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.     

Limiting similarity and functional diversity along environmental gradients

Recent developments in community models emphasize the importance of incorporating stochastic processes (e.g. ecological drift) in models of niche‐structured community assembly. We constructed a finite, spatially explicit, lottery model to simulate the distribution of species in a one‐dimensional landscape with an underlying gradient in environmental conditions. Our framework combines the potential for ecological drift with environmentally‐mediated competition for space in a heterogeneous environment. We examined the influence of niche breadth, dispersal distances, community size (total number of individuals) and the breadth of the environmental gradient on levels of species and functional trait diversity (i.e. differences in niche optima). Three novel results emerge from this model: (1) niche differences between adjacent species (e.g. limiting similarity) increase in smaller communities, because of the interaction of competitive effects and finite population sizes; (2) immigration from a regional species pool, stochasticity and niche‐assembly generate a bimodal distribution of species residence times (‘transient’ and ‘resident’) under a heterogeneous environment; and (3) the magnitude of environmental heterogeneity has a U‐shaped effect on diversity, because of shifts in species richness of resident vs. transient species. These predictions illustrate the potential importance of stochastic (although not necessarily neutral) processes in community assembly.     

Point process models,the dimensions of biodiversity and the importance of small-scale biotic interactions

Aims Recent mechanistic explanations for community assembly focus on the debates surrounding niche-based deterministic and dispersal-based stochastic models. This body of work has emphasized the importance of both habitat filtering and dispersal limitation, and many of these works have utilized the assumption of species spatial independence to simplify the complexity of the spatial modeling in natural communities when given dispersal limitation and/or habitat filtering. One potential drawback of this simplification is that it does not consider species interactions and how they may influence the spatial distribution of species, phylogenetic and functional diversity. Here, we assess the validity of the assumption of species spatial independence using data from a subtropical forest plot in southeastern China.Methods We use the four most commonly employed spatial statistical models—the homogeneous Poisson process representing pure random effect, the heterogeneous Poisson process for the effect of habitat heterogeneity, the homogenous Thomas process for sole dispersal limitation and the heterogeneous Thomas process for joint effect of habitat heterogeneity and dispersal limitation—to investigate the contribution of different mechanisms in shaping the species, phylogenetic and functional structures of communities.Important findings Our evidence from species, phylogenetic and functional diversity demonstrates that the habitat filtering and/or dispersal-based models perform well and the assumption of species spatial independence is relatively valid at larger scales (50×50 m). Conversely, at local scales (10×10 and 20×20 m), the models often fail to predict the species, phylogenetic and functional diversity, suggesting that the assumption of species spatial independence is invalid and that biotic interactions are increasingly important at these spatial scales.     

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.     

黄土高原腹地人工林下草本层群落构建机制

群落构建机制是生态学研究的核心论题。生态位理论和中性理论是阐明群落构建的两种主要理论, 但这两种理论分别强调的环境过滤和扩散限制对群落构建的影响尚存争议。该研究以黄土高原人工林下草本层群落为研究对象, 将群落物种组成数据与地理空间、气候、地形以及生物因子相结合, 运用随机森林模型(RF)和基于距离矩阵的多元回归方法(MRM), 探究了各个因子的重要性, 并通过邻体主坐标矩阵(PCNM)和基于距离的冗余分析(db-RDA)分别筛选显著的空间结构和环境因子, 最后结合筛选出的PCNM特征值和环境变量进行变差分解。研究结果显示: 1)林下草本层群落组成相似性随地理距离和生境差异的增加而减小。2)地理距离与生境差异共同解释了群落组成相似性变化的47.8%。其中, 空间因子和环境因子的独立解释率分别为14.1%和9.8%, 两者的联合解释率为23.9%。3)地理距离和年降水量是引起研究区内物种组成变化的关键因子, 且地理距离的重要性大于年降水量。在黄土高原腹地, 扩散限制与环境过滤共同主导了人工林下草本层群落的构建过程。     

Microbial biogeography of permafrost thaw ponds across the changing northern landscape

