Data for the article <b>Multisite integrated population model reveals contrasting vital rates contributions on population dynamics of a highly mobile species</b>

The data presented in this repository include the following datasets used in the article <i>Multisite Integrated Population Model Reveals Contrasting Vital Rate Contributions on Population Dynamics of a Highly Mobile Species, </i>were we studied three neighbouring populations (Catalonia -CAT-, Aragon -ARA- and Valencian Community -VAL-) of the Eurasian griffon vulture (<i>Gyps fulvus</i>) in the northeastern Iberian Peninsula and assessed site-specific population dynamics over 14 years, while accounting for dispersal across these populations using a Bayesian multisite integrated population model. Below is a detailed description of each file:<br><b>"Productivity and count data.xlsx"</b>: An Excel file containing data on reproductive pair counts and productivity (number of fledglings per monitored pair) across the three studied regions.<b>"CH.csv"</b>: Capture-recapture history data used for the multi-state model.<b>"msmodel.txt"</b> and <b>"msIPMscript.txt"</b>: These files contain the code for the Bayesian multi-state model and the multisite Integrated Population Model, respectively, written in JAGS language using the <code>jagsui</code> package.For further details on the methods and modeling, please refer to the original article and supplementary material.本仓库所提供的数据，均来自论文《多站点整合种群模型揭示高度移动物种种群动态的生存贡献差异》（Multisite Integrated Population Model Reveals Contrasting Vital Rate Contributions on Population Dynamics of a Highly Mobile Species）中的相关数据集。本研究以伊比利亚半岛东北部的欧亚秃鹫（*Gyps fulvus*）为对象，选取其相邻的三个种群——加泰罗尼亚（Catalonia -CAT-）、阿拉贡（Aragon -ARA-）与巴伦西亚自治区（Valencian Community -VAL-），开展了为期14年的位点特异性种群动态评估，并通过贝叶斯多站点整合种群模型量化了种群间的扩散过程。以下为各文件的详细说明： <b>"生产力与计数数据.xlsx"</b>：该Excel文件涵盖三个研究区域的繁殖对数量与繁殖生产力（每监测繁殖对的出飞幼鸟数）相关数据。 <b>"CH.csv"</b>：用于多状态模型的捕获-重捕历史数据（Capture-recapture history data）。 <b>"msmodel.txt"</b>与<b>"msIPMscript.txt"</b>：这两个文件分别包含贝叶斯多状态模型与多站点整合种群模型的代码，采用JAGS语言编写，并使用了<code>jagsui</code>包。 若需了解方法与建模的更多细节，请参阅原论文及其补充材料。