Data and scripts underlying the publication: Unveiling the roles of temporal periodicity, the spatial environment and behavioural modes in terrestrial animal movement

Data and scripts underlying the publication: Unveiling the roles of temporal periodicity, the spatial environment and behavioural modes in terrestrial animal movement.<br>The RData file Linssen_2024_JMovEcol_data contains everything needed to be able to run the code for the analysis:- Data tables with location data (timestamp, x, y...), one for each species. These data have been pre-processed, cleaned and annotated with environmental covariates as described in the manuscript.- A custom function collectmuHMMoutput(), which is used to collect all the relevant components of a HMM fit (the model itself, starting parameters, Viterbi decoding et cetera) into one list object.- A custom function mutatePar0(), which takes starting parameters for a model and creates four sets of perturbations of those starting values (as described in the manuscript under Model fitting).<br>The R file Linssen_2024_JMovEcol_script contains the code needed to run the analysis. The code can be ran from top to bottom to run the analysis for eland; for wildebeest and zebra the "species" parameter in line 13 should be set to either of these.

本数据集与配套脚本支撑发表论文《揭示陆生动物运动中时间周期性、空间环境与行为模式的作用》（Unveiling the roles of temporal periodicity, the spatial environment and behavioural modes in terrestrial animal movement）。

名为`Linssen_2024_JMovEcol_data`的RData文件包含运行分析代码所需的全部内容：
- 按物种划分的位置数据表（包含时间戳、x坐标、y坐标等字段），每个物种对应一张数据表。所有数据均已按照论文手稿中的描述完成预处理、清洗，并标注了环境协变量。
- 自定义函数`collectmuHMMoutput()`：用于将隐马尔可夫模型（Hidden Markov Model，HMM）拟合结果的所有相关组件（模型本体、初始参数、维特比解码（Viterbi decoding）等）整合为单个列表对象。
- 自定义函数`mutatePar0()`：接收模型的初始参数，并按照论文手稿“模型拟合”章节中的描述，生成四组该初始参数的扰动值集合。

名为`Linssen_2024_JMovEcol_script`的R脚本文件包含运行分析所需的全部代码。该代码可按从上至下的顺序直接运行，以完成大羚羊（eland）的运动分析；若需对牛羚（wildebeest）或斑马（zebra）进行分析，只需将第13行的"species"参数设置为对应物种即可。