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.

中文翻译：

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选择环境描述符对于模拟南极底栖物种的分布至关重要

南极生物学家越来越多地将物种分布模型 (SDM) 用于生态和生物地理学研究，包括用于保护和管理目的。在建模过程中，模型校准是确保模型可靠性和稳健性的关键步骤，尤其是在 SDM 的情况下，所选环境描述符的数量及其共线性是一个反复出现的问题。增强回归树 (BRT) 以前被认为是纠正此类偏差的最佳建模方法之一。在本研究中，我们使用不同数量的环境描述符（无论是否共线）测试 BRT 在模拟南大洋物种分布方面的性能。为六个海星物种生成了模型，这些海星物种在整个南大洋具有对比鲜明的生态位和广泛的分布范围。对于六个研究的物种，整体建模性能不受用于生成模型的环境描述符数量的影响，BRT 使用信息量最大的描述符并最大限度地减少模型过度拟合。然而，删除共线描述符也有助于减少模型过度拟合。我们的结果证实 BRT 可能表现良好，并且与处理南极生物多样性分布研究的复杂和冗余环境信息相关。在建模之前选择有限数量的非共线描述符可能会生成更简单的模型并促进其解释。尽管物种生态位不同，模拟的分布在不同物种之间没有显着差异。这一意外结果强调了基于有限的空间聚合数据和低分辨率描述符使用 SDM 进行大尺度空间研究的重要局限性。