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.     

Null model analysis of communities on gradients

Aim I employed a novel null model and metric to uncover unusual species co‐occurrence patterns in a herpetofaunal assemblage of 49 species collected at discrete elevations along a gradient. Location Mount Kupe, Cameroon. Methods Using a construction algorithm that started from a matrix of 0s, a sample null space of 25,000 unique null matrices was generated by simultaneously conserving (1) the number of occurrences of each species, (2) site richness and (3) species range spans derived from the observed incidence matrix. I then compared the number of times each pair of confamilial species co‐occurred in the null space with the same number derived from the observed incidence matrix. Two cases dealing with embedded absences in species ranges were tested: (1) embedded absences were maintained, and (2) embedded absences were assumed to be sampling omissions and were replaced by presences. Results In the observed absence/presence assemblage there were 147 possible confamilial species pairs. Therefore, 5% or eight were expected by chance alone to have co‐occurrence patterns that differed from chance expectations by chance alone. Of these confamilial species pairs, 38 were congeneric and so 5% or two were expected to differ from chance expectations. For case (1) 16, and for case (2) 17 confamilial species pairs’ co‐occurrence patterns differed significantly from chance expectations. For case (1) nine congeneric species pairs, and for case (2) 10 congeneric pairs differed significantly from chance expectations. For case (1) four, and for case (2) five congeneric species pairs formed checkerboards (patterns of mutual exclusion). Results from case (1) were a proper subset of case (2) indicating that sampling omissions did not alter greatly the results. Main conclusions I have demonstrated that null models are valuable tools to analyse ecological communities provided that proper models are employed. The choice of the appropriate null space to analyse distributions is critical. The null model employed to analyse birds on islands of an archipelago can be adapted to analyse species along gradients provided an additional range constraint is added to the null model. Moreover, added precision to results can be obtained by analysing each species pair separately, particularly those in the same family or genus, as opposed to applying a community‐wide metric to the faunal assemblage. My results support some of the speculations of previous authors who were unable to demonstrate their suspicions analytically.     

Ecological traits influence the phylogenetic structure of bird species co‐occurrences worldwide

The extent to which species’ ecological and phylogenetic relatedness shape their co‐occurrence patterns at large spatial scales remains poorly understood. By quantifying phylogenetic assemblage structure within geographic ranges of >8000 bird species, we show that global co‐occurrence patterns are linked – after accounting for regional effects – to key ecological traits reflecting diet, mobility, body size and climatic preference. We found that co‐occurrences of carnivorous, migratory and cold‐climate species are phylogenetically clustered, whereas nectarivores, herbivores, frugivores and invertebrate eaters tend to be more phylogenetically overdispersed. Preference for open or forested habitats appeared to be independent from the level of phylogenetic clustering. Our results advocate for an extension of the tropical niche conservatism hypothesis to incorporate ecological and life‐history traits beyond the climatic niche. They further offer a novel species‐oriented perspective on how biogeographic and evolutionary legacies interact with ecological traits to shape global patterns of species coexistence in birds.     

Bat assemblages on Neotropical land-bridge islands: nested subsets and null model analyses of species co-occurrence patterns

A fundamental goal of ecology is to understand whether ecological communities are structured according to general assembly rules or are essentially dictated by random processes. In the context of fragmentation, understanding assembly patterns and their mechanistic basis also has important implications for conservation. Using distribution data of 20 bat species collected on 11 islands in Gatún Lake, Panama, we tested for non‐randomness in presence–absence matrices with respect to nestedness and negative species co‐occurrence. We examined the causal basis for the observed patterns and conducted separate analyses for the entire assemblage and for various species submatrices reflecting differences in species’ trophic position and mobility. Furthermore, we explored the influence of weighting factors (area, isolation, abundance) on co‐occurrence analyses. Unweighted analyses revealed a significant negative co‐occurrence pattern for the entire assemblage and for phytophagous bats alone. Weighting analyses by isolation retained a pattern of species segregation for the whole assemblage but nullified the non‐random structure for phytophagous bats and suggested negative associations for animalivores and species with low mobility. Area‐ and abundance‐weighted analyses always indicated random structuring. Bat distributions followed a nested subset structure across islands, regardless of whether all species or different submatrices were analysed. Nestedness was in all cases unrelated to island area but weakly correlated with island isolation for incidence matrices of all species, phytophagous bats, and mobile species. Overall, evidence for negative interspecific interactions indicative of competitive effects was weak, corroborating previous studies based on ecomorphological analyses. Our findings indicate that bat assemblages on our study islands are most strongly shaped by isolation effects and species’ differential movement and colonization ability. From a conservation viewpoint this suggests that even in systems with high fragment–matrix contrast, a purely area‐based approach may be inadequate, and structural and functional connectivity among patches are important to consider in reserve planning.     

