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A geographically scaled analysis of adaptation to climate change with spatial models using agricultural systems in Africa

Published online by Cambridge University Press:  25 March 2011

S. N. SEO*
Affiliation:
Faculty of Agriculture, Food and Natural Resources, The University of Sydney, Australia
*
To whom all correspondence should be addressed. Email: niggol.seo@sydney.edu.au

Summary

The present paper provides a geographically scaled analysis of adaptation to climate change using adoption of agricultural systems observed across Africa. Using c. 9000 farm surveys, spatial logit models were applied to explain observed agricultural system choices by climate variables after accounting for soils, geography and other household characteristics. The results reveal that strong neighbourhood effects exist and a spatial re-sampling and bootstrapping approach can remove them. The crops-only system is adopted most frequently in the lowland humid forest, lowland sub-humid, mid-elevation sub-humid Agro-Ecological Zones (AEZs) and in the highlands in the east and in southern Africa. Integrated farming is favoured in the lowland dry savannah, moist savannah and semi-arid zones in West Africa and eastern coastal zones. A livestock-only system is favoured most in the mid/high-elevation moist savannahs located in southern Africa. Under a hot and dry Canadian Climate Centre (CCC) scenario, the crops-only system should move out from the currently favoured regions of humid zones in the lowlands towards the mid-/high elevations. It declines by more than 5% in the lowland savannahs. Integrated farming should increase across all the AEZs by as much as 5%, but less so in the deserts or in the humid forest zones in the mid-/high elevations. A livestock-only system should increase by 2–5% in the lowland semi-arid, dry savannah and moist savannah zones in the lowlands. Adaptation measures should be carefully scaled, up or down, considering geographic and ecological differentials as well as household characteristics, as proposed in the present study.

Type
Climate Change and Agriculture
Copyright
Copyright © Cambridge University Press 2011

