FACCE MACSUR Reports (Modelling European Agriculture with Climate Change for Food Security)
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Crop responses to soil salinization in the context of climate change
No full textSoil salinization is an expanding phenomenon, exacerbated by climate change. Mediterranean environments are exposed to salinization. Assessment of the specific crop-environment interactions is therefore critical for these areas. In this context, models to evaluate crop response to salinity, including applications of SWAP and Hydrus models to study viable water management options and water movement in salinized agricultural zones can contribute to identify optimal mitigation strategies
Reconciling estimates of climate change effects on nitrate leaching from agricultural crops
No full textNitrate leaching from agricultural systems constitutes a severe environmental effect in regions with valuable groundwater resources and vulnerable aquatic ecosystems. Therefore cropping systems should in many parts of Europe reduce the amount of nitrate leached from the root zone. Since soil nitrogen transformation and loss processes are highly influenced by climate, including temperature and precipitation, estimates of climate change effects on nitrate leaching is in high demand for evaluating future groundwater and surface water protection policies. Modelling studies using both the FASSET and Daisy models for cereal crops as well as arable crop rotations in Denmark have shown increased nitrate leaching under projected climate change. Sensitivity analyses using these models have shown a higher response to changes in temperature than to precipitation, although in particular precipitation responses differ between soil types. Simulations for crop rotations show that current catch crop management may not be sufficient to maintain low nitrate leaching levels in future. These effects of temperature and precipitation as well as crop management are confirmed in an empirical analysis of nitrate leaching from a long-term cropping system experiment in Denmark. The main uncertainties on climate change effects on future nitrate leaching appears to be related to effects of climate change on soil organic matter and thus on the amount of soil total N available for mineralization as well as the effects of enhanced atmospheric CO2 concentration on crop residue quality and N mineralization
Simulating the sensitivity of carbon and water fluxes as well as yield within the ClimAfrica project
No full textSub Saharan Africa (SSA) is a region expected to be particularly sensitive to climate change effects on crop yield (Barrios et al. 2008). Annual precipitation, calculated as averages for each African country, is expected to change by −39 to +64 mm by 2030 (Jarvis et al. 2012). The effect of climate also becomes larger as ~97 % of all agricultural land in SSA is rain fed (Rockström et al. 2004). The aim of the ClimAfrica project (FP7) is to better understand and predict climate change in SSA and to analyse the impacts on ecosystems and populations. Within the modeling Work Package (WP3) the main goal is to quantify the sensitivity of vegetation productivity and water resources to seasonal interannual decadal variability in weather and climate using a set of crop models. Here we present some results on the sensitivity of simulated carbon fluxes and FAPAR for different representations of cropland in a vegetation model (LPJ-GUESS: Lindeskog et al. 2013) as well as the sensitivity on simulated fluxes of carbon water and crop yield using a range of vegetation and crop models (LPJ-GUESS, LPJmL, ORCHIDEE and DSSAT), climate datasets, GCM output and bias correction/downscaling techniques
Relationships between temperature humidity index, mortality, milk yield and composition in Italian dairy cows
Get PDFThe aim of this presentation is to illustrate the activities performed by the LiveM-Task L1.2. group based at the University of Tuscia, Viterbo, Italy. Three different pluriannual databases were built to perform retrospective studies aimed at establishing the relationships between temperature humidity index (THI) and parameters of interest for dairy cow farms. The THI combines temperature and humidity in a single value and has been widely used to quantify heat stress in farm animals. The first database was built to assess the relationships between THI and mortality over a 6 yr period (2002-2007); the second one was a 7 yr database (2001-2007) which was built to establish the relationships between THI and milk yield; the last database included THI, milk somatic cell counts, total bacterial counts, fat and protein percentages data collected over a 7 yr period (2003-2009). The analysis of the three databases provided several equations which demonstrated and quantified an increase of mortality, reduction of milk yield and a worsening of milk quality in hot environment. Results of these analyzes authorized speculations about risks for dairy cows and their productivity in a warming planet. Furthermore, the same results are being utilized by economists also working within MACSUR at the University of Tuscia for an integrated study aimed at establishing the economic impact of climate change in the dairy sector. Combining this information with climate change regional scenarios might permit prediction of the impact of global warming and identification of adaptation measures that are appropriate for specific contexts
