Multi-dimensional Precision Livestock Farming: A potential toolbox for sustainable rangeland management

Autores
Di Virgilio, Agustina Soledad; Morales, Juan Manuel; Lambertucci, Sergio Agustin; Shepard, Emily L.C.; Wilson, Rory P.
Año de publicación
2018
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Background. Precision Livestock Farming (PLF) is a promising approach to minimize the conflicts between socio-economic activities and landscape conservation. However, its application on extensive systems of livestock production can be challenging. The main difficulties arise because animals graze on large natural pastures where they are exposed to competition with wild herbivores for heterogeneous and scarce resources, predation risk, adverse weather, and complex topography. Considering that the 91% of the world's surface devoted to livestock production is composed of extensive systems (i.e., rangelands), our general aim was to develop a PLF methodology that quantifies: (i) detailed behavioural patterns, (ii) feeding rate, and (iii) costs associated with different behaviours and landscape traits. Methods. For this, we used Merino sheep in Patagonian rangelands as a case study. We combined data from an animal-attached multi-sensor tag (tri-axial acceleration, tri-axial magnetometry, temperature sensor and Global Positioning System) with landscape layers from a Geographical Information System to acquire data. Then, we used high accuracy decision trees, dead reckoning methods and spatial data processing techniques to show how this combination of tools could be used to assess energy balance, predation risk and competition experienced by livestock through time and space. Results. The combination of methods proposed here are a useful tool to assess livestock behaviour and the different factors that influence extensive livestock production, such as topography, environmental temperature, predation risk and competition for heterogeneous resources. We were able to quantify feeding rate continuously through time and space with high accuracy and show how it could be used to estimate animal production and the intensity of grazing on the landscape. We also assessed the effects of resource heterogeneity (inferred through search times), and the potential costs associated with predation risk, competition, thermoregulation and movement on complex topography. Discussion. The quantification of feeding rate and behavioural costs provided by our approach could be used to estimate energy balance and to predict individual growth, survival and reproduction. Finally, we discussed how the information provided by this combination of methods can be used to develop wildlife-friendly strategies that also maximize animal welfare, quality and environmental sustainability.
Fil: Di Virgilio, Agustina Soledad. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Norte. Instituto de Investigaciones en Biodiversidad y Medioambiente. Universidad Nacional del Comahue. Centro Regional Universidad Bariloche. Instituto de Investigaciones en Biodiversidad y Medioambiente; Argentina
Fil: Morales, Juan Manuel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Norte. Instituto de Investigaciones en Biodiversidad y Medioambiente. Universidad Nacional del Comahue. Centro Regional Universidad Bariloche. Instituto de Investigaciones en Biodiversidad y Medioambiente; Argentina
Fil: Lambertucci, Sergio Agustin. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Norte. Instituto de Investigaciones en Biodiversidad y Medioambiente. Universidad Nacional del Comahue. Centro Regional Universidad Bariloche. Instituto de Investigaciones en Biodiversidad y Medioambiente; Argentina
Fil: Shepard, Emily L.C.. Swansea University; Reino Unido
Fil: Wilson, Rory P.. Swansea University; Reino Unido
Materia
HUMAN-WILDLIFE CONFLICTS
PRECISION LIVESTOCK FARMING
RANGELAND CONSERVATION
SPATIAL-MULTI-SENSOR APPROACH
SUSTAINABLE LIVESTOCK MANAGEMENT
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/91088

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network_name_str CONICET Digital (CONICET)
spelling Multi-dimensional Precision Livestock Farming: A potential toolbox for sustainable rangeland managementDi Virgilio, Agustina SoledadMorales, Juan ManuelLambertucci, Sergio AgustinShepard, Emily L.C.Wilson, Rory P.HUMAN-WILDLIFE CONFLICTSPRECISION LIVESTOCK FARMINGRANGELAND CONSERVATIONSPATIAL-MULTI-SENSOR APPROACHSUSTAINABLE LIVESTOCK MANAGEMENThttps://purl.org/becyt/ford/1.6https://purl.org/becyt/ford/1Background. Precision Livestock Farming (PLF) is a promising approach to minimize the conflicts between socio-economic activities and landscape conservation. However, its application on extensive systems of livestock production can be challenging. The main difficulties arise because animals graze on large natural pastures where they are exposed to competition with wild herbivores for heterogeneous and scarce resources, predation risk, adverse