Null model tests of clustering of species, negative co-occurrence patterns and nestedness in meta-communities

We propose tests for patterns in meta-community structure. The tests for clustering and nestedness of the occurrences of species and negative co-occurrence patterns provide four important innovations. Firstly, they are not restricted to the analysis of communities along one-dimensional gradients or to the main axis of variation. Secondly, abundance data can also be considered in the null model whereas most previous approaches could consider only presence/absence data. And thirdly, habitat suitability and spatial autocorrelation can be incorporated in the null model so that patterns that might be caused by biotic interactions can be distinguished from patterns which are the result of differences in the suitability or accessibility of sites for the examined organisms. Finally, the test for nestedness is also appropriate if there is more than one set of nested subsets. A re-analysis of 35 data sets with these tests showed the importance of considering the autocorrelation of the occurrences of species in analyses of meta-community structure and demonstrated the advantage of abundance data for tests of clustering of species. With abundance data it could be shown that there is a significant clustering of species, i.e. there are positive associations of species in most meta-communities, even if an environmentally or spatially constrained null model is used for the test. Co-occurrence patterns that might indicate interspecific competition were found in many of the analysed presence/absence data sets. Surprisingly the analysis of abundance data sets provides less evidence for interspecific competition. A hierarchical organization of communities, i.e. nestedness, turned out to be a rare pattern, if the autocorrelation of the occurrences of species is considered.     

Environmentally constrained null models: site suitability as occupancy criterion

Null models have proven to be an important quantitative tool in the search for ecological processes driving local diversity and species distribution. However, there remains an important concern that different processes, such as environmental conditions and biotic interactions may produce similar patterns in species distributions. In this paper we present an analytical protocol for incorporating habitat suitability as an occupancy criterion in null models. Our approach involves modeling species presence or absence as a function of environmental conditions, and using the estimated site-specific probabilities of occurrence as the likelihood of species occupancy of a site during the generation of "null communities". We validated this approach by showing that type I error is not affected by the use of probabilities as a site occupancy criterion and is robust against a variety of predictive performances of the species-environmental models. We describe the expected differences when contrasting classical and the environmentally constrained null models, and illustrate our approach with a data set of Dutch dune hunting spider assemblages. Together, an environmentally constrained approach to null models will provide a more robust evaluation of species associations by facilitating the distinction between mutually exclusive processes that may shape species distributions and community assembly.     

Statistical methods for analysis of communities' species structure (with riverine macrozoobenthos as an example)

Species turnover or coherence in species co-occurrence as well as boundary clumping and nestedness in structural composition of ecological communities reflect the extent of determinancy in their organization (Leibold, Mikkelson, 2002). These phenomena may be a consequence of either interactions between species or heterogeneity in spatial distribution of populations density. We have examined statistical patterns of species structure variability using benthic communities of riverine ecosystems as an example. The ecosystems studied are characterized by strongly pronounced linear gradient of landscape features and environmental factors. The results of a long-term hydrobiological survey being conducted at 22 observational stations on the Sok River along with its tributary, the Baytugan River (Lower Volga basin, total watercourse length is 375 km) are involved into the analysis. A spreadsheet for statistical processing of the data included 375 macrozoobenthic taxa contained in 147 samples. An assessment of species structure nestedness in benthic communities at separate sites and along the watercourse as a whole has been carried out using various metrics such as nestedness "temperature" (Patterson, Atmar, 2000), discrepancy measure (Brualdi, Sanderson, 1999), nestedness based on overlap and decreasing fill (NODE--Almeida-Neto et al., 2008) and others. Statistical significance of ecosystems structural determinancy has been tested by means of randomization procedures and standard null models (Gotelli, 2000). The conclusions seem to be ambiguous and dependent on a level and scale of an ecosystem resolution into separate blocks, also on configuration and completion of initial bio-geographical tables. A searching for reliable and representative criteria of nestedness, invariant to various non-ecological modifications of the matrices but sensitive to estimation of analyzed ecological processes and suitable for comparisons of communities, is clearly needed. A quantitative estimation of species turnover and coherence in species cooccurrence has been performed using different indices of unique combinations and checkerboard score (Stone, Roberts, 1992) as well as Schluter's variance test. By means of empirical Bayesian approach (Gotelli, Ulrich, 2010) records of species pairwise combinations are formed where the frequency of species co-occurrence cannot be interpreted as a random value. Positive and negative relationships between taxa in macrozoobenthic communities, which are found out to be statistically significant, in most cases can be explained as being not the consequence of competition for resources but of spatial heterogeneity of biotopical conditions along the whole length of the watercourse.     

