Recursive movement patterns have been used to detect behavioral structure within individual movement trajectories in the context of foraging ecology, home-ranging behavior, and predator avoidance. Some animals exhibit movement recursions to locations that are tied to reproductive functions, including nests and dens; while existing literature recognizes that, no method is currently available to explicitly target different types of revisited locations. Moreover, the temporal persistence of recursive movements to a breeding location can carry information regarding the fate of breeding attempts, but it has never been used as a metric to quantify recursive movement patterns. Here, we introduce a method to locate breeding attempts and estimate their fate from GPS-tracking data of central place foragers. We tested the performance of our method in three bird species differing in breeding ecology (wood stork (Mycteria americana), lesser kestrel (Falco naumanni), Mediterranean gull (Ichthyaetus melanocephalus)) and implemented it in the R package ‘nestR’. We identified breeding sites based on the analysis of recursive movements within individual tracks. Using trajectories with known breeding attempts, we estimated a set of species-specific criteria for the identification of nest sites, which we further validated using non-reproductive individuals as controls. We then estimated individual nest survival as a binary measure of reproductive fate (success, corresponding to fledging of at least one chick, or failure) from nest-site revisitation histories during breeding attempts, using a Bayesian hierarchical modeling approach that accounted for temporally variable revisitation patterns, probability of visit detection, and missing data. Across the three species, positive predictive value of the nest-site detection algorithm varied between 87 and 100% and sensitivity between 88 and 92%, and we correctly estimated the fate of 86–100% breeding attempts. By providing a method to formally distinguish among revisited locations that serve different ecological functions and introducing a probabilistic framework to quantify temporal persistence of movement recursions, we demonstrated how the analysis of recursive movement patterns can be applied to estimate reproduction in central place foragers. Beyond avian species, the principles of our method can be applied to other central place foraging breeders such as denning mammals. Our method estimates a component of individual fitness from movement data and will help bridge the gap between movement behavior, environmental factors, and their fitness consequences.

中文翻译：

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分析运动递归以检测繁殖事件并估计它们在中心地方觅食者中的命运。

在觅食生态、家庭范围行为和捕食者回避的背景下，递归运动模式已被用于检测个体运动轨迹内的行为结构。一些动物表现出运动递归到与生殖功能相关的位置，包括巢穴和巢穴；虽然现有文献承认这一点，但目前没有任何方法可以明确针对不同类型的重访地点。此外，到繁殖地点的递归运动的时间持续性可以携带有关繁殖尝试命运的信息，但它从未被用作量化递归运动模式的指标。在这里，我们介绍了一种方法来定位繁殖尝试并根据中心地方觅食者的 GPS 跟踪数据估计它们的命运。我们测试了我们的方法在繁殖生态学不同的三种鸟类（木鹳（Mycteria americana）、小红隼（Falco naumanni）、地中海鸥（Ichthyaetus melanocephalus））中的性能，并在R包'nestR'中实施。我们根据对单个轨道内递归运动的分析确定了繁殖地点。使用具有已知繁殖尝试的轨迹，我们估计了一组特定于物种的巢址识别标准，我们使用非繁殖个体作为对照进一步验证了这些标准。然后，我们根据繁殖尝试期间的巢址重访历史，将个体巢穴存活率估计为繁殖命运（成功，对应于至少一只雏鸟的羽化，或失败）的二元测量，使用贝叶斯分层建模方法，该方法考虑了时间可变的重访模式、访问检测概率和缺失数据。在这三个物种中，巢址检测算法的阳性预测值在 87% 到 100% 之间变化，灵敏度在 88% 到 92% 之间变化，我们正确估计了 86% 到 100% 的繁殖尝试的命运。通过提供一种方法来正式区分服务于不同生态功能的重新访问的位置，并引入一个概率框架来量化运动递归的时间持续性，我们展示了如何应用递归运动模式的分析来估计中心地方觅食者的繁殖。除了鸟类，我们方法的原理还可以应用于其他中心地区觅食的繁殖者，例如巢穴哺乳动物。