A consistent metric for nestedness analysis in ecological systems: reconciling concept and measurement

Nestedness has been widely reported for both metacommunities and networks of interacting species. Even though the concept of this ecological pattern has been well-defined, there are several metrics by which it can be quantified. We noted that current metrics do not correctly quantify two major properties of nestedness: (1) whether marginal totals (i.e. fills) differ among columns and/or among rows, and (2) whether the presences (1's) in less-filled columns and rows coincide, respectively, with those found in the more-filled columns and rows. We propose a new metric directly based on these properties and compare its behavior with that of the most used metrics, using a set of model matrices ranging from highly-nested to alternative structures in which no nestedness should be detected. We also used an empirical dataset to explore possible biases generated by the metrics as well as to evaluate correlations between metrics. We found that nestedness has been quantified by metrics that inappropriately detect this pattern, even for matrices in which there is no nestedness. In addition, the most used metrics are prone to type I statistical errors while our new metric has better statistical properties and consistently rejects a nested pattern for different types of random matrices. The analysis of the empirical data showed that two nestedness metrics, matrix temperature and the discrepancy measure, tend to overestimate the degrees of nestedness in metacommunities. We emphasize and discuss some implications of these biases for the theoretical understanding of the processes shaping species interaction networks and metacommunity structure.     

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).     

Rethinking the relationship between nestedness and beta diversity: a comment on Baselga (2010)

Baselga [Partitioning the turnover and nestedness components of beta diversity. Global Ecology and Biogeography, 19 , 134–143, 2010] proposed pairwise (β_nes) and multiple‐site (β_NES) beta‐diversity measures to account for the nestedness component of beta diversity. We used empirical, randomly created and idealized matrices to show that both measures are only partially related to nestedness and do not fit certain fundamental requirements for consideration as true nestedness‐resultant dissimilarity measures. Both β_nes and β_NES are influenced by matrix size and fill, and increase or decrease even when nestedness remains constant. Additionally, we demonstrate that β_NES can yield high values even for matrices with no nestedness. We conclude that β_nes and β_NES are not true measures of the nestedness‐resultant dissimilarity between sites. Actually, they quantify how differences in species richness that are not due to species replacement contribute to patterns of beta diversity. Finally, because nestedness is a special case of dissimilarity in species composition due to ordered species loss (or gain), the extent to which differences in species composition is due to nestedness can be measured through an index of nestedness.     

Treating the nestedness temperature calculator as a "black box" can lead to false conclusions

We used the nestedness temperature calculator to examine patterns of nestedness in two datasets on birds in fragmented landscapes in southeastern Australia. During our initial analyses, we found that the nestedness calculator was susceptible to detect nestedness as an artifact of passive sampling. To examine this problem in more detail, we created random matrices that simulated a situation where nestedness did not occur, and we re-analysed two previously published datasets. Our results showed that the nestedness calculator may (1) overestimate the degree of nestedness and its statistical significance, and (2) consider some datasets which include both ubiquitous and rare species to be significantly nested although they are not. Our results highlight the danger of blindly relying on the p -values generated by analytical packages such as the nestedness calculator. We suggest that users of analytical packages (often field ecologists) will need to be more critical in future and familiarise themselves in more detail with the packages they use. In addition, the developers of analytical packages (often theoretical ecologists) will need to communicate more clearly the limitations and assumptions underlying analytical tools such as the nestedness calculator.     

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.     

False Correlates of Nested Patterns: A Case Study Using Temporary Pond Microcrustaceans

Nestedness analysis is a popular tool for inferring spatial species distributions, and therefore has management and conservation relevance. Ecologists frequently compute nestedness and subsequently use Spearman rank correlations for inferring relationships between the observed nested ranks of sites with biogeographic and environmental variables. Using temporary pond microcrustaceans hatched from microcosms as a case study, this paper shows that the application of this method can be problematic. While the overall degree and significance of nestedness was robust against a statistical error, the results obtained from randomly generated matrices, in which community structure from the original microcrustacean incidence matrix was maintained (fixed rows –fixed columns constraints), showed that rank correlations of observed nested patterns can be vulnerable to a Type 1 error (detecting an effect when there is none). Using expected nestedness patterns derived from rarefied original matrices to control for sample size effects did not change this result. This problem may have arisen as a result of a quantitative bias related to the disproportionate impact of rank positions of individual ponds in the analysis. Future extensive simulations studies, involving different community structures, should help identify the general reliability of rank correlation results in nestedness analyses. (© 2009 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)     

