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

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DataCite Commons2023-04-06 更新2024-08-18 收录
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https://figshare.com/articles/dataset/Dataset_for_Pangolin_studies_paper_title_Sunda_pangolins_show_inconsistent_responses_to_disturbances_across_multiple_scales_/22566721
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<strong>Datasets:</strong> “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. <strong>Data collection:</strong> Data was collected both through a literature review and with new camera trapping surveys. <strong>Data-specific information:</strong> “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
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figshare
创建时间:
2023-04-06
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