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References

Adams, R., Mccarl, B., Segerson, K., Rosenzweig, C., Bryant, K., Dixon, B., Connor, R., Evenson, R. & Ojima, D. (1999). The economic effects of climate change on US agriculture. In The Impact of Climate Change on the United States Economy (Eds Mendelsohn, R. & Neumann, J.), pp. 1854. Cambridge: Cambridge University Press.CrossRefGoogle Scholar
Anderson, K. & Masters, W. A. (2009). Distortions to Agricultural Incentives in Africa. Washington, DC: World Bank.CrossRefGoogle Scholar
Anselin, L. (1988). Spatial Econometrics: Methods and Models. Dordrecht, The Netherlands: Kluwer Academic Publishers.CrossRefGoogle Scholar
Antle, J. M., Capalbo, S. M., Elliott, E. T. & Paustian, K. H. (2004). Adaptation, spatial heterogeneity and the vulnerability of agricultural systems to climate change and CO2 fertilization: an integrated assessment approach. Climatic Change 64, 289315.CrossRefGoogle Scholar
Basist, A., Grody, N. C., Peterson, T. C. & Williams, C. N. (1998). Using the Special Sensor Microwave Imager to monitor land surface temperature, wetness, and snow cover. Journal of Applied Meteorology 37, 888911.2.0.CO;2>CrossRefGoogle Scholar
Beron, K. J. & Vijverberg, W. P. M. (2004). Probit in a spatial context: a Monte Carlo approach. In Advances in Spatial Econometrics: Methodology, Tools and Applications (Eds Anselin, L., , R. J. G. M. Florax, & Rey, S. J.), pp. 169192. Heidelberg, Germany: Springer-Verlag.CrossRefGoogle Scholar
Boer, G. J., Flato, G. & Ramsden, D. (2000). A transient climate change simulation with greenhouse gas and aerosol forcing: projected climate for the 21st Century. Climate Dynamics 16, 427450.CrossRefGoogle Scholar
Boko, M., Niang, I., Nyong, A., Vogel, C., Githeko, A., Medany, M., Osman-Elasha, B., Tabo, R. & Yanda, R. (2007). Africa. In Contribution of Working Group II to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change (Eds Parry, M. L., Canziani, O. F., Palutikof, J. P., van der Linden, P. J. & Hanson, C. E.), pp. 433467. Cambridge: Cambridge University Press.Google Scholar
Butt, T. A., Mccarl, B. A., Angerer, J., Dyke, P. T. & Stuth, J. W. (2005). The economic and food security implications of climate change in Mali. Climatic Change 68, 355378.CrossRefGoogle Scholar
Byerlee, D. & Eicher, C. K. (1997). Africa's Emerging Maize Revolution. Boulder, CO: Lynne Rienner Publishers Inc.CrossRefGoogle Scholar
Case, A. (1992). Neighborhood influence and technological change. Regional Science and Urban Economics 22, 491508.CrossRefGoogle Scholar
Cline, W. R. (1996). The impact of global warming on agriculture: comment. American Economic Review 86, 13091311.Google Scholar
Cressie, N. A. C. (1993). Statistics for Spatial Data. New York: John Wiley & Sons.CrossRefGoogle Scholar
Deressa, T. T., Hassan, R. M. & Ringler, C. (2010). Perception of and adaptation to climate change by farmers in the Nile basin of Ethiopia. The Journal of Agricultural Science, Cambridge 149, 2331.CrossRefGoogle Scholar
Dinar, A., Hassan, R., Mendelsohn, R. O. & Benhin, J. (2008). Climate Change and Agriculture in Africa: Impact Assessment and Adaptation Strategies. London: EarthScan.Google Scholar
Efron, B. (1979). Bootstrap methods: another look at the jackknife. The Annals of Statistics 7, 126.CrossRefGoogle Scholar
Efron, B. & Tibshirani, R. J. (1994). An Introduction to the Bootstrap. Boca Raton, FL: Chapman & Hall/CRC.CrossRefGoogle Scholar
Eitzinger, J., Orlandini, S., Stefanski, R. & Naylor, R. E. L. (2010). Climate change and agriculture: introductory editorial. The Journal of Agricultural Science, Cambridge 148, 499500.CrossRefGoogle Scholar
Evenson, R. E. & Gollin, D. (2003). Assessing the impact of the Green Revolution 1960–2000. Science 300, 758762.CrossRefGoogle Scholar
Food and Agriculture Organization (FAO). (2003). The Digital Soil Map of the World (DSMW) CD-ROM. Rome. Available online at: http://www.fao.org/geonetwork/srv/en/metadata.show?id=14116 (verified 19 Jan 2011).Google Scholar
