain: Segregation by habitat vs. interspecific competition

Disentangling the relative influence of the environment and biotic interactions in determining species coexistence patterns is a major challenge in ecology. The zonation occurring along elevation gradients, or at bioclimatic contact zones, offers a good opportunity to improve such understanding because the small scale at which the partitioning occurs facilitates inference based on experiments and ecological modelling. We studied the influence of abiotic gradients, habitat types, and interspecific competition in determining the spatial turnover between two pipit and two bunting species in NW Spain. We explored two independent lines of evidence to draw inference about the relative importance of environment and biotic interactions in driving range partitioning along elevation, latitude, and longitude. We combined occurrence data with environmental data to develop joint species distribution models (JSDM), in order to attribute co‐occurrence (or exclusion) to shared (or divergent) environmental responses and to interactions (attraction or exclusion). In the same region, we tested for interference competition by means of playback experiments in the contact zone. The JSDMs highlighted different responses for the two species pairs, although we did not find direct evidence of interspecific aggressiveness in our playback experiments. In pipits, partitioning was explained by divergent climate and habitat requirements and also by the negative correlations between species not explained by the environment. This significant residual correlation may reflect forms of competition others than direct interference, although we could not completely exclude the influence of unmeasured environmental predictors. When bunting species co‐occurred, it was because of shared habitat preferences, and a possible limitation to dispersal might cause their partitioning. Our results indicate that no single mechanism dominates in driving the distribution of our study species, but rather distributions are determined by the combination of many small forces including biotic and abiotic determinants of niche, whose relative strengths varied among species.     

Environmental heterogeneity,dispersal mode,and co‐occurrence in stream macroinvertebrates

Both environmental heterogeneity and mode of dispersal may affect species co‐occurrence in metacommunities. Aquatic invertebrates were sampled in 20–30 streams in each of three drainage basins, differing considerably in environmental heterogeneity. Each drainage basin was further divided into two equally sized sets of sites, again differing profoundly in environmental heterogeneity. Benthic invertebrate data were divided into three groups of taxa based on overland dispersal modes: passive dispersers with aquatic adults, passive dispersers with terrestrial winged adults, and active dispersers with terrestrial winged adults. The co‐occurrence of taxa in each dispersal mode group, drainage basin, and heterogeneity site subset was measured using the C‐score and its standardized effect size. The probability of finding high levels of species segregation tended to increase with environmental heterogeneity across the drainage basins. These patterns were, however, contingent on both dispersal mode and drainage basin. It thus appears that environmental heterogeneity and dispersal mode interact in affecting co‐occurrence in metacommunities, with passive dispersers with aquatic adults showing random patterns irrespective of environmental heterogeneity, and active dispersers with terrestrial winged adults showing increasing segregation with increasing environmental heterogeneity.     

Ecological assembly rules in plant communities—approaches,patterns and prospects

Understanding how communities of living organisms assemble has been a central question in ecology since the early days of the discipline. Disentangling the different processes involved in community assembly is not only interesting in itself but also crucial for an understanding of how communities will behave under future environmental scenarios. The traditional concept of assembly rules reflects the notion that species do not co‐occur randomly but are restricted in their co‐occurrence by interspecific competition. This concept can be redefined in a more general framework where the co‐occurrence of species is a product of chance, historical patterns of speciation and migration, dispersal, abiotic environmental factors, and biotic interactions, with none of these processes being mutually exclusive. Here we present a survey and meta‐analyses of 59 papers that compare observed patterns in plant communities with null models simulating random patterns of species assembly. According to the type of data under study and the different methods that are applied to detect community assembly, we distinguish four main types of approach in the published literature: species co‐occurrence, niche limitation, guild proportionality and limiting similarity. Results from our meta‐analyses suggest that non‐random co‐occurrence of plant species is not a widespread phenomenon. However, whether this finding reflects the individualistic nature of plant communities or is caused by methodological shortcomings associated with the studies considered cannot be discerned from the available metadata. We advocate that more thorough surveys be conducted using a set of standardized methods to test for the existence of assembly rules in data sets spanning larger biological and geographical scales than have been considered until now. We underpin this general advice with guidelines that should be considered in future assembly rules research. This will enable us to draw more accurate and general conclusions about the non‐random aspect of assembly in plant communities.     

