Our May issue is out now!

Our May issue is now online now! This issue contains 18 articles about the latest methods in ecology and evolution, including species distribution models, temperature measurements and much more! Read to find out about this month’s featured articles and the article behind our cover.

Featured articles

The insurance effect of biodiversity—that diversity stabilises aggregate ecosystem properties—is mechanistically underlain by inter- and intraspecific trait variation in organismal responses to the environment. This variation, termed response diversity, is therefore a potentially critical determinant of ecological stability. Here, Ross et al. review methods for measuring response diversity and from them distil a methodological framework for quantifying response diversity from experimental and/or observational data, which can be practically applied in laboratory and field settings across a range of taxa.

Among the many diversity indices in the ecologist toolbox, measures that can be partitioned into additive terms are particularly useful as the different components can be related to different ecological processes shaping community structure. The value of the proposed diversity decomposition is demonstrated by the analysis of actual abundance data on plant assemblages sampled in grazed and ungrazed grasslands in Tuscany (Central Italy).

Neighbor-net is a widely used network reconstructing method that approximates pairwise distances between taxa by a circular phylogenetic network. We present Lpnet, a variant of Neighbor-net. We first apply standard methods to construct a binary phylogenetic tree and then use integer linear programming to compute an optimal circular ordering that agrees with all tree splits.

Keyfitz’ entropy is a widely used metric to quantify the shape of the survivorship curve of populations, from plants to animals and microbes. Keyfitz’ entropy was originally defined using a continuous-time model, and has since been discretised to facilitate its calculation from discrete-time demographic data. Here, de Vries et al. show that the previously used discretisation of the continuous-time metric does not preserve the relationship with increasing, decreasing or constant mortality rates. To resolve this discrepancy, we propose a new discrete-time formula for Keyfitz’ entropy for age-classified life histories.

The prediction of species interactions is gaining momentum as a way to circumvent limitations in data volume. Yet, ecological networks are challenging to predict because they are typically small and sparse. Using simple mathematical arguments and numerical experiments in which a variety of classifiers are trained on simulated networks, Poisot develops a series of guidelines related to the choice of measures to use for model selection, and the ways to assemble the training dataset.

The fish on the cover

This month’s cover photo depicts a small coral reef goby – Pleusosicya mossambica – resting on a bubble coral in the Red Sea, Saudi Arabia. Like other cryptobenthic fishes, this tiny (< 2cm) animal is a common resident of tropical coral reefs, but our ability to survey and monitor these fishes is severely hampered by their small size and hidden lifestyle. In this issue, Simon Brandl and colleagues introduce a new, standardized method for monitoring cryptobenthic fish biodiversity: fish-specific autonomous reef monitoring structures (FARMS). FARMS consist of cheap and easily obtained materials (PVC pipes and sheets), and can be deployed and retrieved using a variety of methods that grant access to environments that are impossible to sample with other techniques. Their paper shows that FARMS can attract a locally representative suite of cryptobenthic fish species that is comparable to other sampling methods based on the sampled area. Thus, FARMS provide a useful complementary technique to document and monitor the smallest reef fishes, especially in places where other sampling methods are rendered unfeasible due to high turbidity, depth, or restrictions on the use of chemicals. © Tane Sinclair-Taylor.

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