Selecting environmental descriptors is critical for modelling the distribution of Antarctic benthic species
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ORIGINAL PAPER
Selecting environmental descriptors is critical for modelling the distribution of Antarctic benthic species Guillaumot Charlène1,2 · Danis Bruno1 · Saucède Thomas2 Received: 8 October 2019 / Revised: 12 June 2020 / Accepted: 25 June 2020 © Springer-Verlag GmbH Germany, part of Springer Nature 2020
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. Keywords Species distribution models (SDMs) · Boosted regression trees (BRT) · Southern ocean · Collinearity · Asteroidea · Conservation · Environmental descriptors
Introduction The Southern Ocean is one of the regions on Earth that is undergoing climate change at the fastest pace (Convey et al. 2009; Turner et al. 2014; Henley et al. 2019). Predicting the response of Antarctic species and communities to environmental changes is challenging but it has become a pressing Electronic supplementary material The online version of this article (https://doi.org/10.1007/s00300-020-02714-2) contains supplementary material, which is available to authorized users. * Guillaumot Charlène [email protected] 1
Université Libre de Bruxelles, Marine Biology Lab., Avenue F.D. Roosevelt, 50. CP 160/15, 1050 Bruxelles, Belgium
UMR 6282 Biogéosciences, Univ. Bourgogne Franche-Comté, CNRS, 6 bd Gabriel, 21000 Dijon, France
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