Natasha J. Klappstein, Théo Michelot, John Fieberg, Eric J. Pedersen, Joanna Mills Flemming
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引用次数: 0
摘要
阶跃选择函数（SSF）用于共同描述动物的运动模式和栖息地偏好。最近的研究对这一框架进行了扩展，以模拟个体间的差异，解释动物空间利用中无法解释的结构，并捕捉随时间变化的运动和生境选择模式。在本文中，我们用惩罚性平滑（类似于广义加性模型）制定了 SSF，以统一新的和现有的扩展模型，并在流行的开源 mgcv R 软件包中方便地实现了这些模型。我们探索了运动和栖息地选择的非线性模式，并利用惩罚平滑样条和随机效应之间的等价性来实现个体水平和空间随机效应。该框架还可用于拟合变化系数模型，以解释时间或空间上的异质性选择模式（如行为变化导致的选择模式），或动物运动决策驱动因素之间的任何其他非线性相互作用。我们提供了必要的技术细节，以便理解平滑法的几种关键特例及其在 mgcv 中的实现，通过两个示例展示了其生态相关性，并提供了 R 代码以方便这些方法的采用。本文概述了如何应用平滑效应来提高 SSF 的灵活性和生物真实性。
期刊介绍：
A British Ecological Society journal, Methods in Ecology and Evolution (MEE) promotes the development of new methods in ecology and evolution, and facilitates their dissemination and uptake by the research community. MEE brings together papers from previously disparate sub-disciplines to provide a single forum for tracking methodological developments in all areas.
MEE publishes methodological papers in any area of ecology and evolution, including:
-Phylogenetic analysis
-Statistical methods
-Conservation & management
-Theoretical methods
-Practical methods, including lab and field
-This list is not exhaustive, and we welcome enquiries about possible submissions. Methods are defined in the widest terms and may be analytical, practical or conceptual.
A primary aim of the journal is to maximise the uptake of techniques by the community. We recognise that a major stumbling block in the uptake and application of new methods is the accessibility of methods. For example, users may need computer code, example applications or demonstrations of methods.
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