Indian Journal of Animal Research

  • Chief EditorK.M.L. Pathak

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Indian Journal of Animal Research, volume 50 issue 4 (august 2016) : 569-579

Geographic distribution of livestock products in China- an application of spatial autocorrelation analysis

Ling Gan, Xisheng HU*1
1<p>Department of Veterinary Medicine, Rongchang Campus,&nbsp;Southwest University, Chongqing, 402460, China.</p>
Cite article:- Gan Ling, HU*1 Xisheng (2016). Geographic distribution of livestock products in China- anapplication of spatial autocorrelation analysis . Indian Journal of Animal Research. 50(4): 569-579. doi: 10.18805/ijar.9367.

The rapid increase in the livestock industry in China in recent two decades has played an important role in the livelihoods of people and has become a very significant issue in terms of sustainable animal food supply chains. Knowledge gaps in the geographic distribution may hinder the sustainable development of livestock industry. This paper investigates the spatial distribution in the outputs of livestock products (meat, milk and egg, respectively) in China using exploratory spatial data analysis. This method is a set of GIS spatial statistical techniques that are useful in describing and visualizing the spatial distribution, detecting patterns of hot-spots, and suggesting spatial regimes. The global Moran’s I statistics for the three products reveal strong positive and significant spatial autocorrelation. Furthermore, the Moran significance maps indicate four hot-spots (North-eastern cluster, Northern Coast cluster, Central Inland cluster and Southern cluster) and one cold-spot (Western cluster) in the meat product distribution, one large hot-spot (Northern cluster) and one large cold-spot (South-central cluster) for the milk product, four relatively small hot-spots (North-eastern cluster, Northern Coast cluster, Eastern Coast cluster and Central Inland cluster) and one large cold-spot (Western cluster) for the egg product. Based on the results, we show that livestock products are polarized into clusters and the outputs of the products tend to be reducing from east to west and from north to south China. Implications are drawn, such as priority of resource allocations for hot-spot area in terms of animal-source food security and the utilization of spillover effects from hot-spots.

  1. Anselin, L. (1995). Local indicators of spatial association: LISA. Geogr. Anal. 27: 93-115.

  2. Anselin, L. (1999). Interactive techniques and exploratory spatial data analysis, in: P. A. Longley, M. F. Godchild & D. J. Maguire (Eds) Geographical Information Systems. New York: John Wiley & Sons.

  3. Anselin, L. (2003). Spatial externalities, spatial multipliers, and spatial econometrics. Int. Regional Sci. Rev. 26: 153-166.

  4. Anselin, L. and Rey, S.J. (1997). Introduction to the special issue on spatial econometrics. Int. Regional Sci. Rev. 20: 1-7.

  5. Anselin, L., Syabri, I. and Kho, Y. (2006). GeoDa: an introduction to spatial data analysis. Geogr. Anal. 38: 5-22.

  6. Bryssinckx, W., Ducheyne, E., Muhwezi, B., Godfrey, S., Mintiens, K., Leirs, H. and Hendrickx, G. (2012). Improving the accuracy of livestock distribution estimates through spatial interpolation. Geospatial Health, 7: 101-109. 

  7. Butler, D. (2013). Mapping the H7N9 avian flu outbreaks. Nature, 24, doi:101038/nature201312863.

  8. Cecchi, G., Wint, W., Shaw, A., Marletta, A., Mattioli, R. and Robinson, T. (2010). Geographic distribution and environmental characterization of livestock production systems in Eastern Africa. Age. Ecosyst. Environ. 135: 98-110. 

  9. Cho, S.H., Chen, Z. and Poudyal, N.C. (2010). Spatial structure of agricultural production in China. Appl. Econ. 

  10. 42: 2031-2040.

  11. Cracolici, M.F., Cuffaro, M. and Nijkamp, P. (2009). A spatial analysis on Italian unemployment differences. Stat. Method. Appl. 18: 275-291.

  12. Eisler, M.C., Lee, M.R.F., Tarlton, J.F., Martin, G.B., Beddington, J., Dungait, J.A.J., Greathead, H., Liu, J.X., Mathew, S., Miller, H., Misselbrook, T., Murray, P., Vinod, V.K., Saun, R.V. and Winter, M. (2014). Agriculture: Steps to sustainable livestock. Nature, 507: 32-34.

  13. Fotheringham, A.S., Brunsdon, C. and Charlton, M. (2003). Geographically weighted regression: the analysis of spatially varying relationships. New York: John Wiley & Sons.

  14. Fu, Q., Zhu, Y.Q., Kong, Y.F. and Sun, J.L. (2012). Spatial analysis and districting of the livestock and poultry breeding in China. J. Geogr. Sci. 22: 1079-1100.

  15. Gao, D., Chen, T.B., Liu, B., Zheng, Y.M., Zheng, G.D. and Li, Y.X. (2006). Releases of pollutants from poultry manure in China and recommended strategies for the pollution prevention. Geogr. Res. 25: 311-319. (in Chinese with English abstract)

  16. Gilbert, M., Mitchell, A.., Bourn, D., Mawdsley, J., Clifton-Hadley, R. and Wint, W. (2005). Cattlemovements and bovine tuberculosis in Great Britain. Nature, 435: 491-496.

