Data from: Data-driven bioregionalization: A seascape-scale study of macrobenthic communities in the Eurasian Arctic ...
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;...
| Main Authors: | , , , |
|---|---|
| Format: | Dataset |
| Language: | English |
| Published: |
Dryad
2021
|
| Subjects: | |
| Online Access: | https://dx.doi.org/10.5061/dryad.8pk0p2nn9 https://datadryad.org/stash/dataset/doi:10.5061/dryad.8pk0p2nn9 |
| Summary: | 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 ... : 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'. ... |
|---|