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1 15 ABSTRACT 16 Plant phenology, which describes the timing of plant development, is a major aspect of 17 plant response to environment and for crops, a major determinant of yield. Many studies have 18 focused on comparing model equations for describing how phenology responds to climate but 19 the effect of crop model calibration, also important for determining model performance, has 20 received much less attention. The objectives here were to obtain a rigorous evaluation of 21 prediction capability of wheat phenology models, to analyze the role of calibration and to 22 document the various calibration approaches. The 27 participants in this multi-model study 23were provided experimental data for calibration and asked to submit predictions for sites and 24 years not represented in those data. Participants were instructed to use and document their 25 "usual" calibration approach. Overall, the models provided quite good predictions of 26 phenology (median of mean absolute error of 6.1 days) and did much better than simply using 27 the average of observed values as predictor. The results suggest that calibration can 28 compensate to some extent for different model formulations, specifically for differences in 29 simulated time to emergence and differences in the choice of input variables. Conversely, 30 different calibration approaches were associated with major differences in prediction error 31 between the same models used by different groups. Given the large diversity of calibration 32 approaches and the importance of calibration, there is a clear need for guidelines and tools to 33 aid with calibration. Arguably the most important and difficult choice for calibration is the 34 choice of parameters to estimate. Several recommendations for calibration practices are 35 proposed. Model applications, including model studies of climate change impact, should 36 focus more on the data used for calibration and on the calibration methods employed. 37