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Inferring parturition and neonate survival from movement patterns of female ungulates: a case study using woodland caribou

机译:从有蹄类动物的运动模式推断分娩和新生儿存活:以林地驯鹿为例的研究

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摘要

Analyses of animal movement data have primarily focused on understanding patterns of space use and the behavioural processes driving them. Here, we analyzed animal movement data to infer components of individual fitness, specifically parturition and neonate survival. We predicted that parturition and neonate loss events could be identified by sudden and marked changes in female movement patterns. Using GPS radio-telemetry data from female woodland caribou (Rangifer tarandus caribou), we developed and tested two novel movement-based methods for inferring parturition and neonate survival. The first method estimated movement thresholds indicative of parturition and neonate loss from population-level data then applied these thresholds in a moving-window analysis on individual time-series data. The second method used an individual-based approach that discriminated among three a priori models representing the movement patterns of non-parturient females, females with surviving offspring, and females losing offspring. The models assumed that step lengths (the distance between successive GPS locations) were exponentially distributed and that abrupt changes in the scale parameter of the exponential distribution were indicative of parturition and offspring loss. Both methods predicted parturition with near certainty (>97% accuracy) and produced appropriate predictions of parturition dates. Prediction of neonate survival was affected by data quality for both methods; however, when using high quality data (i.e., with few missing GPS locations), the individual-based method performed better, predicting neonate survival status with an accuracy rate of 87%. Understanding ungulate population dynamics often requires estimates of parturition and neonate survival rates. With GPS radio-collars increasingly being used in research and management of ungulates, our movement-based methods represent a viable approach for estimating rates of both parameters.
机译:对动物运动数据的分析主要集中在了解空间利用的模式和驱动它们的行为过程。在这里,我们分析了动物运动数据以推断出个体适应性的组成部分,特别是分娩和新生儿存活率。我们预测分娩和新生儿丢失事件可以通过女性运动模式的突然而明显的变化来识别。利用来自雌性林地驯鹿(Rangifer tarandus驯鹿)的GPS无线电遥测数据,我们开发并测试了两种基于运动的新颖方法来推断分娩和新生儿存活率。第一种方法是从人口水平数据中估计指示分娩和新生儿流产的运动阈值,然后将这些阈值应用于单个时间序列数据的移动窗口分析中。第二种方法使用基于个体的方法,该方法在三个先验模型之间进行了区分,这些模型分别代表未分娩的雌性,存活后代的雌性和失去后代的雌性的运动模式。这些模型假设步长(连续GPS位置之间的距离)呈指数分布,并且指数分布的比例参数的突然变化指示分娩和后代损失。两种方法都可以几乎确定地预测分娩(准确率> 97%),并且可以对分娩日期进行适当的预测。两种方法的数据质量都会影响新生儿存活率的预测。但是,当使用高质量数据(即缺少少量GPS位置)时,基于个体的方法效果更好,预测新生儿生存状态的准确率为87%。了解有蹄类动物的种群动态通常需要估计分娩和新生儿存活率。随着GPS无线电项圈越来越多地用于有蹄类动物的研究和管理中,我们基于运动的方法代表了一种可行的方法来估算两个参数的比率。

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