Geolocation tracking to monitor spatial distribution and habitat selection of cows, horses and sheep grazing in mountainous areas

Precision Livestock Farming (PLF) technologies offer an opportunity to monitor livestock, enhancing farmers’ decision-making for improved control, better animal performance, and reduced environmental impact through proper management of pasture areas. The objective of this study was to assess the pot...

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Autores: Vidal-Cardos, Roger, Fàbrega-Romans, Emma, DALMAU, ANTONI
Tipo de recurso: artículo
Fecha de publicación:2025
País:España
Institución:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
Repositorio:Recercat. Dipósit de la Recerca de Catalunya
OAI Identifier:oai:recercat.cat:20.500.12327/4714
Acceso en línea:http://hdl.handle.net/20.500.12327/4714
https://doi.org/10.1016/j.applanim.2025.106776
Access Level:acceso abierto
Palabra clave:636
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spelling Geolocation tracking to monitor spatial distribution and habitat selection of cows, horses and sheep grazing in mountainous areasVidal-Cardos, RogerFàbrega-Romans, EmmaDALMAU, ANTONI636Precision Livestock Farming (PLF) technologies offer an opportunity to monitor livestock, enhancing farmers’ decision-making for improved control, better animal performance, and reduced environmental impact through proper management of pasture areas. The objective of this study was to assess the potential of data provided by commercial geolocation collars, along with open data resources such as information on natural habitats, topography, and vegetation, to detect grazing preferences of mountain livestock. We monitored 240 animals from three different herds and species (140 cows, 50 horses, and 50 sheep) during the grazing season (6 months) using geolocation collars in the Alt Pirineu Natural Park (80,000 ha), located in Catalonia, Spain. Animal distributions were analysed spatially and temporally across different seasonal periods (Spring: May-Jun, Summer: Jul-Aug and Autumn: Sep-Oct). Geolocation data were used to assess livestock preferences and avoidances regarding different types of terrain, land cover, and vegetation, estimated using Jacob’s selection index (JSI), a metric indicating whether animals use a particular area more or less than expected based on its availability. Additionally, we examined the influence of these environmental factors and the distance to water sources on animal distribution, and we identified high-density grazing hotspots. Results indicated that cows and horses positively selected areas with lower altitudes (JSI = 0.29 and 0.17, p < 0.05) and gentler slopes (JSI = 0.38 and 0.22, p < 0.05), whereas sheep preferred higher altitudes (JSI = 0.10, p < 0.05). Only cows showed a preference for areas with bare or dispersed vegetation. In general, all three species selected land covers such as open forests, meadows, wetlands, and water points, but changed depending on the season and species. The distance to water was greater for cows and sheep, particularly during the summer, whereas only horses showed a strong dependence on proximity to water sources. Finally, we identified and compared high-density grazing hotspots among the three species. These findings reveal not only interesting heterogeneity in distribution patterns among species sharing the same area, but also clear seasonal differences. In conclusion, data automatically collected from geolocation collars demonstrate strong potential for studying livestock grazing preferences, particularly in remote or hard-to-access mountainous areas. This information improves our understanding of livestock-environment interactions without requiring physical presence and can be effectively applied to support extensive grazing management.info:eu-repo/semantics/publishedVersionElsevierProducció AnimalBenestar Animal2025info:eu-repo/semantics/article12http://hdl.handle.net/20.500.12327/4714https://doi.org/10.1016/j.applanim.2025.106776reponame:Recercat. Dipósit de la Recerca de Catalunyainstname:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)InglésApplied Animal Behaviour ScienceMICINN/Programa Estatal para impulsar la investigación cientifico-técnica y su transferencia/TED2021-129315B-C21/ES/Integration of animal welfare into the digital evolution of livestock farming/SMARTWELGRAZAttribution-NonCommercial-NoDerivatives 4.0 Internationalhttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccessoai:recercat.cat:20.500.12327/47142026-05-29T05:05:01Z
dc.title.none.fl_str_mv Geolocation tracking to monitor spatial distribution and habitat selection of cows, horses and sheep grazing in mountainous areas
title Geolocation tracking to monitor spatial distribution and habitat selection of cows, horses and sheep grazing in mountainous areas
spellingShingle Geolocation tracking to monitor spatial distribution and habitat selection of cows, horses and sheep grazing in mountainous areas
Vidal-Cardos, Roger
636