Assembly rules and community models for unicellular organisms: patterns in diatoms of boreal streams

1. Many studies have addressed either community models (e.g. Clementsian versus Gleasonian gradients) or assembly rules (e.g. nestedness, checkerboards) for higher plant and animal communities, but very few studies have examined different non‐random distribution patterns simultaneously with the same data set. Even fewer studies have addressed generalities in the distribution patterns of unicellular organisms, such as diatoms. 2. We studied non‐randomness in the spatial distribution and community composition of stream diatoms. Our data consisted of diatom surveys from 47 boreal headwater streams and small rivers in northern Finland. Our analytical approaches included ordinations, cluster analysis, null model analyses, and associated randomisation tests. 3. Stream diatom communities did not follow discrete Clementsian community types, where multiple species occur exclusively in a single community type. Rather, diatom species showed rather individualistic responses, leading to continuous Gleasonian variability in community composition. 4. Although continuous variability was the dominating pattern in the data, diatoms also showed significant nestedness and less overlap in species distribution than expected by chance. However, these patterns were probably only secondary signals from species’ individualistic responses to the environment. 5. Although unicellular organisms, such as diatoms, differ from multicellular organisms in several biological characteristics, they nevertheless appear to show largely similar non‐random distribution patterns previously found for higher plants and metazoans.     

Ecological traits reveal functional nestedness of bird communities in habitat islands: a global survey

The widespread destruction and fragmentation of natural habitats around the world creates a strong incentive to understand how species and communities respond to such pressures. The vast majority of research into habitat fragmentation has focused solely on species presence or absence. However, analyses using innovative functional methodologies offer the prospect of providing new insights into the key questions surrounding community structure in fragmented systems. A key topic in fragmentation research is nestedness (i.e. the ordered composition of species assemblages involving a significant tendency for packing of the presence–absence matrix into a series of proper subsets). To date, nestedness analyses have been concerned solely with nestedness of species membership. Here, we capitalize on the publication of a recent nestedness index (traitNODF) in which the branch lengths of functional dendrograms are incorporated into the standard NODF nestedness index. Using bird community data from 18 forest‐habitat‐island studies, and measurements of eight continuous functional traits from over 1000 bird species, we conduct the first synthetic analysis of nestedness from a functional perspective (i.e. a nestedness analysis which incorporates how similar species are in terms of their ecological traits). We use two null models to test the significance of any observed functional nestedness, and investigate the role of habitat island area in driving functional nestedness. We also determine whether functional nestedness is driven primarily by species composition or by differences in species’ traits. We found that the majority (94%) of datasets were functionally nested by island area when a permutation null model was used, although only 11–22% of datasets were significantly functionally nested when a more conservative fixed‐fixed null model was used. Species composition was always the most important driver of functional nestedness, but the effect of differences in species traits was occasionally quite large. Our results isolate the importance of island area in driving functional nestedness where it does occur and show that habitat loss results in the ordered loss of functional traits. This analysis demonstrates the potential insights that may derive from testing for ordered patterns of functional diversity. Synthesis The widespread fragmentation of natural habitats around the world creates a strong incentive to understand how ecological communities respond to such pressures. A key topic in this research agenda is nestedness; however, to date, nestedness analyses have been concerned solely with species presence or absence. Using data from 18 bird‐habitat‐island studies we conduct the first synthetic analysis of nestedness from a functional perspective (i.e. a nestedness analysis which incorporates how similar species are in terms of their ecological traits). Our findings suggest that many bird‐habitat island communities are significantly functionally nested, although our results were sensitive to the null model used. Our study demonstrates the benefits of testing for ordered patterns of functional diversity.     

Network properties of arboreal plants: Are epiphytes,mistletoes and lianas structured similarly?

