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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.
Title To what extent is climate change adaptation a novel challenge for agricultural modellers Type Journal Article
Year 2019 Publication Environmental Modelling & Software Abbreviated Journal Env. Model. Softw.
Volume 120 Issue Pages Unsp 104492
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
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.
Address 2020-02-14
Corporate Author Thesis
Publisher Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1364-8152 ISBN Medium (up) Article
Area Expedition Conference
Notes LiveM, ft_macsur Approved no
Call Number MA @ admin @ Serial 5223
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Author Gomara, I.; Bellocchi, G.; Martin, R.; Rodriguez-Fonseca, B.; Ruiz-Ramos, M.
Title Influence of climate variability on the potential forage production of a mown permanent grassland in the French Massif Central Type Journal Article
Year 2020 Publication Agricultural and Forest Meteorology Abbreviated Journal Agricultural and Forest Meteorology
Volume 280 Issue Pages 107768
Keywords climate variability; grasslands; potential yield; climate services; forage production forecasts; french massif central; pasture simulation-model; dry-matter production; atmospheric; circulation; crop yield; SST anomalies; maize yield; managed grasslands; storm track; ENSO; impacts
Abstract Climate Services (CS) provide support to decision makers across socio-economic sectors. In the agricultural sector, one of the most important CS applications is to provide timely and accurate yield forecasts based on climate prediction. In this study, the Pasture Simulation model (PaSim) was used to simulate, for the period 1959–2015, the forage production of a mown grassland system (Laqueuille, Massif Central of France) under different management conditions, with meteorological inputs extracted from the SAFRAN atmospheric database. The aim was to generate purely climate-dependent timeseries of optimal forage production, a variable that was maximized by brighter and warmer weather conditions at the grassland. A long-term increase was observed in simulated forage yield, with the 1995–2015 average being 29% higher than the 1959–1979 average. Such increase seems consistent with observed rising trends in temperature and CO2, and multi-decadal changes in incident solar radiation. At interannual timescales, sea surface temperature anomalies of the Mediterranean (MED), Tropical North Atlantic (TNA), equatorial Pacific (El Niño Southern Oscillation) and the North Atlantic Oscillation (NAO) index were found robustly correlated with annual forage yield values. Relying only on climatic predictors, we developed a stepwise statistical multi-regression model with leave-one-out cross-validation. Under specific management conditions (e.g., three annual cuts) and from one to five months in advance, the generated model successfully provided a p-value<0.01 in correlation (t-test), a root mean square error percentage (%RMSE) of 14.6% and a 71.43% hit rate predicting above/below average years in terms of forage yield collection. This is the first modeling study on the possible role of large-scale oceanic–atmospheric teleconnections in driving forage production in Europe. As such, it provides a useful springboard to implement a grassland seasonal forecasting system in this continent.
Address 2020-06-08
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium (up) article
Area Expedition Conference
Notes LiveM, ft_macsur Approved no
Call Number MA @ admin @ Serial 5233
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Author Bindi, M.; Palosuo, T.; Trnka, M.; Semenov, M.A.
Title Modelling climate change impacts on crop production for food security INTRODUCTION Type Journal Article
Year 2015 Publication Climate Research Abbreviated Journal Clim. Res.
Volume 65 Issue Pages 3-5
Keywords Crop production; Climate change impact and adaptation assessments; Upscaling; Model ensembles
Abstract Process-based crop models that synthesise the latest scientific understanding of biophysical processes are currently the primary scientific tools available to assess potential impacts of climate change on crop production. Important obstacles are still present, however, and must be overcome for improving crop modelling application in integrated assessments of risk, of sustainability and of crop-production resilience in the face of climate change (e.g. uncertainty analysis, model integration, etc.). The research networks MACSUR and AGMIP organised the CropM International Symposium and Workshop in Oslo, on 10-12 February 2014, and present this CR Special, discussing the state-of-the-art-as well as future perspectives-of crop modelling applications in climate change risk assessment, including the challenges of integrated assessments for the agricultural sector.
Address 2016-10-31
Corporate Author Thesis
Publisher Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0936-577x ISBN Medium (up) Editorial Material
Area Expedition Conference
Notes CropM, ftnotmacsur Approved no
Call Number MA @ admin @ Serial 4785
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Author Schauberger, B.; Rolinski, S.; Müller, C.