weather, and complex topography. Considering that the 91% of the world's surface devoted to livestock production is composed of extensive systems (i.e., rangelands), our general aim was to develop a PLF methodology that quantifies: (i) detailed behavioural patterns, (ii) feeding rate, and (iii) costs associated with different behaviours and landscape traits. Methods. For this, we used Merino sheep in Patagonian rangelands as a case study. We combined data from an animal-attached multi-sensor tag (tri-axial acceleration, tri-axial magnetometry, temperature sensor and Global Positioning System) with landscape layers from a Geographical Information System to acquire data. Then, we used high accuracy decision trees, dead reckoning methods and spatial data processing techniques to show how this combination of tools could be used to assess energy balance, predation risk and competition experienced by livestock through time and space. Results. The combination of methods proposed here are a useful tool to assess livestock behaviour and the different factors that influence extensive livestock production, such as topography, environmental temperature, predation risk and competition for heterogeneous resources. We were able to quantify feeding rate continuously through time and space with high accuracy and show how it could be used to estimate animal production and the intensity of grazing on the landscape. We also assessed the effects of resource heterogeneity (inferred through search times), and the potential costs associated with predation risk, competition, thermoregulation and movement on complex topography. Discussion. The quantification of feeding rate and behavioural costs provided by our approach could be used to estimate energy balance and to predict individual growth, survival and reproduction. Finally, we discussed how the information provided by this combination of methods can be used to develop wildlife-friendly strategies that also maximize animal welfare, quality and environmental sustainability.Fil: Di Virgilio, Agustina Soledad. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Norte. Instituto de Investigaciones en Biodiversidad y Medioambiente. Universidad Nacional del Comahue. Centro Regional Universidad Bariloche. Instituto de Investigaciones en Biodiversidad y Medioambiente; ArgentinaFil: Morales, Juan Manuel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Norte. Instituto de Investigaciones en Biodiversidad y Medioambiente. Universidad Nacional del Comahue. Centro Regional Universidad Bariloche. Instituto de Investigaciones en Biodiversidad y Medioambiente; ArgentinaFil: Lambertucci, Sergio Agustin. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Norte. Instituto de Investigaciones en Biodiversidad y Medioambiente. Universidad Nacional del Comahue. Centro Regional Universidad Bariloche. Instituto de Investigaciones en Biodiversidad y Medioambiente; ArgentinaFil: Shepard, Emily L.C.. Swansea University; Reino UnidoFil: Wilson, Rory P.. Swansea University; Reino UnidoPeerJ2018-05-30info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/91088Di Virgilio, Agustina Soledad; Morales, Juan Manuel; Lambertucci, Sergio Agustin; Shepard, Emily L.C.; Wilson, Rory P.; Multi-dimensional Precision Livestock Farming: A potential toolbox for sustainable rangeland management; PeerJ; PeerJ; 2018; 5; 30-5-2018; 1-232167-8359CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://peerj.com/articles/4867/info:eu-repo/semantics/altIdentifier/doi/10.7717/peerj.4867info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T10:19:57Zoai:ri.conicet.gov.ar:11336/91088instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-29 10:19:57.829CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Multi-dimensional Precision Livestock Farming: A potential toolbox for sustainable rangeland management
title Multi-dimensional Precision Livestock Farming: A potential toolbox for sustainable rangeland management
spellingShingle Multi-dimensional Precision Livestock Farming: A potential toolbox for sustainable rangeland management
Di Virgilio, Agustina Soledad
HUMAN-WILDLIFE CONFLICTS
PRECISION LIVESTOCK FARMING
RANGELAND CONSERVATION
SPATIAL-MULTI-SENSOR APPROACH
SUSTAINABLE LIVESTOCK MANAGEMENT
title_short Multi-dimensional Precision Livestock Farming: A potential toolbox for sustainable rangeland management
title_full Multi-dimensional Precision Livestock Farming: A potential toolbox for sustainable rangeland management
title_fullStr Multi-dimensional Precision Livestock Farming: A potential toolbox for sustainable rangeland management
title_full_unstemmed Multi-dimensional Precision Livestock Farming: A potential toolbox for sustainable rangeland management
title_sort Multi-dimensional Precision Livestock Farming: A potential toolbox for sustainable rangeland management
dc.creator.none.fl_str_mv Di Virgilio, Agustina Soledad
Morales, Juan Manuel
Lambertucci, Sergio Agustin
Shepard, Emily L.C.
