DOI: 10.5061/dryad.jsxksn0g4
title: Data from: Using camera traps to estimate habitat preferences and occupancy patterns of vertebrates in boreal wetlands

description: Wetlands are a critical habitat for boreal mammals and birds that rely on
 them for breeding, foraging, and resting. However, wetlands in boreal
 regions are increasingly experiencing natural and human pressures. These
 impacts can lead to a reduction in the availability of wetland
 habitats for boreal mammals and birds that rely on wetlands for
 breeding, foraging, and resting. To inform management and conservation,
 camera traps provide an opportunity to survey mammals and birds to
 investigate their habitat preferences. We aimed to evaluate the effect of
 habitat features on the occupancy of mammals and birds in boreal wetlands.
 We used a multispecies occupancy model to estimate the habitat
 associations of 11 mammals and 45 avian species detected at 50 sampling
 ponds during the summers of 2018 and 2019 in Northern Quebec. Our results
 indicate that certain mammals, such as Red Fox and River Otters, and birds
 including the American Pipit, Common Raven, Hooded Merganser, and Greater
 Yellowlegs showed a preference for peatland ponds, whereas the Common
 Grackle preferred beaver ponds. We found few effects of distance to roads,
 and no effect of amount of forest cover on species occupancy. The
 occupancy of 27% of mammals and 24% of birds decreased with increasing
 latitude. These findings offer valuable insights for informing
 conservation initiatives focused on the preservation of wetlands in
 northern Quebec. By discerning the specific types of ponds preferred by
 each species, conservationists can strategically ensure the preservation
 and proper management of these habitats, thereby enhancing their
 conservation efforts.
description: Camera trap
 survey We conducted camera trap surveys at
 50 wetlands over two summers in 2018 and 2019, using three cameras per
 pond in a triangular configuration. We used scent lures as attractants,
 and cameras were rotated and baited accordingly. Data collection occurred
 during two sessions of seven consecutive days per year. Each camera array
 consisted of three infrared Bushnell Trophy Cam HD motion-sensing digital
 cameras set to be active 24 hours/day. Cameras were placed at the edge of
 the pond and secured to a tree or a wooden stake at an average height of
 30–60 cm at about 2–5 m from the water. Cameras were triggered by animal
 movements and programmed to take three photographs per trigger event, and
 a following video of 10-s, with a 1-min interval delay between detections
 to avoid that a single animal would be the subject of a long event of
 recording. We placed scent lure on a stick at 2 -5 m in front of the
 camera trap to increase the probability of detecting animals approaching
 the lure. At the end of each session, cameras were checked, photos were
 analyzed to identify bird and mammal species, and records from the same
 species at the same pond on the same day were combined into one detection
 event. Covariates such as pond type, forest cover, year, latitude, and
 distance to the nearest road were considered in analyzing bird and mammal
 occupancy and detection probability. Variables such as cumulative
 rainfall, days since snowmelt, and sampling effort were also factored into
 the detection analysis. Data processing and
 analysis To enhance species detection, we
 combined observations from three camera traps at a specific site on a
 given day, resulting in a data matrix of 100 rows and 14 columns per
 species. Using a multispecies occupancy framework, we analyzed bird and
 mammal communities, considering various factors such as pond type, forest
 cover, year, latitude, and distance to the nearest road. Model parameters
 were estimated using a Bayesian approach with Markov chain Monte Carlo in
 JAGS 4.3.0 within R 4.1.2. Convergence of the chains was assessed through
 trace plots, posterior density plots, and the Brooks-Gelman-Rubin
 statistic. Model fit was evaluated using posterior predictive checks and
 the area under the receiver operating characteristic curve.
description: We estimated model parameters using a Bayesian approach based on
 Markov chain Monte Carlo (MCMC) in JAGS 4.3.0 within R 4.1.2 using the
 jagsUI package (Plummer et al. 2006; Lunn et al. 2013; Kellner 2019; R
 Core Team 2021). The description of each column header for each
 spreadsheet is provided in an associated ReadMe file. The steps to follow
 for each analysis are provided in the R code files. The final dataset
 included detection/non-detection data for 11 mammal species and 45 avian
 species from 50 ponds from May to August 2018 and 2019
 ("Cam_multisp_v4.Rdata"). This dataset is shared in one file in
 the form of a 3-dimensional array table, which contained rows for pond
 units (n=100), columns for visits (n=14), and rectangular matrices for
 species (n=56). Please contact the author for any additional inquiries of
 how data was collected and analyze.
description: This README file was generated on 2023-10-09 by Mariano J. Feldman.
 GENERAL INFORMATION 1. Title of Dataset: Data from: Using camera traps to
 estimate habitat preferences and occupancy patterns of vertebrates in
 boreal wetlands 2. Author Information A. Principal Contact Information
 Name: Mariano J. Feldman Institution: Université du Quebec en
 Abitibi-Temiscamingue (UQAT), Conservation Biology Group. Landscape
 Dynamics and Biodiversity programme. Forest Science and Technology Center
 of Catalonia (CTFC), Solsona, Catalonia, Spain. Email:
 mariano.feldman@ctfc.cat <br> B. Alternative Contact Information
 Name: Marc J. Mazerolle Institution: Université Laval Email:
 marc.mazerolle@sbf.ulaval.ca 3. Date of data collection: Data was
 collected from May to August 2018 and 2019. 4. Geographic location of data
 collection: All peatland and beaver ponds were located in Northern Quebec,
 Canada. 5. Information about funding sources that supported the collection
 of the data: NSERC of Canada, Université du Québec en
 Abitibi-Témiscamingue (UQAT) industrial research chair on northern
 biodiversity in a mining context SHARING/ACCESS INFORMATION 1.