Microbial diversity varies at multiple spatial scales, but little is known about how climate change may influence this variation. Here we assessed the free‐living bacterioplankton composition of thaw ponds over a north‐south gradient of permafrost degradation in the eastern Canadian subarctic. Three nested spatial scales were compared: 1) among ponds within individual valleys 2) between two valleys within each landscape type, and 3) between landscape types (southern sporadic versus northern discontinuous permafrost). As a reference point, we sampled rock‐basin lakes whose formation was not related to permafrost thawing. β‐diversity was low at the smallest scale despite marked differences in limnological properties among neighboring ponds. β‐diversity was high among valleys, associated with greater environmental heterogeneity. The largest differences were between landscape types and appeared to reflect the concomitant effects of environmental filtering and dispersal limitation. Raup–Crick β‐diversity indicated that community assembly was driven by both stochastic (random extinction, dispersal, ecological drift) and deterministic (environmental filtering) processes. Communities sampled in the most degraded valley appeared primarily assembled through stochastic processes, while environmental filtering played a greater role at the other valleys. These results imply that climate warming and ongoing permafrost degradation will influence microbial community assembly, which in turn is likely to affect the functioning of thaw pond ecosystems.     

Stochastic and deterministic processes drive wetland community assembly across a gradient of environmental filtering

The role of deterministic and stochastic processes in community assembly is a key question in community ecology. We evaluated the effect of an abiotic filter (hydroperiod) on the partitioned diversity of three taxonomic groups (birds, vegetation, macroinvertebrates) from prairie pothole wetlands in Alberta, Canada, which naturally vary in water permanence. We observed that alpha and gamma diversity were higher in permanent than temporary wetlands (16–25% and 34–47% respectively, depending on the taxon). This suggests an influence of deterministic constraints on the number of species a wetland can support. Taxa which cannot persist in shallow, temporary wetlands are excluded by the deterministic constraints that a shortened hydroperiod imposes. In contrast, we observed that beta diversity was significantly higher (2–12%) in temporary wetlands than permanent ones, and temporary wetlands supported more unique combinations of community composition than permanent wetlands, despite having a smaller regional species pool. This observation contradicts prior mesocosm studies that found beta diversity mirrored the pattern in gamma diversity along an environmental filtering gradient. We conclude that deterministic processes are more influential in more stable permanent wetlands, whereas stochastic processes play a more important role in assembly in dynamic temporary wetlands that must disassemble and re‐establish annually. Considering three distinct taxonomic groups differing in their relative mobility, our large‐scale field study demonstrates that both stochastic and deterministic processes act together to influence the assembly of multiple communities and that the relative importance of the two processes varies consistently along a gradient of environmental filtering.     

Environmental changes affect the assembly of soil bacterial community primarily by mediating stochastic processes

Both ‘species fitness difference’‐based deterministic processes, such as competitive exclusion and environmental filtering, and ‘species fitness difference’‐independent stochastic processes, such as birth/death and dispersal/colonization, can influence the assembly of soil microbial communities. However, how both types of processes are mediated by anthropogenic environmental changes has rarely been explored. Here we report a novel and general pattern that almost all anthropogenic environmental changes that took place in a grassland ecosystem affected soil bacterial community assembly primarily through promoting or restraining stochastic processes. We performed four experiments mimicking 16 types of environmental changes and separated the compositional variation of soil bacterial communities caused by each environmental change into deterministic and stochastic components, with a recently developed method. Briefly, because the difference between control and treatment communities is primarily caused by deterministic processes, the deterministic change was quantified as (mean compositional variation between treatment and control) – (mean compositional variation within control). The difference among replicate treatment communities is primarily caused by stochastic processes, so the stochastic change was estimated as (mean compositional variation within treatment) – (mean compositional variation within control). The absolute of the stochastic change was greater than that of the deterministic change across almost all environmental changes, which was robust for both taxonomic and functional‐based criterion. Although the deterministic change may become more important as environmental changes last longer, our findings showed that changes usually occurred through mediating stochastic processes over 5 years, challenging the traditional determinism‐dominated view.     

