Agricultural adaptation to climate change in rich and poor countries: Current modeling practice and potential for empirical contributions

doi:10.1016/j.eneco.2014.04.014

Energy Economics

Volume 46, November 2014, Pages 562-575

https://doi.org/10.1016/j.eneco.2014.04.014 Get rights and content

Highlights

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IAMs omit key processes by which climate change impacts crops.
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Omissions are particularly severe in tropics where most of world’s poor reside.
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IAMs likely overstate potential for adaptation in developing countries.
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When combined, these lead decision makers to underestimate the challenge posed by climate change to world’s poor.

Abstract

In this paper we discuss the scope of the adaptation challenge facing world agriculture in the coming decades. Due to rising temperatures throughout the tropics, pressures for adaptation will be greatest in some of the poorest parts of the world where the adaptive capacity is least abundant. We discuss both autonomous (market driven) and planned adaptations, distinguishing: (a) those that can be undertaken with existing technology, (b) those that involve development of new technologies, and (c) those that involve institutional/market and policy reforms. The paper then proceeds to identify which of these adaptations are currently modeled in integrated assessment studies and related analyses at global scale. This, in turn, gives rise to recommendations about how these models should be modified in order to more effectively capture climate change adaptation in the farm and food sector. In general, we find that existing integrated assessment models are better suited to analyzing adaptation by relatively well-endowed producers operating in market-integrated, developed countries. They likely understate climate impacts on agriculture in developing countries, while overstating the potential adaptations. This is troubling, since the need for adaptation will be greatest amongst the lower income producers in the poorest tropical countries. This is also where policies and public investments are likely to have the highest payoff. We conclude with a discussion of opportunities for improving the empirical foundations of integrated assessment modeling with an emphasis on the poorest countries.

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 τ_A, 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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Agricultural adaptation to climate change in rich and poor countries: Current modeling practice and potential for empirical contributions☆

Highlights

Abstract

Introduction

Section snippets

Assessing the scope of the adaptation challenge: climate impacts on agriculture

Thinking about adaptation

Overview of the modeling landscape

Critical assessment and opportunities for empirical contributions

Summary and conclusions

Atmos. Environ.

Agric. Ecosyst. Environ.

Agric. Ecosyst. Environ.

Ecol. Model.

Field Crop Res.

Agric. Ecosyst. Environ.

Glob. Environ. Chang.

Eur. J. Agron.

Agric. Syst.

Trends Plant Sci.

Ecol. Model.

Agric. Syst.

Eur. J. Agron.

Agric. Ecosyst. Environ.

Field Crop Res.

Agric. Syst.

FASOMGHG Conceptual Structure, and Specification: Documentation

Plan or react? Analysis of adaptation costs and benefits using integrated assessment models

Clim. Chang. Econ.

Agriculture and trade opportunities for Tanzania: past volatility and future climate change

Rev. Dev. Econ.

Agricultural Adaptation: Needs, Findings and Effects

Global observed changes in daily climate extremes of temperature and precipitation

J. Geophys. Res.

Research lags and spillovers

Persistence Pays

Respiration and Crop Productivity

Impact on World Prices of Many Countries Using Trade Policy to Stabilize Domestic Food Prices

Adaptation of agricultural and food systems to climate change: an economic and policy perspective

Appl. Econ. Perspect. Policy

Adaptation, spatial heterogeneity, and the vulnerability of agricultural systems to climate change and CO2 fertilization: an integrated assessment approach

Clim. Chang.

The impact of temperature variability on wheat yields

Glob. Chang. Biol.

Taxpayers, Crop Insurance, and the Drought of 2012

Modelling the role of agriculture for the 20th century global terrestrial carbon balance

Glob. Chang. Biol.

Climate policy and the optimal balances between mitigation, adaptation and unavoided damage

Clim. Chang. Econ.

Climate policy and the optimal balance between mitigation, adaptation and unavoided damage

Clim. Chang. Econ.

Integrated Modelling of Global Environmental Change. An Overview of IMAGE 2.4

Can openness mitigate the effects of weather shocks? Evidence from India's famine era

Am. Econ. Rev.

Spatial land use in the GCAM integrated assessment model

Large-scale redistribution of maximum fisheries catch potential in the global ocean under climate change

Glob. Chang. Biol.

A method for evaluating climate change adaptation strategies for small-scale farmers using survey, experimental and modeled data

Agric. Syst.

Vulnerability: a micro perspective

Simulating the effects of climate and agricultural management practices on global crop yield

Glob. Biogeochem. Cycles

An integrated assessment of climate change and the accelerated introduction of advanced energy technologies — an application of MiniCAM 1.0

Mitig. Adapt. Strateg. Glob. Chang.

The impact of environmental and climate constraints on global food supply

Economic Analysis of Land Use in Global Climate Change Policy

Assessing the risk of root rots in common beans in East Africa using simulated, estimated and observed daily rainfall data

Exp. Agric.

ASTI global assessment of agricultural R&D; spending: developing countries accelerate investment (IFPRI) | EGFAR

Patterns of rainfall insurance participation in rural India

World Bank Econ. Rev.

Late-Blight Epidemics on Potato in Finland, 1933–2002; Increased and Earlier Occurrence of Epidemics Associated with Climate Change and Lack of Rotation

Plant Pathology

Climate impacts on agriculture: implications for crop production

Agron. J.

Adaptation, spatial heterogeneity, and the vulnerability of agricultural systems to climate change and CO₂ fertilization: an integrated assessment approach