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Bioregions in Marine Environments: Combining Biological and Environmental Data for Management and Scientific Understanding

Authors :
Timothy D. O'Hara
Cecilie Hansen
Nicholas J. Bax
Piers K. Dunstan
Jarno Vanhatalo
Jock C. Currie
Scott D. Foster
Daniel C. Dunn
Nicole A. Hill
Otso Ovaskainen
Skipton N. C. Woolley
Roger Sayre
Organismal and Evolutionary Biology Research Programme
Research Centre for Ecological Change
Otso Ovaskainen / Principal Investigator
Department of Mathematics and Statistics
Environmental and Ecological Statistics Group
Biostatistics Helsinki
Source :
BioScience. 70:48-59
Publication Year :
2019
Publisher :
Oxford University Press (OUP), 2019.

Abstract

Bioregions are important tools for understanding and managing natural resources. Bioregions should describe locations of relatively homogenous assemblages of species occur, enabling managers to better regulate activities that might affect these assemblages. Many existing bioregionalization approaches, which rely on expert-derived, Delphic comparisons or environmental surrogates, do not explicitly include observed biological data in such analyses. We highlight that, for bioregionalizations to be useful and reliable for systems scientists and managers, the bioregionalizations need to be based on biological data; to include an easily understood assessment of uncertainty, preferably in a spatial format matching the bioregions; and to be scientifically transparent and reproducible. Statistical models provide a scientifically robust, transparent, and interpretable approach for ensuring that bioregions are formed on the basis of observed biological and physical data. Using statistically derived bioregions provides a repeatable framework for the spatial representation of biodiversity at multiple spatial scales. This results in better-informed management decisions and biodiversity conservation outcomes.

Details

ISSN :
15253244 and 00063568
Volume :
70
Database :
OpenAIRE
Journal :
BioScience
Accession number :
edsair.doi.dedup.....0cc3816bd174037e1bd23ea3fcc9d287
Full Text :
https://doi.org/10.1093/biosci/biz133