Environmental filtering affects soil fungal community composition more than dispersal limitation at regional scales

The relative importance of dispersal limitation versus environmental filtering for community assembly has received much attention for macroorganisms. These processes have only recently been examined in microbial communities. Instead, microbial dispersal has mostly been measured as community composition change over space (i.e., distance decay). Here we directly examined fungal composition in airborne wind currents and soil fungal communities across a 40 000 km² regional landscape to determine if dispersal limitation or abiotic factors were structuring soil fungal communities. Over this landscape, neither airborne nor soil fungal communities exhibited compositional differences due to geographic distance. Airborne fungal communities shifted temporally while soil fungal communities were correlated with abiotic parameters. These patterns suggest that environmental filtering may have the largest influence on fungal regional community assembly in soils, especially for aerially dispersed fungal taxa. Furthermore, we found evidence that dispersal of fungal spores differs between fungal taxa and can be both a stochastic and deterministic process. The spatial range of soil fungal taxa was correlated with their average regional abundance across all sites, which may imply stochastic dispersal mechanisms. Nevertheless, spore volume was also negatively correlated with spatial range for some species. Smaller volume spores may be adapted to long-range dispersal, or establishment, suggesting that deterministic fungal traits may also influence fungal distributions. Fungal life-history traits may influence their distributions as well. Hypogeous fungal taxa exhibited high local abundance, but small spatial ranges, while epigeous fungal taxa had lower local abundance, but larger spatial ranges. This study is the first, to our knowledge, to directly sample air dispersal and soil fungal communities simultaneously across a regional landscape. We provide some of the first evidence that soil fungal communities are mostly assembled through environmental filtering and experience little dispersal limitation.     

Beta‐diversity in temperate and tropical forests reflects dissimilar mechanisms of community assembly

Site‐to‐site variation in species composition (β‐diversity) generally increases from low‐ to high‐diversity regions. Although biogeographical differences in community assembly mechanisms may explain this pattern, random sampling effects can create this pattern through differences in regional species pools. Here, we compared assembly mechanisms between spatially extensive networks of temperate and tropical forest plots with highly divergent species pools (46 vs. 607 species). After controlling for sampling effects, β‐diversity of woody plants was similar and higher than expected by chance in both forests, reflecting strong intraspecific aggregation. However, different mechanisms appeared to explain aggregation in the two forests. In the temperate forest, aggregation reflected stronger environmental correlations, suggesting an important role for species‐sorting (e.g. environmental filtering) processes, whereas in the tropics, aggregation reflected stronger spatial correlations, more likely reflecting dispersal limitation. We suggest that biogeographical differences in the relative importance of different community assembly mechanisms contribute to these striking gradients in global biodiversity.     

Environmental filtering by pH and soil nutrients drives community assembly in fungi at fine spatial scales

Whether niche processes, like environmental filtering, or neutral processes, like dispersal limitation, are the primary forces driving community assembly is a central question in ecology. Here, we use a natural experimental system of isolated tree “islands” to test whether environment or geography primarily structures fungal community composition at fine spatial scales. This system consists of isolated pairs of two distantly related, congeneric pine trees established at varying distances from each other and the forest edge, allowing us to disentangle the effects of geographic distance vs. host and edaphic environment on associated fungal communities. We identified fungal community composition with Illumina sequencing of ITS amplicons, measured all relevant environmental parameters for each tree—including tree age, size and soil chemistry—and calculated geographic distances from each tree to all others and to the nearest forest edge. We applied generalized dissimilarity modelling to test whether total and ectomycorrhizal fungal (EMF) communities were primarily structured by geographic or environmental filtering. Our results provide strong evidence that as in many other organisms, niche and neutral processes both contribute significantly to turnover in community composition in fungi, but environmental filtering plays the dominant role in structuring both free‐living and symbiotic fungal communities at fine spatial scales. In our study system, we found pH and organic matter primarily drive environmental filtering in total soil fungal communities and that pH and cation exchange capacity—and, surprisingly, not host species—were the largest factors affecting EMF community composition. These findings support an emerging paradigm that pH may play a central role in the assembly of all soil‐mediated systems.     

