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用不完整数据实现集成步骤选择函数的方法

David D Hofmann^1,2, Gabriele Cozzi^3,4, John Fieberg⁵

¹Department of Evolutionary Biology and Environmental Studies, University of Zurich, Winterthurerstrasse 190, 8057, Zurich, Switzerland. david.hofmann2@uzh.ch.

Movement ecology

|May 9, 2024

概括

这项研究引入了分析不规则时间间隔的动物移动数据的新方法,改进了息地选择模型. 这些方法利用了更多的数据,提高了跟踪动物偏好的准确性.

科学领域:

生态生态学生态生态学
野生动物生物学野生动物生物学
运动生态学运动生态学

背景情况:

综合阶段选择分析 (iSSA) 是研究动物息地和移动偏好的标准.
iSSA需要定期定时的动物位置数据,但由于跟踪不规则,通常无法获得这些数据.
当前的做法往往会丢弃具有时间不规则的有价值数据,限制模型的范围.

研究的目的:

评估综合步骤选择分析 (iSSAs) 的替代方法,以适应动物跟踪数据中的不规则时间间隔.
将这些新方法的性能与忽视时间不规则的基线方法进行比较.
为了证明从暂时不规则的数据集中利用额外的数据点的好处.

主要方法:

开发并测试了四种替代方法来处理iSSAs内的动物位置数据中的时间不规则.
进行了模拟研究,以比较替代方法与基线方法的性能.
将这些方法应用于一个涉及斑点 (Crocuta crocuta) 移动数据的案例研究.

主要成果:

与基线方法相比,替代方法显示了模型性能的潜在改善.
利用具有时间不规则的数据,可以对移动和息地选择进行更强大的分析.
案例研究说明了拟议方法的实际好处.

结论:

研究人员可以通过结合考虑时间不规则的方法来提高综合步骤选择分析的准确性和范围.
这些发现鼓励使用更完整的数据集,即使是那些缺少位置的数据集.
开发的方法提供了对动物行为和息地使用的更全面的了解.

关键词:

动物的运动动物的运动.这些数据是GPS数据.计入算法是指指计入算法.不完整的数据不完全的数据.缺少的修复错过的修复阶段性选择分析分析.步骤选择函数具有步骤选择的功能.

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