1. Lamperty_etal_SGrewildingMSdata_CTmetadata.csv 2. Lamperty_etal_SGrewildingMSdata_CTcaptures.csv
**Lamperty et al 2023 *Conservation Science and Practice***
Lamperty_etal_SGrewildingMSdata_CTmetadata.csv
Data header followed by description.
cell500m_id_year -> a unique identifier for each 500m hexagonal 'cell'. Year is appended to the cell identifier to keep years from being recounted as the same sampling unit (we consider years a new sampling unit because our populations were not closed nor were all locations sampled for consecutive years).
surveys_included -> The surveys (researchers or research organizations) that had camera traps deployed in the sample unit (the hexagonal cell designated by the preceding column) at given time.
camera_id -> unique identifier for each camera that was set in a given cell during that year. Individual camera trap identifiers are separated by '-' here.
region -> the green space (generally speaking, a park or preserve) within Singapore where the camera traps were set.
year -> the year during which the sampling occurred.
cell_effort -> the sum of sampling days in a given cell during that year, pooled across all camera traps deployed in that year in that cell.
x_centroid and y-centroid -> coordinates of the center of the hexagonal cell (all cameras in a cell from all concurrent surveys were aggregated into a single spatial sampling unit to avoid pseudoreplication resulting from considering each camera trap as an independent sampling unit).
forest_500m -> the percentage of the surrounding area within a 500m radius of the center of the cell that was under forest cover.
edge_dist -> the distance in meters to the nearest forest edge from the center of the cell.
road_dist -> the distance in meters to the nearest road from the center of the cell.
urban_dist -> the distance in meters to the nearest urban area from the center of the cell.
region_year -> a unique region_year term used in our models to keep from counting different years as continuous sampling in the same region; given that our data was a concatenation of many camera trap surveys deployed in different spatial arrays over varying time scales, we would be violating the n-mixture occupancy model assumptions without this term.
Lamperty_etal_SGrewildingMSdata_CTcaptures.csv
Data header followed by description.
cell500m_id_year -> a unique identifier for each 500m hexagonal 'cell'. Year is appended to the cell identifier to keep years from being recounted as the same sampling unit (we consider years a new sampling unit because our populations were not closed nor were all locations sampled for consecutive years).
surveys_included -> The surveys (researchers or research organizations) that had camera traps deployed in the sample unit (the hexagonal cell designated by the preceding column) at given time.
camera_id -> unique identifier for each camera that was set in a given cell during that year. Individual camera trap identifiers are separated by '-' here.
x_centroid and y-centroid -> coordinates of the center of the hexagonal cell (all cameras in a cell from all concurrent surveys were aggregated into a single spatial sampling unit to avoid pseudoreplication resulting from considering each camera trap as an independent sampling unit).
date -> the date of camera trap record. Note that data was previously cleaned to only count records > 30 min apart of the same species as independent events.
species -> this indicates which of our two focal species (Sus scrofa, the wild pigs, or Rusa unicolor, the sambar deer) the record corresponds to (all other species captured by camera trap surveys have been omitted).
independent_events -> the number of indpendent (> 30 min apart) captures that occurred that date at the camera for that species.
total_indiv_records -> the total number of individuals recorded on that date at that camera of that species.
year -> the year that capture occurred.
region -> the green space (generally speaking, a park or preserve) within Singapore where the camera traps were set.
region_year -> a unique region_year term used in our models to keep from counting different years as continuous sampling in the same region; given that our data was a concatenation of many camera trap surveys deployed in different spatial arrays over varying time scales, we would be violating the n-mixture occupancy model assumptions without this term.