Accounting for spatial autocorrelation in null models of tree species association

A commonly used null model for species association among forest trees is a well‐mixed community (WMC). A WMC represents a non‐spatial, or spatially implicit, model, in which species form nearest‐neighbor pairs at a rate equal to the product of their community proportions. WMC models assume that the outcome of random dispersal and demographic processes is complete spatial randomness (CSR) in the species’ spatial distributions. Yet, stochastic dispersal processes often lead to spatial autocorrelation (SAC) in tree species densities, giving rise to clustering, segregation, and other nonrandom patterns. Although methods exist to account for SAC in spatially‐explicit models, its impact on non‐spatial models often remains unaccounted for. To investigate the potential for SAC to bias tests based upon non‐spatial models, we developed a spatially‐heterogeneous (SH) modelling approach that incorporates measured levels of SAC. Using the mapped locations of individuals in a tropical tree community, we tested the hypothesis that the identity of nearest‐neighbors represents a random draw from neighborhood species pools. Correlograms of Moran's I confirmed that, for 50 of 51 dominant species, stem density was significantly autocorrelated over distances ranging from 50 to 200 m. The observed patterns of SAC were consistent with dispersal limitation, with most species occurring in distinct patches. For nearly all of the 106 species in the community, the frequency of pairwise association was statistically indistinguishable from that projected by the null models. However, model comparisons revealed that non‐spatial models more strongly underestimated observed species‐pair frequencies, particularly for conspecific pairs. Overall, the CSR models projected more significant facilitative interactions than did SH models, yielding a more liberal test of niche differences. Our results underscore the importance of accounting for stochastic spatial processes in tests of association, regardless of whether spatial or non‐spatial models are employed.     

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.     

辽东山区次生林乔木幼苗分布格局与种间空间关联性

在辽东山区次生林建立4 hm^2样地(200 m×200 m),研究0~50 m尺度范围内乔木幼苗分布格局及种间空间关联性.结果表明:在完全随机零模型下,0~20 m尺度上,95%的树种呈现聚集分布格局;0~16 m尺度上,19个树种呈现聚集分布;随着尺度的增加,聚集分布树种的比例逐渐减少,50 m尺度上,随机分布成为树种分布的主要形式;在异质性泊松过程零模型下,0~24 m尺度上,5%的树种呈现聚集分布,26~50 m尺度上,42%和58%的树种呈现随机和均匀分布.在完全随机零模型下,正相关树种对比例最高,且在50 m尺度下呈现正相关、负相关、无相关3种相关性的树种对比例相同;在异质性泊松过程零模型下,树种对主要呈现负相关,且随尺度增大,负相关的树种对比例逐渐升高.种子扩散限制和生境异质性在某种程度上解释了乔木幼苗的聚集分布格局,乔木幼苗强烈的聚集分布又促使种间空间关联性密切,更新群落稳定性较差.     

Species interactions weakly modify climate‐induced tree co‐occurrence patterns

Aims

Species distributions are hypothesized to be underlain by a complex association of processes that span multiple spatial scales including biotic interactions, dispersal limitation, fine‐scale resource gradients and climate. Species disequilibrium with climate may reflect the effects of non‐climatic processes on species distributions, yet distribution models have rarely directly considered non‐climatic processes. Here, we use a Joint Species Distribution Model (JSDM) to investigate the influence of non‐climatic factors on species co‐occurrence patterns and to directly quantify the relative influences of climate and alternative processes that may generate correlated responses in species distributions, such as species interactions, on tree co‐occurrence patterns.

Location

US Rocky Mountains.

Methods

We apply a Bayesian JSDM to simultaneously model the co‐occurrence patterns of ten dominant tree species across the Rocky Mountains, and evaluate climatic and residual correlations from the fitted model to determine the relative contribution of each component to observed co‐occurrence patterns. We also evaluate predictions generated from the fitted model relative to a single‐species modelling approach.

Results

For most species, correlation due to climate covariates exceeded residual correlation, indicating an overriding influence of broad‐scale climate on co‐occurrence patterns. Accounting for covariance among species did not significantly improve predictions relative to a single‐species approach, providing limited evidence for a strong independent influence of species interactions on distribution patterns.

Conclusions

Overall, our findings indicate that climate is an important driver of regional biodiversity patterns and that interactions between dominant tree species contribute little to explain species co‐occurrence patterns among Rocky Mountain trees.     

