FACCE MACSUR Reports (Modelling European Agriculture with Climate Change for Food Security)
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Long term lysimeter device of Fagnières (F- 51)
No full textThe data has been published as Yin X., Beaudoin N., Louarn G., Ferchaud F., Mary B., Strullu L., Chlébowski F., Clivot H., Herre C., Duval J., Louarn G (in press). Long term modelling of soil N mineralization and N fate using STICS in a 34–year crop rotation experiment. Geoderma. doi: 10.1016/j.geoderma.2019.11395
Data Aggregation effects on the regional N Cycle
No full textData Aggregation effects on the regional N Cycl
Evaluating clover grass as a climate change adaptation measure in agriculture at the sector level
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The regional trends in maize yield in Poland and its prediction according regional GLOBIOM –CAPRI baseline analysis for 2010, 2030 and 2050
No full textThe increase of maize production in Polish agriculture is considered as one of the indicators showing temporal climate change impact. The sowing area of grain maize in Poland increased from 152 thousand hectares in 2000 to 614 thousand hectares in 2013. In the same time, the area of maize production for forage in Poland has increased from 162 to 462 thousand hectares. There is observed increase of yield level but the regional differentiation of this trend is also visible. In the paper we discuss the temporal regional trends in maize yield in Poland connected to the limitation factors (soil, climate, fertilisation) and prognosis for further climate change impact using GLOBIOM-CAPRI regional simulations. The data for the analysis of regional trends for maize production level in 16th regions in Poland (NUTS2) were taken from National Statistical Offices Reports. The GLOBIOM-CAPRI regional simulations for baseline analysis 2010, 2030 and 2050 were obtained from MASCUR knowledge-hab evaluation exercises. As a limitation factors for of maize yield we considered the index for suitable soil and climate suitability index for climate developed in Poland and fertilisation. We have identified that observed positive trend in yield level at NUTS2 is correlated with the climate suitability index and level of NPK fertilisation, whilst there is no statistical relations with soil quality index. The GLOBIOM –CAPRI regional simulation for 2030 shows that the maize yield in Poland will further increase and it can be explained by realisation of existing trends. In simulations for the baseline 2050 year there is visible negative trend in yield level in some regions, where even in current climate there is high probability of deficit precipitation (eg. Wielkopolskia region)
Contributions from bio-eocnomic farm models to the analysis of climate change adaptation: lessons from MACSUR regional pilot studies
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Prototype of stochastic equilibrium model of the food system
Get PDFFood security is an issue of risk. If climate change is not responded to with diet, technology and/or policy changes, it may lead to reduced food security for the world population, in particular the poorer part which in longer periods may not afford to purchase food in sufficient quantity and quality. In order to improve the situation, certain policy changes may be required. In some cases are policy recommendations relatively obvious, while in other cases a deeper insight in the stochastic dynamics of food supply and storage is required to assess the consequences of policy proposals. The relatively obvious part is that farmers need be responsive in periods of low total production, so that sufficient supply restores quickly. Moreover, trade should allow local shortages to be covered. Many national policies with the goal of self-sufficiency aim in the opposite direction with stable prices and production and relatively less flexibility in production. The stochastic dynamics of food supply can be analysed in more detail with a dynamic stochastic general equilibrium model (DSGE). Although agriculture by nature is about taking decisions under uncertainty, quantitative stochastic dynamic models for policy analysis in agriculture have not yet emerged. The contribution in MACSUR is a formalization of a class of DSGE-s based on representation of biological processes managed with regard to outcomes due to uncertain nature.
Synergies and trade-offs of adaptation and mitigation on dairy farms
No full textLivestock farms with ruminants have large and diverse fluxes of greenhouse gases, but are also affected in diverse ways by climate change. This calls for assessments of possible options to mitigate GHG and to adapt to changing climate, primarily at the farm-scale. This study focuses on the effects of adaptation and mitigation options, and their synergies and trade-offs on GHG emissions and production on European dairy farms. The impact of climate change on livestock production systems will vary with livestock type, system design and local conditions. These effects are direct through impacts on animal performance and indirect through effects on crop yield and quality. These impacts demand adaptations of farming systems to cope with the changed climate. Adaptation can be categorized in three main categories: feed, livestock and water management. Several of these adaptation options have impact on greenhouse gas emissions and thus on the mitigation potential. There is therefore need to align measures for reducing greenhouse gas emissions with the likely adaptations to be adopted. Based on expert opinion, assessments have been performed on which adaptation and mitigation measures would likely be adopted for real on maritime dairy farms located in Ireland and the Netherlands
Scenarios of regional agricultural land use under climate change for 4 case study regions in Northern Germany
No full textAgricultural land use in Northern Germany is characterized by a gradient of decreasing precipitation from west to east. Climate change is expected to increase temperature and decrease summer precipitation. In the context of a nationally funded project we aim to analyze climate change adaptation strategies for agricultural land use. The research is focused in 4 study regions from Eastern to Western Germany. The presented modelling approach analyses agricultural land use under climate change and for three policy scenarios (business as usual, biodiversity and climate protection). The biodiversity and climate protection scenarios each reserve area for specific scenario objectives: 10% for specific biodiversity measures and 20% for N-fixing legumes in case of the climate protection scenario. All scenarios are executed for three time steps representing year 2010, 2020 and 2030 with a constant yield increase, extrapolated from past observations. Building on IACS data for a farm typology and expert assessments of current and future land use options, we applied a linear programming farm model. Prices are exogenous and derived from CAPRI model runs for 2020 and 2030. First preliminary results show strong impacts of price assumptions and yield assessments. This results in 2020 in lower gross margins for a number of crops and finally to higher set aside areas in eastern Germany. For 2030 input–output price relations are more favourable for farmers and thus lead to lower set aside areas