DOI: 10.5061/dryad.6hdr7sr2h
title: Assessment of the stream invertebrate β-diversity along an elevation gradient using a bidimensional null model analysis

description: Aim: β-Diversity, commonly defined as the compositional variation among
 localities that links local diversity (α‐diversity) and regional diversity
 (γ‐diversity), can arise from two different ecological phenomena, namely
 the spatial species turnover (i.e. species replacement) and the nestedness
 of assemblages (i.e. species loss). However, any assessment that does not
 account for stochasticity in community assembly could be biased and
 misinform conservation management. In this study, we aimed to provide a
 better understanding of the overall ecological phenomena underlying stream
 β-diversity along elevation gradients, and at contributing to the rich
 debate on null model approaches to identify non-random patterns in the
 distribution of taxa. Location: Swiss Alpine region. Methods: Based on
 presence-absence data of 78 stream invertebrate families from 309 sites,
 we analyzed the effect size of non-random spatial distribution of stream
 invertebrates on the β-diversity and its two components (i.e. turnover and
 nestedness). We used a modelling framework that allows exploring the
 complete range of existing algorithm sused in null model analysis, and to
 assess how distribution patterns vary according to an array of possible
 ecological assumptions. Results: Overall, the turnover of stream
 invertebrates and the nestedness of assemblages were significantly lower
 and higher, respectively, than the ones expected by chance. This pattern
 increased with elevation, and the consistent trend observed along the
 altitudinal gradient, even in the most conservative analysis, strengthened
 our findings. Main conclusions: Our study suggests that deterministic
 distribution of stream invertebrates in the Swiss Alpine region is
 significantly driven by differential dispersal capacity and environmental
 stress gradients. As long as the ecological assumptions for constructing
 the null models and their implications are acknowledged, we believe that
 they still represent useful tools to measure the effect size of non-random
 spatial distribution of taxa on β-diversity.
description: The surveys were carried out across the Swiss Alpine region
 between 2013 and 2017 within the framework of the Swiss Biodiversity
 Monitoring Program (BDM). Standard sampling within streams occurred during
 the optimal period in terms of invertebrate diversity, from March to June
 depending on the elevation. Each site was assigned to one of four
 bioclimatic stages, which were based on mean annual temperature and
 distributed along the altitudinal gradient. R (v.4.1.1) was used for data
 analysis, including the following packages: betapart (v.1.5.4), plyr
 (v.1.8.6), igraph (v.1.2.9), reshape2 (v.1.4.4), foreach (v.1.5.1),
 doParallel (v.1.0.16), ggplot2 (v.3.3.5), ggpubr (v.0.4.0), cowplot
 (v.1.1.1), viridis (v.0.6.2). For the 'Tuning Peg' algorithm, we
 used a slightly modified version of the R script from Strona et al.
 (2018), in order to take into account the β-diversity indices from Baselga
 (2010). Strona,
 G., Ulrich, W. and Gotelli, N.J. (2018), Bi-dimensional null model
 analysis of presence-absence binary matrices. Ecology, 99: 103-115. https://doi.org/10.1002/ecy.2043 Baselga, A. (2010), Partitioning the turnover and nestedness components of beta diversity. Global Ecology and Biogeography, 19: 134-143. https://doi.org/10.1111/j.1466-8238.2009.00490.x