Phylogenetic signals in flea-host interaction networks from four biogeographic realms: differences between interactors and the effects of environmental factors

The structure of ecological interaction networks is associated with evolutionary histories of the interacting species. This is reflected by the phylogenetic signals (PS) in these networks when closely related species interact with similar partners because some traits inherited from the ancestors may determine ecological interactions. We investigated PS for small mammalian hosts and fleas in 80 regional interaction networks from four biogeographic realms (the Palearctic, the Nearctic, the Afrotropics, and the Neotropics). We asked (i) whether the relative strength of PS in host-flea networks is similar between hosts and fleas and/or between realms; (ii) how environmental variation affects the PS of hosts and fleas in their interaction networks; and (iii) whether the PS for hosts or fleas is affected by the phylogenetic diversity of either hosts or fleas, respectively. We found that the PS for hosts was stronger than that for fleas in all realms. An environmental effect on the PS for hosts, but not for fleas, was found in three of the four realms (except the Neotropics). In the Palearctic and the Nearctic, a stronger PS was characteristic for cooler and/or drier regions, whereas the opposite was the case for the Afrotropics in regard to precipitation. The phylogenetic diversity of regional host and flea assemblages was not associated with the values of the respective PS in any realm. We conclude that the pattern of the relative strength of the PS for hosts and fleas in their interaction networks is similar in different biogeographic realms with vastly different host and flea faunas. However, the environmental effects on the PS are geographically variable and might be associated with the history of host-flea associations, as well as the spatial pattern of environmental variation, within a realm.     

Phylogeny and co‐occurrence of mammal species on Southeast Asian islands

Aim Islands have often been used as model systems in community ecology. The incorporation of information on phylogenetic relatedness of species in studies of island assemblage structure is still uncommon, but could provide valuable insights into the processes of island community assembly. We propose six models of island community assembly that make different predictions about the associations between co‐occurrences of species pairs on islands, phylogenetic relatedness and ecological similarity. We then test these models using data on mammals of Southeast Asian islands. Location Two hundred and forty islands of the Sundaland region of Southeast Asia. Methods We quantified the co‐occurrence of species pairs on islands, and identified pairs that co‐occur more frequently (positive co‐occurrence) or less frequently (negative co‐occurrence) than expected under null models. We then examined the distributions of these significantly deviating pairs with respect to phylogenetic relatedness and ecological differentiation, and compared these patterns with those predicted by the six community assembly models. We used permutation regression to test whether co‐occurrence patterns are predicted by relatedness, body size difference or difference in diet quality. Separate co‐occurrence matrices were analysed in this way for seven mammal families and four smaller subsets of the islands of Sundaland. Results In many matrices, average numbers of negative co‐occurrences were higher than expected under null models. This is consistent with assemblage structuring by competition, but may also result from low geographic overlap of species pairs, which contributes to negative co‐occurrences at the archipelago‐wide level. Distributions of species pairs within plots of phylogenetic distance × ecological differentiation were consistent with competition, habitat filtering or within‐island speciation models, depending on the taxon. Regressions indicated that co‐occurrence was more likely among closely related species pairs within the Viverridae and Sciuridae, but in most matrices phylogenetic distance was unrelated to co‐occurrence. Main conclusions Simple deterministic models linking co‐occurrence with phylogeny and ecology are a useful framework for interpreting distributions and assemblage structure of island species. However, island assemblages in Sundaland have probably been shaped by a complex idiosyncratic set of interacting ecological and evolutionary processes, limiting the predictive power of such models.     

Deconstructing spatial patterns in species composition of ectoparasite communities: the relative contribution of host composition,environmental variables and geography

