Dataset for Pangolin studies (paper title: Sunda pangolins show inconsistent responses to disturbances across multiple scales)

Datasets: “Manis_javanica_records_maxent_20210516” contains occurrence data of banded civets from published studies, GBIF, and new camera trapping. “GLMM_SundaPangolin_Data_by_Survey.xlsx” contains camera trapping data from both published studies and new camera trapping. We used it for a GLMM regional-scale analysis. Each row represents a full survey with the number of individual captures across all camera traps of the survey. This dataset includes both data on common palm civets and banded civets. “RN_SundaPangolin_Records_1km_Cells.csv” contains camera trapping data from new surveys and each row represents an individual capture. This dataset includes data on both common palm civets and banded civets. “RN_ECL_Covariates_1km_Cells_20210322.csv” contains the data for covariates at each sampling location (usually 1 camera trap but averaged if more than 1) for the new surveys. We used both of these datasets for a Royle-Nichols local-scale analysis. Data collection: Data was collected both through a literature review and with new camera trapping surveys. Data-specific information: “Manis_javanica_records_maxent_20210516.csv” Species = Species of organism of occurrence data Latitude = Latitude coordinate of occurrence data Longitude = Longitude coordinate of occurrence data “GLMM_SundaPangolin_Data_by_Survey.xlsx” X.1 = Typo column (ignore) X = Typo column (ignore) TAG = Survey identification Species = Species of organisms captured with camera traps records = Number of individual capture in the survey site2 = site name year_start = Year when survey started Landscape = Landscape where survey was located survey_ids_included = IDs of surveys in the individual study region = Region where camera is located country = country where camera is located Protected_area = is the camera in a protected area? (y/n) effort = number of trap nights in survey Y_lat = latitude coordinate of sampling unit X_long = longitude coordinate of sampling unit size_km2 = size of forest where survey is located (km2) n_points = Typo column (ignore) n_cameras = number of camera traps in survey cam_spacing = Spacing between cameras (m) indent_cap_mins = minimum number of minutes before new capture is considered independent AnnualPrecipitation = AnnualPrecipitation at location of survey (mm) “covariate”10K = each column describes data on a covariate measures in a 10 km radius around the center of the survey “covariate”20K = each column describes data on a covariate measures in a 20 km radius around the center of the survey “covariate”30K = each column describes data on a covariate measures in a 30 km radius around the center of the survey forest_type = forest type at location of survey year_end = year when survey ended “RN_SundaPangolin_Records_1km_Cells.csv” cell_survey = ID of sampling unite (Cell ID + survey ID) Polygon1km = ID of polygon (Cell ID) active_cams_at_date = cameras in the same cell_survey id that were active on that day x_centroid = Average latitude coordinate of cameras in the cell y_centroid = Average longitude coordinate of cameras in the cell Date = date of capture species = species captured independent_events = Number of independent captures in the cell on the day total_indiv_records = Number of individuals on the day trap_nights_at_date = Trapping effort per day per cell Sampling_begin = minimum start date of cameras included in the cell_survey Sampling end = maximum end date of cameras included in the cell_survey survey_id = ID of survey where the capture was detected “RN_ECL_Covariates_1km_Cells_20210322.csv” cell_survey = ID of sampling unit (camera trap(s)) Cell_effort = number of trap nights at sampling unit elevation = elevation at location of the sampling unit’s location (m) dist_to_edge = distance from sampling unit to edge (m) human_pop_density_1km = Number of human individuals in 1km2 around sampling unit’s location dist_to_river = distance from sampling unit to river (m) forest_integrity = Forest Integrity Index at the sampling unit’s location human_footprint = Human Footprint Index at the sampling unit’s location forest_cover_1km = Forest cover in 1 km radius of sampling unit’s location (%) forest_cover_2km = Forest cover in 2 km radius of sampling unit’s location (%) degraded_forest_1km = Combined land cover of oil palm, lowland mosaics, lowland open ground and regrowth/plantation in 1 km radius of sampling unit’s location (%) degraded_forest_2km = Combined land cover of oil palm, lowland mosaics, lowland open ground and regrowth/plantation in 2 km radius of sampling unit’s location (%) oil_palm_1km = Oil palm in 1 km radius of sampling unit’s location (%) oil_palm_2km = Oil palm in 2 km radius of sampling unit’s location (%) forest_loss_1km = Forest loss in 1 km radius of sampling unit’s location (%) forest_loss_2km = Forest loss in 2 km radius of sampling unit’s location (%) survey_id = ID of the survey of which the sampling unit is a part of shrink_id = ID of the survey of which the sampling unit is a part of