Aggregative structure is the rule in communities of fleas: null model analysis

We used null models to examine patterns of species co‐occurrences in 59 communities of fleas parasitic on small mammals from 4 biogeographic realms (Afrotropics, Nearctic, Neotropics, and Palaearctic). We compared frequencies of co‐occurrences of flea species across host species with those expected by chance, using a null model approach. We used 4 tests for non‐randomness to identify pairs of species (within a community) that demonstrate significant positive or negative co‐occurrence. The majority of flea communities were non‐randomly assembled. Patterns of flea co‐occurrences on the same host species indicated aggregation but not segregation of flea species (except for the flea community of Madagascar). Although only a small fraction of species pairs were associated significantly (264 of 10, 943 species pairs according to the most liberal criterion), most of these associations were positive (except for 2 negatively associated species pairs). Significantly associated pairs were represented mainly by non‐congeneric species. The degree of non‐randomness of the entire flea community was similar among biogeographic regions, but the strength of pair‐wise association varied geographically, being the highest in the Afrotropics and the lowest in the European region of the Palaearctic.     

On the relationship between abiotic stress and co-occurrence patterns: an assessment at the community level using soil lichen communities and multiple stress gradients

The stress‐gradient hypothesis (SGH) predicts a shift from predominant competition to facilitation as abiotic stress increases. Most empirical tests of the SGH have evaluated the interactions between a single or a few pairs of species, have not considered the effects of multiple stress factors, and have not explored these interactions at nested spatial scales. We sampled 63 0.25‐m² plots, each subdivided into 100 5×5 cm and 25 10×10 cm sampling squares, in a semi‐arid Mediterranean environment to evaluate how co‐occurrence patterns among biological soil crusts (BSC)‐forming lichens changed along natural stress gradients driven by water and nutrient (N, P, K) availability. According to the SGH, we tested the hypothesis that the fine‐scale spatial arrangement of BSC‐forming lichens should shift from prevailing interspecific segregation to aggregation as abiotic stress increases. Co‐occurrence patterns ranged from significant species segregation to aggregation at the two spatial scales studied. When using the 5×5 cm grid, more plots showed significant species segregation than aggregation. At this sampling scale, co‐occurrence increased as water and nutrient availability decreased and increased, respectively. Small increases in soil pH promoted species co‐occurrence. Interspecific segregation was promoted as the cover of highly competitive species, such as Diploschistes diacapsis, increased. No significant relationships between co‐occurrence and the surrogates of abiotic stress were observed when data was arranged in a 10×10 cm grid. Our co‐occurrence analyses partially supported predictions from the SGH, albeit the results obtained were dependent on the type of abiotic stress and the spatial scale considered. They show the difficulties of predicting how co‐occurrence patterns change along complex stress gradients, and highlight the need of incorporating the effects of abiotic stress promoted by different resources, such as water and nutrients, into the conceptual framework of the SGH.     

Species co-occurrence: the case of congeneric species and a causal approach to patterns of species association

Aim To test whether congeneric species are significantly associated with one another in space, either positively or negatively. Also, to provide a framework for a causal investigation of co‐occurrence patterns by a parallel comparison of interactions in geographical and ecological data matrices. Location For the analysis of congeneric species’ co‐occurrences we used 30 matrices covering a wide range of taxa and geographical areas, while for the causal investigation we used the distribution of 50 terrestrial isopod species on 20 islands and 264 sampling stations in the central Aegean archipelago, as well as a number of ecological variables for each sampling station. Methods We developed a software program (cooc ) that incorporates the species‐by‐species approach to co‐occurrence analysis using EcoSim's output of prior null model analysis of co‐occurrence. We describe this program in detail, and use it to investigate one of the most common assembly rules, namely, the decreased levels of co‐occurrence among congeneric species pairs. For the causal analysis, we proceed likewise, cross‐checking the results from the geographical and the ecological matrices. There is only one possible combination of results that can support claims for direct competition among species. Results We do not get any strong evidence for widespread competition among congeneric species, while most communities investigated do not show significant patterns of species associations. The causal analysis suggests that the principal factors behind terrestrial isopod species associations are of historical nature. Some exceptional cases are also discussed. Main conclusions Presence/absence data for a variety of taxa do not support the assembly rule that congeneric species are under more intense competition compared to less related species. Also, these same data do not suggest strong interactions among species pairs, regardless of taxonomic status. When significant species associations can be seen in such matrices, they mainly reflect the effects of history or of habitat requirements.     

