2014/08/19 by Phillip Schumm, Caterina Scoglio, Schumm, Phillip +5
Agricultural and Biological Sciences · Biochemistry, Genetics and Molecular Biology · Environmental Science · Veterinary · #Animal Behavior and Welfare Studies #Animal Disease Management and Epidemiology #Applications (stat.AP) #FOS: Computer and information sciences #Genetic and phenotypic traits in livestock #Wildlife Ecology and Conservation
paper · pdf · doi:10.48550/arxiv.1408.4383
openalex publication_date 2014/08/19 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
The characterization of cattle demographics and especially movements is an\nessential component in the modeling of dynamics in cattle systems, yet for\ncattle systems of the United States (US), this is missing. Through a\nlarge-scale maximum entropy optimization formulation, we estimate cattle\nmovement parameters to characterize the movements of cattle across 10 Central\nStates and 1034 counties of the United States. Inputs to the estimation\nproblem are taken from the United States Department of Agriculture National\nAgricultural Statistics Service database and are pre-processed in a pair of\ntightly constrained optimization problems to recover non-disclosed elements of\ndata. We compare stochastic subpopulation-based movements generated from the\nestimated parameters to operation-based movements published by the United\nStates Department of Agriculture. For future Census of Agriculture\ndistributions, we propose a series of questions that enable improvements for\nour method without compromising the privacy of cattle operations. Our novel\nmethod to estimate cattle movements across large US regions characterizes\ncounty-level stratified subpopulations of cattle for data-driven livestock\nmodeling. Our estimated movement parameters suggest a significant risk level\nfor US cattle systems.\n