Predicting the spatial distribution of animals is an important and widely used tool with applications in wildlife management, conservation, and population health. Wildlife telemetry technology coupled with the availability of spatial data and GIS software have facilitated advancements in species distribution modeling. There are also challenges related to these advancements including the accurate and appropriate implementation of species distribution modeling methodology. Resource Selection Function (RSF) modeling is a commonly used approach for understanding species distributions and habitat usage, and mapping the RSF results can enhance study findings and make them more accessible to researchers and wildlife managers. Currently, there is no consensus in the literature on the most appropriate method for mapping RSF results, methods are frequently not described, and mapping approaches are not always related to accuracy metrics. We conducted a systematic review of the RSF literature to summarize the methods used to map RSF outputs, discuss the relationship between mapping approaches and accuracy metrics, performed a case study on the implications of employing different mapping methods, and provide recommendations as to appropriate mapping techniques for RSF studies. We found extensive variability in methodology for mapping RSF results. Our case study revealed that the most commonly used approaches for mapping RSF results led to notable differences in the visual interpretation of RSF results, and there is a concerning disconnect between accuracy metrics and mapping methods. We make 5 recommendations for researchers mapping the results of RSF studies, which are focused on carefully selecting and describing the method used to map RSF studies, and relating mapping approaches to accuracy metrics.

中文翻译：

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绘制野生动物研究中的资源选择功能：关注点和建议

预测动物的空间分布是一种重要且广泛使用的工具，可应用于野生动物管理、保护和人口健康。野生动物遥测技术与空间数据和 GIS 软件的可用性相结合，促进了物种分布建模的进步。还存在与这些进步相关的挑战，包括准确和适当地实施物种分布建模方法。资源选择函数 (RSF) 建模是了解物种分布和栖息地使用的常用方法，绘制 RSF 结果可以增强研究结果并使研究人员和野生动物管理人员更容易获得这些结果。目前，关于绘制 RSF 结果的最合适方法，文献中没有达成共识，方法经常不被描述，映射方法并不总是与准确度指标相关。我们对 RSF 文献进行了系统审查，以总结用于映射 RSF 输出的方法，讨论映射方法和准确度指标之间的关系，对采用不同映射方法的影响进行案例研究，并提供有关适当映射技术的建议用于 RSF 研究。我们发现映射 RSF 结果的方法存在很大差异。我们的案例研究表明，映射 RSF 结果的最常用方法导致 RSF 结果的视觉解释存在显着差异，并且准确度指标和映射方法之间存在令人担忧的脱节。我们为绘制 RSF 研究结果的研究人员提出 5 条建议，