Agricultural adaptation to climate change in rich and poor countries: Current modeling practice and potential for empirical contributions☆
Introduction
The table has now been set for significant warming of the earth's surface in the coming decades. Climate change mitigation policies currently being debated will do little to alter the expected rate of warming over the next 20–30 years due to the momentum already in the energy and climate systems. The long-lived, carbon-intensive energy systems currently in place in the rapidly growing developing economies of the world, along with continued reliance on expansion of commercial land uses into carbon-rich natural environments, both serve to ensure that GHG concentrations in the atmosphere will rise in the near term. Current estimates suggest that increased radiative forcings will result in temperature increases on the order of 0.3–0.4 °C per decade in most agricultural regions to 2050. As we document here, such temperature increases are likely to threaten agricultural productivity growth — particularly in the tropics where the bulk of the world's poor currently reside and find their livelihoods.
The extent to which these climate impacts on agriculture translate into reductions in human welfare will depend critically on the ability of farmers, agri-businesses, regional and national economies to adapt to these climate-driven changes. Yet adaptation potential is critically dependent on access to markets, as well as the information and credit needed to develop and deploy new technologies. Unfortunately, such access is often missing in the poorest economies. Indeed, their poverty can often be traced back to missing markets, incomplete information and the inability to borrow the money needed for farming operations as elementary as fertilizer applications. So we confront a situation in which climate impacts on agriculture are expected to be most severe precisely in those regions where households are least well-equipped to deal with them. Therefore, understanding the potential for agricultural adaptation to climate change is critical in determining how such changes will affect global poverty, food security and the environmental well-being of the planet for decades to come.
Section snippets
Assessing the scope of the adaptation challenge: climate impacts on agriculture
Before discussing the nature and scale of necessary adaptations to climate change, one must consider the various reasons that climate change poses a risk to agriculture. Climate risks, in the form of intra- and inter-season variability, have always presented a challenge to farmers. Droughts, frosts, floods, heat waves, hail storms, and other extremes are familiar worries. Indeed, natural climate variability causes so many losses, and is so high on the list of current concerns to farmers, that
Thinking about adaptation
Fig. 1, reproduced from Antle and Capalbo (2010), does a nice job of illustrating some of the key concepts associated with adaptation. This figure shows the expected value (given uncertainty associated with weather under a given climate) of a given production system, at a given location, as a function of management intensity, x, which serves as a proxy for the application of seeds, nutrients, water, energy and labor within a given production system or technology, denoted by τA, and conditional
Overview of the modeling landscape
Integrated Assessment Models (henceforth IAMs) seek to combine, into a unified framework, representations of the climate and earth systems together with models of social and economic behavior in order to capture both the societal impacts of climate change and the costs of mitigating the greenhouse gas emissions contributing to such change. The economics-oriented IAMs utilize this interplay between natural and human systems to characterize the ‘optimal’ carbon tax or mitigation pathway — trading
Critical assessment and opportunities for empirical contributions
Overall, our view of the literature in agriculture suggests that there is substantial risk of overstating adaptation potential — especially in poor countries. These model biases exist partly because the costs of adaptation are often ignored, and also because models tend to ignore the biophysical, institutional, economic, informational, and social constraints that prevent adaptation from happening. One could argue that many of these constraints mainly affect the time lag associated with
Summary and conclusions
In their survey of adaptation in IAMs, Patt et al. (2010) make the case that such models are very likely to overstate producers' adaptation response to climate change. Firstly, they suggest that most adaptation occurs in response to extreme events, as opposed to gradual climate change, which is much harder to detect. In this context, they also cite the psychology/behavioral economics literature which suggests that individuals have a difficult time dealing with decisions involving low
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Paper prepared for the NBER workshop on “Climate Adaptation: Improving the connection between empirical research and integrated assessment models”, Cambridge, MA, May 17–18, 2012. Currently under review with Energy Economics. Hertel acknowledges support under the US DOE, Office of Science, Office of Biological and Environmental Research, Integrated Assessment Research Program, Grant No. DE-SC005171. The authors thank Robert Mendelsohn and other participants in the NBER workshop for valuable comments. In addition, valuable comments have been received from Stephanie Rosch, Petr Havlik, Bruce McCarl, Delphine Deryng and two anonymous reviewers.