Food and Agriculture Organization (FAO). (2005). Global Agro-ecological Assessment for Agriculture in the Twenty-first Century (CD-ROM). FAO Land and Water Digital Media Series. Rome: FAO.Google Scholar
Ford, J. & Katondo, K. M. (1977). Maps of tsetse fly (Glossina) distribution in Africa, 1973, according to sub-generic groups on a scale of 1:5 000 000. Bulletin of Animal Health and Production in Africa 15, 187193.Google Scholar
Gitay, H., Brown, S., Easterling, W. & Jallow, B. (2001). Ecosystems and their goods and services. In Climate Change 2001: Impacts, Adaptations, and Vulnerabilities (Eds McCarthy, J. J., Canziani, O. F., Leary, N. A., Dokken, D. J. & White, K. S.), pp. 237342. Cambridge: Cambridge University Press.Google Scholar
Hahn, G. L. (1999). Dynamic responses of cattle to thermal heat loads. Journal of Animal Science 77, 1020.CrossRefGoogle ScholarPubMed
Hulme, M., Doherty, R. M., Ngara, T., New, M. G. & Lister, D. (2001). African climate change: 1900–2100. Climate Research 17, 145168.CrossRefGoogle Scholar
Intergovernmental Panel on Climate Change (IPCC). (2000). Special Report on Emissions Scenarios. Cambridge: Cambridge University Press.Google Scholar
Johnson, H. D. (1965). Response of animals to heat. Meteorological Monographs 6, 109122.Google Scholar
Kelly, D. L., Kolstad, C. D. & Mitchell, G. T. (2005). Adjustment costs from environmental change. Journal of Environmental Economics and Management 50, 468495.CrossRefGoogle Scholar
Lobell, D. B. & Field, C. B. (2008). Estimation of the carbon dioxide (CO2) fertilization effect using growth rate anomalies of CO2 and crop yields since 1961. Global Change Biology 14, 3945.CrossRefGoogle Scholar
Mader, T. L. (2003). Environmental stress in confined beef cattle. Journal of Animal Science 81 (E Suppl. 2), E110E119.Google Scholar
Mcfadden, D. (1974). Conditional logit analysis of qualitative choice behavior. In Frontiers in Econometrics (Ed. Zarembka, P.), pp. 105142. New York: Academic Press.Google Scholar
Mendelsohn, R. O., Dinar, A. & Williams, L. (2006). The distributional impact of climate change on rich and poor countries. Environment and Development Economics 11, 159178.CrossRefGoogle Scholar
Nordhaus, W. (2008). A Question of Balance: Weighing the Options on Global Warming Policies. New Haven, CT: Yale University Press.CrossRefGoogle Scholar
Parry, M. L., Canziani, O. F., Palutikof, J. P., Van Der Linden, P. J. & Hanson, C. E. (2007). Climate Change 2007: Impacts, Adaptations, and Vulnerability. Contribution of Working Group II to the Fourth Assessment Report of the IPCC. Cambridge: Cambridge University Press.Google Scholar
Parry, M. L., Rosenzweig, C. P., Iglesias, A., Livermore, M. & Fischer, G. (2004). Effects of climate change on global food production under SRES emissions and socioeconomic scenarios. Global Environmental Change 14, 5367.CrossRefGoogle Scholar
Polley, H. W., Morgan, J. A. & Fay, P. A. (2011). Application of a conceptual framework to interpret variability in rangeland responses to atmospheric CO2 enrichment. The Journal of Agricultural Science, Cambridge 149, 114.CrossRefGoogle Scholar
Reilly, J., Baethgen, W., Chege, F. E., van de Geijn, S. C., Erda, L., Iglesias, A., Kenny, G., Patterson, D., Rogasik, J., Rotter, R., Rosenzweig, C., Sombroek, W., Westbrook, J., Bachelet, D., Brklacich, M., Dammgen, U., Howden, M., Joyce, R. J. V., Lingren, P. D., Schimmelpfennig, D., Singh, U., Sirotenko, O. & Wheaton, E. (1996). Agriculture in a changing climate: impacts and adaptations. In Climate Change 1995: Impacts, Adaptations, and Mitigation of Climate Change: Scientific-Technical Analyses (Eds Watson, R. T., Zinyowera, M. C., Moss, R. H. & Dokken, D. J.), pp. 427468. Cambridge: Cambridge University Press.Google Scholar