数据集“Manis_javanica_records_maxent_20210516”收录了来自已发表研究、全球生物多样性信息设施（Global Biodiversity Information Facility，GBIF）以及新增红外相机监测的斑灵猫（banded civet）分布记录数据。
数据集“GLMM_SundaPangolin_Data_by_Survey.xlsx”包含来自已发表研究与新增红外相机监测的红外相机捕获数据，本研究使用该数据集开展广义线性混合模型（Generalized Linear Mixed Model, GLMM）区域尺度分析。该数据集每行代表一次完整调查，记录了该调查所有红外相机站点的个体捕获总数量，涵盖普通棕榈狸（common palm civet）与斑灵猫两类物种的相关数据。
数据集“RN_SundaPangolin_Records_1km_Cells.csv”收录了新增调查的红外相机捕获数据，每行对应一次个体捕获事件，涵盖普通棕榈狸与斑灵猫两类物种的相关数据。
数据集“RN_ECL_Covariates_1km_Cells_20210322.csv”收录了新增调查各采样点位的协变量数据（通常单点位仅部署1台红外相机，若存在多台则取均值），本研究使用上述两份数据集开展罗伊尔-尼科尔斯（Royle-Nichols, RN）局域尺度分析。

数据采集：本研究的数据通过文献综述与新增红外相机监测调查两种途径获取。

各数据集字段详细说明：
### 数据集“Manis_javanica_records_maxent_20210516.csv”
- Species：对应物种类别
- Latitude：物种出现点位的纬度坐标
- Longitude：物种出现点位的经度坐标

### 数据集“GLMM_SundaPangolin_Data_by_Survey.xlsx”
- X.1：列名存在笔误，建议忽略
- X：列名存在笔误，建议忽略
- TAG：调查唯一标识编号
- Species：红外相机捕获的物种类别
- records：对应调查站点的个体捕获总数
- site2：调查站点名称
- year_start：调查起始年份
- Landscape：调查所在的景观类型
- survey_ids_included：单个研究区域内纳入的调查编号列表
- region：红外相机部署所在的行政区域
- country：红外相机部署所在国家
- Protected_area：红外相机是否位于保护地内（是/否）
- effort：调查总诱捕夜数
- Y_lat：采样单元的纬度坐标
- X_long：采样单元的经度坐标
- size_km2：调查区域内森林面积（单位：平方千米）
- n_points：列名存在笔误，建议忽略
- n_cameras：调查部署的红外相机总数量
- cam_spacing：相机间布设间距（单位：米）
- indent_cap_mins：判定新捕获事件为独立事件所需的最小间隔时长（单位：分钟）
- AnnualPrecipitation：调查点位的年降水量（单位：毫米）
- "covariate"10K：各列分别代表调查中心点周围10千米半径范围内的协变量数据
- "covariate"20K：各列分别代表调查中心点周围20千米半径范围内的协变量数据
- "covariate"30K：各列分别代表调查中心点周围30千米半径范围内的协变量数据
- forest_type：调查点位的森林类型
- year_end：调查结束年份

### 数据集“RN_SundaPangolin_Records_1km_Cells.csv”
- cell_survey：采样单元唯一标识（单元格ID+调查ID）
- Polygon1km：1平方千米网格多边形ID
- active_cams_at_date：当日同一cell_survey标识下处于激活状态的红外相机数量
- x_centroid：单元格内所有相机的平均纬度坐标
- y_centroid：单元格内所有相机的平均经度坐标
- Date：捕获事件发生日期
- species：被捕获的物种类别
- independent_events：当日单元格内的独立捕获事件总数
- total_indiv_records：当日捕获的个体总数量
- trap_nights_at_date：当日单元格的单日诱捕夜数
- Sampling_begin：纳入该cell_survey的所有相机的最早启动日期
- Sampling end：纳入该cell_survey的所有相机的最晚停止日期
- survey_id：检测到捕获事件的调查编号

### 数据集“RN_ECL_Covariates_1km_Cells_20210322.csv”
- cell_survey：采样单元（红外相机组）的唯一标识编号
- Cell_effort：采样单元的总诱捕夜数
- elevation：采样点位的海拔高度（单位：米）
- dist_to_edge：采样点位至生境边界的距离（单位：米）
- human_pop_density_1km：采样点位周围1平方千米范围内的人口数量
- dist_to_river：采样点位至最近河流的距离（单位：米）
- forest_integrity：采样点位的森林完整性指数
- human_footprint：采样点位的人类足迹指数
- forest_cover_1km：采样点位周围1千米半径范围内的森林覆盖率（百分比）
- forest_cover_2km：采样点位周围2千米半径范围内的森林覆盖率（百分比）
- degraded_forest_1km：采样点位周围1千米半径范围内油棕、低地镶嵌景观、低地开阔地以及次生林/人工林的综合土地覆盖占比（百分比）
- degraded_forest_2km：采样点位周围2千米半径范围内油棕、低地镶嵌景观、低地开阔地以及次生林/人工林的综合土地覆盖占比（百分比）
- oil_palm_1km：采样点位周围1千米半径范围内的油棕种植园占比（百分比）
- oil_palm_2km：采样点位周围2千米半径范围内的油棕种植园占比（百分比）
- forest_loss_1km：采样点位周围1千米半径范围内的森林损失率（百分比）
- forest_loss_2km：采样点位周围2千米半径范围内的森林损失率（百分比）
- survey_id：该采样单元所属的调查编号
- shrink_id：该采样单元所属的调查编号