Data from: Camera traps reveal seasonal variation in activity and occupancy of the Alpine mountain hare (Lepus timidus varronis)
Cite this dataset
Yoccoz, Nigel Gilles et al. (2024). Data from: Camera traps reveal seasonal variation in activity and occupancy of the Alpine mountain hare (Lepus timidus varronis) [Dataset]. Dryad. https://doi.org/10.5061/dryad.b2rbnzsp7
Abstract
Mountain hare is a cold-adapted species threatened by climate change, but despite its emblematic nature, our understanding of the causes of population decline remains limited. Camera traps are increasingly used in ecology as a tool for monitoring animal populations at large spatial and temporal scales. In mountain environments where field work is constrained by difficult access and harsh conditions, camera traps constitute a promising tool for surveying rare and elusive species such as the mountain hare. Our study explored the use of camera traps as a tool for studying seasonal habitat occupancy and daily activity patterns of the mountain hare, in order to carry out long-term monitoring of populations. We installed 46 camera traps along elevation gradients in the Mont-Blanc massif (France) from January 2018 to June 2022. We measured habitat variables at each camera trap site in order to define vegetation composition and habitat structure. We performed multi-season and single-season occupancy models to respectively describe habitat occupancy of the mountain hare throughout the year and identify the environmental variables influencing mountain hare presence during the breeding season. Mountain hares occupy coniferous forest in winter, and then switch to mixed areas of shrubland and grassland above treeline in spring and the beginning of summer. In spring, occupancy probability of the mountain hare increases with relative cover of mixed low shrub and herbaceous layer (i.e. the 10-40 cm vegetation layer), suggesting a link to food resources and protection from predation. Our results also confirm the nocturnal and crepuscular activity of the mountain hare during the breeding season, and strictly nocturnal activity in winter. Our results demonstrate the efficiency of camera traps as tools for monitoring mountain hare habitat occupancy in mountain environments and underline the importance of diverse habitat mosaics for the preservation of the species.
README: Camera traps reveal seasonal variation in activity and occupancy of the Alpine mountain hare (Lepus timidus varronis)
https://doi.org/10.5061/dryad.b2rbnzsp7
Pictures from 46 camera traps located along elevation gradients in the in the Mont-Blanc massif (France) have been used for this paper. Habitat variables at each camera trap site have also been measured in order to define vegetation composition and habitat structure.
Description of the data and file structure
Mountain hare contacts from camera traps are available in the "taghare_1day.csv" dataset. "Station" corresponds to the camera trap name, "Date" corresponds to the date at which a mountain hare has been contacted by the camera trap.
Descriptions of camera traps are available in the "camerainfo.csv" dataset. "Station" corresponds to the camera trap name, "Exposition" corresponds to the orientation of the camera, "Elevation" corresponds at which elevation (in meters) was installed the camera, "Longitude" and "Latitude" indicate the coordinates of the camera, "Slope" indicates the slope of the ground where the camera has been installed, "Habitat" corresponds to the habitat surrounding the camera, "Model" corresponds to the model of the camera, "setup_date" corresponds to the date at which the camera was setup, "Problem[X]" corresponds to the cause of the problem during the period "Problem[X]*from" - "Problem[X]_to".
Vegetation measurements around camera traps are available in the "out_plot.csv", "out_height.csv" and "out_contact.csv" datasets.
In "out_plot. csv", "plot_project" correspond to the name of the camera where the measurements have been done, "date" corresponds to the date of measurements, "name_camera" corresponds to the name of the camera as given in the "camerainfo" dataset, "slope.class" indicates the class of slope where vegetation measurements have been done (1: <10°, 2: 10-25°, 3: 25-40°, 4: >40°), "elevation" corresponds to the elevation (in meters) of the location where vegetation measurements have been done, "orientation" corresponds to the orientation of the location where vegetation measurements have been done, "Latitude" and "Longitude" corresponds to the location where vegetation measurements have been done, "relief.homogeneity" indicates the homogeneity of the relief, "strata.0" gives the percentage of the cover of bare ground, "strata.1" gives the percentage of the cover of vegetation under 10 cm, "strata.2" gives the percentage of the cover of vegetation between 10 and 40 cm, "strata.3" gives the percentage of the cover of vegetation between 40cm and 1.30m, "strata.4" gives the percentage of the cover of vegetation between 1.30 and 4m, "strata.5" gives the percentage of the cover of vegetation over 4m (i.e. cover of the tree layer). Each "strata.[X]" column is described by a class of percentage of the corresponding vegetation cover. 0 corresponds to no vegetation of the corresponding strata, 1 corresponds to a cover less 10%, 2 corresponds to a cover between 10 and 25% , 3 corresponds to a cover between 25 and 50%, 4 corresponds to a cover between 50 and 75% and 5 corresponds to a cover more than 75%.
In "out_height.csv", "point_number" corresponds to the point number at which the "height" of the vegetation has been measured (in cm).
In "out_contact.csv", "ref_fg" corresponds to the vegetation type and "nb_pin_touch" corresponds to the number of contact points for this vegetation type. F: ferns, HG: grass, HF: forbs, LRF: Rhododendron ferrugineum, LRH: Rhododendron hirsutum, LVM: Vaccinium myrtillus, LVU: Vaccinium uliginosum, LVVI: Vaccinium vitis-idaea, LJC: Juniperus communis, LCV: Calluna vulgaris, LEN: Empetrum nigrum, LKP: Kalmia procumbens, SS: small shrub, ST: tall shrub, TC: coniferous tree.
Code/Software
R 3.6.2 (R Development Core Team 2018) has been used to analyze the data. We used occupancy probability methods for unmarked animals as detailed by Gilbert (2020), and used the “unmarked” (Fiske and Chandler 2011) and “camtrapR” (Niedballa et al. 2016) packages to perform subsequent analyses.
Funding
European Fund for Regional Development (FEDER)
Fonds national d'Aménagement et de Développement du Territoire
Conseil Départemental de la Haute-Savoie
Space for Climate Observatory (SCO/CNES)
Office Français de la Biodiversité