Camera-trapping: wild and domestic species occurrences in three Pyrenean pastures
Citation
Vimal R, Ouvrier A, Culos M, Guédon A, Le Guével A, Metz A, Bitsch S, Dewost M, Vinette C, Vilbert O, Guignet J, Lerigoleur E (2024). Camera-trapping: wild and domestic species occurrences in three Pyrenean pastures. Version 1.7. UMR 5602 GEODE Géographie de l’environnement (CNRS/Université Toulouse 2). Occurrence dataset https://doi.org/10.15468/939z6d accessed via GBIF.org on 2024-08-18.Description
The co-existence between brown bears (Ursus arctos Linnaeus, 1758) and farmers in the Pyrenees has been a major concern for several decades. The bear's depredation on livestock has multiple implications for traditional practices of extensive grazing and calls for a better understanding of the various ways in which humans and non-humans interact across different territories. The present dataset stems from "The Pastoralism and Bears in the Pyrenees" research project led by the GEODE laboratory (UMR 5602 CNRS-UT2J) in partnership with the Association Dissonances. Focusing on three summer pastures as places of encounter, this project proposes to explore the definition of co-existence, based on context-dependent and constantly evolving relationships between bears and pastoralists. As part of an interdisciplinary approach combining animal geography and ecology, the spatio-temporal activity of the different species was explored using a network of 118 camera traps. The 118 camera traps were installed on the three summer pastures while livestock was present in the mountains between May and October, from 2021 to 2023 and were set in a 400 m ✕ 400 m grid covering a total area of around 2,000 ha. The present dataset contains 57,928 occurrences of 22 taxon categories, including 19 identified species, two family categories (equids and mustelids) and one class category (birds). As pastoral activity is significantly present in these areas, livestock (sheep (Ovis aries Linnaeus, 1758), equids, cows (Bos taurus Linnaeus, 1758) and goats (Capra hircus Linnaeus, 1758)) account for 16,207 occurrences across the three pastures. The three main wild species captured over the three years and three pastures were the red deer (Cervus elaphus Linnaeus, 1758; 9,517 occurrences), red fox (Vulpes vulpes Linnaeus, 1758; 9,400 occurrences) and wild boar (Sus scrofa Linnaeus, 1758; 4,016 occurrences). Although the sampling effort of each camera, in days, is indicated in the dataset (e.g., 134 days), the details of the functioning days of each camera for each pasture can be found on the following DOI : https://doi.org/10.48579/PRO/XUSK8V, in order to locate data gaps over time and distinguish them from periods without capture events. In addition, the datapaper associated with the dataset can be consulted at the following DOI : https://doi.org/10.3897/BDJ.12.e126097. Data are aggregated at the grid scale. Nonetheless, the exact locations of each camera trap as well as the photos can be requested from us.Purpose
This camera trap sampling is part of the project "Pastoralism and Bear in the Pyrenees" which aims to understand the interactions between humans and non-humans at the micro local scale of three mountain pastures. This dataset provides information on the spatio-temporal use of three pastures by twenty-two taxa, between 2021 and 2023.Sampling Description
Study Extent
The present dataset was collected during three sampling campaigns carried out between May and October 2021, 2022 and 2023 on three mountain pastures located in the Ariège Pyrenees. A total of 118 motion-triggered infrared cameras (Reconyx® Hyperfire 2) were set on the three mountain pastures. As a result of an excessive number of thefts during the three campaigns, one camera has been removed from the Barestet pasture and data from the three years has been removed from the dataset (dataset from 118 cameras instead of the 119 initially installed in 2021). Depending on the pastures and the years, according to the field constraints, the sampling started and ended at variable dates, but at least between 12 June and 6 October. Insofar as the project is likely to continue, the present dataset may evolve, following the same protocol and supplemented by additional years of data on one or more pastures.Sampling
A former exploratory study, carried out in 2020 on one of the three study sites, tested the implementation of camera traps following a regular grid. However, the characteristics of the mountain environment and the topographical diversity of the pastures resulted in camera traps being set up in locations that were particularly unfavourable for the passage of wildlife, pastoral activity and humans (e.g. extremely steep slopes). As a result, the sampling was conducted following a regular grid of 400 m ✕ 400 m cells, in which one camera was installed at a chosen location of potential passages of the mammalian fauna (e.g. path, trail, mountain pass, thinning of vegetation etc.), thus providing a fine spatial anchor on the activity of the species and maximising their detectability. This fine-scale grid was relevant to the study in order to have the greatest possible insight into the spatilities of the various wild and domestic species, given the technical and financial constraints involved. For the purpose of consistency, the same mesh size was used on each of the sites, resulting in different numbers of cameras for the three pastures depending on their respective size (Arreau: 53 cameras, Barestet: 36 cameras, Ourdouas: 29 cameras). Depending on the vegetation and the configuration of the site, the cameras were installed on a tree or on a stake at a height varying from 50 cm to 1 m from the ground, at approximately 3 m and perpendicular to the potential path of the animal. Cameras were set to take three photos without delay between consecutive triggers in burst mode, as long as motion was detected. Cameras automatically record the date, time, moon phase, temperature of the captured events and the unique station’s label. Each