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...

Descripción completa

Detalles Bibliográficos
Autores: Vidal-Cardos, Roger|||0000-0002-2434-9480; Fábrega i Romans, Emma|||0000-0002-1877-8254; Dalmau Bueno, Antoni|||0000-0003-2248-6796
Tipo de documento: Artículo
Fecha de publicación:2025
País:España
Institución:Universitat Autònoma de Barcelona
Repositorio:Dipòsit Digital de Documents de la UAB
Lenguaje:Inglés
OAI Identifier:oai:ddd.uab.cat:323030
Acceso en línea:https://ddd.uab.cat/record/323030
https://dx.doi.org/urn:doi:10.1016/j.applanim.2025.106776
Nivel de acceso:Acceso abierto
Palabra clave:PLF
Grazing management
Geolocation collars
Animal distribution
High-density hotspots
_version_ 1878742762597122048
author Vidal-Cardos, Roger|||0000-0002-2434-9480
author2 Fábrega i Romans, Emma|||0000-0002-1877-8254
Dalmau Bueno, Antoni|||0000-0003-2248-6796
author2_role author
author
author_browse Dalmau Bueno, Antoni|||0000-0003-2248-6796
Fábrega i Romans, Emma|||0000-0002-1877-8254
Vidal-Cardos, Roger|||0000-0002-2434-9480
author_facet Vidal-Cardos, Roger|||0000-0002-2434-9480
Fábrega i Romans, Emma|||0000-0002-1877-8254
Dalmau Bueno, Antoni|||0000-0003-2248-6796
author_role author
collection Dipòsit Digital de Documents de la UAB
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 livestockenvironment interactions without requiring physical presence and can be effectively applied to support extensive grazing management.
eu_rights_str_mv openAccess
format article
id ES_fbcaa59ee32c7eabf18c0af6ba27c51f
institution Universitat Autònoma de Barcelona
instname_str Universitat Autònoma de Barcelona
language eng
network_acronym_str ES
network_name_str España
oai_identifier_str oai:ddd.uab.cat:323030
publishDate 2025
publishDateSort 2025
reponame_str Dipòsit Digital de Documents de la UAB
spelling Geolocation tracking to monitor spatial distribution and habitat selection of cows, horses and sheep grazing in mountainous areas Vidal-Cardos, Roger|||0000-0002-2434-9480 Fábrega i Romans, Emma|||0000-0002-1877-8254 Dalmau Bueno, Antoni|||0000-0003-2248-6796 PLF Grazing management Geolocation collars Animal distribution High-density hotspots 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 livestockenvironment interactions without requiring physical presence and can be effectively applied to support extensive grazing management. https://ddd.uab.cat/record/323030 https://dx.doi.org/urn:doi:10.1016/j.applanim.2025.106776
spellingShingle Geolocation tracking to monitor spatial distribution and habitat selection of cows, horses and sheep grazing in mountainous areas
Vidal-Cardos, Roger|||0000-0002-2434-9480
PLF
Grazing management
Geolocation collars
Animal distribution
High-density hotspots
title 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_short 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
topic PLF
Grazing management
Geolocation collars
Animal distribution
High-density hotspots
topic_facet PLF
Grazing management
Geolocation collars
Animal distribution
High-density hotspots
url https://ddd.uab.cat/record/323030
https://dx.doi.org/urn:doi:10.1016/j.applanim.2025.106776