期刊
AGRICULTURE ECOSYSTEMS & ENVIRONMENT
卷 141, 期 3-4, 页码 381-389出版社
ELSEVIER SCIENCE BV
DOI: 10.1016/j.agee.2011.04.002
关键词
Poultry; China; Distribution modelling; Population estimates; GIS; Epidemiology
资金
- USGS
- U.S. National Institutes of Health through the NIH/NSF [R01-TW007869]
- NSF [OISE-0513222]
- China Ministry of Health [2008ZH1004-012]
- China Ministry of Science and Technology
Global concerns over the emergence of zoonotic pandemics emphasize the need for high-resolution population distribution mapping and spatial modelling. Ongoing efforts to model disease risk in China have been hindered by a lack of available species level distribution maps for poultry. The goal of this study was to develop I km resolution population density models for China's chickens, ducks, and geese. We used an information theoretic approach to predict poultry densities based on statistical relationships between poultry census data and high-resolution agro-ecological predictor variables. Model predictions were validated by comparing goodness of fit measures (root mean square error and correlation coefficient) for observed and predicted values for 1/4 of the sample data which were not used for model training. Final output included mean and coefficient of variation maps for each species. We tested the quality of models produced using three predictor datasets and 4 regional stratification methods. For predictor variables, a combination of traditional predictors for livestock mapping and land use predictors produced the best goodness of fit scores. Comparison of regional stratifications indicated that for chickens and ducks, a stratification based on livestock production systems produced the best results; for geese, an agro-ecological stratification produced best results. However, for all species, each method of regional stratification produced significantly better goodness of fit scores than the global model. Here we provide descriptive methods, analytical comparisons, and model output for China's first high resolution, species level poultry distribution maps. Output will be made available to the scientific and public community for use in a wide range of applications from epidemiological studies to livestock policy and management initiatives. Published by Elsevier B.V.
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