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Simulation and Analysis of Animal Movement Paths Using Numerus Model Builder

机译:数字模型生成器对动物运动路径的仿真与分析

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We address the question of how best to fit animal movement paths, represented by point relocation time series, to a novel stochastic walk model—referred to as M-cubed—in a way that captures movement patterns at several different spatio-temporal scales. We test our approach on simulated data obtained from a high-frequency, multi-mode model constructed using the Numerus Model Builder platform. The advantage of using simulated over empirical data is that we know the processes generating movement. Fitting M-cubed to data requires that we extract movement modes and phases at various scales ranging from subhourly to daily. After fitting the M-cubed model, we evaluate how well it captures movement patterns and find that it performs exceptionally well at minute to hourly scales but needs to be extended to capture daily scale patterns driven by particular landscape features.
机译:我们将解决如何以点重定位时间序列表示的动物运动路径最适合新的随机行走模型(称为M立方体)的问题,这种模型可以捕获几种不同的时空尺度的运动模式。我们使用从使用Numerus Model Builder平台构建的高频,多模式模型获得的模拟数据测试我们的方法。使用模拟数据而不是经验数据的优势在于,我们知道产生运动的过程。使M-cubed适应数据需要我们从次小时到每天的不同尺度提取运动模式和阶段。拟合M-cubed模型后,我们评估了它捕获运动模式的能力,发现它在分钟到小时的尺度上表现出色,但是需要扩展以捕获由特定景观特征驱动的每日尺度模式。

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