Species abundance distributions as a proxy for the niche-neutrality continuum

Aims Species abundance distributions (SADs) are often used to verify mechanistic theories underlying community assembly. However, it is now accepted that SADs alone are not sufficient to reveal biological mechanisms. Recent attention focuses on the relative importance of stochastic dispersal processes versus deterministic processes such as interspecific competition and environmental filtering. Here, we combine a study of the commonness and rarity of species (i.e. the SAD) with mechanistic processes underlying community composition. By comparing the occurrence frequencies of each and every species with its abundance, we quantify the relative contributions of common and rare species to the maintenance of community structure. Essentially, we relate the continuum between commonness and rarity with that of niches and neutrality.Methods An individual-based, spatially explicit model was used to simulate local communities in niche spaces with the same parameters. We generated sets of assemblages from which species were eliminated in opposing sequences: from common to rare and from rare to common, and investigated the relationship between the abundance and frequency of species. We tested the predictions of our model with empirical data from a field experiment in the environmentally homogeneous alpine meadows of the Qinghai–Tibetan plateau.Important findings Our simulations support the widespread notion that common species maintain community structure, while rare species maintain species diversity, in both local and regional communities. Our results, both from theoretical simulations and from empirical observations, revealed positive correlations between the abundance of a particular species and its occurrence frequency. SAD curves describe a continuum between commonness and rarity. Removing species from the 'rare' end of this continuum has little effect on the similarity of communities, but removing species from the 'common' end of the continuum causes significant increases in beta diversity, or species turnover, between communities. In local communities distributed in a homogenous habitat, species located at the 'common' end of the continuum should be selected by environmental filtering, with niche space partitioning governed by interspecific competition. Conversely, species located at the 'rare' end of the continuum are most likely subject to stochastic dispersal processes. Species situated at intermediate locations on this continuum are therefore determined by niche and neutral processes acting together. Our results suggest that, in homogeneous habitats, SAD curves describing the common-rare continuum may also be used to describe the continuum between niches and neutrality.     

Seasonal dynamics of waterbird assembly mechanisms revealed by patterns in phylogenetic and functional diversity in a subtropical wetland

Despite growing interest in using phylogenetic and functional methods to understand community assembly, few studies have examined how these methods can be used to assess seasonal variation in assembly mechanisms among migrant species. Migration can rapidly alter the relative influence of stochastic processes, species interactions, or environmental factors in shaping communities across seasons. Here, we describe seasonal dynamics in the phylogenetic and functional diversity of waterbirds in Mai Po Wetland, a subtropical region with significant and predictable temporal variation in climate and migratory bird density. Phylogenetic α diversity varied seasonally, exhibiting a clustered structure (indicative of environmental filtering) in summer, and over‐dispersed structure (indicative of biotic filtering) in winter. Phylogenetic diversity in spring and autumn exhibited a more intermediate, random structure, consistent with stochastic arrivals and departures of migrants. Functional diversity was clustered in spring but showed over‐dispersion in the other three seasons. Phylogenetic β diversity in summer and winter assemblages was characterized by two distinct groups, while spring and autumn assemblages were mixed. Our results suggest that waterbird assemblages were primarily shaped by interspecific competition in winter, while random processes tended to shape assemblages in spring and fall. Environmental factors played a more important role in summer, during periods of high heat stress. In addition, species co‐occurrence patterns were significantly more strongly related to phylogenetic similarity in winter than in summer. Our results suggest that the relative importance of assemblage mechanisms can vary seasonally in response to changing environmental conditions, suggesting that studies attempting to infer a single dominant assembly mechanism may ignore important assembly processes. Temporal shifts in assembly mechanisms may play an important role in maintaining diversity in subtropical and temperate wetlands and perhaps also in other dynamic systems.     

