FACCE MACSUR Reports (Modelling European Agriculture with Climate Change for Food Security)
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    471 research outputs found

    Farm level approach to manage grass yield variation in changing climate in Jokioinen and St. Petersburg

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    Cattle’s feeding is based on grass silage in Northern Europe, but grass growth is highly dependent on weather conditions. In farms decision making, grass area is usually determined by the variation of yield. To be adequate in every situation, the lowest expected yield level determines the cultivated area. Other way to manage the grass yield risk is to increase silage storage capacity over annual consumption. Variation of grass yield in climate data from years 1961-1990 was compared with 15 different climate scenario models simulating years 2046-2065. A model was developed for evaluating the inadequacy risk in terms of cultivated area and storing capacity. The cost of risk is presented and discussed. In northern Europe a typical farm has storage for roughage consumption of almost one year. In addition, there can be a buffer storage. The  extra storage is to be used before and during the harvest season. New harvest will be fed to animals only after the buffer empty. Shortage in the buffer storage is possible to be filled, when the yield exceeds the target level. For risk management, two alternative mechanisms are given: forage buffer and possibility to alter the field area. According to our results, there are no significant adverse effects in the cost of risk and implied farm profitability due to climate change. Selecting the risk management scenario of 30 % grass yield risk turned out to be the least cost solution

    Comparing visions for CAP reforms post 2015: Farmer intentions and farm bio-economic modelling

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    This paper illustrates the impacts of two of the potential CAP reform post 2015 scenarios using an optimising farm level model and compares results with farmers’ perception about the policy changes, captured in a farmer intentions survey. The model results suggest that beef farms suffer a loss in farm net margins under fully decoupled (up to -21%) as well as under partially decoupled scenario (up to -19%) compared to current historical single farm payments. The model also shows that farm respond by reducing the number of beef animals on farm by up to 5%. However, under a partial decoupled scenario, beef farms increase calf numbers by 15% to benefit from coupled calf payment. A survey of 1,400 beef producers with respect to their intentions toward 2020 was conducted in the Summer of 2013. A set of hypothetical payment scenarios was used to test self-reported response to a number of scenarios related to expanding and extensifying. These were compared with the modelling results and found a range of responses which could, we argue, be used for future calibration and ‘sense-checking’ of results within future modelling strategies

    Data format standards and variable mapping

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    Short report on work being done tools used for standardising data formats, including variable name mapping

    LIAISE – Linking Impact Assessment instruments with sustainability expertise

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    Impact Assessment for Sustainable Development: Knowledge Systems for the Future The ex ante Impact Asssessment of planned policies has developed as an important part of policy making within the European institutions as well as in Member States. The analysis of expected economic, social and environmental impacts informs the decision making. Collecting relevant and trustworthy evidence is a challenge for policy decisions. At the same time, Impact Assessment is an opportunity for researchers, research organisations and funding agencies to develop knowledge relevant for societal decision making.As a European research consortium LIAISE investigated over the past 4.5 years the Impact Assessment (IA) practices in relation to Sustainable Development (SD). Specific attention was given to the question how the process of IA in various venues (i.e. nation states, supra national organizations and local organizations) is related to the processes of research and knowledge production

    “Methods of management with processes and resources in organizations and the economy”, “Application of water saving irrigation and fertigation systems in plants cultivation"

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    The first research project concerns methods of management with processes and resources in organizations and the economy. In order to address socio-economic problems, methods for evaluating the way in which natural resources are globally utilised in the face of the adverse effects of climate change must be developed. Previous findings of the project MACSUR allow to formulate the hypothesis that the method developed in UTP integrated with models of MACSUR partners is useful to assess the impact of climate change on food security in the context of growing economic risks in agricultural production. Verified hypothesis allows us to expect a common understanding on the assessment of the impact of climate change on food security in the light of the growing threat of food production.The second research project is to assess the feasibility and effectiveness of the system of drip irrigation in the cultivation of selected crops in the area of particularly large water shortages . Field studies are carried out in parallel on two soil types in the Research Centre of the University of Technology and Life Sciences near Bydgoszcz. The results confirm the possibility of a significant increase in productivity of irrigated plants on very light and light soils. The most important result of the synergistic relationship of this project to MACSUR project can be economic evaluation of the cost-effectiveness of surveyed plants under conditions of increasing drought probability. The results will be presented to stakeholders - agricultural producers , which will confront their usefulness in the management of farms.This work was co-financed by NCBiR, Contract no. FACCE JPI/04/2012 - P100 PARTNE

    Problems and opportunities in climate change adaptation in North Savo region

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    Crop production for feed dominates land use in North Savo in eastern Finland. The value of dairy and beef production is appr. 70 % of the total value of agricultural production of the region. In climate change adaptation research we are especially interested in dairy and meat sectors, which are directly dependent on the development of productivity of crop production. Climate change implies changes in cereals and forage crop yields and nutritive quality. There are most likely increasing problems and risks related to overwintering and growing periods. Grass silage is mainly self-produced on farms and most often there is no market for silage. Silage production and use are vulnerable to changes in local climate, because lost yield cannot be easily replaced from market. Risks and costs due to increasing inter-annual yield volatility can be reduced by good management practices, such as crop rotation, plant protection, soil improvements and better crop protection against plant diseases.However the profitability of such measures is dependent on market and policy conditions. Nevertheless new cultivars and species, as well as various options for production and risk management, are most likely needed in future climate. Some adaptations may have multiple benefits which however may realize only in medium or long run. It is important to safeguard the most important and obviously needed adaptations, and identify market and socio-economic conditions which inhibit farmers from necessary adaptations and lead to reduced productivity and increased production costs