From sampling stations to archipelagos: investigating aspects of the assemblage of insular biota

Aim To investigate the formation of nestedness and species co‐occurrence patterns at the local (sampling station), the intermediate (island group), and the archipelago scale. Location The study used data on the distribution of terrestrial isopods on 20 islands of the central Aegean (Greece). These islands are assigned to two distinct subgroups (Kyklades and Eastern islands). Methods The Nestedness Temperature Calculator was used to obtain nestedness values and maximally nested matrices, the EcoSim7 software and a modified version of Sanderson (2000 ) method were used for the analysis of species co‐occurrences. Idiosyncratic temperatures of species and the order of species placement in the maximally nested matrices were used for further comparisons among spatial scales. The relationships of nestedness values with beta‐diversity, habitat diversity and a number of ecological factors recorded for each sampling station were also investigated. Results Significant nestedness was found at all spatial scales. Levels of nestedness were not related to beta‐diversity or habitat diversity. Nestedness values were similar among spatial scales, but they were affected by matrix size. The species that contributed most to the nested patterns within single islands were not the same as those that produce nestedness at the archipelago scale. There was significant variation in the frequency of species occurrence among islands and among spatial scales. There was no direct effect of ecological factors on the shaping of patterns of nestedness within individual islands, but habitat heterogeneity was crucial for the existence of such patterns. Positive associations among species prevailed at all scales when species per station were considered, while negative associations prevailed in the species per island matrices. All associations resulted from the habitat structure of sampling stations and from particularities of geographical distributions. Conclusions There was no clear‐cut distinction between nestedness patterns among spatial scales, even though different species, and partially different factors, contributed to the formation of these patterns in each case. There was a core of species that contributed to the formation of nested patterns at all spatial scales, while the patterns of species associations suggested that biotic interactions are not an important causal factor. The results of this study suggest that locally rare species cannot be widespread at a higher spatial scale, while locally common species can have a restricted distribution.     

Nestedness in insular floras: spatiotemporal variation and underlying mechanisms

Aims Nestedness is a characteristic of insular metacommunity structure. Relatively few studies, however, have attempted to evaluate temporal changes in nestedness, or elucidate the mechanisms underlying nestedness. I evaluated both spatial and temporal patterns of nestedness in the insular floras of four archipelagoes of small islands in the Bahamas and the potential underlying environmental gradients.Methods The NODF (a nestedness metric based on overlap and decreasing fill) and the matrix temperature measure, T, were used to quantify nestedness in insular floras on small islands near Abaco, Andros, Great Exuma and the Exuma Cays, Bahamas. Two different null models were employed for each nestedness measure. Six environmental variables were evaluated in relation to nestedness by ordering islands according to gradients and recalculating NODF scores.Important findings All archipelagoes were significantly nested. Nestedness among sites contributed more to overall nestedness than did nestedness among species. NODF scores varied among archipelagoes, but were surprisingly constant over time. Ordering islands by vegetated area yielded the highest nestedness scores for three archipelagoes; ordering islands by protection from exposure yielded the highest nestedness score for one archipelago. Nestedness scores varied little over time even though species compositions changed, indicating that extinctions occurred in a deterministic manner. The relative importance of area suggests extinction is an important mechanism in producing nestedness. Attempting to determine the relative importance of immigrations or extinctions requires some assumptions, however, and both processes are likely cumulative in most cases.     