Aim We determined whether dissimilarity in species composition between parasite communities depends on geographic distance, environmental dissimilarity or host faunal dissimilarity, for different subsets of parasite species with different levels of host specificity. Location Communities of fleas parasitic on small mammals from 28 different regions of the Palaearctic. Method Dissimilarities in both parasite and host species composition were computed between each pair of regions using the Bray–Curtis index. Geographic distances between regions were also calculated, as were measures of environmental dissimilarity consisting of the pairwise Euclidean distances between regions derived from elevation, vegetation and climatic variables. The 136 flea species included in the dataset were divided into highly host‐specific species (using 1–2 host species per region, on average), moderately host‐specific species (2.2–4 hosts per region) and generalist species (>4 hosts per region). The relative influence of geographic distance, host faunal dissimilarity and environmental dissimilarity on dissimilarity of flea species composition among all regions was analysed for the entire set of flea species as well as for the three above subsets using multiple regressions on distance matrices. Results When including all flea species, dissimilarity in flea species composition was affected by all three independent variables, although the pure effect of dissimilarity in host species composition was the strongest. Results were different when the subsets of fleas differing in host specificity were treated separately. In particular, dissimilarity in species composition of highly host‐specific fleas increased solely with environmental dissimilarity, whereas dissimilarity for both moderately specific and non‐specific fleas increased with both geographic distance and dissimilarity in host species composition. Main conclusions Host specificity seems to dictate which of the three factors considered is most likely to affect the dissimilarity between flea communities. Counter‐intuitively, environmental dissimilarity played a key role in determining dissimilarity in species composition of highly host‐specific fleas, possibly because, although their presence in a region relies on the occurrence of particular host species, their abundance is itself mostly determined by climatic conditions. Our results show that deconstructing communities into subsets of species with different traits can make it easier to uncover the mechanisms shaping geographic patterns of diversity.     

Male hosts drive infracommunity structure of ectoparasites

We studied the co-occurrence of flea species in infracommunities of 16 rodents from four regions (South Africa, Tanzania, central Europe and western Siberia) using null models, and predicted that flea co-occurrences will be expressed more strongly in male than in female hosts. We examined patterns of co-occurrence (measured as the C score) in infracommunities of fleas that are parasitic on male and female hosts by comparing co-occurrence frequencies with those expected by chance. When a significant degree of nonrandomness in flea co-occurrences was detected, it indicated aggregative infracommunity structure. In Tanzanian rodents, no significant flea co-occurrences were detected in either male or female hosts. In a South African rodent, significant flea co-occurrences were not detected in males, but were found in females in some localities. In Palaearctic rodents, significant nonrandomness was detected either equally for males and females or more frequently in males than in females. Meta-analyses demonstrated that the frequency of the detection of nonrandomness in flea co-occurrences was significantly higher in male than in female hosts. The values of the standardized effect size (SES) for the C score differed significantly among host species, but not between host genders. When the Palaearctic hosts were analyzed separately, the effects of both host gender and species appeared to be significant, with the SES values for the C score in males being smaller than those in females. The strength of the gender difference in the manifestation of flea community structure increased with increasing gender difference in flea species richness, and with decreasing gender difference in flea prevalence for the Palaearctic hosts. We conclude that male hosts are the main drivers of flea infracommunity structure. However, the manifestation of gender bias in flea community structure varies among host species, and is likely determined by the pattern of species-specific spatial behavior.     

Pattern detection in null model analysis

Synthesis The identification of distinctive patterns in species x site presence‐absence matrices is important for understanding meta‐community organisation. We compared the performance of a suite of null models and metrics that have been proposed to measure patterns of segregation, aggregation, nestedness, coherence, and species turnover. We found that any matrix with segregated species pairs can be re‐ordered to highlight aggregated pairs, indicating that these seemingly opposite patterns are closely related. Recently proposed classification schemes failed to correctly classify realistic matrices that included multiple co‐occurrence structures. We propose using a combination of metrics and decomposing matrix‐wide patterns into those of individual pairs of species and sites to pinpoint sources of non‐randomness. Null model analysis has been a popular tool for detecting pattern in binary presence–absence matrices, and previous tests have identified algorithms and metrics that have good statistical properties. However, the behavior of different metrics is often correlated, making it difficult to distinguish different patterns. We compared the performance of a suite of null models and metrics that have been proposed to measure patterns of segregation, aggregation, nestedness, coherence, and species turnover. We found that any matrix with segregated species pairs can be re‐ordered to highlight aggregated pairs. As a consequence, the same null model can identify a single matrix as being simultaneously aggregated, segregated or nested. These results cast doubt on previous conclusions of matrix‐wide species segregation based on the C‐score and the fixed‐fixed algorithm. Similarly, we found that recently proposed classification schemes based on patterns of coherence, nestedness, and segregation and aggregation cannot be uniquely distinguished using proposed metrics and null model algorithms. It may be necessary to use a combination of different metrics and to decompose matrix‐wide patterns into those of individual pairs of species or pairs of sites to pinpoint the sources of non‐randomness.     

