Animal movement studies have become ubiquitous in animal ecology for estimation of space use and analysis of movement behavior. In these studies, animal movement data are primarily collected at regular time intervals. We propose an irregular sampling design which could lead to greater efficiency and information gain in animal movement studies. Our novel sampling design, called lattice and random intermediate point (LARI), combines samples at regular and random time intervals. We compare the LARI sampling design to regular sampling designs in an example with common black carpenter ant location data, an example with guppy location data, and a simulation study of movement with a point of attraction. We modify a general stochastic differential equation model to allow for irregular time intervals and use this framework to compare sampling designs. When parameters are estimated reasonably well, regular sampling results in greater precision and accuracy in prediction of missing data. However, in each of the data and simulation examples explored in this paper, LARI sampling results in more accurate and precise parameter estimation, and thus better prediction of missing data as well. This result suggests that researchers might gain greater insight into underlying animal movement processes by choosing LARI sampling over regular sampling.

中文翻译：

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动物运动的格子随机中间点抽样设计

动物运动研究在动物生态学中无处不在，用于估计空间使用和分析运动行为。在这些研究中，动物运动数据主要是定期收集的。我们提出了一种不规则的抽样设计，可以提高动物运动研究的效率和信息增益。我们新颖的采样设计称为晶格和随机中间点 (LARI)，以规则和随机时间间隔组合样本。我们将 LARI 抽样设计与常规抽样设计进行了比较，例如使用常见的黑木蚁位置数据、使用孔雀鱼位置数据的示例以及具有吸引点的运动模拟研究。我们修改了一个通用的随机微分方程模型以允许不规则的时间间隔，并使用这个框架来比较抽样设计。当参数估计得相当好时，定期抽样会导致预测丢失数据的精度和准确度更高。然而，在本文探讨的每个数据和模拟示例中，LARI 采样导致更准确和精确的参数估计，从而更好地预测缺失数据。这一结果表明，通过选择 LARI 采样而不是常规采样，研究人员可能会更深入地了解潜在的动物运动过程。