Stress responsiveness in a wild primate predicts survival across an extreme El Niño drought

We know more about the costs of chronic stress than the benefits of the acute stress response – an adaptive response that buffers organisms from life-threatening challenges. Yet, no primate study has empirically identified how the stress response adaptively impacts evolutionary fitness. Here, we take advantage of a natural experiment – an El Niño drought – that produced unprecedented mortality for wild white-faced capuchins. Using a reaction norm approach, we provide evidence from primates that a more robust stress response to a stressor, measured using fecal glucocorticoids, predicts a greater likelihood of survival. We show that individuals with greater stress responsiveness to previous droughts later had higher survival across a severe El Niño drought. Evolutionary models need empirical data on how stress responsivity varies in adaptive ways. While we cannot buffer subjects from catastrophic events, we can use them to understand which aspects of the stress response help animals to “w..., These are observational data: Demographic data and noninvasively obtained fecal samples were collected from a wild population of white-faced capuchin monkeys that are subjects of a long-term study at Lomas Barbudal Biological Reserve, Costa Rica. The rawest form of the demographic data and information about fecal samples are housed in a MySQL database at UCLA, which was queried to produce the data used in this study. Fecal samples were dried in the Lomas Barbudal Monkey Project field lab, and then extracted and assayed in a University of Michigan-Ann Arbor core facility lab., We used the following R packages: brms (versions 2.20.4 and 2.21.0) sjPlot (version 2.8.14) standaRdized (version 1.0) tidyverse (version 2.0.0) , # Data from: Stress responsiveness in a wild primate predicts survival across an extreme El Niño drought Included here are all data and code necessary to replicate findings from “Stress responsiveness in a wild primate predicts survival across an extreme El Niño drought”. Demographic and fecal sample information came from the Lomas Barbudal Monkey Project database. #### Description of the data and file structure THE FOLLOWING DATASETS ARE PROVIDED AS .CSV FILES: Date formats should be yyyy-mm-dd “data_droughtIndices.csv” - drought indices used in main analyses Indices: std_don_pverde, std_don_chelsa, SPI_Don_PVERDE, SPI_Don_CHELSA std_don_pverde: drought index based on Palo Verde estimates (unitless) std_don_chelsa: alternative drought index based on CHELSA estimates (unitless) SPI_Don_PVERDE: alternative drought index based on Palo Verde estimates, using SPI (unitless) SPI_Don_CHELSA: alternative drought index based on CHELSA estimates, using SPI (unitless) “data_glucocorticoids...相较于慢性应激的代价，我们对急性应激反应的益处了解得更为深入——急性应激反应是一种帮助机体抵御致命威胁的适应性应答。然而，目前尚无灵长类动物研究通过实证明确应激反应如何以适应性方式影响进化适合度（evolutionary fitness）。本研究借助自然实验——厄尔尼诺干旱（El Niño drought）——展开研究，该事件曾导致野生白面卷尾猴出现前所未有的死亡率。本研究采用反应规范（reaction norm）分析方法，首次在灵长类动物中提供实证证据：通过粪便糖皮质激素（fecal glucocorticoids）测定的个体对应激源的应激反应越强，其存活概率越高。研究发现，对以往干旱具有更强应激应答能力的个体，在此次极端厄尔尼诺干旱事件中拥有更高的存活率。进化模型亟需关于应激应答能力如何以适应性方式变化的实证数据。尽管我们无法让研究对象免受灾难性事件的影响，但我们可以借助此类事件解析应激反应的哪些特征能够帮助动物…… 本研究使用的观测数据如下：研究样本为哥斯达黎加洛马斯巴尔布达尔生物保护区（Lomas Barbudal Biological Reserve）长期监测的野生白面卷尾猴种群，研究人员收集了该种群的种群统计数据与非侵入式采集的粪便样本。最原始的种群统计数据与粪便样本相关信息存储于加州大学洛杉矶分校（University of California, Los Angeles, UCLA）的MySQL数据库中，本研究使用的数据即通过对该数据库进行查询获取。粪便样本先在洛马斯巴尔布达尔猴类研究项目的野外实验室进行干燥处理，随后在密歇根大学安娜堡分校（University of Michigan-Ann Arbor）的核心设施实验室完成提取与检测。 本研究使用了以下R软件包（R packages）： - brms（版本2.20.4与2.21.0） - sjPlot（版本2.8.14） - standaRdized（版本1.0） - tidyverse（版本2.0.0） # 数据集来源：《野生灵长类动物的应激应答能力可预测极端厄尔尼诺干旱事件中的存活率》 本数据集包含复现上述论文研究结果所需的全部数据与代码。 种群统计数据与粪便样本信息均源自洛马斯巴尔布达尔猴类研究项目数据库。 #### 数据与文件结构说明 以下数据集均以.CSV格式提供： 日期格式需为yyyy-mm-dd "data_droughtIndices.csv"——主分析中使用的干旱指数数据集 包含的指数如下：std_don_pverde、std_don_chelsa、SPI_Don_PVERDE、SPI_Don_CHELSA std_don_pverde：基于Palo Verde估算结果构建的干旱指数（无单位） std_don_chelsa：基于CHELSA估算结果构建的备选干旱指数（无单位） SPI_Don_PVERDE：基于Palo Verde估算结果、采用标准化降水指数（SPI）构建的备选干旱指数（无单位） SPI_Don_CHELSA：基于CHELSA估算结果、采用标准化降水指数（SPI）构建的备选干旱指数（无单位） "data_glucocorticoids……"