Relationship between host diversity and parasite diversity: flea assemblages on small mammals

Aim We examined the relationship between host species richness and parasite species richness using simultaneously collected data on small mammals (Insectivora, Rodentia and Lagomorpha) and their flea parasites. Location The study used previously published data on small mammals and their fleas from 37 different regions. All the world's main geographical regions other than Australasia and Wallacea were represented in the study, i.e. neotropical, nearctic, palaearctic, oriental and afrotropical realms. Methods We controlled the data for the area sampled and sampling effort and then tested this relationship using both cross‐region conventional analysis and the independent contrasts method (to control for the effects of biogeographic historical relationships among different regions). Brooks parsimony analysis was used to construct a region cladogram based on the presence/absence of a host species and host phylogeny. Results Both cross‐region and independent contrasts analyses showed a positive correlation between host species richness and flea species richness. Conventional cross‐region regression under‐ or overestimated fleas species richness in the majority of regions. Main conclusions When the regression derived by the independent contrasts method was mapped onto the original tip data space, points that deviated significantly from the regression originated from Kenya, Mississippi and southern California (lower than expected flea richness) and Chile, Idaho, south‐western California and Kyrgyzstan (higher than expected flea richness). These deviations can be explained by the environmental mediation of host–flea relationships and by a degree of environmental variety in sampled areas.     

Accounting for environmental variation in co‐occurrence modelling reveals the importance of positive interactions in root‐associated fungal communities

Understanding the role of interspecific interactions in shaping ecological communities is one of the central goals in community ecology. In fungal communities, measuring interspecific interactions directly is challenging because these communities are composed of large numbers of species, many of which are unculturable. An indirect way of assessing the role of interspecific interactions in determining community structure is to identify the species co‐occurrences that are not constrained by environmental conditions. In this study, we investigated co‐occurrences among root‐associated fungi, asking whether fungi co‐occur more or less strongly than expected based on the environmental conditions and the host plant species examined. We generated molecular data on root‐associated fungi of five plant species evenly sampled along an elevational gradient at a high arctic site. We analysed the data using a joint species distribution modelling approach that allowed us to identify those co‐occurrences that could be explained by the environmental conditions and the host plant species, as well as those co‐occurrences that remained unexplained and thus more probably reflect interactive associations. Our results indicate that not only negative but also positive interactions play an important role in shaping microbial communities in arctic plant roots. In particular, we found that mycorrhizal fungi are especially prone to positively co‐occur with other fungal species. Our results bring new understanding to the structure of arctic interaction networks by suggesting that interactions among root‐associated fungi are predominantly positive.     

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.     

Geographical variation in the 'bottom-up' control of diversity: fleas and their small mammalian hosts