To the canopy and beyond: Air dispersal as a mechanism of ubiquitous protistan pathogen assembly in tree canopies

Cercozoa and Oomycota contain a huge biodiversity and important pathogens of forest trees and other vegetation. We analyzed air dispersal of these protistan phyla with an air sampler near-ground (~2 m) and in tree crowns (~25 m) of three tree species (oak, linden and ash) in a temperate floodplain forest in March (before leafing) and May (after leaf unfolding) 2019 with a cultivation-independent high-throughput metabarcoding approach. We found a high diversity of Cercozoa and Oomycota in air samples with 122 and 81 OTUs, respectively. Especially oomycetes showed a significant difference in community composition between both sampling dates. Differences in community composition between air samples in tree canopies and close to the ground were however negligible, and also tree species identity did not affect communities in air samples, indicating that the distribution of protistan propagules through the air was not spatially restricted in the forest ecosystem. OTUs of plant pathogens, whose host species did not occur in the forest, demonstrate dispersal of propagules from outside the forest biome. Overall, our results lead to a better understanding of the stochastic processes of air dispersal of protists and protistan pathogens, a prerequisite to understand the mechanisms of their community assembly in forest ecosystems.     

Fungal infection alters the selection,dispersal and drift processes structuring the amphibian skin microbiome

Symbiotic microbial communities are important for host health, but the processes shaping these communities are poorly understood. Understanding how community assembly processes jointly affect microbial community composition is limited because inflexible community models rely on rejecting dispersal and drift before considering selection. We developed a flexible community assembly model based on neutral theory to ask: How do dispersal, drift and selection concurrently affect the microbiome across environmental gradients? We applied this approach to examine how a fungal pathogen affected the assembly processes structuring the amphibian skin microbiome. We found that the rejection of neutrality for the amphibian microbiome across a fungal gradient was not strictly due to selection processes, but was also a result of species‐specific changes in dispersal and drift. Our modelling framework brings the qualitative recognition that niche and neutral processes jointly structure microbiomes into quantitative focus, allowing for improved predictions of microbial community turnover across environmental gradients.     

How to make more out of community data? A conceptual framework and its implementation as models and software

Community ecology aims to understand what factors determine the assembly and dynamics of species assemblages at different spatiotemporal scales. To facilitate the integration between conceptual and statistical approaches in community ecology, we propose Hierarchical Modelling of Species Communities (HMSC) as a general, flexible framework for modern analysis of community data. While non‐manipulative data allow for only correlative and not causal inference, this framework facilitates the formulation of data‐driven hypotheses regarding the processes that structure communities. We model environmental filtering by variation and covariation in the responses of individual species to the characteristics of their environment, with potential contingencies on species traits and phylogenetic relationships. We capture biotic assembly rules by species‐to‐species association matrices, which may be estimated at multiple spatial or temporal scales. We operationalise the HMSC framework as a hierarchical Bayesian joint species distribution model, and implement it as R‐ and Matlab‐packages which enable computationally efficient analyses of large data sets. Armed with this tool, community ecologists can make sense of many types of data, including spatially explicit data and time‐series data. We illustrate the use of this framework through a series of diverse ecological examples.     

Nested patterns of community assembly in the colonisation of artificial canopy habitats by oribatid mites

An observed species–area relationship (SAR) in assemblages of oribatid mites inhabiting natural canopy habitats (suspended soils) led to an experimental investigation of how patch size, height in canopy and moisture influence the species richness, abundance and community composition of arboreal oribatid mites. Colonisation by oribatid mites on 90 artificial canopy habitats (ACHs) of three sizes placed at each of three heights on the trunks of ten western redcedar trees was recorded over a 1‐year period. Fifty‐nine oribatid mite species colonised the ACHs, and richness increased with the moisture content and size of the habitat patch. Oribatid mite species richness and abundance, and ACH moisture content decreased with increasing ACH height in the canopy. Patterns in the species richness and community composition of ACHs were non‐random and demonstrated a significant nested pattern. Correlations of patch size, canopy height and moisture content with community nestedness suggest that species‐specific environmental tolerances combined with the differential dispersal abilities of species contributed to the non‐random patterns of composition in these habitats. In line with the prediction that niche‐selection filters out species from the regional pool that cannot tolerate environmental harshness, moisture‐stressed ACHs in the high canopy had lower community variability than ACHs in the lower canopy. Colonising source pools to ACHs were almost exclusively naturally‐occurring canopy sources, but low levels of colonisation from the forest floor were apparent at low heights within the ACH system. We conclude that stochastic dispersal dynamics within the canopy are crucial to understanding oribatid mite community structure in suspended soils, but that the relative importance of stochastic dispersal assembly may be dependent on a strong deterministic element to the environmental tolerances of individual species which drives non‐random patterns of community assembly.     