Environmental heterogeneity,not distance,structures montane epigaeic spider assemblages in north-western Patagonia (Argentina)

There is considerable controversy around the patterns and processes that influence spatial variation in taxonomic composition in mountain environments. We analysed elevational variation in the taxonomic composition of epigaeic spider assemblages across five mountains in north-western Patagonia (Argentina) to examine the relative importance of dispersal (distance) limitation and environmental heterogeneity on a regional scale. The distance limitation hypothesis predicts greater taxonomic similarity between sampling sites separated by short geographical distances than between mountain peaks separated by longer distances, a lack of indicator species of macro-habitats, and weak associations between spider species composition and environmental gradients. Alternatively, the environmental heterogeneity hypothesis predicts that taxonomic differentiation will occur over short distances along elevation gradients in association with the turnover in major habitats and change in environmental conditions, and that indicator species will be present. We collected spiders using 486 pitfall traps arranged in fifty-four 100-m² grid plots of nine traps separated by ~?100 m of elevation, from the base to the summit of each mountain. Multivariate analyses identified spider assemblages that were associated with macro-habitats rather than with mountains. Local environmental variation (mainly in vegetation cover), precipitation and soil characteristics influenced the spatial variation in species composition. Characteristic indicator species showed high specificity and fidelity to macro-habitats, whereas vulnerable species showed high specificity and low fidelity to mountains or macro-habitats. We conclude that, on a regional scale, species adaptation to environmental gradients plays a more important role than dispersal limitation in structuring the taxonomic composition of spider assemblages. Moreover, the presence of indicator species suggests that spiders have a great potential as ecological indicators for evaluating the response of montane biodiversity to future climatic change.     

Testing the link between species interactions and species co‐occurrence in a trophic network

Species interactions are dynamic processes that vary across environmental and ecological contexts, and operate across scale boundaries, making them difficult to quantify. Nevertheless, ecologists are increasingly interested in inferring species interactions from observational data using statistical analyses of their spatial co‐occurrence patterns. Trophic interactions present a particular challenge, as predators and prey may frequently or rarely co‐occur, depending on the spatial or temporal scale of observation. In this study, we investigate the accuracy of inferred interactions among species that both compete and trophically interact. We utilized a long‐term dataset of pond‐breeding amphibian co‐occurrences from Mt Rainier National Park (Washington, USA) and compiled a new dataset of their empirical interactions from the literature. We compared the accuracy of four statistical methods in inferring these known species interactions from spatial associations. We then used the best performing statistical method, the Markov network, to further investigate the sensitivity of interaction inference to spatial scale‐dependence and the presence of predators. We show that co‐occurrence methods are generally inaccurate when estimating trophic interactions. Further the strength and sign of inferred interactions were dependent upon the spatial scale of observation and predator presence influenced the detectability of competitive interactions among prey species. However, co‐occurrence analysis revealed new patterns of spatial association among pairs of species with known interactions. Overall, our study highlights a limiting frontier in co‐occurrence theory and the disconnect between widely implemented methodologies and their ability to accurately infer interactions in trophically‐structured communities.     

A comprehensive framework for the study of species co‐occurrences,nestedness and turnover

Binary presence–absence matrices (rows = species, columns = sites) are often used to quantify patterns of species co‐occurrence, and to infer possible biotic interactions from these patterns. Previous classifications of co‐occurrence patterns as nested, segregated, or modular have led to contradictory results and conclusions. These analyses usually do not incorporate the functional traits of the species or the environmental characteristics of the sites, even though the outcomes of species interactions often depend on trait expression and site quality. Here we address this shortcoming by developing a method that incorporates realized functional and environmental niches, and relates them to species co‐occurrence patterns. These niches are defined from n‐dimensional ellipsoids, and calculated from the n eigenvectors and eigenvalues of the variance–covariance matrix of measured environmental or trait variables. Average niche overlap among species and the spatial distribution of niches define a triangle plot with vertices of species segregation (low niche overlap), nestedness (high niche overlap), and modular co‐occurrence (clusters of overlapping niches). Applying this framework to temperate understorey plant communities in southwest Poland, we found a consistent modular structure of species occurrences, a pattern not detected by conventional presence–absence analysis. These results suggest that, in our case study, habitat filtering is the most important process structuring understorey plant communities. Furthermore, they demonstrate how incorporating trait and environmental data into co‐occurrence analysis improves pattern detection and provides a stronger theoretical framework for understanding community structure.     

