James W. Jones

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Potential consequences of climate change on crop production can be studied using mechanistic crop simulation models. While a broad variety of maize simulation models exist, it is not known whether different models diverge on grain yield responses to changes in climatic factors, or whether they agree in their general trends related to phenology, growth, and(More)
Proper estimation of model parameters is required for ensuring accurate model predictions and good model-based decisions. The generalized likelihood uncertainty estimation (GLUE) method is a Bayesian Monte Carlo parameter estimation technique that makes use of a likelihood function to measure the closeness-of-fit of modeled and observed data. Various(More)
Cropping systems models have evolved over the last four decades in response to the demand for modeling to address more complex questions, including issues on sustainable production, climate change, and environmental impacts. Early models, which were used primarily for yield gap analysis, have increased in complexity to include not only nutrient and water(More)
Accurate prediction of phenological development in maize (Zea mays L.) is fundamental to determining crop adaptation and yield potential. A number of thermal functions are used in crop models, but their relative precision in predicting maize development has not been quanti ed. e objectives of this study were (i) to evaluate the precision of eight thermal(More)
D igital image correlation (DIC) is a noncontact technique used to track full-field displacements on the surface of an object during mechanical testing. Optical DIC was originally developed in the 1980s and has been improved to the point where commercial software is available to track three-dimensional surface displacements with sub-pixel accuracy [1-3].(More)
The Agricultural Model Intercomparison and Improvement Project (AgMIP) seeks to improve the capability of ecophysiological and economic models to describe the potential impacts of climate change on agricultural systems. AgMIP protocols emphasize the use of multiple models; consequently, data harmonization is essential. This interoperability was achieved by(More)
Project Summary About this summary This summary is an abridged, general audience version of a more technical report submitted to the IAI in October 2000. The full report, which is almost 200 pages long, contains numerous graphs, charts, and statistical analyses for each of the three countries which participated in the project, as well as a comparative(More)
Climate change is projected to push the limits of cropping systems and has the potential to disrupt the agricultural sector from local to global scales. This article introduces the Coordinated Climate-Crop Modeling Project (C3MP), an initiative of the Agricultural Model Intercomparison and Improvement Project (AgMIP) to engage a global network of crop(More)
In most cases authors are permitted to post their version of the article (e.g. in Word or Tex form) to their personal website or institutional repository. Authors requiring further information regarding Elsevier's archiving and manuscript policies are encouraged to visit: a b s t r a c t A new experimental approach is used to quantify the full field(More)
SUM M ARY In recent years, simulation models have been used as a complementary tool for research and for quantifying soil carbon sequestration under widely varying conditions. This has improved the understanding and prediction of soil organic carbon (SOC) dynamics and crop yield responses to soil and climate conditions and crop management scenarios. The(More)