A potato model intercomparison across varying climates and productivity levels

David H. Fleisher*, Bruno Condori, Roberto Quiroz, Ashok Alva, Senthold Asseng, Carolina Barreda, Marco Bindi, Kenneth J. Boote, Roberto Ferrise, Angelinus C. Franke, Panamanna M. Govindakrishnan, Dieudonne Harahagazwe, Gerrit Hoogenboom, Soora Naresh Kumar, Paolo Merante, Claas Nendel, Jorgen E. Olesen, Phillip S. Parker, Dirk Raes, Rubi RaymundoAlex C. Ruane, Claudio Stockle, Iwan Supit, Eline Vanuytrecht, Joost Wolf, Prem Woli

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

103 Citations (Scopus)


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.
Original languageEnglish
Pages (from-to)1258-1281
JournalGlobal Change Biology
Issue number3
Publication statusPublished - 2017


  • climate change
  • crop modeling
  • model improvement
  • solanum tuberosum
  • uncertainty analysis
  • yield sensitivity


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