Deliberative processes for comprehensive evaluation of agro-ecological models
Get PDFBiophysical models are acknowledged for examining interactions of agro-ecological systems and fostering communication between scientists, managers and the public. As the role of models grows in importance, there is an increase in the need to assess their quality and performance (Bellocchi et al., 2010). However, the heterogeneity of factors influencing model outputs makes it difficult a full assessment of model features. Where models are used with or for stakeholders then model credibility depends not only on the outcomes of well-structured statistical evaluation but also less tangible factors may need to be addressed using complementary deliberative processes. To expand our horizons in the evaluation of crop and grassland models, approaches have been reviewed with emphasis on using combined metrics. Comprehensive evaluation of simulation models was developed to integrate expectations of stakeholders via a weighting system where lower and upper fuzzy bounds are applied to a set of evaluation metrics. A questionnaire-based survey helped understanding the multi-faceted knowledge and experience required and the substantial challenges posed by the deliberative process. MACSUR knowledge hub holds potential to advance in good modelling practice in relation with model evaluation (including access to appropriate software tools), an activity which is frequently neglected in the context of time-limited projects
LandPaKT
Get PDFLandPaKT (agricultural techniques: potentials and costs of greenhouse gas mitigation) is a joint project of the Leibniz Institute for Agricultural Engineering (ATB) and the Agricultural-Horticultural Faculty of the Humboldt University Berlin. Within the established graduate school LandPaKT, seven PhD students analyse the mitigation potentials and costs of greenhouse gas emissions systematically and merge them at the farm level. With the re-wetting of organic soils, the carbon sequestration in mineral soils depending on agricultural activities and the livestock husbandry, the most important sectors of agriculture are included in the analyses. With modelling and simulation approaches, single as well as combined measures are analysed with regard to their overall effect. Recommendations for the most-promising measures at farm level are deduced. Based on a farm model for water-use efficiency, developed within another ATB project (AgroHyd), LandPaKT aims to expand the model by greenhouse gas emissions. The graduate school started in May 2013.The increase of the global human population with the resulting increase in food demand accompanied by changed consumption patterns urgently calls for the exploitation of mitigation options in animal husbandry. Based on the Life Cycle Assessment (LCA) approach, methodological recommendations for carbon footprint analyses for dairy farming will be developed. Furthermore, the influence of different feeds and feeding strategies on greenhouse gas emission from dairy farming will be investigated
Methods for regional scale farming systems modelling and uncertainty assessment – sustainability assessment case studies of production, nutrient losses and greenhouse gas emissions from grassland based systems
No full textIn the EU Joint-Programming-Initiative: Modelling European Agriculturewith Climate Change for Food Security (MACSUR, LiveM: http://www.macsur.eu/index.php/livestock-modelling) we develop a research frameworkfor the modelling and sustainability assessment of livestock and grasslandbased farming systems at farm and regional scales.Based on results from related research and model development in Denmark,methodologies used for regional scaling, the description of data requirementsand sources, and methods to predict the effect and effectiveness of climate-and environment related policy measures are developed. In this study we present results from farm modelling in a study areaaround Viborg, Western Denmark using the http://www.Farm-N.dk/ model (Env.Pol. 159 3183-3192), including thedistribution of N-surpluses into different types of losses, and a comparisonwith empirical studies of farm nitrogen balances in the Danish study and fiveadditional European landscapes (Biogeosciences 9, 5303–5321). Based on this,methods and development needs for the mapping and uncertainty assessment ofnutrient losses and greenhouse gas emissions are discussed, referring to the presentdevelopment of the Farm-AC model and ongoing scenario studies in e.g. the www.dNmark.org project. In these scenarios, regional-scale policy measures areimplemented via the responses of a range of stakeholders, such as farmers,public interest groups, regulators and politicians. When modelling the outcomeof the policy measures implementation, it is often assumed that stakeholdersrespond as economically rational entities. However, social and cultural factorsare also known to play a role and modelling methods that permit these factorsto be taken into account will also be discussed
