Page 112 - Climate Change and Food Systems

climate change and food systems: global assessments and implications for food security and trade
combine field trials with the APSIM model to investigates optimum nitrogen applications in millet production in the Sahel and conclude that moderate nitrogen application (15 kilograms of nitrogen/hectare) improves both the long-term average and the minimum yearly guaranteed yield without increasing inter-annual variability compared to no N input. Although average yields are lower than with higher nitrogen
rates, moderate rates are more appropriate
for smallholder, subsistence farmers, as they guarantee higher minimum yields in worst years, thereby reducing their vulnerability. Rurinda et al. (2014) also examine maize and small grains in Southern Africa and conclude that given the superior maize yields over small grains (finger millet, sorghum), substituting maize with small grains is not a robust option for adaptation to increased temperatures and more frequent droughts likely to be experienced in Zimbabwe.
The issue of irrigation management under climate risk is also receiving closer scrutiny. Grove and Oosthuizen (2010) develop
an expected utility optimization model to economically evaluate deficit irrigation within a multi-crop setting while taking into account the increasing production risk of deficit irrigation
in South Africa. To account for future water supply limitations and the resulting crop yield variability, the authors include multiple irrigation schedules into the South African Plant WATer (SAPWAT) optimization model. They use stochastic budgeting procedures to generate gross margins necessary to incorporate risk into the water use optimization model. The authors apply the model to study the impact
of increasing levels of risk aversion on the profitability of deficit irrigation under limited water supply conditions. The authors conclude that although deficit irrigation was stochastically more efficient than full irrigation under limited water supply conditions, irrigation farmers would not willingly choose to conserve water through deficit irrigation and would be expected to be compensated to do so. Deficit irrigation would not save water if the water that was
saved through deficit irrigation were used to plant larger areas to increase the overall profitability of the strategy.
Risk management and the role of climate- based risk insurance is an established research area and is receiving renewed interest in light of climate change. Hansen et al. (2009) apply the APSIM model (Helms et al., 1990) to provide detailed climatic risk analyses at household level and to study the effectiveness of crop insurance.15 Hansen et al. examined the potential use and
value of seasonal forecasts downscaled from
a GCM and the risk implications of smallholder farmers in Kenya responding to forecasts. The authors estimate the potential value of GCM-based seasonal precipitation forecasts for maize planting and fertilizer management decisions under profit maximization assumptions in Kenya. The authors reported the first quantitative test of the hypothesis that profit-maximizing use of seasonal forecasts can increase the exposure of smallholder farmers to risk. Under the study simplifying assumptions, the authors find that the risk from ignoring forecasts is greater than the risk associated with responding to forecasts, and the concern that
the risk of a “wrong forecast” is a disincentive to risk-averse farmers is not supported. The authors conclude that under more realistic assumptions, appropriate use of seasonal climate forecasts would not increase farmers’ risk exposure, although communication failures that distort information about forecast uncertainty could. However, given the limited representativeness of the sites analysed and the simplified assumptions, the authors recommend further validation of the research.
15 While insurance can be used to mitigate against
risk and climate uncertainty, due to moral hazard, purchasing insurance may also reduce adaptation
or increase maladaptation (Kunreuther and Roth, 1998; Rao and Hess (2009). This can happen when insurance is not fully risk adjusted, as is the case when local or state regulations do not allow insurance rates to be risk-adjusted (Collier et al., 2009). Under- insurance can also arise when agents expect that
the public sector will provide disaster assistance (the so-called Samaritan’s dilemma) (Gibson et al., 2005; Raschky et al., 2013).
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