Disentangling niche and neutral influences on community assembly: assessing the performance of community phylogenetic structure tests

Patterns of phylogenetic relatedness within communities have been widely used to infer the importance of different ecological and evolutionary processes during community assembly, but little is known about the relative ability of community phylogenetics methods and null models to detect the signature of processes such as dispersal, competition and filtering under different models of trait evolution. Using a metacommunity simulation incorporating quantitative models of trait evolution and community assembly, I assessed the performance of different tests that have been used to measure community phylogenetic structure. All tests were sensitive to the relative phylogenetic signal in species metacommunity abundances and traits; methods that were most sensitive to the effects of niche-based processes on community structure were also more likely to find non-random patterns of community phylogenetic structure under dispersal assembly. When used with a null model that maintained species occurrence frequency in random communities, several metrics could detect niche-based assembly when there was strong phylogenetic signal in species traits, when multiple traits were involved in community assembly, and in the presence of environmental heterogeneity. Interpretations of the causes of community phylogenetic structure should be modified to account for the influence of dispersal.     

Disentangling biotic interactions,environmental filters,and dispersal limitation as drivers of species co‐occurrence

A key focus in ecology is to search for community assembly rules. Here we compare two community modelling frameworks that integrate a combination of environmental and spatial data to identify positive and negative species associations from presence–absence matrices, and incorporate an additional comparison using joint species distribution models (JSDM). The frameworks use a dichotomous logic tree that distinguishes dispersal limitation, environmental requirements, and interspecific interactions as causes of segregated or aggregated species pairs. The first framework is based on a classical null model analysis complemented by tests of spatial arrangement and environmental characteristics of the sites occupied by the members of each species pair (Classic framework). The second framework, (SDM framework) implemented here for the first time, builds on the application of environmentally‐constrained null models (or JSDMs) to partial out the influence of the environment, and includes an analysis of the geographical configuration of species ranges to account for dispersal effects. We applied these approaches to examine plot‐level species co‐occurrence in plant communities sampled along a wide elevation gradient in the Swiss Alps. According to the frameworks, the majority of species pairs were randomly associated, and most of the non‐random positive and negative species associations could be attributed to environmental filtering and/or dispersal limitation. These patterns were partly detected also with JSDM. Biotic interactions were detected more frequently in the SDM framework, and by JSDM, than in the Classic framework. All approaches detected species aggregation more often than segregation, perhaps reflecting the important role of facilitation in stressful high‐elevation environments. Differences between the frameworks may reflect the explicit incorporation of elevational segregation in the SDM framework and the sensitivity of JSDM to the environmental data. Nevertheless, all methods have the potential to reveal general patterns of species co‐occurrence for different taxa, spatial scales, and environmental conditions.     

The community ecology of pathogens: coinfection,coexistence and community composition

Disease and community ecology share conceptual and theoretical lineages, and there has been a resurgence of interest in strengthening links between these fields. Building on recent syntheses focused on the effects of host community composition on single pathogen systems, we examine pathogen (microparasite) communities using a stochastic metacommunity model as a starting point to bridge community and disease ecology perspectives. Such models incorporate the effects of core community processes, such as ecological drift, selection and dispersal, but have not been extended to incorporate host–pathogen interactions, such as immunosuppression or synergistic mortality, that are central to disease ecology. We use a two‐pathogen susceptible‐infected (SI) model to fill these gaps in the metacommunity approach; however, SI models can be intractable for examining species‐diverse, spatially structured systems. By placing disease into a framework developed for community ecology, our synthesis highlights areas ripe for progress, including a theoretical framework that incorporates host dynamics, spatial structuring and evolutionary processes, as well as the data needed to test the predictions of such a model. Our synthesis points the way for this framework and demonstrates that a deeper understanding of pathogen community dynamics will emerge from approaches working at the interface of disease and community ecology.