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A potato model intercomparison across varying climates and productivity levels
Author(s) -
Fleisher David H.,
Condori Bruno,
Quiroz Roberto,
Alva Ashok,
Asseng Senthold,
Barreda Carolina,
Bindi Marco,
Boote Kenneth J.,
Ferrise Roberto,
Franke Angelinus C.,
Govindakrishnan Panamanna M.,
Harahagazwe Dieudonne,
Hoogenboom Gerrit,
Naresh Kumar Soora,
Merante Paolo,
Nendel Claas,
Olesen Jorgen E.,
Parker Phillip S.,
Raes Dirk,
Raymundo Rubi,
Ruane Alex C.,
Stockle Claudio,
Supit Iwan,
Vanuytrecht Eline,
Wolf Joost,
Woli Prem
Publication year - 2017
Publication title -
global change biology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 4.146
H-Index - 255
eISSN - 1365-2486
pISSN - 1354-1013
DOI - 10.1111/gcb.13411
Subject(s) - evapotranspiration , environmental science , dry matter , climate change , yield (engineering) , productivity , atmospheric sciences , simulation modeling , crop yield , agronomy , mathematics , statistics , ecology , biology , materials science , macroeconomics , mathematical economics , economics , metallurgy , geology
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.