Determining the impact of soil regionalization and climate change on wheat and timothy grass yield in southeastern Norway
No full textSoutheastern Norway is characterized by variable soils, which affect its agricultural productivity. The region is dominated by cereal production, but livestock farming with forage crops has increased the latest years. Climate and socio-economic changes could entail a shift from the current production areas of cereal and forage crops. In this study we used the mechanistic models CSM-CERES and LINGRA to evaluate impacts of climate change and soil variability on wheat and timothy yields in Akerhus and Østfold Counties in Southeastern Norway. The models were run for historical (1961-90) and projected future (2046-2065) climatic conditions, and for four soil regionalizations of different resolution (1, 5, 16 and 76 representative soil profiles). The extrapolation of soil characteristics was based on similarities in texture, organic matter, layering and water holding capacity. Across the whole region, there were small differences in both spring wheat and timothy yield between the different soil regionalization resolutions. However, within certain districts within the region the differences in wheat grain yield and timothy biomass yield among the soil resolutions were up to 20 percent. These results indicate that a relatively detailed resolution of the soil proporties is preferred to better understand the impact of shifts in production between cereals and forage grasses on yield level if spatial variability within regions is considered . The climate change scenario used indicated increased yields of both crop types in a future climate. Further steps could include a weighting of the wheat and timothy production across soils according to economic analyses
A crop modeling response to economists' wishlists
Get PDFAssessments of climate change impacts on agricultural markets and land-use patterns rely on quantification of climate change impacts on the spatial patterns of land productivity. We supply a set of climate impact scenarios on agricultural land productivity derived from two climate models and two biophysical crop growth models to account for some of the uncertainty inherent in climate and impact models. Aggregation in space and time leads to information losses that can determine climate change impacts on agricultural markets and land-use patterns because often aggregation is across steep gradients from low to high impacts or from increases to decreases. The four climate change impact scenarios supplied here were designed to represent the most significant impacts (high emission scenario only, assumed ineffectiveness of carbon dioxide fertilization on agricultural yields, no adjustments in management) but are consistent with the assumption that changes in agricultural practices are covered in the economic models. Globally, production of individual crops decrease by 10 to 38% under these climate change scenarios, with large uncertainties in spatial patterns that are determined by both the uncertainty in climate projections and the choice of impact model. This uncertainty in climate impact on crop productivity needs to be considered by economic assessments of climate change
Application of Biome-BGC MuSo in managed grassland ecosystems in the Euro-Mediteranean region
Get PDFSimulation of the biogeochemical cycles of extensively and intensively managed grasslands and croplands are of particular interest due to the strong connection between ecosystem production, animal husbandry and food security. In the frame of MACSUR LiveM activities, we conducted a series of „blind tests” (i.e. uncalibrated model simulations with previously optimized model) on differently managed grasslands within Europe and Israel. We used the latest version of Biome-BGC MuSo model, the modified version of the widely used biogeochemical Biome-BGC model. Biome-BGC MuSo contains structural improvements, development of management modules, and the extension of the model to simulate herbaceouos ecosystem carbon and water cycles more faithfully. The studied ecosystems were meadows and pastures located in a variety of climate zones from the Atlantic sector to Central Europe, including Mediterranean sites. Managements were intensive and extensive grazing or mowing with or without different kind of fertilizers. Under similar options we simulated ecosystem variables, e.g. Gross Primary Production (GPP) and Net Ecosystem Exchange (NEE). Our experiences show that different sites have different sensitivity to the parameters (maximum root depth, soil parameters, etc.), but overall the model provided realistic fluxes. Experiences gained during the blind tests led us to further improve the model. Biome-BGC MuSo is available as a standalone model in personal computers, but also through virtual laboratory environment and Biome-BGC Projects database (http://ecos.okologia.mta.hu/bbgcdb) developed within the BioVeL project (http://www.biovel.eu). Scientific workflow management, web service and desktop grid technology can support model optimization in the so-called „calibrated runs” within MACSUR