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Faculty of Mathematics and Natural Sciences - Biogeography

Cattle systems in Dry Chaco

 

Pedro D. Fernández, Tobias Kuemmerle, Matthias Baumann, H. Ricardo Grau, José A. Nasca, Alejandro Radrizzani & N. Ignacio Gasparri

 

Summary: Cattle production has major impacts on the environment, but these impacts vary depending on the cattle production systems. Data on these systems are notoriously scarce, which is a real obstacle for context-specific impact assessments and spatial planning. Here, we developed a novel approach that combines vaccination data, which contains detailed information on the location and composition of cattle herds, with fine-scale land-cover information to map cattle production systems.

 

Abstract: Impacts of cattle production vary among different production systems, but data on their distribution is scarce for most world regions. In this work, we combine datasets on cattle vaccination locations and land cover in a regression framework to define and map major cattle production systems in the Argentinean Dry Chaco. We also explore how cattle occurrence relates to spatial determinants. Results indicate that the region harbors about 5.5million heads. Cattle density was mainly described by the share of pasture (69.9%), cropland (28.1%) and aridity (23.8%). We identified 12-major cattle production systems: six cow-calf, three whole-cycle, and three fattening systems. Of these, four systems had high woodland cover (>85%). Data generated is available in a website. Understanding the distribution of cattle production systems is important to assess the environmental impacts of beef production at broad scales. Integrating vaccination data with land-cover information provides a promising avenue to identify livestock systems.

 

Link to the manuscript: DOI: 10.1080/1747423X.2020.1720843

 

Citation: Pedro D. Fernández, Tobias Kuemmerle, Matthias Baumann, H. Ricardo Grau, José A. Nasca, Alejandro Radrizzani & N. Ignacio Gasparri (2020): Understanding the distribution of cattle production systems in the South American Chaco, Journal of Land Use Science, DOI: 10.1080/1747423X.2020.1720843