Nestedness of butterfly assemblages in the Zhoushan Archipelago,China: area effects,life-history traits and conservation implications

The nested subset pattern (nestedness) of faunal assemblages has been a research focus in the fields of island biogeography and conservation biology in recent decades. However, relatively few studies have described nestedness in butterfly assemblages in oceanic archipelago systems. Moreover, previous studies often quantified nestedness using inappropriate nestedness metrics and random fill algorithms with high Type I errors. The aims of this study are to examine the existence of nestedness and underlying causal mechanisms of butterfly assemblages in the Zhoushan Archipelago, China. We used the line-transect method to determine butterfly occupancy and abundance on 42 study islands from July to August 2014. We obtained butterfly life-history traits (wingspan, body weight and minimum area requirement) by field work and island geographical features (area and isolation) from the literature. We used the recently developed metric WNODF to estimate nestedness. Partial Spearman rank correlation was used to evaluate the associations of nestedness and island geographical features as well as butterfly life-history traits related to species extinction risk and colonization ability. The butterfly assemblages were significantly nested. Island area and minimum area requirement of butterflies were significantly correlated with nestedness after controlling for other independent variables. In contrast, the nestedness of butterflies did not appear to result from passive sampling or selective colonization. However, multi-year studies are needed to confirm that target effects are not muddling these results. Our results indicate that selective extinction may be the main driver of nestedness of butterfly assemblages in our study system. From a conservation viewpoint, we should protect both large islands and species with large area requirement to maximize the number of species preserved.     

A null model for randomization tests of nestedness in species assemblages

Analysis of the degree of order in species assemblages in terms of nested subsets has received increased interest during the last decade. However, recently a series of papers have questioned the validity of methods employed for testing whether observed patterns deviate from random expectations. The current view seems to be that the randomization procedure should control for both number of species per site and species frequencies. The randomization procedures used also choose to keep the total number of observations constant in each resample. In this paper I question some of these assumptions when analyzing species-by-site matrices for detecting whether the biota is significantly nested or not. My basic assumption is that the observed species frequency is only an estimate of the probability of occurrence for the particular species. For a test of degree of nestedness all sites should be regarded as being equal. To what extent size, isolation or habitat quality may influence species distribution is a secondary question if nestedness can be statistically proven. This implies that generation of random matrices should only consider the frequency of the species (as an estimate of their probability of occurring in any patch). Such matrices are computationally simple and besides providing a test of nestedness also open the possibility of testing whether the range in species richness is smaller or larger than expected under random expectations. The choice of null model for the test should always be viewed in relation to the question asked. If nestedness is concerned the methods proposed here should be used. However, if other questions are at hand the restrictions of previous approaches may be valid. This is for instance the case if pairwise species co-occurrences are analyzed. In this case, the richness of each site should obviously be incorporated in the randomization to control for the higher probability of co-occurrence at species-rich sites.     

Inferences about nested subsets structure when not all species are detected

Comparisons of species composition among isolated ecological communities of different size have often provided evidence that the species in communities with lower species richness form nested subsets of the species in larger communities. In the vast majority of studies, the question of nested subsets has been addressed using information on presence‐absence, where a “0” is interpreted as the absence of a given species from a given location. Most of the methodological discussion in earlier studies investigating nestedness concerns the approach to generation of model‐based matrices corresponding to the null hypothesis of a nonnested pattern. However, it is most likely that in many situations investigators cannot detect all the species present in the location sampled. The possibility that zeros in incidence matrices reflect nondetection rather than absence of species has not been considered in studies addressing nested subsets, even though the position of zeros in these matrices forms the basis of earlier inference methods. These sampling artifacts are likely to lead to erroneous conclusions about both variation over space in species richness, and the degree of similarity of the various locations. Here we propose an approach to investigation of nestedness, based on statistical inference methods explicitly incorporating species detection probability, that take into account the probabilistic nature of the sampling process. We use presence‐absence data collected under Pollock's robust capture‐recapture design, and resort to an estimator of species richness originally developed for closed populations to assess the proportion of species shared by different locations. We develop testable predictions corresponding to the null hypothesis of a nonnested pattern, and an alternative hypothesis of perfect nestedness. We also present an index for assessing the degree of nestedness of a system of ecological communities. We illustrate our approach using avian data from the North American Breeding Bird Survey collected in Florida Keys.     