Aim We searched for signs of the ‘bottom‐up’ diversity effect in the association between fleas (Siphonaptera) and their small mammalian hosts (Rodentia, Insectivora and Lagomorpha). We asked (1) whether a strong dependence of flea species richness on host species richness is characteristic for both Palaeoarctic and Nearctic realms; (2) if yes, whether the ratio of host species per flea species along the host diversity gradient is similar between the Palaeoarctic and Nearctic; and (3) whether factors other than host species richness (i.e. geographical position, climate and landscape) might better explain variation in flea species richness than host species richness. Location The study used previously published data on species richness of fleas and their small mammalian hosts from 26 Palaeoarctic and 19 Nearctic regions. Methods We regressed the number of flea species on the number of small mammal species across regions, separately for Palaeoarctic and Nearctic realms, using both non‐transformed data as well as data corrected for the confounding effects of host sampling effort and sampling area. To test whether flea species richness is determined by external factors unrelated to the host, we used stepwise multiple regressions of flea species richness against host species richness and parameters describing the geographical position, climate and relief of a region. Results When non‐transformed data were analysed, flea species richness was positively correlated with host species richness in both the Palaeoarctic and Nearctic, although the slopes of the two regressions differed significantly. After removal of the confounding effects of host sampling effort and sampling area, Palaeoarctic flea species richness remained strongly positively correlated with host species richness, whereas in the Nearctic, flea species richness appeared to be completely independent of host species richness. Results of the multiple regressions using corrected data demonstrated that in the Palaeoarctic, flea species richness was correlated with both the number of host species and the mean altitude of the region, whereas in the Nearctic, flea species richness only tended to be weakly correlated with latitude (however, this correlation turned out to be non‐significant after Bonferroni correction). Main conclusions We found evidence of bottom‐up control of flea diversity in the Palaeoarctic regions only, and not in the Nearctic. We explore several potential explanations for the different patterns observed in the two biogeographical realms, including differences in (1) levels of host specialization, (2) history of host–parasite associations and (3) landscape effects on flea diversification. We conclude that these factors combine to create different macroecological patterns in different biogeographical realms, and that diversity is not governed by the same forces everywhere.     

Co‐occurrence patterns in a diverse arboreal ant community are explained more by competition than habitat requirements

A major goal of community ecology is to identify the patterns of species associations and the processes that shape them. Arboreal ants are extremely diverse and abundant, making them an interesting and valuable group for tackling this issue. Numerous studies have used observational data of species co‐occurrence patterns to infer underlying assembly processes, but the complexity of these communities has resulted in few solid conclusions. This study takes advantage of an observational dataset that is unusually well‐structured with respect to habitat attributes (tree species, tree sizes, and vegetation structure), to disentangle different factors influencing community organization. In particular, this study assesses the potential role of interspecific competition and habitat selection on the distribution patterns of an arboreal ant community by incorporating habitat attributes into the co‐occurrence analyses. These findings are then contrasted against species traits, to explore functional explanations for the identified community patterns. We ran a suite of null models, first accounting only for the species incidence in the community and later incorporating habitat attributes in the null models. We performed analyses with all the species in the community and then with only the most common species using both a matrix‐level approach and a pairwise‐level approach. The co‐occurrence patterns did not differ from randomness in the matrix‐level approach accounting for all ant species in the community. However, a segregated pattern was detected for the most common ant species. Moreover, with the pairwise approach, we found a significant number of negative and positive pairs of species associations. Most of the segregated associations appear to be explained by competitive interactions between species, not habitat affiliations. This was supported by comparisons of species traits for significantly associated pairs. These results suggest that competition is the most important influence on the distribution patterns of arboreal ants within the focal community. Habitat attributes, in contrast, showed no significant influence on the matrix‐wide results and affected only a few associations. In addition, the segregated pairs shared more biological characteristic in common than the aggregated and random ones.     

Scale‐dependence of phylogenetic signal in ecological traits of ectoparasites

The non‐independence of traits among closely related species is a well‐documented phenomenon underpinning modern methods for comparative analyses or prediction of trait values in new species. Surprisingly such studies have mainly focused on life‐history or morphological traits of free‐living organisms, ignoring ecological attributes of parasite species in spite of the fact that they are critical for conservation and human health. We tested for a phylogenetic signal acting on two ecological traits, abundance and host specificity, using data for 218 flea species parasitic on small mammals in 19 regions of the Palaearctic and Nearctic, and a phylogenetic tree for these species. We tested for the presence of a phylogenetic signal at both regional and continental scales using three measures (Abouheif/Moran's I, Pagel's λ, and Blomberg et al.'s K). Our results show 1) a consistent positive phylogenetic signal for flea abundance, but only a weaker and erratic signal for host specificity, and 2) a clear dependence on scale, with the signals being stronger at the continental scale and relatively weaker or inconsistent at the regional scale. Whenever values of Blomberg et al.'s K were found significant, they were <1 suggesting that the effects of phylogeny on the evolution of abundance and host specificity in fleas are weaker than expected from a Brownian motion model. The most striking finding is that, within a continental fauna, closely‐related flea species are characterized by similar levels of abundance, though this pattern is weaker within local assemblages, possibly eroded by local biotic or abiotic conditions. We discuss the link between history (represented by phylogeny) and pattern of variation among species in morphological and ecological traits, and use comparisons between the Palaearctic and Nearctic to infer a role of historical events in the probability of detecting phylogenetic signals.     

