期刊
AGRICULTURAL AND FOREST METEOROLOGY
卷 170, 期 -, 页码 67-78出版社
ELSEVIER
DOI: 10.1016/j.agrformet.2011.09.005
关键词
Climatic suitability; Modeling; Impacts; Adaptation; EcoCrop; Sorghum
资金
- CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS)
Climate has been changing in the last three decades and will continue changing regardless of any mitigation strategy. Agriculture is a climate-dependent activity and hence is highly sensitive to climatic changes and climate variability. Nevertheless, there is a knowledge gap when agricultural researchers intend to assess the production of minor crops for which data or models are not available. Therefore, we integrated the current expert knowledge reported in the FAO-EcoCrop database, with the basic mechanistic model (also named EcoCrop), originally developed by Hijmans et al. (2001). We further developed the model, providing calibration and evaluation procedures. To that aim, we used sorghum (Sorghum bicolor Moench) as a case study and both calibrated EcoCrop for the sorghum crop and analyzed the impacts of the SRES-A1B 2030s climate on sorghum climatic suitability. The model performed well, with a high true positive rate (TPR) and a low false negative rate (FNR) under present conditions when assessed against national and subnational agricultural statistics (min TPR = 0.967, max FNR = 0.026). The model predicted high sorghum climatic suitability in areas where it grows optimally and matched the sorghum geographic distribution fairly well. Negative impacts were predicted by 2030s. Vulnerabilities in countries where sorghum cultivation is already marginal are likely (with a high degree of certainty): the western Sahel region, southern Africa, northern India, and the western coast of India are particularly vulnerable. We highlight the considerable opportunity of using EcoCrop to assess global food security issues, broad climatic constraints and regional crop-suitability shifts in the context of climate change and the possibility of coupling it with other large-area approaches. (c) 2011 Elsevier B.V. All rights reserved.
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