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.     

Testing multiple assembly rule models in avian communities on islands of an inundated lake,Zhejiang Province,China

Aim A fundamental question in community ecology is whether general assembly rules determine the structure of natural communities. Although many types of assembly rules have been described, including Diamond’s assembly rules, constant body‐size ratios, favoured states, and nestedness, few studies have tested multiple assembly rule models simultaneously. Therefore, little is known about the relative importance of potential underlying factors such as interspecific competition, inter‐guild competition, selective extinction and habitat nestedness in structuring community composition. Here, we test the above four assembly rule models and examine the causal basis for the observed patterns using bird data collected on islands of an inundated lake. Location Thousand Island Lake, China. Methods  We collected data on presence–absence matrices, body size and functional groups for bird assemblages on 42 islands from 2007 to 2009. To test the above four assembly rule models, we used null model analyses to compare observed species co‐occurrence patterns, body‐size distributions and functional group distributions with randomly generated assemblages. To ensure that the results were not biased by the inclusion of species with extremely different ecologies, we conducted separate analyses for the entire assemblage and for various subset matrices classified according to foraging guilds. Results The bird assemblages did not support predictions by several competitively structured assembly rule models, including Diamond’s assembly rules, constant body‐size ratios, and favoured states. In contrast, bird assemblages were highly significantly nested and were apparently shaped by extinction processes mediated through area effects and habitat nestedness. The nestedness of bird assemblages was not a result of passive sampling or selective colonization. These results were very consistent, regardless of whether the entire assemblage or the subset matrices were analysed. Main conclusions Our results suggest that bird assemblages were shaped by extinction processes mediated through area effects and habitat nestedness, rather than by interspecific or inter‐guild competition. From a conservation point of view, our results indicate that we should protect both the largest islands with the most species‐rich communities and habitat‐rich islands in order to maximize the number of species preserved.     

Pollinator‐mediated assemblage processes in California wildflowers

Community assembly is the result of multiple ecological and evolutionary forces that influence species coexistence. For flowering plants, pollinators are often essential for plant reproduction and establishment, and pollinator‐mediated interactions may influence plant community composition. Here, we use null models and community phylogenetic analyses of co‐occurrence patterns to determine the role of pollinator‐mediated processes in structuring plant communities dominated by congeners. We surveyed three species‐rich genera (Limnanthes, Mimulus and Clarkia) with centres of diversity in the Sierra Nevada of California. Each genus contains species that co‐flower and share pollinators, and each has a robust phylogeny. Within each genus, we surveyed 44–48 communities at three spatial scales, measured floral and vegetative traits and tested for segregation or aggregation of: (i) species, (ii) floral traits (which are likely to be influenced by pollinators), and (iii) vegetative traits (which are likely affected by other environmental factors). We detected both aggregation and segregation of floral traits that were uncorrelated with vegetative trait patterns; we infer that pollinators have shaped the community assembly although the mechanisms may be varied (competition, facilitation, or filtering). We also found that mating system differences may play an important role in allowing species co‐occurrence. Together, it appears that pollinators influence community assemblage in these three clades.     

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 community patterns of nestedness and species co-occurrence

Two opposing patterns of meta‐community organization are nestedness and negative species co‐occurrence. Both patterns can be quantified with metrics that are applied to presence‐absence matrices and tested with null model analysis. Previous meta‐analyses have given conflicting results, with the same set of matrices apparently showing high nestedness (Wright et al. 1998) and negative species co‐occurrence (Gotelli and McCabe 2002). We clarified the relationship between nestedness and co‐occurrence by creating random matrices, altering them systematically to increase or decrease the degree of nestedness or co‐occurrence, and then testing the resulting patterns with null models. Species co‐occurrence is related to the degree of nestedness, but the sign of the relationship depends on how the test matrices were created. Low‐fill matrices created by simple, uniform sampling generate negative correlations between nestedness and co‐occurrence: negative species co‐occurrence is associated with disordered matrices. However, high‐fill matrices created by passive sampling generate the opposite pattern: negative species co‐occurrence is associated with highly nested matrices. The patterns depend on which index of species co‐occurrence is used, and they are not symmetric: systematic changes in the co‐occurrence structure of a matrix are only weakly associated with changes in the pattern of nestedness. In all analyses, the fixed‐fixed null model that preserves matrix row and column totals has lower type I and type II error probabilities than an equiprobable null model that relaxes row and column totals. The latter model is part of the popular nestedness temperature calculator, which detects nestedness too frequently in random matrices (type I statistical error). When compared to a valid null model, a matrix with negative species co‐occurrence may be either highly nested or disordered, depending on the biological processes that determine row totals (number of species occurrences) and column totals (number of species per site).     

