title: Can Impacts of Climate Change and Agricultural Adaptation Strategies Be Accurately Quantified if Crop Models Are Annually Re-Initialized?
abstract: Estimates of climate change impacts on global food production are generally based on statistical or process-based models. Process-based models can provide robust predictions of agricultural yield responses to changing climate and management. However, applications of these models often suffer from bias due to the common practice of re-initializing soil conditions to the same state for each year of the forecast period. If simulations neglect to include year-to-year changes in initial soil conditions and water content related to agronomic management, adaptation and mitigation strategies designed to maintain stable yields under climate change cannot be properly evaluated. We apply a process-based crop system model that avoids re-initialization bias to demonstrate the importance of simulating both year-to-year and cumulative changes in pre-season soil carbon, nutrient, and water availability. Results are contrasted with simulations using annual re-initialization, and differences are striking. We then demonstrate the potential for the most likely adaptation strategy to offset climate change impacts on yields using continuous simulations through the end of the 21st century. Simulations that annually re-initialize pre-season soil carbon and water contents introduce an inappropriate yield bias that obscures the potential for agricultural management to ameliorate the deleterious effects of rising temperatures and greater rainfall variability.
authors.affiliation: Department of Geological Sciences, Michigan State University, East Lansing, MI, United States of America; W. K. Kellogg Biological Station, Michigan State University, Hickory Corners, MI, United States of America.
authors.forename: Bruno
authors.initials: B
authors.lastname: Basso
authors.affiliation: Department of Geological Sciences, Michigan State University, East Lansing, MI, United States of America.
authors.forename: David W
authors.initials: DW
authors.lastname: Hyndman
authors.affiliation: Department of Geological Sciences, Michigan State University, East Lansing, MI, United States of America.
authors.forename: Anthony D
authors.initials: AD
authors.lastname: Kendall
authors.affiliation: Department of Plant, Soil, and Microbial Sciences, Michigan State University, East Lansing, MI, United States of America.
authors.forename: Peter R
authors.initials: PR
authors.lastname: Grace
authors.affiliation: W. K. Kellogg Biological Station, Michigan State University, Hickory Corners, MI, United States of America; Institute of Future Environments, Queensland University of Technology, Brisbane, Australia.
authors.forename: G Philip
authors.initials: GP
authors.lastname: Robertson
mesh_terms: D057914:Agricultural Irrigation; D000383:Agriculture; D057231:Climate Change; D003198:Computer Simulation; D018556:Crops, Agricultural / Q000254:growth & development*; D008962:Models, Theoretical; D009329:Nebraska; D011891:Rain; D012621:Seasons; D012987:Soil; D014867:Water; D003313:Zea mays / Q000254:growth & development
chemical_list: D012987:Soil; D014867:Water