On the methods to assess significance in nestedness analyses

Use of Z values to evaluate nestedness significance is a common procedure. An appealing alternative to the use of Z values is that of using a value of relative nestedness (RN). However, there is no agreement on the preferable procedures to generate the null matrices needed to compute both Z and RN. In general, it is recommended to use restrictive null models that take into account row and column totals. The two most widely used null models of this kind, namely, FF and CE [that generate matrices with row and column sums equal (FF) or proportional (CE) to the row and column totals of the original matrix, respectively], are very different in terms of restrictiveness. We performed a set of comparative analyses on both theoretical and real matrices to investigate the differences between the use of Z and RN values, and between the use of FF and CE null models, when NODF (Nestedness metric based on overlap and decreasing fill) or ρ(A) (i.e., the largest eigenvalue of the adjacency matrix) are used to measure nestedness. We found no difference in the use of Z or RN values. On the other hand, we found that different combinations of nestedness measures and null models may lead to inconsistent outcomes. Our results offer some clarity on a few issues that, despite playing a central role in the practical application of nestedness analysis, have been little explored, and highlight the need for the definition of some commonly accepted standards.     

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     

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.     

Structure of a plant–flower-visitor network in the high-altitude sub-alpine desert of Tenerife, Canary Islands

Confined within a volcanic caldera at 2000 m a.s.l., the sub-alpine desert of Tenerife, Canary Islands, harbors a distinct biota. At this altitude the climate is harsh and the growing season short. Hence, plant and animal communities, constituting the sub-alpine plant–flower-visitor network, are clearly delimited, both spatially and temporally. We investigated species composition and interaction structure of this system. A total of 11 plant species (91% endemics) and 37 flower-visiting animal species (62% endemics) formed 108 interactions. Numbers of interactions among species varied ten-fold within both plant and animal communities. Generalization level of a species was positively correlated with its local abundance. Two separate network analyses revealed a significantly nested structure. In relation to a plant–flower-visitor system, nestedness implies that specialized species (animals or plants) interact with a subset of the species pool visiting (animals) or being visited (plants) by more generalized species. Therefore, specialized, locally rare plants tend to be visited by generalized, locally abundant animals, and specialized, locally rare animals tend to utilize generalized, locally abundant food plants. Such patterns could have implications for conservation of the sub-alpine network, and stress the importance of preserving not only rare species, but also the more abundant ones, which may be key food resources or pollinators in the plant–flower-visitor network.     

The relationship between nested subsets,habitat subdivision,and species diversity

Biotic assemblages are said to be nested when the species making up relatively species-poor biotas comprise subsets of the species present at richer sites. Because species number and site area are often correlated, previous studies have suggested that nestedness may be relevant to questions of how habitat subdivision affects species diversity, particularly with respect to the question of whether a single large, contiguous patch of habitat will generally contain more species than collections of smaller patches having the same total combined area. However, inferences from analyses of nestedness are complicated by (1) variability in degrees of nestedness measured in natural communities, (2) variability in species-area relationships, and (3) the fact that nestedness statistics do not account for the size of habitat patches, only in the degree of overlap among sites with different numbers of species. By comparing various indices of nestedness with a saturation index that more directly measures the effect of habitat subdivision, it is shown that the first two of these factors are not as important as the third. Whether a single large site or several smaller ones having the same total combined area maximizes species diversity is dependent on (1) overlap in species composition among sites and (2) the number of species per unit area in the different sites. Because nestedness indices do not account for species number at a site, they cannot accurately predict how habitat subdivision affects species diversity patterns. Still, nestedness analyses are important in that they indicate the degree to which rare species tend to be found in the largest, or the most species-rich, sites, patterns not revealed by the saturation index. Both types of analysis are important in order to obtain a more complete picture of how species richness and compositional patterns are influenced by habitat subdivision.     

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.     