Longitudinal gradients in the phylogenetic community structure of European Tenebrionidae (Coleoptera) do not coincide with the major routes of postglacial colonization

Species specific colonization abilities and biotic and abiotic filters influence the local and regional faunal composition along colonization trajectories. Using a recent compilation of the occurrences of 1373 darkling beetle (Tenebrionidae) species and subspecies in 49 European countries and major islands, we reconstructed the tenebrionid postglacial colonization of middle and northern Europe from southern European glacial refuges and linked species composition to latitudinal and longitudinal gradients in phylogenetic relatedness across Europe. The majority of European islands and mainland countries appeared to be phylogenetically clustered. We did not find significant latitudinal trends in average phylogenetic relatedness of regional faunas along the supposed postglacial colonization routes but detected a strong positive correlation between mean relatedness and longitude of mainland faunas and an opposite negative correlation for island faunas. The strength of phylogenetic relatedness in the regional tenebrionid faunas decreased significantly with latitude and to a lesser degree with longitude. These findings are in accordance with two trajectories of postglacial colonization from centres in Spain and middle Asia that caused a strong longitudinal trend in the phylogenetic relatedness. Subsequent pair‐wise analyses of species co‐occurrences showed that species of similar distributional ranges tend to be phylogenetically clustered and species of different spatial distribution to be phylogenetically segregated. Both findings are in accordance with the concept of ‘range size heritability’. Our study demonstrates that taxonomic data are sufficiently powerful to infer continental wide patterns in phylogenetic relatedness that can be linked to colonization history and geographic information.     

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.     

The pairwise approach to analysing species co‐occurrence

The analysis of species co‐occurrence patterns continues to be a main pursuit of ecologists, primarily because the coexistence of species is fundamentally important in evaluating various theories, principles and concepts. Examples include community assembly, equilibrium versus non‐equilibrium organization of communities, resource partitioning and ecological character displacement, the local–regional species diversity relationship, and the metacommunity concept. Traditionally, co‐occurrence has been measured and tested at the level of an entire species presence–absence matrix wherein various algorithms are used to randomize matrices and produce statistical null distributions of metrics that quantify structure in the matrix. This approach implicitly recognizes a presence–absence matrix as having some real ecological identity (e.g. a set of species exhibiting nestedness among a set of islands) in addition to being a unit of statistical analysis. An emerging alternative is to test for non‐random co‐occurrence between paired species. The pairwise approach does not analyse matrix‐level structure and thus views a species pair as the fundamental unit of co‐occurrence. Inferring process from pattern is very difficult in analyses of co‐occurrence; however, the pairwise approach may make this task easier by simplifying the analysis and resulting inferences to associations between paired species.     

Co‐occurrence and phylogenetic distance in communities of mammalian ectoparasites: limiting similarity versus environmental filtering

Similarity between species plays a key role in the processes governing community assembly. The co‐occurrence of highly similar species may be unlikely if their similar needs lead to intense competition (limiting similarity). On the other hand, persistence in a particular habitat may require certain traits, such that communities end up consisting of species sharing the same traits (environmental filtering). Relatively little information exists on the relative importance of these processes in structuring parasite communities. Assuming that phylogenetic relatedness reflects ecological similarity, we tested whether the co‐occurrence of pairs of flea species (Siphonaptera) on the same host individuals was explained by the phylogenetic distance between them, among 40 different samples of mammalian hosts (rodents and shrews) from different species, areas or seasons. Our results indicate that frequency of co‐occurrence between flea species increased with decreasing phylogenetic distance between them in 37 out of 40 community samples, with 14 of these correlations being statistically significant. A meta‐analysis across all samples confirmed the overall trend for closely related species to co‐occur more frequently on the same individual hosts than expected by chance, independently of the identity of the host species or of environmental conditions. These findings suggest that competition between closely related, and therefore presumably ecologically similar, species is not important in shaping flea communities. Instead, if only fleas with certain behavioural, ecological and physiological properties can encounter and exploit a given host, and if phylogenetic relationships determine trait similarity among flea species, then a process akin to environmental filtering, or host filtering, could favour the co‐occurrence of related species on the same host.     

