Data used to estimate animal abundance from Cunningham et al (2020) Ecology Letters

This data accompanies our 2020 publication in Ecology Letters titled, "A native apex predator limits an invasive mesopredator and protects native prey: Tasmanian devils protecting bandicoots from cats." If you use these datasets, please cite the paper as well as this dataset. Please see the paper for a detailed description of the data and analysis. Estimating abundance of feral cats The four files beginning with "cats" are used together to estimate the abudance of feral cats at 28 study sites. "cats_capture history.csv" is the capture history of each uniquely identifiable cat at each study site. "cats_marked unidentified.csv" shows the number of detections at each study site of cats with pellage markings that we could not confidently assign to an individual. This usually occurred due to a poor or partial photo. "cats_unmarked black cats.csv" shows the number of detections of unmarked cats at each study site. This was usually the case for cats that were completely black in colour. "cats_site covariates.csv" shows site level covariates used in the mark-resight analysis. Estimating abundance of other species We estimated the abundance of the other species using either the Royle-Nichols model or the N-mixture model. In each case, we recorded species detections for each camera in five temporal periods. These detection histories are shown in the csv files that begin with the common name of a species. We did this for seven species. The file titled "siteCovariates_nMixture_RoyleNichols.csv" is the site-level covariates used for these models. We used two time-varying covariates, one for lure age and one for date: "lureAge.csv" and "dateCovariate.csv"

本数据集配套我们2020年发表于《生态学通讯（Ecology Letters）》的论文《本土顶级捕食者限制入侵中型捕食者并保护本土猎物：袋獾保护袋狸免受猫科动物侵扰》（原英文标题："A native apex predator limits an invasive mesopredator and protects native prey: Tasmanian devils protecting bandicoots from cats."）。若您使用本数据集，请同时引用该研究论文与本数据集。如需了解数据与分析的详细说明，请参阅原论文。

一、流浪猫种群丰度估算
以"cats"为前缀的四个文件可联合用于估算28个研究样地的流浪猫种群丰度。其中，`cats_capture_history.csv`为各研究样地中每只可唯一识别的流浪猫的捕获历史记录；`cats_marked_unidentified.csv`记录了带有皮毛斑纹但无法准确识别个体的猫在各研究样地的检测次数，此类情况通常源于照片质量不佳或仅拍摄到局部；`cats_unmarked_black_cats.csv`记录了纯黑色无斑纹猫在各研究样地的检测次数；`cats_site_covariates.csv`则包含标记重捕分析所用的样地级协变量。

二、其他物种种群丰度估算
我们采用罗伊尔-尼科尔斯模型（Royle-Nichols model）或混合种群模型（N-mixture model）估算其余物种的种群丰度。本次研究将每个相机的检测时段划分为5个时间周期，并记录各物种的检测情况，相关检测历史文件均以对应物种的通用名称为前缀，共覆盖7个物种。`siteCovariates_nMixture_RoyleNichols.csv`为上述模型所用的样地级协变量文件。我们还使用了两个时变协变量：`lureAge.csv`（诱饵使用时长协变量）与`dateCovariate.csv`（日期协变量）。