Network analyses provide a unified framework to evaluate different types of species interactions. We used a network approach to comparatively evaluate three types of arboreal plant metacommunities. Interactions between mistletoes, lianas and epiphytes and their host trees were quantified in two New Zealand forests and individual-based null models were used to test for non-random patterns in network degree, nestedness and negative co-occurrence patterns. Arboreal plants were simulated to randomly occur on individual host trees to derive ‘null’ interaction matrices, which were then compared to the observed matrix. Results showed that mistletoes, lianas and epiphytes had very different network properties. Mistletoe and liana degree distributions exhibited fewer links than expected under the null model, indicating strong host preferences. Conversely, degree distributions for epiphytes were consistent with randomised expectations. Mistletoes and lianas were less nested than null model expectations and instead showed support for negative co-occurrence patterns, meaning mistletoe and liana species tended to have mutually exclusive host preferences. Conversely, epiphytes were more nested than expected by chance and showed positive co-occurrence patterns. Overall results indicate that plant–plant interactions exhibited by different types of arboreal plants have very different network properties. We hypothesize that these differences result from (1) differences in coevolutionary dynamics between arboreal plants and their hosts, which range from parasitic (mistletoes) to commensal (epiphytes), and (2) biotic interactions among arboreal plant species for access to host trees.     

Flow intermittency decreases nestedness and specialisation of diatom communities in Mediterranean rivers

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Amphibian skin fungal communities vary across host species and do not correlate with infection by a pathogenic fungus

Amphibian population declines caused by the fungus Batrachochytrium dendrobatidis (Bd) have prompted studies on the bacterial community that resides on amphibian skin. However, studies addressing the fungal portion of these symbiont communities have lagged behind. Using ITS1 amplicon sequencing, we examined the fungal portion of the skin microbiome of temperate and tropical amphibian species currently coexisting with Bd in nature. We assessed cooccurrence patterns between bacterial and fungal OTUs using a subset of samples for which bacterial 16S rRNA gene amplicon data were also available. We determined that fungal communities were dominated by members of the phyla Ascomycota and Basidiomycota, and also by Chytridiomycota in the most aquatic amphibian species. Alpha diversity of the fungal communities differed across host species, and fungal community structure differed across species and regions. However, we did not find a correlation between fungal diversity/community structure and Bd infection, though we did identify significant correlations between Bd and specific OTUs. Moreover, positive bacterial–fungal cooccurrences suggest that positive interactions between these organisms occur in the skin microbiome. Understanding the ecology of amphibian skin fungi, and their interactions with bacteria will complement our knowledge of the factors influencing community assembly and the overall function of these symbiont communities.     

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.     

Community convergence: Ecological and evolutionary

Ecologists have often compared ecological communities in different areas, for example on different continents. The main interest is that the communities might be more similar in the characters of their species than expected under a null model of random species assortment. We suggest that such a null model should be based only on the species observed across the samples. Species-level convergence and community-level convergence must be distinguished. Physical filters (limitation to growth by the physical environment) can give species-level convergence, but only biotic filtering (based on species interactions) can give community-level convergence. Matching to species and species mutual matching must also be distinguished; the process is different, but the same tests work for both.     

A new dynamic null model for phylogenetic community structure

Phylogenies are increasingly applied to identify the mechanisms structuring ecological communities but progress has been hindered by a reliance on statistical null models that ignore the historical process of community assembly. Here, we address this, and develop a dynamic null model of assembly by allopatric speciation, colonisation and local extinction. Incorporating these processes fundamentally alters the structure of communities expected due to chance, with speciation leading to phylogenetic overdispersion compared to a classical statistical null model assuming equal probabilities of community membership. Applying this method to bird and primate communities in South America we show that patterns of phylogenetic overdispersion – often attributed to negative biotic interactions – are instead consistent with a species neutral model of allopatric speciation, colonisation and local extinction. Our findings provide a new null expectation for phylogenetic community patterns and highlight the importance of explicitly accounting for the dynamic history of assembly when testing the mechanisms governing community structure.     

Linking community assembly and structure across scales in a wild mouse parasite community

Understanding what processes drive community structure is fundamental to ecology. Many wild animals are simultaneously infected by multiple parasite species, so host–parasite communities can be valuable tools for investigating connections between community structures at multiple scales, as each host can be considered a replicate parasite community. Like free‐living communities, within‐host–parasite communities are hierarchical; ecological interactions between hosts and parasites can occur at multiple scales (e.g., host community, host population, parasite community within the host), therefore, both extrinsic and intrinsic processes can determine parasite community structure. We combine analyses of community structure and assembly at both the host population and individual scales using extensive datasets on wild wood mice (Apodemus sylvaticus) and their parasite community. An analysis of parasite community nestedness at the host population scale provided predictions about the order of infection at the individual scale, which were then tested using parasite community assembly data from individual hosts from the same populations. Nestedness analyses revealed parasite communities were significantly more structured than random. However, observed nestedness did not differ from null models in which parasite species abundance was kept constant. We did not find consistency between observed community structure at the host population scale and within‐host order of infection. Multi‐state Markov models of parasite community assembly showed that a host's likelihood of infection with one parasite did not consistently follow previous infection by a different parasite species, suggesting there is not a deterministic order of infection among the species we investigated in wild wood mice. Our results demonstrate that patterns at one scale (i.e., host population) do not reliably predict processes at another scale (i.e., individual host), and that neutral or stochastic processes may be driving the patterns of nestedness observed in these communities. We suggest that experimental approaches that manipulate parasite communities are needed to better link processes at multiple ecological scales.     