Phylogenetic plant community structure along elevation is lineage specific

The trend of closely related taxa to retain similar environmental preferences mediated by inherited traits suggests that several patterns observed at the community scale originate from longer evolutionary processes. While the effects of phylogenetic relatedness have been previously studied within a single genus or family, lineage‐specific effects on the ecological processes governing community assembly have rarely been studied for entire communities or flora. Here, we measured how community phylogenetic structure varies across a wide elevation gradient for plant lineages represented by 35 families, using a co‐occurrence index and net relatedness index (NRI). We propose a framework that analyses each lineage separately and reveals the trend of ecological assembly at tree nodes. We found prevailing phylogenetic clustering for more ancient nodes and overdispersion in more recent tree nodes. Closely related species may thus rapidly evolve new environmental tolerances to radiate into distinct communities, while older lineages likely retain inherent environmental tolerances to occupy communities in similar environments, either through efficient dispersal mechanisms or the exclusion of older lineages with more divergent environmental tolerances. Our study illustrates the importance of disentangling the patterns of community assembly among lineages to better interpret the ecological role of traits. It also sheds light on studies reporting absence of phylogenetic signal, and opens new perspectives on the analysis of niche and trait conservatism across lineages.     

Null matrices and the analysis of species co-occurrences

Patterns in species occurrences on islands have been analyzed by several authors. At issue is the number of non-occurring pairs of species (also known as checkerboards). Previous authors have suggested that if the number of checkerboards differs from what is expected by chance, then island communities might have been structured by competition. Investigators have pursued this problem by first generating random (or null) matrices and then testing a metric derived from the collection of null matrices against the metric calculated from the actual species co-occurrence matrix. The random matrices were constrained by requiring the number of species on each island, and the number of islands on which each species occurred to be equal to their observed values. We show that results from previous studies are generally flawed. We present a fast, efficient algorithm to generate null matrices for any set of fixed row and column sums, and propose a modification of a previously proposed metric as a test statistic. We evaluated the efficacy of our construction method for null creation and our metric using incidence matrices from the avifauna of Vanuatu (formerly New Hebrides). Received: 31 March 1997 / Accepted: 8 April 1998     

Plant–mycorrhizal fungus co‐occurrence network lacks substantial structure

The interactions between plants and arbuscular mycorrhizal fungi (AMF) maintain a crucial link between macroscopic organisms and the soil microbial world. These interactions are of extreme importance for the diversity of plant communities and ecosystem functioning. Despite this importance, only recently has the structure of plant–AMF interaction networks been studied. These recent studies, which used genetic data, suggest that these networks are highly structured, very similar to plant–animal mutualistic networks. However, the assembly process of plant–AMF communities is still largely unknown, and an important feature of plant–AMF interactions has not been incorporated: they occur at an extremely localized scale. Studying plant–AMF networks in a spatial context seems therefore a crucial step. This paper studies a plant–AMF spatial co‐occurrence network using novel methodology based on information theory and a unique set of spatially explicit species‐level data. We apply three null models of which only one accounts for spatial effects. We find that the data show substantial departures from null expectations for the two non‐spatial null models. However, for the null model considering spatial effects, there are few significant co‐occurrences compared with the other two null models. Thus, plant–AMF spatial co‐occurrences seem to be mostly explained by stochasticity, with a small role for other factors related to plant–AMF specialization. Furthermore, we find that the network is not significantly nested or modular. We conclude that this plant–AMF spatial co‐occurrence network lacks substantial structure and, therefore, plants and AMF species do not track each other over space. Thus, random encounters seem more important in the first step of the assembly of plant–AMF communities. Synthesis The symbiotic interaction between plants and arbuscular mycorrhizal fungi (AMF) is crucial for ecosystem functioning. However, the factors affecting the assembly of plant‐AMF communities are poorly understood. An important factor of the assembly of plant‐AMF communities has been overlooked: plant‐AMF interactions occur at a localized spatial scale. Our study investigated the importance of space in the structure of plant‐AMF communities. We studied a plant‐AMF spatial co‐occurrence network using a unique set of spatially explicit data and applied three null models. We found that plant‐AMF spatial co‐occurrences seem to be mostly explained by stochasticity. In particular, our study shows that this plant‐AMF spatial co‐occurrence network lacks substantial structure and, therefore, plants and AMF species do not track each other over space. Thus, random encounters seem to drive the assembly of plant‐AMF communities.     

