Addressing uncertainty when projecting marine species' distributions under climate change

Author:

Davies Sarah C.1ORCID,Thompson Patrick L.23ORCID,Gomez Catalina4,Nephin Jessica2ORCID,Knudby Anders5,Park Ashley E.2,Friesen Sarah K.2,Pollock Laura J.6,Rubidge Emily M.27,Anderson Sean C.18ORCID,Iacarella Josephine C.9,Lyons Devin A.10,MacDonald Andrew11,McMillan Andrew1,Ward Eric J.12,Holdsworth Amber M.2,Swart Neil13,Price Jeff14,Hunter Karen L.1

Affiliation:

1. Pacific Biological Station, Fisheries and Oceans Canada Nanaimo BC Canada

2. Institute of Ocean Science, Fisheries and Oceans Canada Sidney BC Canada

3. Department of Zoology, University of British Columbia BC Canada

4. Bedford Institute of Oceanography, Fisheries and Oceans Canada Dartmouth Nova Scotia Canada

5. Department of Geography, Environment and Geomatics, University of Ottawa Ottawa ON Canada

6. Department of Biology, McGill University Montreal QC Canada

7. Department of Forest and Conservation Sciences, University of British Columbia Vancouver BC Canada

8. Simon Fraser University, Department of Mathematics Burnaby BC Canada

9. Cultus Lake Labs, Fisheries and Oceans Canada Cultus Lake BC Canada

10. Bedford Institute of Oceanography, Fisheries and Oceans Canada Dartmouth NS Canada

11. Département de biologie, Université de Sherbrooke Sherbrooke QC Canada

12. Northwest Fisheries Science Center, NOAA Seattle WA USA

13. Canadian Centre for Climate Modelling and Analysis, Environment and Climate Change Canada Victoria BC Canada

14. Tyndall Centre for Climate Change Research, School of Environmental Sciences, University of East Anglia Norwich UK

Abstract

Species distribution models (SDMs) have been widely used to project terrestrial species' responses to climate change and are increasingly being used for similar objectives in the marine realm. These projections are critically needed to develop strategies for resource management and the conservation of marine ecosystems. SDMs are a powerful and necessary tool; however, they are subject to many sources of uncertainty, both quantifiable and unquantifiable. To ensure that SDM projections are informative for management and conservation decisions, sources of uncertainty must be considered and properly addressed. Here we provide ten overarching guidelines that will aid researchers to identify, minimize, and account for uncertainty through the entire model development process, from the formation of a study question to the presentation of results. These guidelines focus on correlative models and were developed at an international workshop attended by over 50 researchers and practitioners. Although our guidelines are broadly applicable across biological realms, we provide particular focus to the challenges and uncertainties associated with projecting the impacts of climate change on marine species and ecosystems.

Publisher

Wiley

Subject

Ecology, Evolution, Behavior and Systematics

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