  17. Godber, O.F. and Wall, R. (2014). Livestock and food security: vulnerability to population growth and climate change. Global Change Biol. 20: 3092-3102.

  18. Hobololo, V.L. (2009). Spatial distribution of blackfly (Diptera: Simuliildae) challenge for livestock farmers along the Vaal River, South Africa. J. S. Afr. Vet. Assoc. 80: 137-137.

  19. Janzen, H. (2011). What place for livestock on a re-greening earth? Anim. Feed Sci. Tech. 166: 783-796.

  20. Jefferson, B., Laine, A., Stephenson, T. and Judd, S.J. (2001). Advanced biological unit processes for domestic water recycling. Water Sci. Technol. 43: 211-218.

  21. Kabubo-Mariara, J. (2009). Global warming and livestock husbandry in Kenya: impacts and adaptations. Ecol. Econ. 68: 1915-1924.

  22. Kruska, R.L., Reid, R.S., Thornton, P.K., Henninger, N. and Kristjanson, P.M. (2003). Mapping livestock-oriented agricultural production systems for the developing world. Agr. Syst. 77: 39-63.

  23. Muzaffar, S.B., Takekawa, J.Y., Prosser, D.J., Newman, S.H. and Xiao, X. (2010). Rice production systems and avian influenza: Interactions between mixed-farming systems, poultry and wild birds. Waterbirds, 33: 219-230.

  24. Nahuelhual, L., Carmona, A., Lara, A., Echeverría, C. and González, M.E. (2012). Land-cover change to forest plantations: Proximate causes and implications for the landscape in south-central Chile. Landscape Urban Plan. 107: 12-20.

  25. National Bureau of Statistics. (2012). China Statistical Yearbook For Regional Economy. Beijing: China Statistics Press.

  26. Neumann, K., Elbersen, B.S., Verburg, P.H., Staritsky, I., Pérez-Soba, M., de Vries, W. and Rienks, W.A. (2009). Modelling the spatial distribution of livestock in Europe. Landscape Ecol. 24: 1207-1222.

  27. Orhan, H., Ozturk, I., Dogan, Z. and Yurtseven, S. (2009). Examining structural distribution of livestock in eastern and south-eastern Anatolia of Turkey by multivariate statistics. J. Anim. Vet. Adv. 8: 481-487.

  28. Ping, J. L., Green, C.J., Zartman, R.E. and Bronson, K.F. (2004). Exploring spatial dependence of cotton yield using global and local autocorrelation statistics. Field Crop. Res. 89: 219-236.

  29. Poudyal, N.C., Johnson-Gaither, C., Goodrick, S., Bowker, J.M. and Gan, J.B. (2012). Locating spatial variation in the association between wildland fire risk and social vulnerability across six southern states. Environ. Manage. 49: 623-635.

  30. Randolph, S.E. (2008). Dynamics of tick-borne disease systems: a minor role of recent climate change. Rev. Sci. Tech. Oie. 27: 367-381.

  31. Robinson, T.P. and Pozzi, F. (2011). Mapping supply and demand for animal-source foods to 2030. Animal Production and Health Working Paper No. 2. Rome: Food and Agriculture Organisation (FAO) of the United Nations. 164.

  32. Robinson, T.P., Wint, G.R., Conchedda, G., Van Boeckel, T.P., Ercoli, V., Palamara, E., Cinardi, G., D’Aietti, L., Hay, S.I. and Gilbert, M. (2014). Mapping the Global Distribution of Livestock. PLoS One, 9(5), e96084, doi: 10.1371/    journal.pone.0096084. eCollection 2014.

  33. Saizen, I., Maekawa, A. and Yamamura, N. (2010). Spatial analysis of time-series changes in livestock distribution by detection of local spatial associations in Mongolia. Appl. Geogr. 30: 639–649.

  34. Schmidhuber. J. and F.N. Tubiello. 2007. Global food security under climate change. PANAS. 104: 19703-19708.

  35. Thornton, P.K. and Gerber, P.J. (2010). Climate change and the growth of the livestock sector in developing countries. Mitig. Adapt. Strat. Gl. 15: 169-184.

  36. Verburg, P.H. and van Keulen, H. (1999). Exploring changes in the spatial distribution of livestock in China. Agr. Syst. 62: 51-67.

  37. Wall, R. and Ellse, L. (2011). Climate change and livestock parasites: integrated management of sheep blowfly strike in a warmer environment. Global Change Biol. 17: 1770-1777.

  38. Wint, G.R., Robinson, T.P., Bourn, D.M., Durr, P.A., Hay, S.I., Randolph, S.E., Rogers, D.J. (2002). Mapping bovine tuberculosis in Great Britain using environmental data. Trends. Microbiol. 10: 441-444.

  39. Wint, W. and Robinson, T. (2007). Gridded livestock of the world 2007. Aportes (Costa Rica). 129: 50-59.

  40. Yang, Y. and Wong, K.K. (2013). Spatial distribution of tourist flows to China’s cities. Tourism Geogr. 15: 338-363.

  41. Zhang, Y., Xu, J.H. and Zhuang, P.J. (2011). The spatial relationship of tourist distribution in Chinese cities. Tourism Geogr. 13: 75-90.

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