Wilson, Rory P.
author Di Virgilio, Agustina Soledad
author_facet Di Virgilio, Agustina Soledad
Morales, Juan Manuel
Lambertucci, Sergio Agustin
Shepard, Emily L.C.
Wilson, Rory P.
author_role author
author2 Morales, Juan Manuel
Lambertucci, Sergio Agustin
Shepard, Emily L.C.
Wilson, Rory P.
author2_role author
author
author
author
dc.subject.none.fl_str_mv HUMAN-WILDLIFE CONFLICTS
PRECISION LIVESTOCK FARMING
RANGELAND CONSERVATION
SPATIAL-MULTI-SENSOR APPROACH
SUSTAINABLE LIVESTOCK MANAGEMENT
topic HUMAN-WILDLIFE CONFLICTS
PRECISION LIVESTOCK FARMING
RANGELAND CONSERVATION
SPATIAL-MULTI-SENSOR APPROACH
SUSTAINABLE LIVESTOCK MANAGEMENT
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.6
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv Background. Precision Livestock Farming (PLF) is a promising approach to minimize the conflicts between socio-economic activities and landscape conservation. However, its application on extensive systems of livestock production can be challenging. The main difficulties arise because animals graze on large natural pastures where they are exposed to competition with wild herbivores for heterogeneous and scarce resources, predation risk, adverse weather, and complex topography. Considering that the 91% of the world's surface devoted to livestock production is composed of extensive systems (i.e., rangelands), our general aim was to develop a PLF methodology that quantifies: (i) detailed behavioural patterns, (ii) feeding rate, and (iii) costs associated with different behaviours and landscape traits. Methods. For this, we used Merino sheep in Patagonian rangelands as a case study. We combined data from an animal-attached multi-sensor tag (tri-axial acceleration, tri-axial magnetometry, temperature sensor and Global Positioning System) with landscape layers from a Geographical Information System to acquire data. Then, we used high accuracy decision trees, dead reckoning methods and spatial data processing techniques to show how this combination of tools could be used to assess energy balance, predation risk and competition experienced by livestock through time and space. Results. The combination of methods proposed here are a useful tool to assess livestock behaviour and the different factors that influence extensive livestock production, such as topography, environmental temperature, predation risk and competition for heterogeneous resources. We were able to quantify feeding rate continuously through time and space with high accuracy and show how it could be used to estimate animal production and the intensity of grazing on the landscape. We also assessed the effects of resource heterogeneity (inferred through search times), and the potential costs associated with predation risk, competition, thermoregulation and movement on complex topography. Discussion. The quantification of feeding rate and behavioural costs provided by our approach could be used to estimate energy balance and to predict individual growth, survival and reproduction. Finally, we discussed how the information provided by this combination of methods can be used to develop wildlife-friendly strategies that also maximize animal welfare, quality and environmental sustainability.
