| Records |
| Author |
Wallach, D. |
| Title |
Developing skills: how to train adaptive modelers |
Type |
Journal Article |
| Year |
2015 |
Publication |
Advances in Animal Biosciences |
Abbreviated Journal |
Advances in Animal Biosciences |
Volume  |
6 |
Issue |
01 |
Pages |
52-53 |
| Keywords |
capacity building; skills development; training; integrated modeling |
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| Language |
English |
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Series Issue |
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Edition |
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| ISSN |
2040-4700 |
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Article |
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| Notes |
Hub, ft_macsur |
Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
4683 |
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| Author |
Liu, B.; Asseng, S.; Müller, C.; Ewert, F.; Elliott, J.; Lobell, D. B.; Martre, P.; Ruane, A. C.; Wallach, D.; Jones, J. W.; Rosenzweig, C.; Aggarwal, P. K.; Alderman, P. D.; Anothai, J.; Basso, B.; Biernath, C.; Cammarano, D.; Challinor, A.; Deryng, D.; Sanctis, G. D.; Doltra, J.; Fereres, E.; Folberth, C.; Garcia-Vila, M.; Gayler, S.; Hoogenboom, G.; Hunt, L. A.; Izaurralde, R. C.; Jabloun, M.; Jones, C. D.; Kersebaum, K. C.; Kimball, B. A.; Koehler, A.-K.; Kumar, S. N.; Nendel, C.; O’Leary, G. J.; Olesen, J. E.; Ottman, M. J.; Palosuo, T.; Prasad, P. V. V.; Priesack, E.; Pugh, T. A. M.; Reynolds, M.; Rezaei, E. E.; Rötter, R. P.; Schmid, E.; Semenov, M. A.; Shcherbak, I.; Stehfest, E.; Stöckle, C. O.; Stratonovitch, P.; Streck, T.; Supit, I.; Tao, F.; Thorburn, P.; Waha, K.; Wall, G. W.; Wang, E.; White, J. W.; Wolf, J.; Zhao, Z.; Zhu, Y. |
| Title |
Similar estimates of temperature impacts on global wheat yield by three independent methods |
Type |
Journal Article |
| Year |
2016 |
Publication |
Nature Climate Change |
Abbreviated Journal |
Nat. Clim. Change |
| Volume |
6 |
Issue |
12 |
Pages |
1130-1136 |
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1758-678x |
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article |
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| Notes |
CropM |
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no |
| Call Number |
MA @ admin @ |
Serial |
4965 |
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Asseng, S.; Ewert, F.; Martre, P.; Rötter, R.P.; Lobell, D.B.; Cammarano, D.; Kimball, B.A.; Ottman, M.J.; Wall, G.W.; White, J.W.; Reynolds, M.P.; Alderman, P.D.; Prasad, P.V.V.; Aggarwal, P.K.; Anothai, J.; Basso, B.; Biernath, C.; Challinor, A.J.; De Sanctis, G.; Doltra, J.; Fereres, E.; Garcia-Vila, M.; Gayler, S.; Hoogenboom, G.; Hunt, L.A.; Izaurralde, R.C.; Jabloun, M.; Jones, C.D.; Kersebaum, K.C.; Koehler, A.-K.; Müller, C.; Naresh Kumar, S.; Nendel, C.; O’Leary, G.; Olesen, J.E.; Palosuo, T.; Priesack, E.; Eyshi Rezaei, E.; Ruane, A.C.; Semenov, M.A.; Shcherbak, I.; Stöckle, C.; Stratonovitch, P.; Streck, T.; Supit, I.; Tao, F.; Thorburn, P.J.; Waha, K.; Wang, E.; Wallach, D.; Wolf, J.; Zhao, Z.; Zhu, Y. |
| Title |
Rising temperatures reduce global wheat production |
Type |
Journal Article |
| Year |
2014 |
Publication |
Nature Climate Change |
Abbreviated Journal |
Nat. Clim. Change |
| Volume |
5 |
Issue |
2 |
Pages |
143-147 |
| Keywords |
climate-change; spring wheat; dryland wheat; yield; growth; drought; heat; CO2; agriculture; adaptation |
| Abstract |
Crop models are essential tools for assessing the threat of climate change to local and global food production1. Present models used to predict wheat grain yield are highly uncertain when simulating how crops respond to temperature2. Here we systematically tested 30 different wheat crop models of the Agricultural Model Intercomparison and Improvement Project against field experiments in which growing season mean temperatures ranged from 15 °C to 32 °C, including experiments with artificial heating. Many models simulated yields well, but were less accurate at higher temperatures. The model ensemble median was consistently more accurate in simulating the crop temperature response than any single model, regardless of the input information used. Extrapolating the model ensemble temperature response indicates that warming is already slowing yield gains at a majority of wheat-growing locations. Global wheat production is estimated to fall by 6% for each °C of further temperature increase and become more variable over space and time. |
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1758-678x |
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| Notes |
CropM, ft_macsur |
Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
4550 |
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| Author |
Wallach, D.; Rivington, M. |
| Title |
A framework for assessing the uncertainty in crop model predictions |
Type |
Report |
| Year |
2014 |
Publication |
FACCE MACSUR Reports |
Abbreviated Journal |
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| Volume |
3 |
Issue |
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Pages |
D-C4.1.2 |
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| Abstract |
It is of major importance in modeling to understand and quantify the uncertainty in model predictions, both in order to know how much confidence to have in those predictions, and as a first step toward model improvement. Here we show that there are basically three different approaches to evaluating uncertainty, and we explain the advantages and drawbacks of each. This is a necessary first step toward developing protocols for evaluation of uncertainty and so obtaining a clearer picture of the reliability of crop models. No Label |
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no |
| Call Number |
MA @ admin @ |
Serial |
2231 |
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| Author |
Wallach, D.; Rivington, M. |
| Title |
A framework structure to integrate improved methods for uncertainty evaluation, and protocols for methods application |
Type |
Report |
| Year |
2014 |
Publication |
FACCE MACSUR Reports |
Abbreviated Journal |
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| Volume |
3 |
Issue |
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Pages |
D-C4.1.2 |
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CropM |
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no |
| Call Number |
MA @ admin @ |
Serial |
2078 |
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