Incorporating phylogenetic metrics to microbial co‐occurrence networks based on amplicon sequences to discern community assembly processes

Co‐occurrence network analysis based on amplicon sequences is increasingly used to study microbial communities. Patterns of co‐existence or mutual exclusion between pairs of taxa are often interpreted as reflecting positive or negative biological interactions. However, other assembly processes can underlie these patterns, including species failure to reach distant areas (dispersal limitation) and tolerate local environmental conditions (habitat filtering). We provide a tool to quantify the relative contribution of community assembly processes to microbial co‐occurrence patterns, which we applied to explore soil bacterial communities in two dry ecosystems. First, we sequenced a bacterial phylogenetic marker in soils collected across multiple plots. Second, we inferred co‐occurrence networks to identify pairs of significantly associated taxa, either co‐existing more (aggregated) or less often (segregated) than expected at random. Third, we assigned assembly processes to each pair: patterns explained based on spatial or environmental distance were ascribed to dispersal limitation (2%–4%) or habitat filtering (55%–77%), and the remaining to biological interactions. Finally, we calculated the phylogenetic distance between taxon pairs to test theoretical expectations on the linkages between phylogenetic patterns and assembly processes. Aggregated pairs were more closely related than segregated pairs. Furthermore, habitat‐filtered aggregated pairs were closer relatives than those assigned to positive interactions, consistent with phylogenetic niche conservatism and cooperativism among distantly related taxa. Negative interactions resulted in equivocal phylogenetic signatures, probably because different competitive processes leave opposing signals. We show that microbial co‐occurrence networks mainly reflect environmental tolerances and propose that incorporating measures of phylogenetic relatedness to networks might help elucidate ecologically meaningful patterns.     

Anthropogenic modification disrupts species co‐occurrence in stream invertebrates

The question of whether species co‐occurrence is random or deterministic has received considerable attention, but little is known about how anthropogenic disturbance mediates the outcomes. By combining experiments, field surveys and analysis against null models, we tested the hypothesis that anthropogenic habitat modification disrupts species co‐occurrence in stream invertebrates across spatial scales. Whereas communities in unmodified conditions were structured deterministically with significant species segregation, catchment‐scale conversion to agriculture and sediment deposition at the patch‐ or micro‐habitat scale apparently randomized species co‐occurrences. This shift from non‐random to random was mostly independent of species richness, abundance and spatial scale. Data on community‐wide life‐history traits (body size, dispersal ability and predatory habits) and beta‐diversity indicated that anthropogenic modification disrupted community assembly by affecting biotic interactions and, to a lesser extent, altering habitat heterogeneity. These data illustrate that the balance between predictable and stochastic patterns in communities can reflect anthropogenic modifications that not only transcend scales but also change the relative forces that determine species coexistence. Research into the effects of habitat modification as a key to understanding global change should extend beyond species richness and composition to include species co‐occurrence, species interactions and any functional consequences.     

Soil environmental heterogeneity allows spatial co‐occurrence of competitor earthworm species in a gallery forest of the Colombian ‘Llanos’

Disentangling how communities of soil organisms are deterministically structured by abiotic and biotic factors is of utmost relevance, and few data sets on co‐occurrence patterns exist in soil ecology compared to other disciplines. In this study, we assessed species spatial co‐occurrence and niche overlap together with the heterogeneity of selected soil properties in a gallery forest (GF) of the Colombian Llanos. We used null‐model analysis to test for non‐random patterns of species co‐occurrence and body size in assemblages of earthworms and whether the pattern observed was the result of environmental heterogeneity or biotic processes structuring the community at small scales by means of co‐inertia analysis (CoIA). The results showed that earthworm species co‐occurred more frequently than expected by chance at short distances, and CoIA highlighted a significant specific relationship between earthworm species and soil variables. The effect of soil environmental heterogeneity on one litter‐feeding species but also the impact of soil‐feeding species on soil physical properties was revealed. Correlogram analysis on the first axis extracted in the CoIA showed the scale of the common structure shared by the fauna and soil variable tables. The earthworm community was not deterministically structured by competition and co‐occurrence of competing species was facilitated by soil environmental heterogeneity at small scales in the GF. Our results agreed with the coexistence aggregation model which suggests that spatial aggregation of competitors at patchily distributed resources (environment) can facilitate species coexistence.     

