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

Journal

ANTARCTIC SCIENCE
Volume 33, Issue 4, Pages 349-372

Publisher

CAMBRIDGE UNIV PRESS
DOI: 10.1017/S0954102021000183

Keywords

Antarctica; biases; limits; marine benthic invertebrates; modelling performance

Funding

  1. 'Fonds pour la formation a la Recherche dans l'Industrie et l'Agriculture' (FRIA)
  2. Bourse fondation de la mer
  3. Belgian Science Policy Office (BELSPO) [BR/132/A1/vERSO]
  4. 'Refugia and Ecosystem Tolerance in the Southern Ocean' project (RECTO) - Belgian Science Policy Office (BELSPO) [BR/154/A1/RECTO]

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Species distribution modelling in the Southern Ocean faces challenges due to its unique characteristics and limitations in data and model calibration, affecting model performance. Attention to details in model construction and evaluation and communication of model uncertainties are crucial in improving model performance.
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.

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