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Author  |
Mas, K.; Pardo, G.; Galán, E.; del Prado, A. |
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Title |
Assessing dairy farm sustainability using whole-farm modelling and life cycle analysis |
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Journal Article |
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Year |
2016 |
Publication |
Advances in Animal Biosciences |
Abbreviated Journal |
Advances in Animal Biosciences |
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Volume |
7 |
Issue |
03 |
Pages |
259-260 |
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2040-4700 |
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LiveM, ft_macsur |
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MA @ admin @ |
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4863 |
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Author |
Marton, T. |
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Title |
Assessing the impact of agro-climatic factors and farm characteristics on the yield variation of the Norwegian fruit sector |
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Report |
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Year |
2016 |
Publication |
FACCE MACSUR Reports |
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Volume |
9 C6 - |
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Pages |
Sp9-5 |
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Main drivers of ag. yields:–Technology–R&D (new hybrids etc.)–Weather–Etc.•Common sense and anecdotal observations (remember the Tromsø presentation) revealed extreme events tended to impact wide geographic areas•This was called the «systemic» nature of agriculture No semi-aggregation farm-level•Not the boring corn, maize, wheat fruits•No OLS-like Pearson correlation or functional form approach for conditioning spatial correlations on weather SDM•Finally, if we are smart enough to set the explanatory proxies in a meaningful way presumably we can make the distinction between the effects of, say draught and extreme heat.•And much more in policy relevance |
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MA @ admin @ |
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4857 |
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Author |
Mandryk, M. |
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Title |
Integrated assessment of farm level adaptation to climate change in agriculture – an application to Flevoland, The Netherlands |
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Book Whole |
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Year |
2016 |
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Ph.D. thesis |
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Wageningen University |
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Wageningen |
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PhD |
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PhD |
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CropM |
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MA @ admin @ |
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5162 |
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Maiorano, A.; Martre, P.; Asseng, S.; Ewert, F.; Müller, C.; Rötter, R.P.; Ruane, A.C.; Semenov, M.A.; Wallach, D.; Wang, E.; Alderman, P.D.; Kassie, B.T.; Biernath, C.; Basso, B.; Cammarano, D.; Challinor, A.J.; Doltra, J.; Dumont, B.; Rezaei, E.E.; Gayler, S.; Kersebaum, K.C.; Kimball, B.A.; Koehler, A.-K.; Liu, B.; O’Leary, G.J.; Olesen, J.E.; Ottman, M.J.; Priesack, E.; Reynolds, M.; Stratonovitch, P.; Streck, T.; Thorburn, P.J.; Waha, K.; Wall, G.W.; White, J.W.; Zhao, Z.; Zhu, Y. |
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Title |
Crop model improvement reduces the uncertainty of the response to temperature of multi-model ensembles |
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Journal Article |
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Year |
2016 |
Publication |
Field Crops Research |
Abbreviated Journal |
Field Crops Research |
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Volume |
202 |
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Pages |
5-20 |
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Keywords |
Impact uncertainty; High temperature; Model improvement; Multi-model ensemble; Wheat crop model |
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To improve climate change impact estimates and to quantify their uncertainty, multi-model ensembles (MMEs) have been suggested. Model improvements can improve the accuracy of simulations and reduce the uncertainty of climate change impact assessments. Furthermore, they can reduce the number of models needed in a MME. Herein, 15 wheat growth models of a larger MME were improved through re-parameterization and/or incorporating or modifying heat stress effects on phenology, leaf growth and senescence, biomass growth, and grain number and size using detailed field experimental data from the USDA Hot Serial Cereal experiment (calibration data set). Simulation results from before and after model improvement were then evaluated with independent field experiments from a CIMMYT world-wide field trial network (evaluation data set). Model improvements decreased the variation (10th to 90th model ensemble percentile range) of grain yields simulated by the MME on average by 39% in the calibration data set and by 26% in the independent evaluation data set for crops grown in mean seasonal temperatures >24 °C. MME mean squared error in simulating grain yield decreased by 37%. A reduction in MME uncertainty range by 27% increased MME prediction skills by 47%. Results suggest that the mean level of variation observed in field experiments and used as a benchmark can be reached with half the number of models in the MME. Improving crop models is therefore important to increase the certainty of model-based impact assessments and allow more practical, i.e. smaller MMEs to be used effectively. |
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2016-09-13 |
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Newsletter July 2016 |
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0378-4290 |
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Article |
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CropM |
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CropMwp;wos; ft=macsur; wsnot_yet; |
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no |
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Call Number |
MA @ admin @ |
Serial |
4776 |
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Author |
Luo, K.; Tao, F.; Moiwo, J.P.; Xiao, D. |
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Title |
Attribution of hydrological change in Heihe River Basin to climate and land use change in the past three decades |
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Journal Article |
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Year |
2016 |
Publication |
Scientific Reports |
Abbreviated Journal |
Scientific Reports |
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6 |
Issue |
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Pages |
33704 |
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Keywords |
water-resources; groundwater recharge; stream-flow; surface-energy; china; runoff; impact; evapotranspiration; cover; availability; Science & Technology – Other Topics |
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The contributions of climate and land use change (LUCC) to hydrological change in Heihe River Basin (HRB), Northwest China were quantified using detailed climatic, land use and hydrological data, along with the process-based SWAT (Soil and Water Assessment Tool) hydrological model. The results showed that for the 1980s, the changes in the basin hydrological change were due more to LUCC (74.5%) than to climate change (21.3%). While LUCC accounted for 60.7% of the changes in the basin hydrological change in the 1990s, climate change explained 57.3% of that change. For the 2000s, climate change contributed 57.7% to hydrological change in the HRB and LUCC contributed to the remaining 42.0%. Spatially, climate had the largest effect on the hydrology in the upstream region of HRB, contributing 55.8%, 61.0% and 92.7% in the 1980s, 1990s and 2000s, respectively. LUCC had the largest effect on the hydrology in the middle-stream region of HRB, contributing 92.3%, 79.4% and 92.8% in the 1980s, 1990s and 2000s, respectively. Interestingly, the contribution of LUCC to hydrological change in the upstream, middle-stream and downstream regions and the entire HRB declined continually over the past 30 years. This was the complete reverse (a sharp increase) of the contribution of climate change to hydrological change in HRB. |
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2016-10-18 |
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English |
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ISSN |
2045-2322 |
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CropM, ft_macsur |
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Call Number |
MA @ admin @ |
Serial |
4668 |
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