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.

中文翻译：

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南大洋底栖生物的物种分布模型：方法、注意事项和解决方案综述

物种分布模型研究了物种出现记录与其环境环境之间的关系，为预测南大洋 (SO) 的物种分布提供了一种有价值的方法，由于其地处偏远和极端天气和海况，这是一个需要调查的具有挑战性的区域。SO 研究的特殊性，包括受限的现场访问和采样、观察的缺乏和进行生物实验的困难，限制了物种分布模型的性能。在这篇综述中，我们讨论了在准备数据集和校准模型时可能影响模型性能的一些问题，即环境描述符的选择和质量，可能影响发生数据质量的空间和时间偏差，建模算法的选择以及投影区域的空间尺度和限制。我们强调评估和交流模型不确定性的重要性，并对最常见的评估指标进行了相应的审查和讨论。基于对 SO 底栖无脊椎动物的一系列案例研究，我们强调了在模拟 SO 物种分布时应注意的重要事项和应避免的陷阱，并提供一些指导方针以及可用于提高模型性能的潜在方法和原始解决方案.