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.     

Are ectoparasite communities structured? Species co-occurrence, temporal variation and null models

1. We studied temporal variation in the structure of flea communities on small mammalian hosts from eastern Slovakia using null models. We asked (a) whether flea co-occurrences in infracommunities (in the individual hosts) in different hosts as well as in the component communities (in the host species) demonstrate a non-random pattern; (b) whether this pattern is indicative of either positive or negative flea species interactions; (c) whether this pattern varies temporally; and (d) whether the expression of this pattern is related to population size of either fleas or hosts or both. 2. We constructed a presence/absence matrix of flea species for each temporal sample of a host species and calculated four metrics of co-occurrence, namely the C-score, the number of checkerboard species pairs, the number of species combinations and the variance ratio (V-ratio). Then we compared these metrics with the respective indices calculated for 5000 null matrices that were assembled randomly using two algorithms, namely fixed-fixed (FF) and fixed-equiprobable (FE). 3. Most co-occurrence metrics calculated for real data did not differ significantly from the metrics calculated for simulated matrices using the FF algorithm. However, the indices observed for 42 of 75 presence/absence matrices differed significantly from the null expectations for the FE models. Non-randomness was detected mainly by the C-score and V-ratio metrics. In all cases, the direction of non-randomness was the same, namely the aggregation, not competition, of flea species in host individuals and host species. 4. The inclusion or exclusion of the uninfested hosts in the FE models did not affect the results for individual host species. However, exclusion of the uninfested host species led to the acceptance of the null hypothesis for only six of 13 temporal samples of the component flea communities for which non-randomness was detected when the uninfested hosts were included in the analysis. 5. In most host species, the absolute values of the standardized size effect of both the C-score and V-ratio increased with an increase in host density and a concomitant decrease in flea abundance and prevalence. 6. Results of this study demonstrated that (a) flea assemblages on small mammalian hosts were structured at some times, whereas they appeared to be randomly assembled at other times; (b) whenever non-randomness of flea co-occurrences was detected, it suggested aggregation but never segregation of flea species in host individuals or populations; and (c) the expression of structure in flea assemblages depended on the level of density of both fleas and hosts.     

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.     

Phylogenetic composition and structure of tree communities shed light on historical processes influencing tropical rainforest diversity

The Neotropics, Afrotropics and Madagascar have different histories which have influenced their respective patterns of diversity. Based on current knowledge of these histories, we developed the following predictions about the phylogenetic structure and composition of rainforest tree communities: (Hypothesis 1) isolation of Gondwanan biotas generated differences in phylogenetic composition among biogeographical regions; (H2) major Cenozoic extinction events led to lack of phylogenetic structure in Afrotropical and Malagasy communities; (H3) greater angiosperm diversification in the Neotropics led to greater phylogenetic clustering there than elsewhere; (H4) phylogenetic overdispersion is expected near the Andes due to the co‐occurrence of magnoliids tracking conserved habitat preferences and recently diversified eudicot lineages. Using abundance data of tropical rainforest tree species from 94 communities in the Neotropics, Afrotropics and Madagascar, we computed net relatedness index (NRI) to assess local phylogenetic structure, i.e. phylogenetic clustering vs. overdispersion relative to regional species pools, and principal coordinates of phylogenetic structure (PCPS) to assess variation in phylogenetic composition across communities. We observed significant differences in phylogenetic composition among biogeographical regions (agreement with H1). Overall phylogenetic structure did not differ among biogeographical regions, but results indicated variation from Andes to Amazon. We found widespread phylogenetic randomness in most Afrotropical and all Malagasy communities (agreement with H2). Most of central Amazonian communities were phylogenetically random, although some communities presented phylogenetic clustering (partial agreement with H3). We observed phylogenetic overdispersion near the Andes (agreement with H4). We were able to identify how differences in lineage composition are related to local phylogenetic co‐occurrences across biogeographical regions that have been undergoing different climatic and orographic histories during the past 100 Myr. We observed imprints of the history following Gondwana breakup on phylobetadiversity and local phylogenetic structure of rainforest tree communities in the Neotropics, Afrotropics and Madagascar.     

