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A potato model intercomparison across varying climates and productivity levels.

  • Fleisher, David H1
  • Condori, Bruno1
  • Quiroz, Roberto2
  • Alva, Ashok3
  • Asseng, Senthold4
  • Barreda, Carolina2
  • Bindi, Marco5
  • Boote, Kenneth J4
  • Ferrise, Roberto5
  • Franke, Angelinus C6
  • Govindakrishnan, Panamanna M7
  • Harahagazwe, Dieudonne8
  • Hoogenboom, Gerrit4
  • Naresh Kumar, Soora9
  • Merante, Paolo5
  • Nendel, Claas10
  • Olesen, Jorgen E11
  • Parker, Phillip S10
  • Raes, Dirk12
  • Raymundo, Rubi4
  • And 6 more
  • 1 Crop Systems and Global Change Laboratory, USDA-ARS, Beltsville, MD, USA.
  • 2 Production Systems and the Environment, International Potato Center, Lima, Peru. , (Peru)
  • 3 Desert Agriculture and Ecosystem Program, Kuwait Institute for Scientific Research, Safat, Kuwait. , (Kuwait)
  • 4 Agricultural & Biological Engineering Department, University of Florida, Gainesville, FL, USA.
  • 5 Department of Agrifood Production and Environmental Sciences, University of Florence, Florence, Italy. , (Italy)
  • 6 Soil, Crop and Climate Sciences, University of the Free State, Bloemfontein, South Africa. , (South Africa)
  • 7 Central Potato Research Institute, Shimla, India. , (India)
  • 8 Production Systems and the Environment, International Potato Center SSA, Nairobi, Kenya. , (Kenya)
  • 9 Centre for Environment Science and Climate Resilient Agriculture, Indian Agricultural Research Institute, New Delhi, India. , (India)
  • 10 Leibniz Centre for Agricultural Landscape Research, Institute of Landscape Systems Analysis, Müncheberg, Germany. , (Germany)
  • 11 Department of Agroecology, Aarhus University, Tjele, Denmark. , (Denmark)
  • 12 Department of Earth and Environmental Sciences, KU Leuven University, Leuven, Belgium. , (Belgium)
  • 13 NASA Goddard Institute for Space Studies, New York, NY, USA.
  • 14 Biological Systems Engineering, Washington State University, Pullman, WA, USA.
  • 15 Earth System Science and Climate Adaptive Land Management, Wageningen University and Research Center, Wageningen, The Netherlands. , (Netherlands)
  • 16 Plant Production Systems, Wageningen University and Research Center, Wageningen, The Netherlands. , (Netherlands)
  • 17 AgWeatherNet Program, Washington State University, Pullman, WA, USA.
Published Article
Global Change Biology
Wiley (Blackwell Publishing)
Publication Date
Mar 01, 2017
DOI: 10.1111/gcb.13411
PMID: 27387228


A potato crop multimodel assessment was conducted to quantify variation among models and evaluate responses to climate change. Nine modeling groups simulated agronomic and climatic responses at low-input (Chinoli, Bolivia and Gisozi, Burundi)- and high-input (Jyndevad, Denmark and Washington, United States) management sites. Two calibration stages were explored, partial (P1), where experimental dry matter data were not provided, and full (P2). The median model ensemble response outperformed any single model in terms of replicating observed yield across all locations. Uncertainty in simulated yield decreased from 38% to 20% between P1 and P2. Model uncertainty increased with interannual variability, and predictions for all agronomic variables were significantly different from one model to another (P < 0.001). Uncertainty averaged 15% higher for low- vs. high-input sites, with larger differences observed for evapotranspiration (ET), nitrogen uptake, and water use efficiency as compared to dry matter. A minimum of five partial, or three full, calibrated models was required for an ensemble approach to keep variability below that of common field variation. Model variation was not influenced by change in carbon dioxide (C), but increased as much as 41% and 23% for yield and ET, respectively, as temperature (T) or rainfall (W) moved away from historical levels. Increases in T accounted for the highest amount of uncertainty, suggesting that methods and parameters for T sensitivity represent a considerable unknown among models. Using median model ensemble values, yield increased on average 6% per 100-ppm C, declined 4.6% per °C, and declined 2% for every 10% decrease in rainfall (for nonirrigated sites). Differences in predictions due to model representation of light utilization were significant (P < 0.01). These are the first reported results quantifying uncertainty for tuber/root crops and suggest modeling assessments of climate change impact on potato may be improved using an ensemble approach. © 2016 John Wiley & Sons Ltd.

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