camera was checked approximately every three weeks for data recovery, battery replacement and camera maintenance. Despite regular and frequent monitoring of the camera traps throughout the study period, some traps did not operate continuously over the study period due to various technical problems, thefts or damage by cattle. Although the sampling effort of each camera, in days, is indicated in the dataset (e.g. 134 days), the details of the functioning days of each camera for each pasture can be found on the following DOI: https://doi.org/10.48579/PRO/XUSK8V, in order to locate data gaps over time and distinguish them from periods without capturing events. During the entire study period, a total of 49,271 trap-days were sampled. The obtained pictures were manually identified on Timelapse Software (see https://saul.cpsc.ucalgary.ca/timelapse/pmwiki.php?n=Main.Licence). For wild species, two pictures separated by a time interval of at least two minutes were considered different capture events. When a capture event was recorded, only the first photo where the species was identifiable was annotated (i.e. species, temperature, date, time and number of individuals). When different individuals of the same species appeared later in the same capture event, the total number of individuals in the capture event was filled in using the first annotated photo. However, if an individual of another species appeared later in the same capture event, a new photo was annotated as the first identifiable photo of the species. Consequently, the date and time indicated for each capture event do not necessarily correspond to the exact number of individuals passing through at that precise time, but rather to the start of an event of variable duration containing that number of individuals. In some rare cases, two photos separated by an interval of more than two minutes were considered a single capture event. For example, an individual may have been sleeping in front of the camera, triggering it only occasionally. In such cases, a single event was recorded. Regarding livestock (i.e. cows, equids, goats and sheep), the photos were annotated on the basis of an hour's time. Thus, the minimum time interval between two consecutive capture events was one hour. In addition, as their behaviour can involve long periods of static in front of the cameras, in cases where a domestic species was continuously recorded for several hours, a new capture event was registered every hour after the start of the event. Moreover, for livestock data, the number of individuals was not recorded precisely since it mainly corresponded to the passage of herds. Thus, the value entered in the dataset is “many.” A precise number of individuals was only registered when an event showed only five sheep or less in order to identify isolated groups of sheep, which was relevant to answering the study goals. The dataset provided contains rows corresponding to each occurrence and, therefore, only shows information corresponding to the single annotated photo in each capture event. When two species appeared at the same time in a photo, the photo was annotated with both species, inducing two occurrences for one capture event. In the dataset, the row for this capture event was duplicated to obtain one row per occurrence.Quality Control
The species identification of all tagged photos has been double-checked by the authors. At the first identification, the error rate was 0.32% and these identified errors were corrected at the second verification, bringing the final error rate to nearly 0%. Potential gaps (e.g. missing temperature information) have also been checked and photos of humans were systematically removed from the dataset.Method steps
- The study areas – three mountain pastures in Ariège – were selected on the basis of criteria relevant to the project (e.g. differences in pastoral activity, confirmed and dense bear presence, accessibility etc.). The choice of sectors was also dictated by the agreement of the pastoral groups present on the pastures to host the project for at least three years. Authorisations to use vehicles on the tracks approaching the pastures and authorisations to set photographic traps were then requested from the manager of these territories, in this case the Office national des forêts (ONF), which oversees the integrity of the forest estate, the conservation of structures and the protection of forest stands and natural environments, as well as the management of wildlife and hunting. A 400 m ✕ 400 m grid covering the entire surface of each mountain pasture was chosen according to the objectives of the study, as mentionned above and the location of the camera traps in each grid cell was chosen according to the most suitable place for fauna to pass (e.g. path, trail, mountain pass, thinning of vegetation etc.). When the camera traps were installed, the main habitat in which the cameras were installed was noted. As this information was not necessary for the project's objectives, habitat characterisation was done on sight and in an arbitrary manner. The cameras, set to take three photos without delay between consecutive triggers in burst mode as long as motion was detected, were installed approximately between May and October of the three years of the project, depending on field constraints (e.g. snow cover) and were checked approximately every three weeks. The data collected were processed using Timelapse software, according to the photo completion protocol explained above. Photos have been identified at the class, family or species level and photos of humans were systematically removed from the dataset. The dataset was then checked to control identification errors and potential gaps (e.g. missing temperature information) and to standardise the data. The dataset, deposited on the Global Biodiversity Information Facility platform (GBIF), was standardised in Darwin Core Archive (DwC-A) format to create an occurrence dataset corresponding to the standards recommended by Darwin Core.
