遇见数据集

Seasonal variation in the activity patterns of wild mammals and their interactions with vegetation cover and anthropogenic activities in a montane forest of the central highlands of Madagascar

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Zenodo2026-06-30 更新2026-08-13 收录
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This dataset contains camera trap occurrence records and associated environmental covariates for mammal communities in Madagascar. Data were collected over a full continuous year, from May 1, 2019, to April 30, 2020, covering both the dry season (May–October) and the rainy season (November–April). The study involved 45 camera trap stations deployed across various habitat types, totaling 7,591 trap days of sampling effort. The dataset captures a total of 4,928 independent camera trap events representing 19 distinct mammal species across 9 families (including Tenrecidae , Eupleridae , Lemuridae , and Indriidae ). Along with the recording records, the dataset provides detailed landscape and environmental covariates for each camera station—such as elevation and distance to various anthropogenic and natural features (e.g., dense forests, degraded forests, crops, and rivers)—to facilitate ecological and spatial modeling. 1.camera_trap_records.csv Contains the raw, independent camera trap detection events for the study period. record_id: Unique identifier for each camera trap event. sstation:Camera station ID (corresponds to station_covariates.csv). species_code: Unique alphanumeric code for the species (corresponds to species_list.csv). scientific_name: Scientific name of the recorded species. season: Season of the recording ( Dry or Rainy ). date : Date of the detection (YYYY-MM-DD). time/datetime: Local time and full timestamp of the detection. time_decimal / time_radians: Time of detection converted to decimal hours and radians (useful for circular density and activity pattern analysis). activity_period: General activity classification at the time of detection (eg, Nocturnal , Diurnal , Dusk ). independent: Boolean indicating if the record is considered an independent event. 2.species_list.csv A taxonomic summary and observational frequency overview for all 19 recorded species. species_code: Unique alphanumeric code for the species. scientific_name / common_en / common_mg: The scientific, English, and local Malagasy names (eg, Tandraka , Vontsira mena ). Order/family: Taxonomic classification. activity_pattern: Primary activity pattern of the species. IUCN: Current IUCN Red List conservation status. dry_records / rainy_records : Total number of independent detection events per season. dry_stations / rainy_stations: Number of unique stations where the species was detected, separated by season. ecuador_analog: Ecological analog species found in Ecuador (included for cross-continental comparative studies). 3.station_covariates.csv Geographical and environmental covariate data for each of the 45 camera trap stations. station: Camera station ID. x_utm / y_utm / longitude / latitude: Geographic coordinates of the station (approximate location: 18.2°S, 47.2°E). elevation_m : Elevation in meters above sea level. Distance Covariates (m): 11 specific variables measuring the distance from the station to various landscape features (e.g.). 4.covariate_dictionary.csv A data dictionary explaining the environmental variables found in the station_covariates.csvfile. Code: Covariate ID code. variable: The exact column name as it appears in the station dataset (eg, Dis_for_dense ). type: The category of the variable (eg, Habitat ). description: Detailed explanation of the covariate and its unit of measurement (meters). ecuador_equivalent: Equivalent habitat classification for comparative neotropical analyses. 5.sampling_effort.csv A high-level summary of the camera trapping effort across seasons. season: Broad season category (dry, rainy, total). season_local : Localized name and precise months for the given season. trap_days : Total number of operational trap days during that period. n_stations: Number of active camera stations. n_species_recorded: Total number of unique species detected during the period.

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Zenodo
创建时间:
2026-06-30
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