Patterns of co‐occurrences in a killifish metacommunity are more related with body size than with species identity

Body size may be more important than species identity in determining species interactions and community structure. However, co‐occurrence of organisms has commonly been analysed from a taxonomic perspective and the body size is rarely taken into account. On six sampling occasions, we analysed patterns of killifish co‐occurrences in nestedness (tendency for less rich communities to be subsamples of the richest), checkerboard structure (tendency for species segregation), and modularity (tendency for groups to co‐occur more frequently than random expectation) in a pond metacommunity located in Uruguay. We contrasted co‐occurrence patterns among species and body size‐classes (individuals from different species were combined into size categories). The analysis was performed at two spatial scales: ponds (communities) and sample units within ponds. Observed nestedness was frequently smaller than the null expectation, with significantly greater deviations for body size‐classes than for species, and for sample units than for communities. At the sample unit level, individuals tended to segregate (i.e. clump into a checkerboard pattern) to a larger extent by body size rather than by taxonomy. Modularity was rarely detected, but nevertheless indicated a level of taxonomic organization not evident in nestedness or checkerboard indices. Identification of the spatial scale and organization at which ecological forces determine community structure is a basic requirement for advancement of robust theory. In our study system, these ecological forces probably structured the community by body sizes of interacting organisms rather than by species identities.     

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).     

尖峰岭热带山地雨林根部真菌-植物互作网络结构特征

不同功能群的根部真菌可能会与植物差异性地互作, 并进一步影响地下真菌与植物群落构建。本研究采用Illumina Miseq测序方法检测了海南尖峰岭热带山地雨林中常见植物的根部真菌; 采用网络分析法比较了丛枝菌根(AM)真菌、外生菌根(ECM)真菌, 以及所有根部真菌与植物互作的二分网络(bipartite networks)结构特性。从槭树科、番荔枝科、夹竹桃科、冬青科、棕榈科、壳斗科、樟科和木犀科等8科植物的根系中, 检测到297,831条真菌ITS1序列, 这些序列被划为1,279个真菌分类单元(OTUs), 其中子囊菌门748个、担子菌门354个、球囊菌亚门80个, 以及未知真菌97个。核心根部真菌群落(420个OTUs)中, 至少有三类不同生态功能的真菌常见, 即丛枝菌根真菌(40个OTUs, 占总序列数23.4%)、外生菌根真菌(48个OTUs, 13.9%)和腐生型真菌(83个OTUs, 19.8%)。尖峰岭山地雨林根部真菌-植物互作网络结构特性的指标普遍显著高于/低于假定物种随机互作的零模型期待值。在群落水平, 不同功能型的根部真菌-植物互作网络表现出不同或相反的结构特性, 如丛枝菌根互作网络表现为比零模型预测值高的嵌套性和连接性, 以及比零模型低的专一性, 而外生菌根互作网络呈现出比零模型预测值低的嵌套性和连接性, 以及比零模型高的专一性。在功能群水平, 植物的生态位重叠度在AM互作网络高, 而ECM互作网络低; 真菌的生态位宽度在ECM互作网络窄, 而在AM互作网络较宽。共现(co-occurrence)网络分析进一步揭示, ECM群落的物种对资源的高度种间竞争(植物、真菌高C-score), 以及AM群落的物种无明显种间竞争(低C-score), 可能分别是形成反嵌套ECM互作网络及高嵌套AM互作网络结构的原因。上述结果说明, 尖峰岭山地雨林中至少有两种及以上的种间互作机制调节群落构建: 驱动AM互作网络冗余(nestedness)及ECM互作网络的高生态位分化(专一性)。本研究在同一个森林内探讨了不同功能型的真菌-植物互作特性, 对深入理解热带森林的物种共存机制和生态恢复具有重要意义。     

