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Synthesis and Review: An Inter-Method Comparison of Climate Change Impacts on Agriculture
Published: June 26, 2018
Posted: August 27, 2019

Impact estimates are more accurate if different methodological approaches are combined in some way.

The Science
Studies have shown that climate impacts on the agricultural sector can have serious distributional consequences, with worrying implications for global food security. Yet there are still no definitive answers to fundamental questions such as (1) what will agricultural impacts be for different warming levels, (2) what is the role of carbon fertilization, and (3) which cost-effective adaptation measures exist to mitigate potential impacts on specific crops and locations. A key reason behind the lack of consensus in the literature is the diversity of methodological approaches. They range from using statistical correlations between climate change variables and agricultural yields (the statistical or empirical approach) to more detailed models capturing the relevant biophysical links (the process-based or mechanistic crop model approach) to more holistic approaches like those of integrated assessment models (IAMs). Each of the three methodological approaches differs in what is captured and what is not.

The Impact
The purpose of this focus issue of Environmental Research Letters is to provide a better understanding of the magnitude and causes of differences in results from these alternative methodological approaches—statistical models, process models, and IAMs. A common theme that emerged from most of these studies is that the estimates are more accurate if the different methodological approaches are combined in some way. A valuable outcome of the inter-method comparison studies included in this focus issue is the identification of important research areas that require much further attention.

Summary
The agricultural sector is one of the most sensitive to climate change, with potentially significant implications for food security and welfare. Alternative methodological approaches—such as process models, statistical models, and IAMs—have been used to estimate climate impacts on agriculture, not always with consistent results. This focus issue intends to shed light on the size and order of magnitude of agricultural impacts under 2°C and higher warming levels. This letter synthesizes the set of articles in the focus issue that have been tasked with providing a systematic assessment of how results from these different methodological approaches compare and why they are different. From this synthesis, we offer thoughts on research priorities going forward to fill key voids in the literature on this important topic.

Contacts (BER PM)
Bob Vallario
U.S. Department of Energy Office of Science, Office of Biological and Environmental Research
Climate and Environmental Sciences Division (SC-23.1)
Multisector Dynamics
bob.vallario@science.doe.gov

(PI Contact)
John Weyant
Stanford University
weyant@stanford.edu

Funding
This work was supported by the U.S. Department of Energy, Office of Science, Biological and Environmental Research Program, Integrated Assessment Research Program, Grant Number DE-SC0005171.

Publications
Ciscar, J-C., K. Fisher-Vanden, and D. Lobell. “Synthesis and review: An inter-method comparison of climate change impacts on agriculture.” Environmental Research Letters 13(7), 070104 (2018). [DOI: 10.1088/1748-9326/aac7cb]

Related Links
Article

Topic Areas:

  • Research Area: Earth and Environmental Systems Modeling
  • Research Area: Multisector Dynamics (formerly Integrated Assessment)

Division: SC-33.1 Earth and Environmental Sciences Division, BER

 

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