 Licenses/restrictions placed on the data: None 2. Links to publications
 that cite or use the data: Feldman M.J., Mazerolle, M.J., Imbeau, I.,
 Fenton, N.J. (2023). Using camera traps to estimate habitat preferences
 and occupancy patterns of vertebrates in boreal wetlands. Wetlands. 3.
 Links to other publicly accessible locations of the data: None 4.
 Links/relationships to ancillary data sets: None 5. Was data derived from
 another source? No A. If yes, list source(s): NA 6. Recommended citation
 for this dataset: Feldman M.J., Mazerolle, M.J., Imbeau, I., Fenton, N.J.
 (2023). Data from: Using camera traps to estimate habitat preferences and
 occupancy patterns of vertebrates in boreal wetlands. Dryad Digital. DATA
 & FILE OVERVIEW 1. File List: Dataset is divided into 6 files: 4
 spreadsheets, 1 table code including the multispecies model structure, and
 one R file that contains presence/absence data for 11 mammal species and
 45 avian species in a form of an array 3-dimensional table (A-
 “Cam_multisp_v4.Rdata”). All occupancy variables used for analysis are
 included in the same form (B- “cam_ocsite_v3.csv”). Three detection
 covariates are included in separate files, containing the cumulative
 rainfall during a given day names as C- “det_precip_acum.csv”. The number
 of days since snowmelt is included as a numerical variable in the same
 form, and named as D- “det_degel.csv”. The number of active cameras during
 a given day is included as E- “det_cam_active.csv”. The multispecies model
 code is named F- “Code_Multispecies model.docx”. A) Cam_multisp_v4.Rdata
 B) cam_ocsite_v3.csv C) det_precip_acum.csv D) det_degel.csv E)
 det_cam_active.csv F) Code_Multispecies model.docx 2. Relationship between
 files, if important: Files from A to E are the source for the F 3.
 Additional related data collected that was not included in the current
 data package: None 4. Are there multiple versions of the dataset? No A. If
 yes, name of file(s) that was updated: NA i. Why was the file updated? NA
 ii. When was the file updated? NA
 #########################################################################
 DATA-SPECIFIC INFORMATION FOR: cam_ocsite_v3.csv Occupancy variables used
 for analysis 1. Number of variables: 5 2. Number of cases/rows: 100 3.
 Variable List: * id_site: site identification * anne: year
 ("0"=2018, "1"=2019) * type_hab: pond type
 ("castor": beaver pond; "tourb": peatland pond) *
 chemin_dist: distance from the road to the pond site in metres * latitud:
 latitude of pond sites * foret: Forest cover surrounding ponds within 1 km
 4. Missing data codes: Data not available for some sites in column
 "foret" 5. Specialized formats or other abbreviations used: None
 #########################################################################
 DATA-SPECIFIC INFORMATION FOR: det_precip_acum.csv Detection covariate:
 cumulative rainfall during a given day 1. Number of variables: 14 2.
 Number of cases/rows: 100 3. Variable List: * ident: site identification *
 vis 1 to vis 7: visit survey of pond site from day 1 ("vis 1")
 to day 7 ("vis 7") in 2018 * vis 8 to vis 14: visit survey of
 pond site from day 1 ("vis 8") to day 7 ("vis 14") in
 2019 4. Missing data codes: Data not available for one site in 2019
 ("CASA_TO_8 2019") 5. Specialized formats or other abbreviations
 used: None
 #########################################################################
 DATA-SPECIFIC INFORMATION FOR: det_degel.csv Detection covariate: number
 of days since snowmelt 1. Number of variables: 14 2. Number of cases/rows:
 100 3. Variable List: * ident: site identification * vis 1 to vis 7: visit
 survey of pond site from day 1 ("vis 1") to day 7 ("vis
 7") in 2018 * vis 8 to vis 14: visit survey of pond site from day 1
 ("vis 8") to day 7 ("vis 14") in 2019 4. Missing data
 codes: Data not available for one site in 2019 ("CASA_TO_8
 2019") 5. Specialized formats or other abbreviations used: None
 #########################################################################
 DATA-SPECIFIC INFORMATION FOR: det_cam_active.csv Detection covariate:
 number of days since snowmelt 1. Number of variables: 14 2. Number of
 cases/rows: 100 3. Variable List: * ident: site identification * vis 1 to
 vis 7: visit survey of pond site from day 1 ("vis 1") to day 7
 ("vis 7") in 2018 * vis 8 to vis 14: visit survey of pond site
 from day 1 ("vis 8") to day 7 ("vis 14") in 2019 4.
 Missing data codes: Data not available for one site in 2019
 ("CASA_TO_8 2019") 5. Specialized formats or other abbreviations
 used: None