Additional info
In this dataset, each row corresponds to an occurrence. As an occurrence is part of a capture event composed of several photographs of the individual, each row corresponds to the single annotated photo in each capture event. When two species appeared at the same time in a photo, the photo was annotated with both species, inducing two occurrences for one capture event. In the dataset, the row for this capture event was duplicated to obtain one row per occurrence. With a view to preserving areas of quietude, life, and passage for sensitive species, the GPS locations of brown bear and capercaillie occurrences, respectively classified as critically endangered and vulnerable on the French red list, have been blurred. The coordinates shown correspond to the centroids of each summer pasture. For all other species, the location of each passage is given at the scale of the 400 m X 400 m grid cell centroid in which the camera trap that recorded the passage is installed. While the dataset therefore only shows points (two centroid scales), the geometry of each grid cell can be found in the additional files (https://doi.org/10.48579/PRO/XUSK8V) to facilitate the cartographic use of the data. To work directly with the exact locations of brown bear, capercaillie and other species capture events, please contact us directly. Insofar as the project is likely to continue, the present dataset may evolve, following the same protocol, being supplemented by additional years of data from one or more pastures. Although the raw data (pictures) are not made available, and since these data might be useful to some projects (e.g. species recognition software), it is possible to contact us to obtain the pictures, which are sorted by camera trap and by time period.Taxonomic Coverages
Whenever possible, the taxonomic identification was made at the species level. Due to study objectives and identification difficulties, birds, equids and mustelids were not identified at the species level, but at the class level or at the family level, except for Western capercaillie and European badger. Thus, a total of one class, two families and nineteen species were recorded.
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Avescommon name: Birds rank: class
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Equidaecommon name: Equids rank: family
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Mustelidaecommon name: Mustelids rank: family
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Bos tauruscommon name: Cow rank: species
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Canis familiariscommon name: Dog rank: species
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Capra hircuscommon name: Feral goat rank: species
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Capreolus capreoluscommon name: Roe deer rank: species
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Cervus elaphuscommon name: Red deer rank: species
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Felis silvestriscommon name: Wildcat rank: species
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Lepus europaeuscommon name: European hare rank: species
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Marmota marmotacommon name: Alpine marmot rank: species
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Meles melescommon name: European badger rank: species
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Ovis ariescommon name: Sheep rank: species
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Rupicapra rupicapracommon name: Pyrenean chamois rank: species
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Sciurus vulgariscommon name: Eurasian red squirrel rank: species
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Sus scrofacommon name: Wild boar rank: species
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Tetrao urogalluscommon name: Western capercaillie rank: species
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Usrus arctoscommon name: Brown bear rank: species
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Vulpes vulpescommon name: Red fox rank: species
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Dama damacommon name: Fallow deer rank: species
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Erinaceus europaeuscommon name: West european hedgehog rank: species
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Genetta genettacommon name: Common genet rank: species
Geographic Coverages
The present study focuses on three Pyrenean summer pastures, Arreau (around 890 ha), Barestet (around 645 ha) and Ourdouas (around 527 ha), two of which are located in the Ariège Department and one of which is located in both the Departments of Ariège and Haute-Garonne, France. The three pastures are respectively part of one, two and one municipalities: Seix, Melles – Saint-Lary and Sentein.
Bibliographic Citations
Contacts
Ruppert Vimaloriginator
position: Researcher
UMR 5602 Géographie de l'environnement (CNRS/Université Toulouse 2)
email: ruppert.vimal@univ-tlse2.fr
userId: https://orcid.org/0000-0001-7233-8957
Alice Ouvrier
originator
position: PhD student
UMR 5602 Géographie de l'environnement (CNRS/Université Toulouse 2)
email: alice.ouvrier@univ-tlse2.fr
userId: https://orcid.org/0009-0005-7948-7783
Manon Culos
originator
position: Employee
Association Dissonances
email: manon.culos@gmail.com
Anaïs Guédon
originator
position: Volunteer
Association Dissonances
Agathe Le Guével
originator
position: Volunteer
Association Dissonances
Aymeric Metz
originator
position: Volunteer
Association Dissonances
Sarah Bitsch
originator
position: Volunteer
Association Dissonances
Marie Dewost
originator
position: Volunteer
Association Dissonances
Coline Vinette
originator
position: Volunteer
Association Dissonances
Oscar Vilbert
originator
position: Volunteer
Association Dissonances
Jonas Guignet
originator
position: Provider
Association Dissonances
Ruppert Vimal
metadata author
position: Researcher
UMR 5602 Géographie de l'environnement (CNRS/Université Toulouse 2)
email: ruppert.vimal@univ-tlse2.fr
userId: https://orcid.org/0000-0001-7233-8957
Alice Ouvrier
metadata author
position: PhD student
UMR 5602 Géographie de l'environnement (CNRS/Université Toulouse 2)
email: alice.ouvrier@univ-tlse2.fr
userId: https://orcid.org/0009-0005-7948-7783
Manon Culos
metadata author
position: Employee
Association Dissonances
email: manon.culos@gmail.com
Emilie Lerigoleur
metadata author
position: Researcher
UMR 5602 Géographie de l'environnement (CNRS/Université Toulouse 2)
email: emilie.lerigoleur@univ-tlse2.fr
userId: https://orcid.org/0000-0002-0864-659X
distributor
GBIF France
email: connexion@gbif.fr
Ruppert Vimal
administrative point of contact
position: Researcher
UMR 5602 Géographie de l'environnement (CNRS/Université Toulouse 2)
email: ruppert.vimal@univ-tlse2.fr
userId: https://orcid.org/0000-0001-7233-8957