Title A network-based approach for semi-quantitative knowledge mining and its application to yield variability Type Journal Article
Year 2016 Publication Environmental Research Letters Abbreviated Journal Environ. Res. Lett.
Volume 11 Issue 12 Pages 123001
Keywords yield variability; crop models; interaction network; plant process; wheat; maize; rice; Global Food Security; Climate-Change; Crop Production; Stress Tolerance; Wheat Yields; Heat-Stress; Temperature Variability; Environmental-Factors; United-States; Elevated CO2
Abstract Variability of crop yields is detrimental for food security. Under climate change its amplitude is likely to increase, thus it is essential to understand the underlying causes and mechanisms. Crop models are the primary tool to project future changes in crop yields under climate change. Asystematic overview of drivers and mechanisms of crop yield variability (YV) can thus inform crop model development and facilitate improved understanding of climate change impacts on crop yields. Yet there is a vast body of literature on crop physiology and YV, which makes a prioritization of mechanisms for implementation in models challenging. Therefore this paper takes on a novel approach to systematically mine and organize existing knowledge from the literature. The aim is to identify important mechanisms lacking in models, which can help to set priorities in model improvement. We structure knowledge from the literature in a semi-quantitative network. This network consists of complex interactions between growing conditions, plant physiology and crop yield. We utilize the resulting network structure to assign relative importance to causes of YV and related plant physiological processes. As expected, our findings confirm existing knowledge, in particular on the dominant role of temperature and precipitation, but also highlight other important drivers of YV. More importantly, our method allows for identifying the relevant physiological processes that transmit variability in growing conditions to variability in yield. We can identify explicit targets for the improvement of crop models. The network can additionally guide model development by outlining complex interactions between processes and by easily retrieving quantitative information for each of the 350 interactions. We show the validity of our network method as a structured, consistent and scalable dictionary of literature. The method can easily be applied to many other research fields.
Address 2017-04-07
Corporate Author Thesis
Publisher Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1748-9326 ISBN Medium (up) Review
Area Expedition Conference
Notes CropM, ft_macsur Approved no
Call Number MA @ admin @ Serial 4942
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Author D’Ottavio, P.; Francioni, M.; Trozzo, L.; Sedic, E.; Budimir, K.; Avanzolini, P.; Trombetta, M.F.; Porqueddu, C.; Santilocchi, R.; Toderi, M.
Title Trends and approaches in the analysis of ecosystem services provided by grazing systems: A review Type Journal Article
Year 2018 Publication Grass and Forage Science Abbreviated Journal Grass Forage Sci.
Volume 73 Issue 1 Pages 15-25
Keywords climate regulation; food, habitat services; land degradation prevention; moderation of extreme events; natural (landscape) heritage; primary production; regulation of water flows; water quality regulation; Grassland Management; Plant-Communities; Land Degradation; Inner-Mongolia; Trade-Offs; Biodiversity; Provision; Impact; Consequences; Conservation
Abstract The ecosystem services (ES) approach is a framework for describing the benefits of nature to human well-being, and this has become a popular instrument for assessment and evaluation of ecosystems and their functions. Grazing lands can provide a wide array of ES that depend on their management practices and intensity. This article reviews the trends and approaches used in the analysis of some relevant ES provided by grazing systems, in line with the framework principles of the Millennium Ecosystem Assessment (MA). The scientific literature provides reports of many studies on ES in general, but the search here focused on grazing systems, which returned only sixty-two papers. This review of published papers highlights that: (i) in some papers, the concept of ES as defined by the MA is misunderstood (e.g., lack of anthropocentric vision); (ii) 34% of the papers dealt only with one ES, which neglects the need for the multisectoral approach suggested by the MA; (iii) few papers included stakeholder involvement to improve local decision-making processes; (iv) cultural ES have been poorly studied despite being considered the most relevant for local and general stakeholders; and (v) stakeholder awareness of well-being as provided by ES in grazing systems can foster both agri-environmental schemes and the willingness to pay for these services.
Address 2018-03-02
Corporate Author Thesis
Publisher Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0142-5242 ISBN Medium (up) Review
Area Expedition Conference
Notes LiveM, ft_macsur Approved no
Call Number MA @ admin @ Serial 5191
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