A consumer's guide to nestedness analysis

Abstract

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.

The ghost of nestedness in ecological networks

“…For both binary and quantitative matrices, we define three null models for constructing B 0 : (i) preserve |P|, |A| and place |E| edges at random within the matrix; (ii) as in (i), but accept only connected matrices; and (iii) as in (ii), but conserve the degree distribution (the row and column sums of B). As measures of nestedness can be very sensitive to matrix size, fill and configuration 10,11 , we used null model implementations that preserve |P|, |A| and |E| (null models (i) and (ii)) and degree distribution (iii) exactly, and not just their expected values.…”

“…In a nested bipartite network or graph, interactions are organized such that specialists (for example, pollinators that visit few plants) interact with subsets of the species with whom generalists (for example, pollinators that visit many plants) interact. A nested structure corresponds to a systematic arrangement of non-zero entries in the binary matrix used to represent a network, and existing detection methods are based on distinguishing the nested pattern from other possible arrangements of matrix elements 10,11 . However, these methods are often computationally expensive for large matrices and are not applicable to quantitative networks (binary metrics extended to work with quantitative data, such as WNODF 12 , do not make full use of the available quantitative information).…”

Emergence of structural and dynamical properties of ecological mutualistic networks

“…The relatively low abundances of the specialist species make them more vulnerable to extinction and results in correspondingly lower community resilience, as measured by the maximum real part of the eigenvalues of the community matrix community ( Figure 4B). The advantage of having a high total population leading to increased robustness against extinction due to demographic fluctuations, carries with it the cost associated with a lower resilience -the optimized network recovers from perturbations on a longer timescale than its random counterpart 12,14,27 (Figure 4C). …”

Checklist, diversity and distribution of testate amoebae in Chile

“…The temperature metric evaluates the degree of disor-der as estimated by the temperature of a binary matrix, where T • = 0 • indicates perfect nestedness and T • = 100 • indicates complete randomness. Before calculating the degree of nestedness, the binary matrix was sorted according to the marginal row and column sums, with common taxa placed in the upper rows and taxa-rich latitudinal bands placed in the left-hand column (Ulrich et al 2009;Fernández 2015). Islands and the Antarctic continent were treated as having a direct borderline with continental Chile.…”