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How will climate change spatially affect agriculture production in Ethiopia? Case studies of important cereal crops

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Abstract

Nearly all of Ethiopia’s agriculture is dependent on rainfall, particularly the amount and seasonal occurrence. Future climate change predictions agree that changes in rainfall, temperature, and seasonality will impact Ethiopia with dramatic consequences. When, where, and how these changes will transpire has not been adequately addressed. The objective of our study was to model how projected climate change scenarios will spatially and temporally impact cereal production, a dietary staple for millions of Ethiopians. We used Maxent software fit with crop data collected from household surveys and bioclimatic variables from the WorldClim database to develop spatially explicit models of crop production in Ethiopia. Our results were extrapolated to three climate change projections (i.e., Canadian Centre for Climate Modeling and Analysis, Hadley Centre Coupled Model v3, and Commonwealth Scientific and Industrial Research Organization), each having two emission scenarios. Model evaluations indicated that our results had strong predictability for all four cereal crops with area under the curve values of 0.79, 0.81, 0.79, and 0.83 for teff, maize, sorghum, and barley, respectively. As expected, bioclimatic variables related to rainfall were the greatest predictors for all four cereal crops. All models showed similar decreasing spatial trends in cereal production. In addition, there were geographic shifts in land suitability which need to be accounted for when assessing overall vulnerability to climate change. The ability to adapt to climate change will be critical for Ethiopia’s agricultural system and food security. Spatially explicit models will be vital for developing early warning systems, adaptive strategies, and policy to minimize the negative impacts of climate change on food production.

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Abbreviations

IPCC:

Intergovernmental Panel on Climate Change

Maxent:

Maximum Entropy

EASE:

Ethiopian Agriculture Sample Enumeration

GIS:

Geographic Information Systems

CCCMA:

Canadian Centre for Climate Modeling and Analysis

HadCM3:

Hadley Centre Coupled Model v3

CSIRO:

Commonwealth Scientific and Industrial Research Organization

AUC:

Area under the curve

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Acknowledgments

The authors would like to thank The Murulle Foundation and Project Mercy for research support; particularly, Ato Bete Demeke for initiating this important project. We also thank our colleagues at the Natural Resource Ecology Laboratory at Colorado State University and the US Geological Survey at the Fort Collins Science Center for their added expertise and suggestions. Lastly, we thank A. Randell and A. Birtwhistle for editorial comments and suggestions. To all, we are grateful.

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Author notes

  1. Jonathan Burnett

    Present address: Department of Forest Engineering, Resources and Management, College of Forestry, Oregon State University, 280 Peavy Hall, Corvallis, OR, 97331, USA

Authors and Affiliations

  1. Natural Resource Ecology Laboratory, B254 NESB, Colorado State University, Fort Collins, CO, 80524-1499, USA

    Paul Evangelista, Nicholas Young & Jonathan Burnett

Authors
  1. Paul Evangelista
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  2. Nicholas Young
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Correspondence to Paul Evangelista.

Appendices

Appendices

Table 2 Predicted areas (in square kilometers) for teff production using (1) historic 50-year climate averages and (2) three future climate projections (i.e., HadCM3, CCCMA, and CSIRO) averaged and independently
Full size table
Table 3 Predicted areas (in square kilometers) for maize production using (1) historic 50-year climate averages and (2) three future climate projections (i.e., HadCM3, CCCMA, and CSIRO) averaged and independently
Full size table
Table 4 Predicted areas (in square kilometers) for sorghum production using (1) historic 50-year climate averages and (2) three future climate projections (i.e., HadCM3, CCCMA, and CSIRO) averaged and independently
Full size table
Table 5 Predicted areas (in square kilometers) for barley production using (1) historic 50-year climate averages and (2) three future climate projections (i.e., HadCM3, CCCMA, and CSIRO) averaged and independently
Full size table

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Evangelista, P., Young, N. & Burnett, J. How will climate change spatially affect agriculture production in Ethiopia? Case studies of important cereal crops. Climatic Change 119, 855–873 (2013). https://doi.org/10.1007/s10584-013-0776-6

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