Bioregions in marine environments: Combining Biological and Environmental Data for Management and Scientific Understanding

Skipton Woolley, Nicolas Bax, Jock Currie, Daniel Dunn, Cecilie Hansen, Nicole Hill, Timothy O'Hara, Otso Ovaskainen, Roger Sayre, Jarno Vanhatalo, Piers Dunstan

Research output: Contribution to journalArticleScientificpeer-review

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.

Original languageEnglish
JournalBioScience
Volume70
Issue number1
Pages (from-to)48-59
Number of pages12
ISSN0006-3568
DOIs
Publication statusPublished - Jan 2020
MoE publication typeA1 Journal article-refereed

Fields of Science

  • 1172 Environmental sciences
  • 112 Statistics and probability
  • biogeography
  • community ecology
  • statistics
  • marine biology
  • GENERALIZED LINEAR-MODELS
  • POINT PROCESS MODELS
  • SPECIES DISTRIBUTION
  • BIAS CORRECTION
  • BIODIVERSITY
  • IMPLEMENTATION
  • PREDICTIONS
  • ECOREGIONS
  • FRAMEWORK
  • REGIONS

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