| Records |
| 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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CropM |
Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
4965 |
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| Author |
Porter, J.R.; Durand, J.L.; Elmayan, T. |
| Title |
Edited plants should not be patented |
Type |
Journal Article |
| Year |
2016 |
Publication |
Nature |
Abbreviated Journal |
Nature |
| Volume |
530 |
Issue |
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Pages |
33 |
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CropM, ftnotmacsur |
Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
4827 |
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| Author |
Porter, J.R.; Wratten, S. |
| Title |
National carbon stocks: Move on to a carbon currency standard |
Type |
Journal Article |
| Year |
2014 |
Publication |
Nature |
Abbreviated Journal |
Nature |
| Volume |
506 |
Issue |
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Pages |
295 |
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| Abstract |
Alongside Robert Costanza and colleagues’ plea to abandon gross domestic product as a measure of national success (see Nature 505, 283–285; 2014), we believe that there is an urgent need to change the way currencies are valued — by using a new ‘carbon standard’ that links economy to ecology. This would work in a similar way to the old gold-exchange standard, except that a country’s currency value would instead be determined by its saved and standing stocks of fossil and non-fossil carbon. Governments would need to decide whether to risk devaluing their currency by depleting carbon stocks — while still honouring a commitment to keep fossil-carbon stocks at 80% as a safeguard against extreme climate change. After the Second World War, huge investments radically altered the economies of the United States, the Soviet Union and the United Kingdom. In the face of climate change, it is now the global energy system that needs reinvention. |
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English |
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CropM |
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no |
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MA @ admin @ |
Serial |
4635 |
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| Author |
Refsgaard, J.C.; Arnbjerg-Nielsen, K.; Drews, M.; Halsnaes, K.; Jeppesen, E.; Madsen, H.; Markandya, A.; Olesen, J.E.; Porter, J.R.; Christensen, J.H. |
| Title |
The role of uncertainty in climate change adaptation strategies – a Danish water management example |
Type |
Journal Article |
| Year |
2013 |
Publication |
Mitigation and Adaptation Strategies for Global Change |
Abbreviated Journal |
Mitig. Adapt. Strateg. Glob. Change |
| Volume |
18 |
Issue |
3 |
Pages |
337-359 |
| Keywords |
Climate change; Adaptation; Uncertainty; Risk; Water sectors; Multi-disciplinary; change impacts; global change; winter-wheat; models; scenarios; ensembles; denmark; vulnerability; community; knowledge |
| Abstract |
We propose a generic framework to characterize climate change adaptation uncertainty according to three dimensions: level, source and nature. Our framework is different, and in this respect more comprehensive, than the present UN Intergovernmental Panel on Climate Change (IPCC) approach and could be used to address concerns that the IPCC approach is oversimplified. We have studied the role of uncertainty in climate change adaptation planning using examples from four Danish water related sectors. The dominating sources of uncertainty differ greatly among issues; most uncertainties on impacts are epistemic (reducible) by nature but uncertainties on adaptation measures are complex, with ambiguity often being added to impact uncertainties. Strategies to deal with uncertainty in climate change adaptation should reflect the nature of the uncertainty sources and how they interact with risk level and decision making: (i) epistemic uncertainties can be reduced by gaining more knowledge; (ii) uncertainties related to ambiguity can be reduced by dialogue and knowledge sharing between the different stakeholders; and (iii) aleatory uncertainty is, by its nature, non-reducible. The uncertainty cascade includes many sources and their propagation through technical and socio-economic models may add substantially to prediction uncertainties, but they may also cancel each other. Thus, even large uncertainties may have small consequences for decision making, because multiple sources of information provide sufficient knowledge to justify action in climate change adaptation. |
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English |
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1381-2386 1573-1596 |
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CropM, ftnotmacsur |
Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
4613 |
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| Author |
Tomozeiu, R.; Pasqui, M.; Quaresima, S. |
| Title |
Future changes of air temperature over Italian agricultural areas: a statistical downscaling technique applied to 2021–2050 and 2071–2100 periods |
Type |
Journal Article |
| Year |
2017 |
Publication |
Meteorology and Atmospheric Physics |
Abbreviated Journal |
Meteorology and Atmospheric Physics |
| Volume |
in press |
Issue |
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Pages |
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| Abstract |
Climate change scenarios of seasonal minimum and maximum temperature over different Italian agricultural areas, during the periods 2021–2050 and 2071–2100 against 1961–1990, are assessed. The areas are those selected in the framework of the Agroscenari project and are represented by: Padano–Veneta plain, Marche, Beneventano, Destra Sele, Oristano, Puglia and Sicilia, all areas of prominent agricultural vocation with excellence productions. A statistical downscaling technique applied to ENSEMBLES global climate simulations, emission scenario A1B, is used to achieve this objective. The statistical scheme consists of a multivariate regression based on Canonical Correlation Analysis. The scheme is constructed using large-scale fields derived from ECMWF reanalysis and seasonal mean minimum, maximum temperature derived from national observed daily gridded data that cover 1959–2008 period. Once the most skillful model has been selected for each season and variable, this is then applied to GCMs of ENSEMBLES runs. The statistical downscaling method developed reveals good skill over the case studies of the present work, underlying the possibility to apply the scheme over whole Italian peninsula. In addition, the results emphasize that the temperature at 850 hPa is the best predictor for surface air temperature. The future projections show that an increase could be expected to occur under A1B scenario conditions in all seasons, both in minimum and maximum temperatures. The projected increases are about 2 °C during 2021–2050 and between 2.5 and 4.5 °C during 2071–2100, respect to 1961–1990. The spatial distribution of warming is projected to be quite uniform over the territory to the end of the century, while some spatial differences are noted over 2021–2050 period. For example, the increase in minimum temperature is projected to be slightly higher in areas from northern and central part than those situated in the southern part of Italian peninsula, during 2021–2050 period. The peak of changes is projected to appear during summer season, for both minimum and maximum temperature. The probability density function tends to shift to warmer values during both periods, with increases more intense during summer and to the end of the century, when the lower tail is projected to shift up to 3 °C and the upper tail up to 6 °C. All these projected changes have important impacts on viticulture, intensive fruit and tomatoes, some of the main agricultural systems analyzed in the Agroscenari project. |
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0177-7971 |
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CropM, ft_macsur |
Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
4970 |
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