Mapping the Global Distribution of Livestock

By T. Robinson, G. Wint, G. Conchedda, T. Boeckel, V. Ercoli, E. Palamara, G. Cinardi, L. D'Aietti, Simon Iain Hay, M. Gilbert. PLoS ONE, 2014

831 citations recorded by the source corpus.

Livestock contributes directly to the livelihoods and food security of almost a billion people and affects the diet and health of many more. With estimated standing populations of 1.43 billion cattle, 1.87 billion sheep and goats, 0.98 billion pigs, and 19.60 billion chickens, reliable and accessible information on the distribution and abundance of livestock is needed for a many reasons. These include analyses of the social and economic aspects of the livestock sector; the environmental impacts of livestock such as the production and management of waste, greenhouse gas emissions and livestock-related land-use change; and large-scale public health and epidemiological investigations. The Gridded Livestock of the World (GLW) database, produced in 2007, provided modelled livestock densities of the world, adjusted to match official (FAOSTAT) national estimates for the reference year 2005, at a spatial resolution of 3 minutes of arc (about 5×5 km at the equator). Recent methodological improvements have significantly enhanced these distributions: more up-to date and detailed sub-national livestock statistics have been collected; a new, higher resolution set of predictor variables is used; and the analytical procedure has been revised and extended to include a more systematic assessment of model accuracy and the representation of uncertainties associated with the predictions. This paper describes the current approach in detail and presents new global distribution maps at 1 km resolution for cattle, pigs and chickens, and a partial distribution map for ducks. These digital layers are made publically available via the Livestock Geo-Wiki (http://www.livestock.geo-wiki.org), as will be the maps of other livestock types as they are produced.

Subfields: Ecology, Genetics, Management, Monitoring, Policy and Law

View Paper: https://www.semanticscholar.org/paper/1360d580eb60357c33e362df0a4566b3fd21c5c9

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Citations in the corpus

Biodiversity impacts and conservation implications of urban land expansion projected to 2050 (2022, methodology): “Pasture In the GLOBIO 2015 LULC map, the distribution of land used for pasture is determined based on land suitability defined by the Gridded Livestock of the World (GLW) dataset – a global gridded dataset that models livestock density based on vegetation, topography, climate and demography (5).”
Livestock: On our plates or eating at our table? A new analysis of the feed/food debate (2017, background): “Livestock distribution based on Gridded Livestock of the World (Robinson et al., 2014).”
How do you find the green sheep? A critical review of the use of remotely sensed imagery to detect and count animals (2018, background): “Kadlec & Drury, 1968; Leonard & Fish, 1974; Löffler & Margules, 1980), studies generally have used indirect measures or surrogates based on an animal’s ecology to predict population abundances and distributions, or environmental proxies related to their presence (e.g. LaRue et al., 2014; Lynch et al”
Mapping global patterns of drought risk: An empirical framework based on sub-national estimates of hazard, exposure and vulnerability (2016, methodology): “The freely accessible maps are created through the spatial disaggregation of sub-national statistical data based on empirical relationships with environmental variables in similar agro-ecological zones (Robinson et al., 2014).”
Global hotspots and correlates of emerging zoonotic diseases (2017, methodology): “We used the Gridded Livestock of the World (GLW) data set 47 , which contains data for poultry, goat, buffalo, cattle, sheep, and pig headcounts.”
Managing the middle: A shift in conservation priorities based on the global human modification gradient (2019, methodology): “For agriculture, the Unified Cropland Layer (Waldner et al., 2016) provided our cropland estimates, while the Gridded Livestock of the World v2 database (Robinson et al., 2014) identified livestock densities.”
Drivers of changes in agricultural intensity in Europe (2016, background): “While progress has recently been made in mapping spatial patterns of agricultural intensity (see Fritz et al. (2015) for global cropland and field size, Estel et al. (2016) for cropland-use intensity in Europe, Robinson et al. (2014) for the global distribution of livestock, Temme and Verburg (2011)”
Evidence based review: positive versus negative effects of livestock grazing on wildlife. What do we really know? (2016, background): “Far fewer studies have been done in the developing world, in Africa, Asia, and Central and South America, even though these regions support large livestock populations and many people in these regions rely on livestock for their livelihoods (Robinson et al 2014).”
Mapping human pressures on biodiversity across the planet uncovers anthropogenic threat complexes (2020, methodology): “We also included data on cattle density, which was based on subnational livestock data that were statistically downscaled using multiple predictors (Robinson et al., 2014).”