DOI: 10.5061/dryad.vhhmgqnqp
title: Cross-continental analysis of coastal biodiversity change

description: Whereas the anthropogenic impact on marine biodiversity is undebated, the
 quantification and prediction of this change is not trivial. Simple
 traditional measures of biodiversity (e.g., richness, diversity indices)
 do not capture the magnitude and direction of changes in species or
 functional composition. In this paper, we apply recently developed methods
 for measuring biodiversity turnover to time-series data of four broad
 taxonomic groups from two coastal regions: the southern North Sea
 (Germany) and the South African coast. Both areas share geomorphological
 features and ecosystem types, allowing for a critical assessment of the
 most informative metrics of biodiversity change across organism groups. We
 found little evidence for directional trends in univariate metrics of
 diversity for either the effective number of taxa or the amount of
 richness change. However, turnover in composition was high (on average
 nearly 30% of identities when addressing presence or absence of species)
 and even higher when taking the relative dominance of species into
 account. This turnover accumulated over time at similar rates across
 regions and organism groups. We conclude that biodiversity metrics
 responsive to turnover provide a more accurate reflection of community
 change relative to conventional metrics (absolute richness or relative
 abundance) and are spatially broadly applicable.
description: Data
 comprised community composition assessments for major organism groups in
 two coastal regions (Germany, South Africa), including phytoplankton and
 zooplankton (grouped collectively as ‘plankton’ hereafter), benthic
 macroinvertebrates, fish and coastal birds. Site descriptions for the
 sampling locations of these regions are expanded upon in the respective
 article. Each dataset reports on the presence and abundance of species (or
 in some cases, a coarser taxonomic level, but hereafter ‘species’ are
 referred to) in coastal marine and estuarine ecosystems. We pooled the
 data to yearly averages per species and site across all samplings.
 Datasets were checked for consistent naming of species and reporting, but
 otherwise used as reported. We used the
 approach suggested by Hillebrand et al. (2018, as
 cited in the articles) to quantify the amount of change
 in species composition. All analyses were performed in R, we
 used the vegan
 package to calculate taxon richness and
 effective number of species (ENS) as measures of standing diversity, where
 ENS is the standardized species diversity measure assuming equal abundance
 in the community.For turnover, we used the
 presence-absence based Jaccard index to calculate the species exchange
 ratio based on richness (SERr), where 0 is no exchange of species
 identities, and 1 a complete overturn. We used Wishart’s dissimilarity as
 a measure of abundance-based species exchange ratio (SERa), which is based
 on Simpson’s index of dominance, a feature shared with
 ENS. SERa also ranges between 0 and 1,
 with 0 indicating that species identity and relative abundance remains
 unchanged, but 1 indicating a complete exchange of species or a change in
 dominance structure.    
description: Two data
 sets are provided year.csv For each sampling station
 (StationID), identifying the organism group analysed (organism) and region
 (region), we report the annual ENS and species richness (S) for each year
 (year_start) as well as the change in richness, SERr and SERa to the
 following year x+1. all.csv
 To analyse
 how biodiversity change accumulates over time, we calculated SERa and SERr
 for all combinations of years, i.e., between any year x and any
 consecutive year y. For each sampling station (StationID), identifying the
 organism group analysed (organism) and region (region), we give the
 starting year (year_start = x) and the temporal distance between y and x
 (dist), and the measures for SERa and SERr as well as the corresponding
 change in species richness.