Published March 26, 2020 | Version v1
Dataset Open

Cross-continental analysis of coastal biodiversity change

  • 1. Carl von Ossietzky University of Oldenburg
  • 2. Nelson Mandela University
  • 3. University of Johannesburg
  • 4. University of KwaZulu-Natal
  • 5. ,
  • 6. Alfred Wegener Institute for Polar and Marine Research
  • 7. Wadden Sea National Park of Lower Saxony*

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.

Notes

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.

                 

Funding provided by: Deutsche Forschungsgemeinschaft
Crossref Funder Registry ID: http://dx.doi.org/10.13039/501100001659
Award Number: DFG HI848/25-1

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