Accounting for temporal change in multiple biodiversity patterns improves the inference of metacommunity processes

Guzman, Laura Melissa and Thompson, Patrick L. and Viana, Duarte S. and Vanschoenwinkel Bram, Bram and Horváth, Zsófia and Ptacnik, Robert and Jeliazkov, Alienor and Gascón, Stéphanie and Lemmens, Pieter and Anton-Pardo, Maria and Langenheder, Silke and De Meester, Luc and Chase, Jonathan M. (2022) Accounting for temporal change in multiple biodiversity patterns improves the inference of metacommunity processes. ECOLOGY, 103 (6). No-e3683. ISSN 0012-9658

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Abstract

In metacommunity ecology, a major focus has been on combining observa- tional and analytical approaches to identify the role of critical assembly pro- cesses, such as dispersal limitation and environmental filtering, but this work has largely ignored temporal community dynamics. Here, we develop a “vir- tual ecologist” approach to evaluate assembly processes by simulating meta- communities varying in three main processes: density-independent responses to abiotic conditions, density-dependent biotic interactions, and dispersal. We then calculate a number of commonly used summary statistics of community structure in space and time and use random forests to evaluate their utility for inferring the strength of these three processes. We find that (i) both spatial and temporal data are necessary to disentangle metacommunity processes based on the summary statistics we test, and including statistics that are mea- sured through time increases the explanatory power of random forests by up to 59% compared to cases where only spatial variation is considered; (ii) the three studied processes can be distinguished with different descriptors; and (iii) each summary statistic is differently sensitive to temporal and spatial sam- pling effort. Including repeated observations of metacommunities over time was essential for inferring the metacommunity processes, particularly dis- persal. Some of the most useful statistics include the coefficient of variation of species abundances through time and metrics that incorporate variation in the relative abundances (evenness) of species. We conclude that a combination of methods and summary statistics is probably necessary to understand the pro- cesses that underlie metacommunity assembly through space and time, but we recognize that these results will be modified when other processes or summary statistics are used.

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