DOI: 10.5061/dryad.8pk0p2nv3
title: Climate-associated variation in the drivers of benthic macroinvertebrate species-area relationships across shallow freshwater lakes

description: The island species-area relationship (ISAR) describes how species richness
 increases with increasing area of a given island or island-like habitat,
 such as freshwater lakes. While the ISAR is one of the most common
 phenomena observed in ecology, there is variation in both the form of the
 relationship and its underlying mechanisms. We compiled a global dataset
 of benthic macroinvertebrates from 524 shallow freshwater lakes, ranging
 from 1 to 293300 ha in area. We used individual-based rarefaction to
 determine the degree to which ISAR was influenced by mechanisms other than
 passive sampling (larger islands passively sample more individuals from
 the regional pool and, therefore, have more species than smaller islands),
 which would bias results away from expected relationships between rarefied
 species richness (and other measures that capture relative abundances) and
 lake area. We also examined how climate may alter the shape of
 the ISARs. We found that both rarefied species richness (the number of
 species standardized by area or number of individuals) and a measure of
 evenness emphasizing common species exhibit non-significant relationships
 with lake area, suggesting that the expected ISARs in these lakes most
 likely result from passive sampling. While there was considerable
 variation among ISARs across the investigated lakes, we found an overall
 positive rarefied ISAR for lakes in warm (i.e., tropical/subtropical)
 regions (n = 195), and in contrast, an overall negative rarefied ISAR in
 cool (i.e., north temperate) lakes (n = 329). This suggested that
 mechanisms beyond passive sampling (e.g., colonization-extinction dynamics
 and/or heterogeneity) were more likely to operate in warm lakes. One
 possible reason for this difference is that the area-dependent intensity
 of fish predation, which can lead to flatter ISARs, is weaker in
 warmer relative to cooler lakes. Our study illustrates the importance of
 understanding both the pattern and potential processes underlying the
 ISARs of freshwater lakes in different climatic regions. Further, it
 provides a baseline for understanding how further changes to the ecosystem
 (i.e., in lake area or climate) might influence biodiversity patterns.
description: We
 compiled data from studies that used a similar sampling methodology to
 collect macroinvertebrates from lakes that varied in area.
 Our dataset consisted of 524 freshwater
 lakes from across the globe sampled at least once from 1974–2021. Data from
 505 lakes was contributed by co-authors of this study and
 included lakes in
 Denmark (n = 198), China
 (n =131), Finland (n = 96), USA (n = 48), New Zealand (n = 15), Greece (n
 =11), Mexico (n = 4) and Russia (n = 2). Most of these data had been published
 previously.
 We also included data from an
 additional 19 lakes identified in a Google Scholar literature review using
 the search terms "shallow lake" AND "zoobenthos" OR
 "benthic macroinvertebrate". From this, we identified sources
 that reported taxonomic-level abundance and nutrient concentrations and
 met the sampling criteria applied in the other studies (mean depth
 &lt; 10 m and sampling conducted in offshore zones and warm seasons).
 These data come from six publications. See details in paper.
description: # Climate-associated variation in the drivers of benthic macroinvertebrate
 species-area relationships across shallow freshwater lakes ## Description
 of the data and file structure These are the metadata and codes of the
 study "Climate-associated variation in the drivers of benthic
 macroinvertebrate species-area relationships across shallow freshwater
 lakes", which has been accepted in the Journal of Animal Ecology. Our
 dataset consisted of 524 freshwater lakes from across the globe sampled at
 least once from 1974–2021. Data from 505 lakes was contributed by
 co-authors of this study and included lakes in Denmark, China, Finland,
 USA, New Zealand , Greece, Mexico and Russia. Most of these data had been
 published previously (Drake et al., 2011; Hu et al., 2014; Jyväsjärvi et
 al., 2014; Ntislidou et al., 2018; Cortés-Guzmán et al., 2019; Zhang et
 al., 2019; Jeppesen et al., 2020; Loskutova, 2020; Jovem-Azevêdo et al.,
 2022; Wu et al., 2022). We also included data from an additional 19 lakes
 identified in a Google Scholar literature review using the search terms
 "shallow lake" AND "zoobenthos" OR "benthic
 macroinvertebrate". These data come from six publications
 (Lindergaard & Jónasson, 1979; Takamura et al., 2009; Atobatele
 & Ugwumba, 2010; Çamur-Elipek et al., 2010; Chakrabarty et al.,
 2010; Dou et al., 2022). Please see the references in our paper and cited
 when used the dataset. The archive **species.zip** contains species data
 for each study, a table describing the average abundance (ind.
 m<sup>-2</sup>) of each species in a lake. Note that in this
 synthesis study, the species symbols, e.g., "sp1, sp2...", only
 represent the names of species in a lake within a study. That is to say,
 the same symbols (e.g. sp1) in different studies maybe represent different
 species. For instance, 'sp1' in Danish lakes represent a species
 of oligochaeta, but is a bivalve species in Finish lakes. The archieve
 **env.zip** contains relevant environmental parameters, included lakeno
 (lake name), year (sampling time), area (lake surface area,
 km<sup>2</sup>), waterdepth (sampling depth, m), total
 nitrogen (tn, mg/L), total phosphorus (tp, mg/L), elevation (m),
 coordinates (N, S), mesh size (μm), number of sampling sites, replicates
 per sites, sampler area (cm<sup>2</sup>), ClimateZ (climate
 code based on Koppen system, see paper), climate2 (climate zones based on
 koppen system, see paper) climate (climate group in our study), Missing
 values are coded as "NA". ## Sharing/Access information Data was
 also achieved from the following sources:
 https://github.com/hehuabc/benthic-macroinvertebrates-of-global-lakes ##
 Code/Software We have also updated 3 code files, which have detailly
 showed the analysis processes in our paper. All calculation and analysis
 processes were conducted in R software. Packages of "iNEXT" and
 "glmmTMB" were mainly used for analysis, and "ggplot2"
 for graphic work. The figures with high resolution were also attached.