    Effect of drought and heat stresses on transpiration and photosynthesis of wheat

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    Global warming and frequent extreme weather conditions affect crop yields worldwide. Drought and high temperatures are among stresses that often act simultaneously. Therefore the aim of the studies was to analyze effect of combined drought and heat stresses on growth and function of spring wheat. The experiment was conducted in a growth chamber conditions. Spring wheat cv Łagwa was planted in soil columns of 10cm in diameter and 45cm high filled with Orthic Luvisol developed from loess and grown up  to the end of flowering.  The treatments were: (C) control with optimum growth soil water potential 160 hPa (pF 2.2) , 250 µmol m-2s-1 PAR, 22/18 °C day / night temperatures and  60% air relative humidity throughout growing period; (D) drought stress with soil water potential 250 kPa (pF 3.4) at flowering; (HT) high temperature stress with air temperature 34/24°C and optimum soil water potential ; (DHT) drought  (as above) and high temperature (34/24°C day / night) stresses at flowering. During the experiment photosynthesis rate, transpiration and stomatal conductance were  measured using the gas exchange system GFS-3000 and DualPAM 100 (Walz, Germany). Drought stress reduced photosynthesis rate by  11%, high temperature by 19% and both stresses by 79% as compared to control  (100%). However, drought stress decreased transpiration rate similarly as combined drought and high temperature stresses (by 60-63%). Transpiration rate under high temperature stress compared to control slightly increased

    Farm level dynamic economic modelling of crop rotation with adaptation practices

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    Agriculture is facing increasing challenges under volatile commodity markets, on-going climate change with more frequent extreme weather events and tightened environmental constraints. Crop rotation is considered essential and may even gain more importance for sustainable farming in the context of climate change challenges while monocropping is expected to become increasingly problematic. This is, among others, because of increasing plant protection challenges due to warmer climate which is expected to result in severe droughts, heavy rainfall and waterlogging in northern latitudes more frequently. Such changes require improved soil structure and water retention, also aided by crop rotations, to avoid yield losses. Our objective is to build and apply a dynamic optimization model of farm level crop rotation on many field parcels over 30-40 years. The model takes into account various adaptation management methods such as fungicide treatment, soil improvements such as liming, and nitrogen fertilization, simultaneously with dynamic crop rotation choices. However, these management options come along with costs. Using the model, outcomes of crop growth simulation modeling can be included into economic analysis. Simulated new cultivars, suited for a longer growing season, can be defined as alternatives to current cultivars, both having specific nutrient and other input requirements such as water, labor or pesticides. The model is used in evaluating the value of future cultivars and other management practices in climate and socio-economic scenarios. The first results show that expected market prices have major impacts on the management choices, the resulting yield levels, production and income over time

    Climate change impacts on natural pasturelands of Italian Apennines

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    As well as the entire Mediterranean area, the Italian Apennines have been affected by increasing temperatures, rainfall extreme events and decreases in annual precipitation due to climate change. Moreover, permanent grasslands, species-diverse ecosystems characterizing the marginal areas of the Apennines landscape, are acknowledged as very sensitive and vulnerable to climate variation. Building on these premises, statistical classification models coupled with data integration by GIS techniques, were used to territorially assess future climate change impacts on pastoral communities on the Italian Apennines chain. Specifically, a machine learning approach (Random Forest - RF), firstly calibrated  for the present period and then applied to future conditions, as projected by HadCM3 General Circulation Model (GCM), was used to simulate potential expansion/reduction and/or altitudinal shifts of the Apennine pasturelands in two time slices, centred on 2050 and 2080, under A2 and B2 SRES scenarios. RF classification model proved to be robust and very efficient to predict lands suited to pastures with regards to present period (classification error: 12%). Furthermore, according to RF simulations, relevant reductions (46 and 34%) of areas potentially suitable for pastoral resource are expected under A2 at the middle and end of the century, respectively, as depicted by the GCM and SRES scenarios. Moreover, progressive upwards shifts are predicted by the model under both SRES scenarios. These reductions will likely interest the central area of the chain threatening the typical and unique herbaceous biodiversity characterizing the Apennine pasturelands

    A comprehensive climate characterization of the Oristano (Sardinia) regional pilot case study.

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    In order to assess probability distributions of critical response variables in a full crop modelling system, a complete climate characterization has been implemented to identify principal variability components in the Oristano (Sardinia) regional pilot study area with a particular emphasis on current vs near future climate. The past climate variability along with the near future climate perspective (2020-2030) has been analyzed to highlight and address the transition period and to better identify effective adaptive response of cropping systems to climate change. Surface atmospheric fields as temperature and rainfall, along with large scale atmospheric circulation types have been analysed to provide a comprehensive nexus for seasonal and sub-seasonal variability over the recent past and near future in the Central Mediterranean basin. Furthermore a robust stratification of sub-seasonal atmospheric regimes as wet/dry spells and hot/cold spells has been defined to identify main forcing mechanisms over specific critical periods for agronomical practices and studying their links with potential remote climate centre of actions

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    FACCE MACSUR Reports (Modelling European Agriculture with Climate Change for Food Security)
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