Fine-scale structure and cross-taxon congruence of bird and beetle assemblages in an old-growth boreal forest mosaic

Aim Nestedness occurs when species present in depauperate sites are subsets of those found in species‐rich sites. The degree of congruence of site nestedness among different assemblages can inform commonalities of mechanisms structuring the assemblages. Well‐nested assemblages may still contain idiosyncratic species and sites that notably depart from the typical assemblage pattern. Idiosyncrasy can arise from multiple processes, including interspecific interactions and habitat preferences, which entail different consequences for species co‐occurrences. We investigate the influence of fine‐scale habitat variation on nestedness and idiosyncrasy patterns of beetle and bird assemblages. We examine community‐level and pairwise species co‐occurrence patterns, and highlight the potential influence of interspecific interactions for assemblage structure. Location Côte‐Nord region of Québec, Canada. Methods We sampled occurrences of ground‐dwelling beetles, flying beetles and birds at sites within old‐growth boreal forest. We examined the nestedness and idiosyncrasy of sites and sought relationships to habitat attributes. We analysed non‐random species co‐occurrence patterns at pairwise and community levels, using null model analysis and five ‘association’ indices. Results All three assemblages were significantly nested. There was limited congruence only between birds and flying beetles whose nestedness was related to canopy openness. For ground‐dwelling beetles, nestedness was related to high stand heterogeneity and sapling density, whereas site idiosyncrasy was inversely related to structural heterogeneity. For birds, site idiosyncrasy increased with canopy cover, and most idiosyncratic species were closed‐canopy specialists. In all assemblages, species idiosyncrasy was positively correlated with the frequency of negative pairwise associations. Species co‐occurrence patterns were non‐random, and for flying beetles and birds positive species pairwise associations dominated. Community‐level co‐occurrence summaries may not, however, always reflect these patterns. Main conclusions Nestedness patterns of different assemblages may not correlate, even when sampled at common locations, because of different responses to local habitat attributes. We found idiosyncrasy patterns indicating opposing habitat preferences, consistent with antagonistic interactions among species within assemblages. Analysis of such patterns can thus suggest the mechanisms generating assemblage structures, with implications for biodiversity conservation.     

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).     

Geographic patterns of diversification: an example with ectoparasitic insects

On any spatial scale, the species composition of a taxonomic group often departs from a phylogenetically random subset drawn from the pool of species available on a higher scale. Analysis of the uneven representation of related lineages in different assemblages can reveal the action of various forces shaping their diversification. For any assemblage, unequal diversification among lineages can be estimated using diversity skewness, an index of the balance of a phylogenetic tree whose values increase with increasing differences in diversification rates among tree branches. We tested for geographical patterns in the diversity skewness of flea assemblages parasitic on small mammals in 26 distinct geographic localities from the Palaearctic and 15 from the Nearctic. Overall, diversity skewness of the Nearctic flea assemblage was unexpectedly high compared to that of the global flea fauna, whereas that of the Palaearctic did not depart from the expectations of a null model. On a smaller scale, the diversity skewness of local flea assemblages was sometimes lower, sometimes higher, but, in most of the 41 localities, it did not differ significantly from that of random subsets taken from the species pool available on the larger spatial scale (either the world fauna or that of the biogeographical realm, i.e. Palaearctic or Nearctic). More importantly, among Palaearctic assemblages, diversity skewness increased with increasing latitude and/or decreasing mean air temperatures. The different patterns observed in the Palaearctic and Nearctic may be in part due the fact that flea diversification appears to have been more intense in the former than the latter, and to differences between them in relief and glacial history. Temperature‐driven speciation rates may well explain the latitudinal gradient in diversity skewness in the Palaearctic. The results illustrate the action of various biogeographical processes in shaping the uneven differentiation of flea lineages on different spatial scales. © 2008 The Linnean Society of London, Biological Journal of the Linnean Society, 2008, 95 , 807–814.     

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.