Published March 1, 2019 | Version v1
Report Open

Use of species distribution modeling in the deep sea

  • 1. Fisheries and Oceans Canada, Bedford Institute of Oceanography, Dartmouth, NS, Canada
  • 2. National University of Galway, Ireland
  • 3. University of Ottawa, Ottawa, Ontario, Canada
  • 4. Institute of Marine Research, Azores, Portugal
  • 5. Secretariat of the Convention on Biological Diversity, Montreal, Quebec, Canada
  • 6. University of Bangor, Bangor, Wales, United Kingdom
  • 7. CSIRO Oceans and Atmosphere, Hobart, Tasmania, Australia
  • 8. Fisheries and Oceans Canada, Institute of Ocean Sciences, Sidney, British Columbia, Canada
  • 9. Fisheries and Oceans Canada, Pacific Biological Station, Nanaimo, British Columbia, Canada
  • 10. University of Plymouth, Plymouth, England, United Kingdom
  • 11. Nova Scotia Community College, Dartmouth, Nova Scotia, Canada
  • 12. University of Edinburgh, Edinburgh, Scotland, United Kingdom
  • 13. Alaska Fisheries Science Center, Seattle, Washington, United States of America
  • 14. National Institute of Water and Atmospheric Research, Wellington, New Zealand
  • 15. Marine Scotland Science, Aberdeen, Scotland, United Kingdom
  • 16. Princeton University, Princeton, New Jersey, United States of America
  • 17. University of Helsinki, Helsinki, Finland
  • 18. Zoological Society of London, London, England, United Kingdom

Description

Use of Species Distribution Modeling in the Deep Sea.  Published in the Canadian Technical Report of
Fisheries and Aquatic Sciences 3296 (2019)

In the last two decades the use of species distribution modeling (SDM) for the study and management of marine species has increased dramatically. The availability of predictor variables on a global scale and the ease of use of SDM techniques have resulted in a proliferation of research on the topic of species distribution in the deep sea. Translation of research projects into management tools that can be used to make decisions in the face of changing climate and increasing exploitation of deep-sea resources has been less rapid but necessary. The goal of this workshop was to discuss methods and variables for modeling species distributions in deep-sea habitats and produce standards that can be used to judge SDMs that may be useful to meet management and conservation goals. During the workshop, approaches to modeling and environmental data were discussed and guidelines developed including the desire that 1) environmental variables should be chosen for ecological significance a priori; 2) the scale and accuracy of environmental data should be considered in choosing a modeling method; 3) when possible proxy variables such as depth should be avoided if causal variables are available; 4) models with statistically robust and rigorous outputs are preferred, but not always possible; and 5) model validation is important. Although general guidelines for SDMs were developed, in most cases management issues and objectives should be considered when designing a modeling project. In particular, the trade-off between model complexity and researcher’s ability to communicate input data, modeling method, results and uncertainty is an important consideration for the target audience.

Files

Kenchington et al. (2019) Species Distribution Modelling in the Deep Sea Technical Report.pdf

Additional details

Funding

ATLAS – A Trans-AtLantic Assessment and deep-water ecosystem-based Spatial management plan for Europe 678760
European Commission