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Species distribution modelling of the Southern Ocean benthos: a review on methods, cautions and solutions

Published online by Cambridge University Press:  21 June 2021

Charlène Guillaumot Open the ORCID record for Charlène Guillaumot [Opens in a new window] ,
Bruno Danis Open the ORCID record for Bruno Danis [Opens in a new window]  and
Thomas Saucède Open the ORCID record for Thomas Saucède [Opens in a new window]
Charlène Guillaumot*
Affiliation:
Université Libre de Bruxelles, Marine Biology Lab, Avenue F.D. Roosevelt, 50. CP 160/15 1050Bruxelles, Belgium UMR 6282 Biogéosciences, Univ. Bourgogne Franche-Comté, CNRS, 6 bd Gabriel F-21000, Dijon, France
Bruno Danis
Affiliation:
Université Libre de Bruxelles, Marine Biology Lab, Avenue F.D. Roosevelt, 50. CP 160/15 1050Bruxelles, Belgium
Thomas Saucède
Affiliation:
UMR 6282 Biogéosciences, Univ. Bourgogne Franche-Comté, CNRS, 6 bd Gabriel F-21000, Dijon, France
*
[email protected]
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Abstract

Species distribution modelling studies the relationship between species occurrence records and their environmental setting, providing a valuable approach to predicting species distribution in the Southern Ocean (SO), a challenging region to investigate due to its remoteness and extreme weather and sea conditions. The specificity of SO studies, including restricted field access and sampling, the paucity of observations and difficulties in conducting biological experiments, limit the performance of species distribution models. In this review, we discuss some issues that may influence model performance when preparing datasets and calibrating models, namely the selection and quality of environmental descriptors, the spatial and temporal biases that may affect the quality of occurrence data, the choice of modelling algorithms and the spatial scale and limits of the projection area. We stress the importance of evaluating and communicating model uncertainties, and the most common evaluation metrics are reviewed and discussed accordingly. Based on a selection of case studies on SO benthic invertebrates, we highlight important cautions to take and pitfalls to avoid when modelling the distribution of SO species, and we provide some guidelines along with potential methods and original solutions that can be used for improving model performance.

Keywords

Antarcticabiaseslimitsmarine benthic invertebratesmodelling performance
Type
Biological Sciences
Information
Antarctic Science , Volume 33 , Issue 4 , August 2021 , pp. 349 - 372
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Copyright
Copyright © Antarctic Science Ltd 2021

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