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Dono, G.; Cortignani, R.; Dell’Unto, D.; Deligios, P.; Doro, L.; Lacetera, N.; Mula, L.; Pasqui, M.; Quaresima, S.; Vitali, A.; Roggero, P.P. |
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Title |
Winners and losers from climate change in agriculture: Insights from a case study in the Mediterranean basin |
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Journal Article |
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Year |
2016 |
Publication |
Agricultural Systems |
Abbreviated Journal |
Agricultural Systems |
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147 |
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65-75 |
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Adaptation of farms to CC; Mediterranean region; Discrete Stochastic Programming; Regional Atmospheric Modelling System; Crop models; Livestock models |
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The Mediterranean region has always shown a marked inter-annual variability in seasonal weather, creating uncertainty in decisional processes of cultivation and livestock breeding that should not be neglected when modeling farmers’ adaptive responses. This is especially relevant when assessing the impact of climate change (CC), which modifies the atmospheric variability and generates new uncertainty conditions, and the possibility of adaptation of agriculture. Our analysis examines this aspect reconstructing the effects of inter-annual climate variability in a diversified farming district that well represents a wide range of rainfed and irrigated agricultural systems in the Mediterranean area. We used a Regional Atmospheric Modelling System and a weather generator to generate 150 stochastic years of the present and near future climate. Then, we implemented calibrated crop and livestock models to estimate the corresponding productive responses in the form of probability distribution functions (PDFs) under the two climatic conditions. We assumed these PDFs able to represent the expectations of farmers in a discrete stochastic programming (DSP) model that reproduced their economic behaviour under uncertainty conditions. The comparison of the results in the two scenarios provided an assessment of the impact of CC, also taking into account the possibility of adjustment allowed by present technologies and price regimes. The DSP model is built in blocks that represent the farm typologies operating in the study area, each one with its own resource endowment, decisional constraints and economic response. Under this latter aspect, major differences emerged among farm typologies and sub-zones of the study area. A crucial element of differentiation was water availability, since only irrigated C3 crops took full advantage from the fertilization effect of increasing atmospheric CO2 concentration. Rainfed crop production was depressed by the expected reduction of spring rainfall associated to the higher temperatures. So, a dualism emerges between the smaller impact on crop production in the irrigated plain sub-zone, equipped with collective water networks and abundant irrigation resources, and the major negative impact in the hilly area, where these facilities and resources are absent. However intensive dairy farming was also negatively affected in terms of milk production and quality, and cattle mortality because of the increasing summer temperatures. This provides explicit guidance for addressing strategic adaptation policies and for framing farmers’ perception of CC, in order to help them to develop an awareness of the phenomena that are already in progress, which is a prerequisite for effective adaptation responses. |
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0308521x |
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CropM, LiveM, TradeM, ft_macsur |
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MA @ admin @ |
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4756 |
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Dumont, B.; Basso, B.; Bodson, B.; Destain, J.-P.; Destain, M.-F. |
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Title |
Assessing and modeling economic and environmental impact of wheat nitrogen management in Belgium |
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Journal Article |
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2016 |
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Environmental Modelling & Software |
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Env. Model. Softw. |
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79 |
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184-196 |
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Tactical nitrogen management; Climatic variability; Probability risk; assessment; LARS-WG; Crop model; STICS; stics crop model; generic model; simulation; yield; water; soil; fertilizer; behavior; climate; maize |
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Future progress in wheat yield will rely on identifying genotypes & management practices better adapted to the fluctuating environment Nitrogen (N) fertilization is probably the most important practice impacting crop growth. However, the adverse environmental impacts of inappropriate N management (e.g., lixiviation) must be considered in the decision-making process. A formal decisional algorithm was developed to tactically optimize the economic & environmental N fertilization in wheat. Climatic uncertainty analysis was performed using stochastic weather time-series (LARS-WG). Crop growth was simulated using STICS model. Experiments were conducted to support the algorithm recommendations: winter wheat was sown between 2008 & 2014 in a classic loamy soil of the Hesbaye Region, Belgium (temperate climate). Results indicated that, most of the time, the third N fertilization applied at flag-leaf stage by farmers could be reduced. Environmental decision criterion is most of the time the limiting factor in comparison to the revenues expected by farmers. (C) 2016 Elsevier Ltd. All rights reserved. |
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1364-8152 |
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CropM, ft_macsur |
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MA @ admin @ |
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4749 |
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Matthews, A. |
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Is agriculture off the hook in the EU’s 2030 Climate Policy |
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2016 |
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FACCE MACSUR Reports |
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9 C6 - |
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Sp9-6 |
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EU climate policy and AFOLU•Overall 2030 level of ambition agreed by European Council October 2014•Commission ESR proposal July 2016 – sharing of effort in NETS across MS plus trading mechanisms•Commission LULUCF proposal – integration of LULUCF into climate policy•AFOLU mitigation pursued through CAP as well as flanking environmental policies•No specific EU targets for agricultural mitigation in NETS•Ultimately, how AFOLU mitigation is pursued will depend on MS decisions2Implications of EU bubble•Commission has put in place trading mechanisms in NETS sectors to ensure least-cost fulfilment of overall EU targets•Challenge of MS ESR targets also depends on use MS make of trading mechanisms•MS have not to date made use of these mechanisms and prefer to meet targets domestically•A number of MS have domestic targets in addition to EU targets•ESR IA looked at adding central information site, central market place for AEA transfers or mandatory auctioning•Links with annual monitoring and 5-year legal compliance checks (2027 and 2032) |
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MA @ admin @ |
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4843 |
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Fulu, T. |
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Case 5: Design future climate-resilient barley cultivars using crop model ensembles |
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2016 |
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Presentation SC 2.10 Farming systems. Case 5: Design future climate-resilient barley cultivars using crop model ensembles, Tao Fulu, Natural Resources Institute Finland (LUKE), Finland (2016). Presented at the international conference Adaptation Futures 2016, Rotterdam, the Netherlands. No Label |
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Rotterdam (Netherlands) |
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AdaptationFutures 2016, 10-13 May 2016, Rotterdam |
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MA @ admin @ |
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2445 |
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Ewert, F.; Boote, K.J.; Rötter, R.P.; Thorburn, P.; Nendel, C. (eds) |
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Crop modelling for agriculture and food security under global change. Abstracts. International Crop Modelling Symposium iCROPM2016, 15-17 March 2016, Berlin, Germany |
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Book Whole |
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2016 |
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CropM; MACSUR_ACK |
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Berlin |
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Ewert, F.; Boote, K.J.; Rötter, R.P.; Thorburn, P.; Nendel, C. |
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MA @ admin @ |
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2428 |
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