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Selecting environmental descriptors is critical for modelling the distribution of Antarctic benthic species

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Abstract

Species distribution models (SDMs) are increasingly used in ecological and biogeographic studies by Antarctic biologists, including for conservation and management purposes. During the modelling process, model calibration is a critical step to ensure model reliability and robustness, especially in the case of SDMs, for which the number of selected environmental descriptors and their collinearity is a recurring issue. Boosted regression trees (BRT) was previously considered as one of the best modelling approach to correct for this type of bias. In the present study, we test the performance of BRT in modelling the distribution of Southern Ocean species using different numbers of environmental descriptors, either collinear or not. Models are generated for six sea star species with contrasting ecological niches and wide distribution ranges over the entire Southern Ocean. For the six studied species, overall modelling performance is not affected by the number of environmental descriptors used to generate models, BRT using the most informative descriptors and minimizing model overfitting. However, removing collinear descriptors also helps reduce model overfitting. Our results confirm that BRTs may perform well and are relevant to deal with complex and redundant environmental information for Antarctic biodiversity distribution studies. Selecting a limited number of non-collinear descriptors before modelling may generate simpler models and facilitate their interpretation. The modelled distributions do not differ noticeably between the different species despite contrasting species ecological niches. This unexpected result stresses important limitations in using SDMs for broad scale spatial studies, based on limited, spatially aggregated data, and low-resolution descriptors.

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Acknowledgements

This work was supported by a “Fonds pour la formation à la Recherche dans l’Industrie et l’Agriculture” (FRIA) and “Bourse Fondation de la mer” grants to C. Guillaumot. This is contribution no. 31 to the vERSO project and no. 10 to the RECTO project (www.rectoversoprojects.be), funded by the Belgian Science Policy Office (BELSPO, contracts no. BR/132/A1/vERSO and no. BR/154/A1/RECTO). This is contribution to the IPEV programs n°1124 REVOLTA and n°1044 PROTEKER. We are grateful to the crew and participants of all the cruises and research programs involved in the capture of the samples included in this dataset (see Moreau et al. 2018): POKER 2, REVOLTA 1 & 2, CEAMARC, JR144, JR179, JR230, JR262, JR275, JR287, JR15005.

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  1. Université Libre de Bruxelles, Marine Biology Lab., Avenue F.D. Roosevelt, 50. CP 160/15, 1050, Bruxelles, Belgium

    Guillaumot Charlène & Danis Bruno

  2. UMR 6282 Biogéosciences, Univ. Bourgogne Franche-Comté, CNRS, 6 bd Gabriel, 21000, Dijon, France

    Guillaumot Charlène & Saucède Thomas

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  1. Guillaumot Charlène
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Charlène, G., Bruno, D. & Thomas, S. Selecting environmental descriptors is critical for modelling the distribution of Antarctic benthic species. Polar Biol 43, 1363–1381 (2020). https://doi.org/10.1007/s00300-020-02714-2

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