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Correlative and dynamic species distribution modelling for ecological predictions in the Antarctic a cross-disciplinary concept

  • Developments of future scenarios of Antarctic ecosystems are still in their infancy, whilst predictions of the physical environment are recognized as being of global relevance and corresponding models are under continuous development. However, in the context of environmental change simulations of the future of the Antarctic biosphere are increasingly demanded by decision makers and the public, and are of fundamental scientific interest. This paper briefly reviews existing predictive models applied to Antarctic ecosystems before providing a conceptual framework for the further development of spatially and temporally explicit ecosystem models. The concept suggests how to improve approaches to relating species' habitat description to the physical environment, for which a case study on sea urchins is presented. In addition, the concept integrates existing and new ideas to consider dynamic components, particularly information on the natural history of key species, from physiological experiments and biomolecular analyses. Thereby, weDevelopments of future scenarios of Antarctic ecosystems are still in their infancy, whilst predictions of the physical environment are recognized as being of global relevance and corresponding models are under continuous development. However, in the context of environmental change simulations of the future of the Antarctic biosphere are increasingly demanded by decision makers and the public, and are of fundamental scientific interest. This paper briefly reviews existing predictive models applied to Antarctic ecosystems before providing a conceptual framework for the further development of spatially and temporally explicit ecosystem models. The concept suggests how to improve approaches to relating species' habitat description to the physical environment, for which a case study on sea urchins is presented. In addition, the concept integrates existing and new ideas to consider dynamic components, particularly information on the natural history of key species, from physiological experiments and biomolecular analyses. Thereby, we identify and critically discuss gaps in knowledge and methodological limitations. These refer to process understanding of biological complexity, the need for high spatial resolution oceanographic data from the entire water column, and the use of data from biomolecular analyses in support of such ecological approaches. Our goal is to motivate the research community to contribute data and knowledge to a holistic, Antarctic-specific, macroecological framework. Such a framework will facilitate the integration of theoretical and empirical work in Antarctica, improving our mechanistic understanding of this globally influential ecoregion, and supporting actions to secure this biodiversity hotspot and its ecosystem services.show moreshow less

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Author details:Julian Gutt, Damaris ZurellORCiDGND, Thomas J. Bracegridle, William Cheung, Melody S. Clark, Peter Convey, Bruno Danis, Bruno David, Claude De Broyer, Guido di Prisco, Huw Griffiths, Remi Laffont, Lloyd S. Peck, Benjamin Pierrat, Martin J. Riddle, Thomas Saucede, John Turner, Cinzia Verde, Zhaomin Wang, Volker GrimmORCiDGND
DOI:https://doi.org/10.3402/polar.v31i0.11091
ISSN:0800-0395
Title of parent work (English):Polar research : a Norwegian journal of Polar research
Publisher:Co-Action Publ.
Place of publishing:Jarfalla
Publication type:Article
Language:English
Year of first publication:2012
Publication year:2012
Release date:2017/03/26
Tag:Environmental change; biodiversity; habitat suitability models; integrative modelling framework; spatially and temporally explicit modelling macroecology
Volume:31
Issue:6
Number of pages:23
Organizational units:Mathematisch-Naturwissenschaftliche Fakultät / Institut für Geowissenschaften
Peer review:Referiert
Publishing method:Open Access
Institution name at the time of the publication:Mathematisch-Naturwissenschaftliche Fakultät / Institut für Erd- und Umweltwissenschaften
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