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Author |
Kahiluoto, H.; Kaseva, J.; Balek, J.; Olesen, J.E.; Ruiz-Ramos, M.; Gobin, A.; Kersebaum, K.C.; Takac, J.; Ruget, F.; Ferrise, R.; Bezak, P.; Capellades, G.; Dibari, C.; Makinen, H.; Nendel, C.; Ventrella, D.; Rodriguez, A.; Bindi, M.; Trnka, M. |
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Title |
Decline in climate resilience of European wheat |
Type |
Journal Article |
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Year |
2019 |
Publication |
Proceedings of the National Academy of Sciences of the United States of America |
Abbreviated Journal |
Proc. Natl. Acad. Sci. U. S. A. |
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Volume |
116 |
Issue |
1 |
Pages |
123-128 |
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Keywords |
wheat; cultivar; Europe; climate resilience; response diversity; Diversity; Weather; Growth; Shifts; Crops; Yield; Variability |
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Abstract |
Food security relies on the resilience of staple food crops to climatic variability and extremes, but the climate resilience of European wheat is unknown. A diversity of responses to disturbance is considered a key determinant of resilience. The capacity of a sole crop genotype to perform well under climatic variability is limited; therefore, a set of cultivars with diverse responses to weather conditions critical to crop yield is required. Here, we show a decline in the response diversity of wheat in farmers’ fields in most European countries after 2002-2009 based on 101,000 cultivar yield observations. Similar responses to weather were identified in cultivar trials among central European countries and southern European countries. A response diversity hotspot appeared in the trials in Slovakia, while response diversity “deserts” were identified in Czechia and Germany and for durum wheat in southern Europe. Positive responses to abundant precipitation were lacking. This assessment suggests that current breeding programs and cultivar selection practices do not sufficiently prepare for climatic uncertainty and variability. Consequently, the demand for climate resilience of staple food crops such as wheat must be better articulated. Assessments and communication of response diversity enable collective learning across supply chains. Increased awareness could foster governance of resilience through research and breeding programs, incentives, and regulation. |
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2019-01-17 |
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ISSN |
0027-8424 |
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Article |
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Notes  |
CropM, ft_macsur |
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no |
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Call Number |
MA @ admin @ |
Serial |
5226 |
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Author |
Trnka, M.; Feng, S.; Semenov, M.A.; Olesen, J.E.; Kersebaum, K.C.; Roetter, R.P.; Semeradova, D.; Klem, K.; Huang, W.; Ruiz-Ramos, M.; Hlavinka, P.; Meitner, J.; Balek, J.; Havlik, P.; Buntgen, U. |
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Title |
Mitigation efforts will not fully alleviate the increase in water scarcity occurrence probability in wheat-producing areas |
Type |
Journal Article |
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Year |
2019 |
Publication |
Science Advances |
Abbreviated Journal |
Sci. Adv. |
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Volume |
5 |
Issue |
9 |
Pages |
eaau2406 |
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Keywords |
climate-change impacts; sub-saharan africa; atmospheric co2; crop; yields; drought; agriculture; variability; irrigation; adaptation; carbon |
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Abstract |
Global warming is expected to increase the frequency and intensity of severe water scarcity (SWS) events, which negatively affect rain-fed crops such as wheat, a key source of calories and protein for humans. Here, we develop a method to simultaneously quantify SWS over the world’s entire wheat-growing area and calculate the probabilities of multiple/sequential SWS events for baseline and future climates. Our projections show that, without climate change mitigation (representative concentration pathway 8.5), up to 60% of the current wheat-growing area will face simultaneous SWS events by the end of this century, compared to 15% today. Climate change stabilization in line with the Paris Agreement would substantially reduce the negative effects, but they would still double between 2041 and 2070 compared to current conditions. Future assessments of production shocks in food security should explicitly include the risk of severe, prolonged, and near- simultaneous droughts across key world wheat-producing areas. |
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2020-02-14 |
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ISSN |
2375-2548 |
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CropM, ft_macsur |
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no |
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Call Number |
MA @ admin @ |
Serial |
5227 |
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Author |
Cassardo, C.; Andreoli, V. |
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Title |
On the Representativeness of UTOPIA Land Surface Model for Creating a Database of Surface Layer, Vegetation and Soil Variables in Piedmont Vineyards, Italy |
Type |
Journal Article |
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Year |
2019 |
Publication |
Applied Sciences-Basel |
Abbreviated Journal |
Applied Sciences-Basel |
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Volume |
9 |
Issue |
18 |
Pages |
3880 |
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Keywords |
land-surface; UTOPIA; NOAH; GLDAS; micrometeorology; exchanges; processes; vineyards; cabernet-sauvignon; climate-change; wine color; temperature; parameterization; simulations; circulation; balances; moisture; sunlight |
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Abstract |
The main aim of the paper is to show how, and how many, simulations carried out using the Land Surface Model UTOPIA (University of TOrino model of land Process Interaction with Atmosphere) are representative of the micro-meteorological conditions and exchange processes at the atmosphere/biosphere interface, with a particular focus on heat and hydrologic transfers, over an area of the Piemonte (Piedmont) region, NW Italy, which is characterized by the presence of many vineyards. Another equally important aim is to understand how much the quality of the simulation outputs was influenced by the input data, whose measurements are often unavailable for long periods over country areas at an hourly basis. Three types of forcing data were used: observations from an experimental campaign carried out during the 2008, 2009, and 2010 vegetative seasons in three vineyards, and values extracted from the freely available Global Land Data Assimilation System (GLDAS, versions 2.0 and 2.1). Since GLDAS also contains the outputs of the simulations performed using the Land Surface Model NOAH, an additional intercomparison between the two models, UTOPIA and NOAH, both driven by the same GLDAS datasets, was performed. The intercomparisons were performed on the following micro-meteorological variables: net radiation, sensible and latent turbulent heat fluxes, and temperature and humidity of soil. The results of this study indicate that the methodology of employing land surface models driven by a gridded database to evaluate variables of micro-meteorological and agronomic interest in the absence of observations is suitable and gives satisfactory results, with uncertainties comparable to measurement errors, thus, allowing us to also evaluate some time trends. The comparison between GLDAS2.0 and GLDAS2.1 indicates that the latter generally produces simulation outputs more similar to the observations than the former, using both UTOPIA and NOAH models. |
