This Occupancy data of lynx, wildcat, and wolf readme.txt file was generated on 2022-04-25 by Marissa A. Dyck Code for this analysis is available via GitHub at: https://github.com/marissadyck/Multi_occ_LWW GENERAL INFORMATION 1. Title of Dataset: Data for: Dracula’s ménagerie: A multispecies occupancy analysis of lynx, wildcat, and wolf in the Romanian Carpathians 2. Author Information A. Principal Investigator Contact Information Name: Marissa A. Dyck Institution: Ohio University Address: Athens, OH USA Email: marissadyck17@gmail.com B. Associate or Co-investigator Contact Information Name: Viorel D. Popescu Institution: Ohio University Address: Athens, OH USA Email: popescu@ohio.edu 3. Date of data collection: between 2018 and 2020 4. Geographic location of data collection: Southern Carpathians, Romania 5. Information about funding sources that supported the collection of the data: Field work was funded by the OAK Foundation grant number OCAY-11-136 and by the European Commission through the Operational Programme 'Environment', grant number SMIS 102086. VDP was partially supported by a grant from the Romanian National Authority for Scientific Research (PN-III-P1-1.1-TE-2019-0835). Travel for MAD to Romania was provided by the Ohio University College of Arts and Sciences. SHARING/ACCESS INFORMATION 1. Licenses/restrictions placed on the data: No 2. Links to publications that cite or use the data: https://doi.org/10.22541/au.164441279.98362695/v1 3. Links to other publicly accessible locations of the data: No 4. Links/relationships to ancillary data sets: No 5. Was data derived from another source? No A. If yes, list source(s): 6. Recommended citation for this dataset: Dyck, Marissa et al. (2022) Dracula’s menagerie: A multispecies occupancy analysis of lynx, wildcat, and wolf in the Romanian Carpathians. Ecology and Evolution DATA & FILE OVERVIEW 1. File List: species_matrix contains presence/absence data for all 3 species. cams_data contains landcover and environmental data associated with the location of each camera trap. Trap_effort contains data for camera trap activity in each session. If one camera was working every day of a session the value will = 14; any days where both cameras were inactive subtracts 1 from this value. 'Winter' files contain data from 2018/12/17 to 2019/3/31 and 'autumn' contain data from 2019/10/9 to 2020/1/15. 2. Relationship between files, if important: 3. Additional related data collected that was not included in the current data package: 4. Are there multiple versions of the dataset? no A. If yes, name of file(s) that was updated: i. Why was the file updated? ii. When was the file updated? METHODOLOGICAL INFORMATION 1. Description of methods used for collection/generation of data: Methodological details are provided in the paper 2. Methods for processing the data: WE used multi species occupancy models to process the data. Full details can be found in the paper 3. Instrument- or software-specific information needed to interpret the data: We used program R version 3.5.1 with package unmarked 4. Standards and calibration information, if appropriate: 5. Environmental/experimental conditions: 6. Describe any quality-assurance procedures performed on the data: 7. People involved with sample collection, processing, analysis and/or submission: The data was collected by an experienced team of wildlife rangers from Foundation Conservation Carapthia (FCC;https://www.carpathia.org/) with the help of volunteers. DATA-SPECIFIC INFORMATION FOR: [cams_data_autumn] 1. Number of variables: 26 2. Number of cases/rows: 76 3. Variable List: TrapCode, unique identifier for each camera trap station X/Y, GPS coordinates for each camera trap station Z, altitude for each camera trap station Impact, description of anthropogenic impact at camera trap station distnatlro, distance to nearest national road (equivalent of highways), meters distsettle, distance to nearest human settlement, meters diststream, distance to nearest stream, meters denslocalr, the density of local roads measured using a moving window approach, km/km2 distlocalr, distance to nearest local road, meters TRI5, Terrain Roughness Index within a 50m buffer, see Riley, S. J., DeGloaria, S. J., & Elliot, R. (n.d.). Index that quantifies topographic heterogeneity. Intermountain Journal of Sciences, 5(1–4), 23–27 for full details CLC2018, the landcover type in 2018 as defined by CORINE Land Cover Classification system (https://land.copernicus.eu/eagle/files/eagle-related-projects/pt_clc-conversion-to-fao-lccs3_dec2010) CLC112-512, proportions of each CORINE land cover type within each 2.7 x 2.7km cell, see https://land.copernicus.eu/eagle/files/eagle-related-projects/pt_clc-conversion-to-fao-lccs3_dec2010 for full list of all land cover types DATA-SPECIFIC INFORMATION FOR: [cams_data_winter] 1. Number of variables: 26 2. Number of cases/rows: 64 3. Variable List: TrapCode, unique identifier for each camera trap station X/Y, GPS coordinates for each camera trap station Z, altitude for each camera trap station Impact, description of anthropogenic impact at camera trap station distnatlro, distance to nearest national road (equivalent of highways), meters distsettle, distance to nearest human settlement, meters diststream, distance to nearest stream, meters denslocalr, the density of local roads measured using a moving window approach, km/km2 distlocalr, distance to nearest local road, meters TRI5, Terrain Roughness Index within a 50m buffer, see Riley, S. J., DeGloaria, S. J., & Elliot, R. (n.d.). Index that quantifies topographic heterogeneity. Intermountain Journal of Sciences, 5(1–4), 23–27 for full details CLC2018, the landcover type in 2018 as defined by CORINE Land Cover Classification system (https://land.copernicus.eu/eagle/files/eagle-related-projects/pt_clc-conversion-to-fao-lccs3_dec2010) CLC112-512, proportions of each CORINE land cover type within each 2.7 x 2.7km cell, see https://land.copernicus.eu/eagle/files/eagle-related-projects/pt_clc-conversion-to-fao-lccs3_dec2010 for full list of all land cover types DATA-SPECIFIC INFORMATION FOR: [species_matrix_autumn] 1. Number of variables: 22 2. Number of cases/rows: 76 3. Variable List: TrapCode, unique identifier for each camera trap station Lynx_1-Lynx_7, presence/absences data for Eurasian lynx (Lynx lynx) for each session Wildcat_1-Wildcat_7, presence/absence data for European wildcat (Felis silvestris) for each session Wolf_1-Wolf_7, presence/absence data for grey wolf (Canis lupus) for each session DATA-SPECIFIC INFORMATION FOR: [species_matrix_winter] 1. Number of variables: 22 2. Number of cases/rows: 64 3. Variable List: TrapCode, unique identifier for each camera trap station Lynx_1-Lynx_7, presence/absences data for Eurasian lynx (Lynx lynx) for each session Wildcat_1-Wildcat_7, presence/absence data for European wildcat (Felis silvestris) for each session Wolf_1-Wolf_7, presence/absence data for grey wolf (Canis lupus) for each session DATA-SPECIFIC INFORMATION FOR: [Trap_effort_autumn] 1. Number of variables: 8 2. Number of cases/rows: 76 3. Variable List: TrapCode, unique identifier for each camera trap station Session_1-Session_7, camera trap activity for each session. If one camera was working every day of a session the value will = 14; any days where both cameras were inactive subtracts 1 from this value. DATA-SPECIFIC INFORMATION FOR: [Trap_effort_winter] 1. Number of variables: 8 2. Number of cases/rows: 64 3. Variable List: TrapCode, unique identifier for each camera trap station Session_1-Session_7, camera trap activity for each session. If one camera was working every day of a session the value will = 14; any days where both cameras were inactive subtracts 1 from this value.