Camera-trap data for fitting the random encounter model to estimate densities of coyotes and black-tailed jackrabbits in the Mojave Desert

These data are comprised of input files formatted for fitting the random encounter model to estimate seasonal densities of coyotes (Canis latrans) and black-tailed jackrabbits (Lepus californicus) in the Mojave Desert, USA. Data were collected from 40 camera-traps that were randomly placed with respect to coyote and/or jackrabbit sign (e.g., tracks, scat, direct observations) and 43 camera-traps that were strategically placed where coyote and/or jackrabbit sign existed. Data were collected within and adjacent to the Boulder City Conservation Easment, Nevada, USA, during 2019-2021. Data were collected as part of a predator-prey ecology study for which one component was to estimate seasonal densities of coyotes and black-tailed jackrabbits through time., Data were collected from 40 camera-traps that were randomly placed with respect to coyote and/or jackrabbit sign (e.g., tracks, scat, direct observations) and 43 camera-traps that were strategically placed where coyote and/or jackrabbit sign existed. Data were collected within and adjacent to the Boulder City Conservation Easment, Nevada, USA. Data files are formatted for fitting the random encounter model, and are organized by season (wet vs. dry), year (2019, 2020, 2021), and species (coyote vs. jackrabbit)., , # Camera-trap data for fitting the random encounter model to estimate densities of coyotes and black-tailed jackrabbits in the Mojave Desert

[https://doi.org/10.5061/dryad.djh9w0w6v](https://doi.org/10.5061/dryad.djh9w0w6v)

Camera-trap detection data (**REM_Camera_Data_2019-2021.csv**) comprised of coyote and black-tailed jackrabbit detections, camera detection parameters, and camera operation times formatted for fitting the random encounter model to estimate densities.

## Description of the data and file structure

Data are formatted specifically for fitting the random encounter model using the remBoot package in R ([GitHub - arcaravaggi/remBoot: R package for Random Encounter Modelling](https://github.com/arcaravaggi/remBoot)). Descriptions of variables are provided below:

Camera - Categorical identifier for each camera-trap site. Randomly deployed cameras have A through J prefixes. Strategically deployed cameras have WC prefixes.

Site - Categorical identifier for each species x ...

本数据集包含为适配随机相遇模型（random encounter model）以估算美国莫哈韦沙漠郊狼（Canis latrans）和黑尾长耳大野兔（Lepus californicus）季节种群密度而格式化的输入文件，数据集文件按季节（干湿季）、年份（2019、2020、2021）及物种（郊狼与黑尾长耳大野兔）进行分类组织。
数据采集于2019-2021年间，采集区域涵盖美国内华达州博尔德城保护地役权区域及其周边地带。本次研究共布设83台红外相机（camera-trap）：其中40台依据郊狼和/或黑尾长耳大野兔的痕迹（如足迹、粪便、直接观测记录）随机布设，剩余43台则针对性布设在存在上述物种活动痕迹的区域。本数据为一项捕食者-猎物生态学研究的组成部分，该研究的核心目标之一便是按时间序列估算郊狼与黑尾长耳大野兔的季节种群密度。

# 适配随机相遇模型以估算莫哈韦沙漠郊狼和黑尾长耳大野兔种群密度的红外相机数据
DOI: 10.5061/dryad.djh9w0w6v
红外相机探测数据文件（**REM_Camera_Data_2019-2021.csv**）包含郊狼与黑尾长耳大野兔的探测记录、相机探测参数及相机运行时长，格式适配随机相遇模型的种群密度估算需求。

## 数据与文件结构说明
本数据集专为适配R语言remBoot包的随机相遇模型而格式化（[GitHub - arcaravaggi/remBoot: 随机相遇建模专用R包](https://github.com/arcaravaggi/remBoot)）。变量说明如下：
Camera：各红外相机点位的分类标识符。随机布设的相机编号前缀为A至J，针对性布设的相机编号前缀为WC。
Site：各物种×...的分类标识符