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Pinkernell, Stefan (2017): Modeling the biogeography of pelagic diatoms of the Southern Ocean, links to model results and images [dataset publication series]. PANGAEA, https://doi.org/10.1594/PANGAEA.878263, Supplement to: Pinkernell, S (2017): Modeling the biogeography of pelagic diatoms of the Southern Ocean. PhD Thesis, University of Rostock, Germany

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Abstract:
Species distribution models (SDM) are a widely used and well established method for biogeographical research on terrestrial organisms. Though already used for decades, experience with marine species is scarce especially for protists. More and more observation data, sometimes even aggregated over centuries, become available also for the marine world, which together with high quality environmental data form a promising base for marine SDMs. In contrast to these SDMs, typical biogeographical studies of diatoms only considered observation data from a few transects.
Species distribution methods were evaluated for marine pelagic diatoms in the Southern Ocean at the example of F. kerguelensis. Based on the experience with these models, SDMs for further species are built to study biogeographical patterns. The anthropogenic impact of climate change on these species is assessed by model projections on future scenarios for the end of this century.
Besides observation data from public data repositories such as GBIF, data from the Hustedt diatom collection was used. The models presented here rely on so called presence only observation data. For this simple data type Maxent has been proven to be a good modeling method.
SDM seems a suitable modeling method to study biogeography of marine pelagic diatoms in the Southern Ocean. Models of decent quality could be build, despite partly poor data. Future projections indicate a moderate decrease of the suitable areas towards the end of the century for most of the species.
Funding:
German Research Foundation (DFG), grant/award no. 5472008: Priority Programme 1158 Antarctic Research with Comparable Investigations in Arctic Sea Ice Areas
Size:
3 datasets

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