From null community to non-randomly structured actual plant assemblages: parsimony analysis of species co-occurrences

Null community is a spatio‐temporal abstraction of an initial regional species pool from which local species pools and actual community assemblages are organized. Any process that causes joint responses of species with similar susceptibilities affects community assembly. Through time, sequential assembly processes change the composition of a species pool in a way analogous to the one in which evolutionary processes promote character changes from an ancestor to current species. The segregation of species occurrences in an actual community suggests that assembly processes non‐randomly structured the observed community assemblages. However, going backwards to imply the causes of a particular arrangement of species is a non‐trivial challenge. I merge these premises with the philosophical and methodological foundations of cladistics. I propound parsimony analysis of species co‐occurrences as an outstanding means of devising operational hypotheses about the assembly of any non‐randomly structured set of actual community assemblages related to a common species pool. To explore this approach, I used field data gathered in a suite of 10 wetland assemblages. First, I tested independence of 101 plant species occurrences by a null model. As significant non‐random species co‐occurrence was detected, I applied a parsimony analysis taking the species occurrences as attributes, the assemblages as terminal units, and a putative null community constituted by all the present local species as the root of the assembly suite. The analysis produced four most parsimonious trees of assembly relationships. These trees maximize the number of similarities among community assemblages that can be explained by the sole fact of sharing a common regional species pool. One most parsimonious spatio‐temporal arrangement of species occurrence changes was reconstructed on one of the trees. I interpret this reconstruction in terms of assembly events, species exclusions and recruitments, showing the potentialities of this analysis to formulate operational hypotheses about community organization.     

An integrated framework to improve the concept of resource specialisation

Resource specialisation, although a fundamental component of ecological theory, is employed in disparate ways. Most definitions derive from simple counts of resource species. We build on recent advances in ecophylogenetics and null model analysis to propose a concept of specialisation that comprises affinities among resources as well as their co‐occurrence with consumers. In the distance‐based specialisation index (DSI), specialisation is measured as relatedness (phylogenetic or otherwise) of resources, scaled by the null expectation of random use of locally available resources. Thus, specialists use significantly clustered sets of resources, whereas generalists use over‐dispersed resources. Intermediate species are classed as indiscriminate consumers. The effectiveness of this approach was assessed with differentially restricted null models, applied to a data set of 168 herbivorous insect species and their hosts. Incorporation of plant relatedness and relative abundance greatly improved specialisation measures compared to taxon counts or simpler null models, which overestimate the fraction of specialists, a problem compounded by insufficient sampling effort. This framework disambiguates the concept of specialisation with an explicit measure applicable to any mode of affinity among resource classes, and is also linked to ecological and evolutionary processes. This will enable a more rigorous deployment of ecological specialisation in empirical and theoretical studies.     

Shared environmental responses drive co‐occurrence patterns in river bird communities

Positive or negative patterns of co‐occurrence might imply an influence of biotic interactions on community structure. However, species may co‐occur simply because of shared environmental responses. Here, we apply two complementary modelling methodologies – a probabilistic model of significant pairwise associations and a hierarchical multivariate probit regression model – to 1) attribute co‐occurrence patterns in 100 river bird communities to either shared environmental responses or to other ecological mechanisms such as interaction with heterospecifics, and 2) examine the strength of evidence for four alternative models of community structure. Species co‐occurred more often than would be expected by random community assembly and the species composition of bird communities was highly structured. Co‐occurrence patterns were primarily explained by shared environmental responses; species’ responses to the environmental variables were highly divergent, with both strong positive and negative environmental correlations occurring. We found limited evidence for behaviour‐driven assemblage patterns in bird communities at a large spatial scale, although statistically significant positive associations amongst some species suggested the operation of facilitative mechanisms such as heterospecific attraction. This lends support to an environmental filtering model of community assembly as being the principle mechanism shaping river bird community structure. Consequently, species interactions may be reduced to an ancillary role in some avifaunal communities, meaning if shared environmental responses are not quantified studies of co‐occurrence may overestimate the role of species interactions in shaping community structure.     

Research frontiers in null model analysis

Null models are pattern‐generating models that deliberately exclude a mechanism of interest, and allow for randomization tests of ecological and biogeographic data. Although they have had a controversial history, null models are widely used as statistical tools by ecologists and biogeographers. Three active research fronts in null model analysis include biodiversity measures, species co‐occurrence patterns, and macroecology. In the analysis of biodiversity, ecologists have used random sampling procedures such as rarefaction to adjust for differences in abundance and sampling effort. In the analysis of species co‐occurrence and assembly rules, null models have been used to detect the signature of species interactions. However, controversy persists over the details of computer algorithms used for randomizing presence–absence matrices. Finally, in the newly emerging discipline of macroecology, null models can be used to identify constraining boundaries in bivariate scatterplots of variables such as body size, range size, and population density. Null models provide specificity and flexibility in data analysis that is often not possible with conventional statistical tests.