Nested assemblages of Orthoptera species in the Netherlands: the importance of habitat features and life-history traits

Aim Species communities often exhibit nestedness, the species found in species‐poor sites representing subsets of richer ones. In the Netherlands, where intensification of land use has led to severe fragmentation of nature, we examined the degree of nestedness in the distribution of Orthoptera species. An assessment was made of how environmental conditions and species life‐history traits are related to this pattern, and how variation in sampling intensity across sites may influence the observed degree of nestedness. Location The analysis includes a total of 178 semi‐natural sites in the Pleistocene sand region of the Netherlands. Methods A matrix recording the presence or absence of all Orthoptera species in each site was compiled using atlas data. Additionally, separate matrices were constructed for the species of suborders Ensifera and Caelifera. The degree of nestedness was measured using the binmatnest calculator. binmatnest uses an algorithm to sort the matrices to maximal nestedness. We used Spearman’s rank correlations to evaluate whether sites were sorted by area, isolation or habitat heterogeneity, and whether species were sorted by their dispersal ability, rate of development or degree of habitat specificity. Results We found the Orthoptera assemblages to be significantly nested. The rank correlation between site order and sampling intensity was high. The degree of nestedness was lower, but remained significant when under‐ and over‐sampled sites were excluded from the analysis. Site order was strongly correlated with both size of sample site and number of habitat types per site. Rank correlations showed that species were probably ordered by variation in habitat specificity, rather than by variation in dispersal capacity or rate of development of the species. Main conclusions Variation in sampling intensity among sites had a strong impact on the observed degree of nestedness. Nestedness in habitats may underlie the observed nestedness within the Orthoptera assemblages. Habitat heterogeneity is closely related to site area, which suggests that several large sites should be preserved, rather than many small sites. Furthermore, the results corroborate a focus of nature conservation policy on sites where rare species occur, as long as the full spectrum of habitat conditions and underlying ecological processes is secured.     

On nestedness analyses: rethinking matrix temperature and anti-nestedness

The analysis of nested structures in sets of species assemblages across different sites or in networks of interspecific interactions has become common practice in ecological studies. Although new analyses and metrics have been proposed, few studies have scrutinized the concepts that subtend nestedness analysis. We note two important conceptual problems that can lead to terminological inconsistencies and flawed interpretations. First, the thermodynamic analogy that underlies the most common metric of nestedness, matrix temperature, is flawed and has led some authors to incorrect interpretations. Second, the term "anti-nestedness" is a potential source of confusion and inconsistencies. We review four concepts for anti-nestedness and examine how distinct they are. "Anti-nested" matrices, i.e. less nested than expected by chance, may result from different ecological processes and show distinct structural patterns. Thus, there is no single unequivocal opposite of nestedness to be represented as "anti-nestedness". A more profitable approach is to designate and test each distinct non-nested pattern according to its specific assumptions and mechanistic hypotheses.     

Nestedness and niche‐based species loss in moorland plant communities

Communities in isolated habitat patches surrounded by inhospitable matrices often form a nested subset pattern. However, the underlying causal mechanisms and conservation implications of nestedness in regional communities remain controversial. The nested ranks of species in a nested species‐by‐site matrix may reflect a gradient of species vulnerability to extinction or of colonization ability. However, nestedness analysis has rarely been used to explore determinants of species rank; consequently, little is known of underpinning mechanisms. In this study, we examined nestedness in moorland plant communities widely interspersed within the subalpine zone of northern Japan. Moorland sites differed in area (1000–160 000 m²) and were naturally isolated from one another to various extents within an inhospitable forest matrix. We also determined whether site characteristics (physical and morphometric measures) and species characteristics (niche position and breadth, based on species’ traits) are related to nestedness. Moorland plant communities in the study area were significantly nested. The pH and moorland kernel density (proxy for spatial clustering of moorlands around the focal site) were the most important predictors of moorland site nested rank in a nestedness matrix. Niche breadths of species (measured as variation in leaf mass area and height) predicted species’ nested ranks. Selective environmental tolerances imposed by environmental harshness and selective extinction caused by declines in site carrying capacities probably account for the nested subset pattern in moorland plant communities. The nested rank of species in the nestedness matrix can therefore be translated into the potential order of species loss explainable by species niche breadths (based on variation in functional traits). Complementary understanding of the determinants of site ranking and species ranking in the nestedness matrix provides powerful insight into ecological processes underlying nestedness and into the ways by which communities are assembled or disassembled by such processes.