Toward ecologically explicit null models of nestedness

A community is "nested" when species assemblages in less rich sites form nonrandom subsets of those at richer sites. Conventional null models used to test for statistically nonrandom nestedness are under- or over-restrictive because they do not sufficiently isolate ecological processes of interest, which hinders ecological inference. We propose a class of null models that are ecologically explicit and interpretable. Expected values of species richness and incidence, rather than observed values, are used to create random presence-absence matrices for hypothesis testing. In our examples, based on six datasets, expected values were derived either by using an individually based random placement model or by fitting empirical models to richness data as a function of environmental covariates. We describe an algorithm for constructing unbiased null matrices, which permitted valid testing of our null models. Our approach avoids the problem of building too much structure into the null model, and enabled us to explicitly test whether observed communities were more nested than would be expected for a system structured solely by species-abundance and species-area or similar relationships. We argue that this test or similar tests are better determinants of whether a system is truly nested; a nested system should contain unique pattern not already predicted by more fundamental ecological principles such as species-area relationships. Most species assemblages we studied were not nested under these null models. Our results suggest that nestedness, beyond that which is explained by passive sampling processes, may not be as widespread as currently believed. These findings may help to improve the utility of nestedness as an ecological concept and conservation tool.     

Are soil lichen communities structured by biotic interactions? A null model analysis

Question: Are soil lichen communities structured by biotic interactions? Location: Gypsum outcrops located next to Belmonte del Tajo, central Spain. Methods: We sampled a total of 68 (50 cm × 50 cm) plots in gypsum outcrops from central Spain. Each plot was divided into 100 (5 cm × 5 cm) sampling quadrats, and the presence of all lichen species in every quadrat was recorded (6800 quadrats in total). We used two realistic null models to generate random communities unstructured by biotic interactions, and used them to test the hypothesis that soil lichen species co‐occur less often than expected by chance. Results: We found fewer species combinations and less co‐occurrence than expected by chance. However, the latter result was dependent on the null model selected. The number of checkerboard pairs did not differ significantly from the null expectation. Conclusions: Overall, our results suggest that gypsiferous soil lichen communities are structured by competitive interactions. They are consistent with studies conducted with a wide variety of taxa, and fill a gap in our knowledge of the factors driving the small‐scale distribution of these important organisms.     

A consumer's guide to nestedness analysis

Nestedness analysis has become increasingly popular in the study of biogeographic patterns of species occurrence. Nested patterns are those in which the species composition of small assemblages is a nested subset of larger assemblages. For species interaction networks such as plant–pollinator webs, nestedness analysis has also proven a valuable tool for revealing ecological and evolutionary constraints. Despite this popularity, there has been substantial controversy in the literature over the best methods to define and quantify nestedness, and how to test for patterns of nestedness against an appropriate statistical null hypothesis. Here we review this rapidly developing literature and provide suggestions and guidelines for proper analyses. We focus on the logic and the performance of different metrics and the proper choice of null models for statistical inference. We observe that traditional 'gap-counting' metrics are biased towards species loss among columns (occupied sites) and that many metrics are not invariant to basic matrix properties. The study of nestedness should be combined with an appropriate gradient analysis to infer possible causes of the observed presence–absence sequence. In our view, statistical inference should be based on a null model in which row and columns sums are fixed. Under this model, only a relatively small number of published empirical matrices are significantly nested. We call for a critical reassessment of previous studies that have used biased metrics and unconstrained null models for statistical inference.     

Using intraspecific variation of functional traits and environmental factors to understand the formation of nestedness patterns of a local forest community

从功能性状的种内变异和环境因子的角度理解局域森林群落嵌套格局的成因     

Abundance and nestedness in interaction networks

Nestedness is a useful metric that characterizes the generalist–specialist balance in ecological communities. Although several nestedness indices have been proposed, few have explored how species abundance per se affects their performance and the ability to detect true interaction networks. We here develop a mathematical framework that takes into account abundance in estimates of nestedness. We use an analytical approach to relate abundance and nestedness. In our null model the probability of interaction among species is determined solely as function of their abundances. Assuming a power-law abundance model we analytically find the nestedness index and its coefficient of variability. We find that the sloping abundance distribution of our null model generates more nested structures. On the other hand steeper abundances lead to higher coefficients of variability. Both results suggest that nestedness analysis should be evaluated and explanations sought carefully.