TY - JOUR
T1 - A potato model intercomparison across varying climates and productivity levels
AU - Fleisher, David H.
AU - Condori, Bruno
AU - Quiroz, Roberto
AU - Alva, Ashok
AU - Asseng, Senthold
AU - Barreda, Carolina
AU - Bindi, Marco
AU - Boote, Kenneth J.
AU - Ferrise, Roberto
AU - Franke, Angelinus C.
AU - Govindakrishnan, Panamanna M.
AU - Harahagazwe, Dieudonne
AU - Hoogenboom, Gerrit
AU - Naresh Kumar, Soora
AU - Merante, Paolo
AU - Nendel, Claas
AU - Olesen, Jorgen E.
AU - Parker, Phillip S.
AU - Raes, Dirk
AU - Raymundo, Rubi
AU - Ruane, Alex C.
AU - Stockle, Claudio
AU - Supit, Iwan
AU - Vanuytrecht, Eline
AU - Wolf, Joost
AU - Woli, Prem
PY - 2017
Y1 - 2017
N2 - 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.
AB - 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.
KW - climate change
KW - crop modeling
KW - model improvement
KW - solanum tuberosum
KW - uncertainty analysis
KW - yield sensitivity
U2 - 10.1111/gcb.13411
DO - 10.1111/gcb.13411
M3 - Article
SN - 1354-1013
VL - 23
SP - 1258
EP - 1281
JO - Global Change Biology
JF - Global Change Biology
IS - 3
ER -