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2020-02-14 |
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CropM, ft_macsur |
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no |
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Call Number |
MA @ admin @ |
Serial |
5228 |
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Author |
Nguyen, T.P.L.; Seddaiu, G.; Roggero, P.P. |
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Title |
Declarative or procedural knowledge? Knowledge for enhancing farmers’ mitigation and adaptation behaviour to climate change |
Type |
Journal Article |
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Year |
2019 |
Publication |
Journal of Rural Studies |
Abbreviated Journal |
Journal of Rural Studies |
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Volume |
67 |
Issue |
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Pages |
46-56 |
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Keywords |
Farming systems; Knowledge; Attitude; Practice; Social construction |
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Abstract |
Climate change poses a major challenge for farmers, but agricultural sustainability, mitigation, and adaptation can effectively decrease climate impacts on agricultural systems. Changes in farming practices are necessary to reduce emissions and to adapt to climate change. However, such modifications to common practices depend, to a large extent, on farmers’ knowledge and attitudes towards climate risks. An empirical study of farmers’ attitudes and knowledge of climate change mitigation and adaptation practices is useful to understand how farmers’ knowledge influences their attitudes and practices towards climate change mitigation and adaptation. Based on a case study characterised by four agricultural farming systems (extensive dairy sheep, intensive dairy cattle, horticultural farming, and rice farming) in the Province of Oristano in Italy, this study contains an investigation of (i) farmers’ knowledge of climate change causes and effects, how they construct such knowledge, and how they adapt to the phenomenon; (ii) what and how are farmers’ attitudes towards climate change causes are shaped under their contextual social interests and values; and (iii) if their practices in responding to climate variability are influenced by their constructed knowledge. The research results showed that farmers’ declarative knowledge of climate change did not affect their adaptation practices but directed farmers’ attitudes towards climate change causes. The findings also underscore the necessity of facilitating social learning spaces for enhancing virtuous behaviours towards climate change mitigation and the sharing and co-production of procedural knowledge for developing shared sustainable climate adaptation practices at the farm level. |
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2019-02-19 |
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ISSN |
0743-0167 |
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article |
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CropM, TradeM, ft_macsur |
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no |
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Call Number |
MA @ admin @ |
Serial |
5217 |
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Author |
Kipling, R.P.; Topp, C.F.E.; Bannink, A.; Bartley, D.J.; Blanco-Penedo, I.; Cortignani, R.; del Prado, A.; Dono, G.; Faverdin, P.; Graux, A.-I.; Hutchings, N.J.; Lauwers, L.; Gulzari, S.O.; Reidsma, P.; Rolinski, S.; Ruiz-Ramos, M.; Sandars, D.L.; Sandor, R.; Schoenhart, M.; Seddaiu, G.; van Middelkoop, J.; Shrestha, S.; Weindl, I.; Eory, V. |
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Title |
To what extent is climate change adaptation a novel challenge for agricultural modellers |
Type |
Journal Article |
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Year |
2019 |
Publication |
Environmental Modelling & Software |
Abbreviated Journal |
Env. Model. Softw. |
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Volume |
120 |
Issue |
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Pages |
Unsp 104492 |
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Keywords |
Adaptation; Agricultural modelling; Climate change; Research challenges; greenhouse-gas emissions; farm-level adaptation; land-use; food; security; adapting agriculture; livestock production; decision-making; change impacts; dairy farms; crop |
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Abstract |
Modelling is key to adapting agriculture to climate change (CC), facilitating evaluation of the impacts and efficacy of adaptation measures, and the design of optimal strategies. Although there are many challenges to modelling agricultural CC adaptation, it is unclear whether these are novel or, whether adaptation merely adds new motivations to old challenges. Here, qualitative analysis of modellers’ views revealed three categories of challenge: Content, Use, and Capacity. Triangulation of findings with reviews of agricultural modelling and Climate Change Risk Assessment was then used to highlight challenges specific to modelling adaptation. These were refined through literature review, focussing attention on how the progressive nature of CC affects the role and impact of modelling. Specific challenges identified were: Scope of adaptations modelled, Information on future adaptation, Collaboration to tackle novel challenges, Optimisation under progressive change with thresholds, and Responsibility given the sensitivity of future outcomes to initial choices under progressive change. |
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Address |
2020-02-14 |
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English |
Summary Language |
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Abbreviated Series Title |
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Edition |
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ISSN |
1364-8152 |
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Notes |
LiveM, ft_macsur |
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no |
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Call Number |
MA @ admin @ |
Serial |
5223 |
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