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

摘要: 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 large natural pastures where they are exposed competition with wild herbivores for heterogeneous scarce resources, predation risk, adverse weather, complex topography. Considering that 91% world's surface devoted composed (i.e., rangelands), our general aim was develop PLF methodology quantifies: (i) detailed behavioural patterns, (ii) feeding rate, (iii) costs associated different behaviours traits. Methods For this, we used Merino sheep in Patagonian rangelands as case study. We combined data from an animal-attached multi-sensor tag (tri-axial acceleration, tri-axial magnetometry, temperature sensor Global Positioning System) layers Geographical Information System acquire data. Then, high accuracy decision trees, dead reckoning methods spatial processing techniques show how this combination tools could assess energy balance, risk experienced by through time space. Results proposed here useful tool behaviour factors influence production, such topography, environmental temperature, resources. were able quantify rate continuously space it estimate animal intensity grazing landscape. also assessed effects resource heterogeneity (inferred search times), potential competition, thermoregulation movement Discussion quantification provided balance predict individual growth, survival reproduction. Finally, discussed information wildlife-friendly strategies maximize welfare, quality sustainability.