Data from: Data-driven bioregionalization: A seascape-scale study of macrobenthic communities in the Eurasian Arctic
Pantiukhin, Dmitrii; Piepenburg, Dieter; Hansen, Miriam L. S.; Kraan, Casper (2022), Data from: Data-driven bioregionalization: A seascape-scale study of macrobenthic communities in the Eurasian Arctic, Dryad, Dataset, https://doi.org/10.5061/dryad.8pk0p2nn9
Aim: We conduct the first model-based assessment of the biogeographical subdivision of Eurasian Arctic seas to (1) delineate spatial distribution and boundaries of macrobenthic communities on a seascape level; (2) assess the significance of environmental drivers of macrobenthic community structures; (3) compare our modelling results to historical biogeographical classifications; and (4) couple the model to climate-change scenarios of environmental changes to project potential shifts in the distribution and composition of macrobenthic communities by 2100.
Location: Eurasian Arctic seas, in particular Barents, Kara, and Laptev Seas
Taxon: Macrobenthic fauna
Methods: We employed the Region of Common Profile (RCP) approach to assess the regionalization patterns of Eurasian Arctic seafloor communities.
Results: Four RCPs were identified based on the spatial distribution patterns of 169 macrobenthic species and a set of environmental factors, such as sediment composition, sea-ice concentration, depth of the euphotic zone, particulate organic carbon concentration at the ocean surface, as well as near-bottom water temperature and salinity. The identified regions are in strong agreement with previous classifications of macrobenthic communities. The projections are driven by climate-change scenario “Representative Concentration Pathway 6.0” suggested a general eastward shift of the RCPs over the 21st century, correlated to retreating sea-ice and increasing sea-bottom temperature.
Main conclusions: The RCP approach allowed us to identify seascape-scale distribution patterns of macrobenthic communities in Eurasian Arctic seas by simultaneously considering biotic and environmental data within one modelling step. This technique can represent biota and ecoregions in a probabilistic form together with assessment of uncertainties of the predictions, and assess the significance of a broad selection of environmental drivers. This first quantitative assessment of potential climate-driven changes in macrobenthic biodiversity will promote their inclusion in conservation measures.
We employed the Region of Common Profile (RCP) approach to assess the regionalization patterns of Eurasian Arctic seafloor communities. The entire data analysis was conducted in R using package 'RCPmod'.
Federal Ministry of Education and Research (Germany), project ‘The Changing Arctic Transpolar System (CATS)', Award: Grant 03F0776
Marie Skłodowska-Curie action, Award: Grant 700796