Using functional diversity patterns to explore metacommunity dynamics: a framework for understanding local and regional influences on community structure

The metacommunity concept, describing how local and regional scale processes interact to structure communities, has been successfully applied to patterns of taxonomic diversity. Functional diversity has proved useful for understanding local scale processes, but has less often been applied to understanding regional scale processes. Here, we explore functional diversity patterns within a metacommunity context to help elucidate how local and regional scale processes influence community assembly. We detail how each of the four metacommunity perspectives (species sorting, mass effects, patch dynamics, neutral) predict different patterns of functional beta‐ and alpha‐diversity and spatial structure along two key gradients: dispersal limitation and environmental conditions. We then apply this conceptual model to a case study from alpine tundra plant communities. We sampled species composition in 17 ‘sky islands’ of alpine tundra in the Colorado Rocky Mountains, USA that differed in geographic isolation and area (key factors related to dispersal limitation) and temperature and elevation (key environmental factors). We quantified functional diversity in each site based on specific leaf area, leaf area, stomatal conductance, plant height and chlorophyll content. We found that colder high elevation sites were functionally more similar to each other (decreased functional beta‐diversity) and had lower functional alpha‐diversity. Geographic isolation and area did not influence functional beta‐ or alpha‐diversity. These results suggest a strong role for environmental conditions structuring alpine plant communities, patterns consistent with the species sorting metacommunity perspective. Incorporating functional diversity into metacommunity theory can help elucidate how local and regional factors structure communities and provide a framework for observationally examining the role of metacommunity dynamics in systems where experimental approaches are less tractable.     

Determinants of palm species distributions across Africa: the relative roles of climate,non‐climatic environmental factors,and spatial constraints

Most of the Earth's biodiversity resides in the tropics. However, a comprehensive understanding of which factors control range limits of tropical species is still lacking. Climate is often thought to be the predominant range‐determining mechanism at large spatial scales. Alternatively, species’ ranges may be controlled by soil or other environmental factors, or by non‐environmental factors such as biotic interactions, dispersal barriers, intrinsic population dynamics, or time‐limited expansion from place of origin or past refugia. How species ranges are controlled is of key importance for predicting their responses to future global change. Here, we use a novel implementation of species distribution modelling (SDM) to assess the degree to which African continental‐scale species distributions in a keystone tropical group, the palms (Arecaceae), are controlled by climate, non‐climatic environmental factors, or non‐environmental spatial constraints. A comprehensive data set on African palm species occurrences was assembled and analysed using the SDM algorithm Maxent in combination with climatic and non‐climatic environmental predictors (habitat, human impact), as well as spatial eigenvector mapping (spatial filters). The best performing models always included spatial filters, suggesting that palm species distributions are always to some extent limited by non‐environmental constraints. Models which included climate provided significantly better predictions than models that included only non‐climatic environmental predictors, the latter having no discernible effect beyond the climatic control. Hence, at the continental scale, climate constitutes the only strong environmental control of palm species distributions in Africa. With regard to the most important climatic predictors of African palm distributions, water‐related factors were most important for 25 of the 29 species analysed. The strong response of palm distributions to climate in combination with the importance of non‐environmental spatial constraints suggests that African palms will be sensitive to future climate changes, but that their ability to track suitable climatic conditions will be spatially constrained.     

Inferring ecological processes from taxonomic, phylogenetic and functional trait β-diversity

Understanding the influences of dispersal limitation and environmental filtering on the structure of ecological communities is a major challenge in ecology. Insight may be gained by combining phylogenetic, functional and taxonomic data to characterize spatial turnover in community structure (β-diversity). We develop a framework that allows rigorous inference of the strengths of dispersal limitation and environmental filtering by combining these three types of β-diversity. Our framework provides model-generated expectations for patterns of taxonomic, phylogenetic and functional β-diversity across biologically relevant combinations of dispersal limitation and environmental filtering. After developing the framework we compared the model-generated expectations to the commonly used "intuitive" expectation that the variance explained by the environment or by space will, respectively, increase monotonically with the strength of environmental filtering or dispersal limitation. The model-generated expectations strongly departed from these intuitive expectations: the variance explained by the environment or by space was often a unimodal function of the strength of environmental filtering or dispersal limitation, respectively. Therefore, although it is commonly done in the literature, one cannot assume that the strength of an underlying process is a monotonic function of explained variance. To infer the strength of underlying processes, one must instead compare explained variances to model-generated expectations. Our framework provides these expectations. We show that by combining the three types of β-diversity with model-generated expectations our framework is able to provide rigorous inferences of the relative and absolute strengths of dispersal limitation and environmental filtering. Phylogenetic, functional and taxonomic β-diversity can therefore be used simultaneously to infer processes by comparing their empirical patterns to the expectations generated by frameworks similar to the one developed here.