Mereu, V., Spano, D., Gallo, A., & Carboni, G. (2014). Climate change impacts and adaptation strategies evaluation on staple food crops in different agro-climatic zones. FACCE MACSUR Mid-term Scientific Conference, 3(S) Sassari, Italy.
Abstract: Increasing temperatures, changed precipitation patterns and more frequent extreme events may lead to an increase in crop failure and to a substantial decrease of crop yields. The assessment of climate change impacts on agricultural sector has a particular interest to stakeholders and policy makers, in order to identify specific agricultural sectors and agro-climatic zones that could be more vulnerable to changes in climatic conditions and to develop the most appropriate policies to cope with these threats. For these reasons, the evaluation of climate change impacts for key crops in different agro-climatic zones was made exploring climate uncertainty and focusing on short period monitoring, which is particularly useful for food security and risk management. The analysis was made using the DSSAT-CSM (Decision Support System for Agrotechnology Transfer – Cropping System Model) software, version 4.5. Crop models implemented into DSSAT-CSM were used, for each selected crop, to evaluate climate change impacts on crop production. Multiple combinations of soils and climate conditions, crop management and varieties were considered for different agro-climatic zones. The climate impact was assessed using future climate projections, statistically and/or dynamically downscaled, for the specific areas. Direct and indirect effects of different CO2 concentrations, projected for the future periods, were separately explored to estimate their effects on crops. Finally, several adaptation strategies were evaluated with the aim to reduce the negative impact of climate change on crop production. The results of the study, analysed at local and regional scale, will be discussed.
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Milford, A. B. (2014). Sustainable food consumption as a mitigation and adaptation strategy. FACCE MACSUR Mid-term Scientific Conference, 3(S) Sassari, Italy.
Abstract: Studies of GHG emissions from agriculture show that there are large differences in emissions from different products. In addition some foods require more land and water resources than others, which mean that in a future with food scarcity, moving from less to more sustainable food may become a necessity for there to be enough food for everyone. A changing of consumption and production from less to more sustainable food is thus both a mitigation strategy, as well as an adaptation strategy if climate change results in less available agricultural land and water resources, and more food loss due to more extreme weather conditions. Forecasting the economic consequences of climate change on agricultural production cannot be done without taking into account our future consumption patterns. What will be produced will always to a large extent be a result of what is being demanded by consumers. This is a presentation of two ongoing projects related to this theme. One is a newly started project on factors which influence meat consumption. In a cross-country regression analysis we will estimate the importance of different factors such as income, price levels and degree of urbanization. We are particularly interested in the interlinkages between meat production and consumption at national levels. The other project looks at typical diets in England, Spain and Norway, and will estimate through a multi objective optimization process how the diets can be changed, through taxes and subsidies, towards a diet which is both more healthy and climate friendly.
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Minet, J., Laloy, E., Tychon, B., & François, L. (2014). Outcomes from the MACSUR grassland model inter-comparison with the model CARAIB..
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Minet, J., Laloy, E., Tychon, B., & François, L. (2014). Bayesian inference of a dynamic vegetation model for grassland. FACCE MACSUR Mid-term Scientific Conference, 3(S) Sassari, Italy.
Abstract: As a part of the MACSUR task L2.4, we probabilistically calibrated the CARAIB dynamic vegetation model by Markov chain Monte Carlo (MCMC) simulation with the DREAMZS sampler. CARAIB is a mechanistic model that calculates the carbon assimilation of the vegetation as a function of the soil and climatic conditions, and can thus be used for simulating grassland production under cutting or grazing management. Bayesian model inversion was performed at 4 grassland sites across Europe: Oensingen, CH; Grillenburg, DE; Laqueuille, FR and Monte-Bodone, IT. Four daily measured variables from these sites: the Gross Primary Productivity (GPP), Net Ecosystem Exchange (NEE), Evapotranspiration (ET) and Soil Water Content (SWC) were used to sample 10 parameters related to rooting depth, stomatal conductance, specific leaf area, carbon-nitrogen ratio and water stresses. The maximized likelihood function therefore involved four objectives, whereas the applied Bayesian framework allowed for assessing the so called parameter posterior probability density function (pdf), which quantifies model parameter uncertainty caused by measurement and model errors. Sampling trials were performed using merged data from all sites (all-sites-sampling) and for each site (site-specific sampling) separately. The derived posterior parameter pdfs from the all-sites sampling and site-specific sampling runs showed differences in relation with the specificities of each site. Analysis of these distributions also revealed model sensitivity to parameters conditioned on the measured data, as well as parameter correlations.
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Minet, J., Tychon, B., Jacquemin, I., & François, L. (2014). Can a global dynamic vegetation model be used for both grassland and crop modeling at the local scale..
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