Fil: Di Virgilio, Agustina Soledad. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Norte. Instituto de Investigaciones en Biodiversidad y Medioambiente. Universidad Nacional del Comahue. Centro Regional Universidad Bariloche. Instituto de Investigaciones en Biodiversidad y Medioambiente; Argentina
Fil: Morales, Juan Manuel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Norte. Instituto de Investigaciones en Biodiversidad y Medioambiente. Universidad Nacional del Comahue. Centro Regional Universidad Bariloche. Instituto de Investigaciones en Biodiversidad y Medioambiente; Argentina
Fil: Lambertucci, Sergio Agustin. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Norte. Instituto de Investigaciones en Biodiversidad y Medioambiente. Universidad Nacional del Comahue. Centro Regional Universidad Bariloche. Instituto de Investigaciones en Biodiversidad y Medioambiente; Argentina
Fil: Shepard, Emily L.C.. Swansea University; Reino Unido
Fil: Wilson, Rory P.. Swansea University; Reino Unido
description Background. Precision Livestock Farming (PLF) is a promising approach to minimize the conflicts between socio-economic activities and landscape conservation. However, its application on extensive systems of livestock production can be challenging. The main difficulties arise because animals graze on large natural pastures where they are exposed to competition with wild herbivores for heterogeneous and scarce resources, predation risk, adverse weather, and complex topography. Considering that the 91% of the world's surface devoted to livestock production is composed of extensive systems (i.e., rangelands), our general aim was to develop a PLF methodology that quantifies: (i) detailed behavioural patterns, (ii) feeding rate, and (iii) costs associated with different behaviours and landscape traits. Methods. For this, we used Merino sheep in Patagonian rangelands as a case study. We combined data from an animal-attached multi-sensor tag (tri-axial acceleration, tri-axial magnetometry, temperature sensor and Global Positioning System) with landscape layers from a Geographical Information System to acquire data. Then, we used high accuracy decision trees, dead reckoning methods and spatial data processing techniques to show how this combination of tools could be used to assess energy balance, predation risk and competition experienced by livestock through time and space. Results. The combination of methods proposed here are a useful tool to assess livestock behaviour and the different factors that influence extensive livestock production, such as topography, environmental temperature, predation risk and competition for heterogeneous resources. We were able to quantify feeding rate continuously through time and space with high accuracy and show how it could be used to estimate animal production and the intensity of grazing on the landscape. We also assessed the effects of resource heterogeneity (inferred through search times), and the potential costs associated with predation risk, competition, thermoregulation and movement on complex topography. Discussion. The quantification of feeding rate and behavioural costs provided by our approach could be used to estimate energy balance and to predict individual growth, survival and reproduction. Finally, we discussed how the information provided by this combination of methods can be used to develop wildlife-friendly strategies that also maximize animal welfare, quality and environmental sustainability.
publishDate 2018
dc.date.none.fl_str_mv 2018-05-30
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
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info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/91088
Di Virgilio, Agustina Soledad; Morales, Juan Manuel; Lambertucci, Sergio Agustin; Shepard, Emily L.C.; Wilson, Rory P.; Multi-dimensional Precision Livestock Farming: A potential toolbox for sustainable rangeland management; PeerJ; PeerJ; 2018; 5; 30-5-2018; 1-23
2167-8359
CONICET Digital
CONICET
url http://hdl.handle.net/11336/91088
identifier_str_mv Di Virgilio, Agustina Soledad; Morales, Juan Manuel; Lambertucci, Sergio Agustin; Shepard, Emily L.C.; Wilson, Rory P.; Multi-dimensional Precision Livestock Farming: A potential toolbox for sustainable rangeland management; PeerJ; PeerJ; 2018; 5; 30-5-2018; 1-23
2167-8359
CONICET Digital
CONICET
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https://creativecommons.org/licenses/by/2.5/ar/
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