title_short Geolocation tracking to monitor spatial distribution and habitat selection of cows, horses and sheep grazing in mountainous areas
title_full Geolocation tracking to monitor spatial distribution and habitat selection of cows, horses and sheep grazing in mountainous areas
title_fullStr Geolocation tracking to monitor spatial distribution and habitat selection of cows, horses and sheep grazing in mountainous areas
title_full_unstemmed Geolocation tracking to monitor spatial distribution and habitat selection of cows, horses and sheep grazing in mountainous areas
title_sort Geolocation tracking to monitor spatial distribution and habitat selection of cows, horses and sheep grazing in mountainous areas
dc.creator.none.fl_str_mv Vidal-Cardos, Roger
Fàbrega-Romans, Emma
DALMAU, ANTONI
author Vidal-Cardos, Roger
author_facet Vidal-Cardos, Roger
Fàbrega-Romans, Emma
DALMAU, ANTONI
author_role author
author2 Fàbrega-Romans, Emma
DALMAU, ANTONI
author2_role author
author
dc.contributor.none.fl_str_mv Producció Animal
Benestar Animal
dc.subject.none.fl_str_mv 636
topic 636
description Precision Livestock Farming (PLF) technologies offer an opportunity to monitor livestock, enhancing farmers’ decision-making for improved control, better animal performance, and reduced environmental impact through proper management of pasture areas. The objective of this study was to assess the potential of data provided by commercial geolocation collars, along with open data resources such as information on natural habitats, topography, and vegetation, to detect grazing preferences of mountain livestock. We monitored 240 animals from three different herds and species (140 cows, 50 horses, and 50 sheep) during the grazing season (6 months) using geolocation collars in the Alt Pirineu Natural Park (80,000 ha), located in Catalonia, Spain. Animal distributions were analysed spatially and temporally across different seasonal periods (Spring: May-Jun, Summer: Jul-Aug and Autumn: Sep-Oct). Geolocation data were used to assess livestock preferences and avoidances regarding different types of terrain, land cover, and vegetation, estimated using Jacob’s selection index (JSI), a metric indicating whether animals use a particular area more or less than expected based on its availability. Additionally, we examined the influence of these environmental factors and the distance to water sources on animal distribution, and we identified high-density grazing hotspots. Results indicated that cows and horses positively selected areas with lower altitudes (JSI = 0.29 and 0.17, p < 0.05) and gentler slopes (JSI = 0.38 and 0.22, p < 0.05), whereas sheep preferred higher altitudes (JSI = 0.10, p < 0.05). Only cows showed a preference for areas with bare or dispersed vegetation. In general, all three species selected land covers such as open forests, meadows, wetlands, and water points, but changed depending on the season and species. The distance to water was greater for cows and sheep, particularly during the summer, whereas only horses showed a strong dependence on proximity to water sources. Finally, we identified and compared high-density grazing hotspots among the three species. These findings reveal not only interesting heterogeneity in distribution patterns among species sharing the same area, but also clear seasonal differences. In conclusion, data automatically collected from geolocation collars demonstrate strong potential for studying livestock grazing preferences, particularly in remote or hard-to-access mountainous areas. This information improves our understanding of livestock-environment interactions without requiring physical presence and can be effectively applied to support extensive grazing management.
publishDate 2025
dc.date.none.fl_str_mv 2025
dc.type.none.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv http://hdl.handle.net/20.500.12327/4714
https://doi.org/10.1016/j.applanim.2025.106776
url http://hdl.handle.net/20.500.12327/4714
https://doi.org/10.1016/j.applanim.2025.106776
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv Applied Animal Behaviour Science
MICINN/Programa Estatal para impulsar la investigación cientifico-técnica y su transferencia/TED2021-129315B-C21/ES/Integration of animal welfare into the digital evolution of livestock farming/SMARTWELGRAZ
dc.rights.none.fl_str_mv Attribution-NonCommercial-NoDerivatives 4.0 International
http://creativecommons.org/licenses/by-nc-nd/4.0/
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Attribution-NonCommercial-NoDerivatives 4.0 International
http://creativecommons.org/licenses/by-nc-nd/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 12
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv reponame:Recercat. Dipósit de la Recerca de Catalunya
instname:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
instname_str Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
reponame_str Recercat. Dipósit de la Recerca de Catalunya
collection Recercat. Dipósit de la Recerca de Catalunya
repository.name.fl_str_mv
repository.mail.fl_str_mv
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