Sankaran, M., Hanan, N. P., Scholes, R. J., Ratnam, J., Augustine, D. J., Cade, B. S., Gignoux, J., Higgins, S. I., Le Roux, X., Ludwig, F., Ardo, J., Banyikwa, F., Bronn, A., Bucini, G., Caylor, K. K., Coughenour, M. B., Diouf, A., Ekaya, W., Feral, C. J., February, E. C., Frost, P. G. H., Hiernaux, P., Hrabar, H., Metzger, K. L., Prins, H. H. T., Ringrose, S., Sea, W., Tews, J., Worden, J. & Zambatis, N. (2005). Determinants of woody cover in African savannas. Nature 438, 846849.CrossRefGoogle ScholarPubMed
Schlenker, W. & Roberts, M. J. (2009). Nonlinear temperature effects indicate severe damages to U. S. crop yields under climate change. Proceedings of National Science of Academy of the United States 106, 1559415598.CrossRefGoogle Scholar
Schultz, T. P. (2004). Evidence of returns to schooling in Africa from household surveys: monitoring and restructuring the market for education. Journal of African Economies 13(Suppl. 2), ii95ii148.CrossRefGoogle Scholar
Seo, S. N. (2010). Is an integrated farm more resilient against climate change? A micro-econometric analysis of portfolio diversification in African agriculture. Food Policy 35, 3240.CrossRefGoogle Scholar
Seo, S. N. & Mendelsohn, R. (2008). Measuring impacts and adaptations to climate change: a structural Ricardian model of African livestock management. Agricultural Economics 38, 151165.Google Scholar
Seo, S. N., Mendelsohn, R., Dinar, A., Hassan, R. & Kurukulasuriya, P. (2009). A Ricardian analysis of the distribution of climate change impacts on agriculture across Agro-Ecological Zones in Africa. Environmental and Resource Economics 43, 313332.CrossRefGoogle Scholar
Smit, B. & Pilifosova, O. (2001). Adaptation to climate change in the context of sustainable development and equity. In Climate Change 2001: Impacts, Adaptation, and vulnerability – Contribution of Working Group II to the Third Assessment Report of the Intergovernmental Panel on Climate Change (Eds McCarthy, J. J., Canziani, O. F., Leary, N. A., Dokken, D. J. & White, K. S.), pp. 877912. Cambridge: Cambridge University Press.Google Scholar
Smith, P. & Olesen, J. E. (2010). Synergies between the mitigation of, and adaptation to, climate change in agriculture. The Journal of Agricultural Science, Cambridge 148, 543552.CrossRefGoogle Scholar
Solomon, S., Qin, D., Manning, M., Marquis, M., Averyt, K. B., Tignor, M., Miller, H. L. & Chen, Z. (2007). Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the IPCC. Cambridge: Cambridge University Press.Google Scholar
Strzepek, K. & Mccluskey, A. (2006). District Level Hydroclimatic Time Series and Scenario Analyses to Assess the Impacts of Climate Change on Regional Water Resources and Agriculture in Africa. CEEPA Discussion Paper No. 13. Pretoria, Republic of South Africa: Centre for Environmental Economics and Policy in Africa, University of Pretoria.Google Scholar
Tobin, J. (1958). Liquidity preference as behavior towards risk. Review of Economic Studies 25, 6586.CrossRefGoogle Scholar
University of Georgia, College of Veterinary Medicine. (2007). Foreign Animal Diseases: The Gray Book. St, Joseph, MO: USAHA.Google Scholar
USGS (United States Geological Survey). (2004). Global 30 Arc Second Elevation Data. Reston, VA: USGS National Mapping Division, EROS Data Centre. Available online at: http://eros.usgs.gov/#/Find_Data/Products_and_Data_Available/gtopo30_info (verified 19 Jan 2011).Google Scholar
Washington, W. M., Weatherly, J. W., Meehl, G. A., Semtner, A. J. Jr., Bettge, T. W., Craig, A. P., Strand, W. G. Jr., Arblaster, J., Wayland, V. B., James, R. & Zhang, Y. (2000). Parallel climate model (PCM): control and transient scenarios. Climate Dynamics 16, 755774.CrossRefGoogle Scholar
World Bank (2003). Africa Rainfall and Temperature Evaluation System (ARTES). Washington, DC: World Bank.Google Scholar
World Bank (2008). World Development Report 2008: Agriculture for Development. Washington, DC: World Bank.Google Scholar
World Bank (2009). Africa Infrastructure and Country Diagnostics (AICD). Washington, DC: World Bank. Available online at: siteresources.worldbank.org/INTAFRICA/Resources/AICD_exec_summ_9-30-08a.pdf (verified 19 Jan 2011).Google Scholar