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Del Prado, A., Van den Pol-van Dasselaar, A., Chadwick, D., Misselbrook, T., Sandars, D., Audsley, E., et al. (2015). Synergies between mitigation and adaptation to Climate Change in grassland-based farming systems (Vol. 6).
Abstract: Climate change mitigation and adaptation have generally been considered in separate settings for both scientific and policy viewpoints. Recently, it has been stressed (e.g. by the latest IPCC reports) the importance to consider both mitigation and adaptation from land management together. To date, although there is already large amount of studies considering climate mitigation and adaptation in relation to grassland-based systems, there are no studies that analyse the potential synergies and tradeoffs for the main climate change mitigation and adaptation measures within the current European Policy context. This paper reviews which mitigation and adaptation measures interact with each other and how, and it explores the potential limitations and strengths of the different policy instruments that may have an effect in European grassland-based livestock systems. No Label
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Dalgaard, T., Kjeldsen, C., & Graversgard, M. (2015). Review of regional scale models in the EU and methods commonly used when modelling outcomes of the implementation of the climate change mitigation policies (Vol. 6).
Abstract: Management of Nitrogen (N) losses and the related greenhouse gas emissions is one of the most important environmental issues related to agriculture. This report shows examples of an integrated model tool, developed to quantify the N-dynamics at the complex interface between agriculture and the environment, and quantify effects of different management practices. Based on results from the EU funded research projects NitroEurope (www.NitroEurope.eu) and MEAscope (www.MEA-scope.org), examples from the quantification of farm N-losses in European agricultural landscapes are demonstrated. Applications of the dynamic whole farm model FASSET (www.FASSET.dk), and the Farm-N tool (www.farm-N.dk/FarmNTool) to calculate farm N balances, and distribute the surplus N between different types of N-losses (volatilisation, denitrification, leaching), and the related greenhouse gas emissions, show significant variation between landscapes and management practices. Moreover, significant effects of the nonlinearities, appearing when integrating over time, and scaling up from farm to landscape, are demonstrated. Finally, perspectives for stakeholder involvement is included and general recommendations for landscape level management of farm related nitrogen and greenhouse gas fluxes are made, and discussed in relation to ongoing research in the European research projects. No Label
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Dalgaard, T. (2015). Models for regional scale farming system evaluation of climate change mitigation options and environmental impact assessment (Vol. 5).
Abstract: The aim of the present paper is to exemplify and discuss the importance of farm scale modeling in relation to The EU Joint Programming Initiative (JPI-FACCE) knowledge hub on Agriculture, Food Security and Climate Change project.In particular, livestock production systems include complex interactions, with non-linear relationships between input factors, production, emissions, local climate as well as natural resources (e.g. soil types, rotational land versus permanent grasslands etc.). Moreover, management options pursued by the different types of farmers and other relevant decision makers are important to integrate. Consequently, results of regional scale impact assessments depend on the farming systems model approach, the approach to upscale results, and the inclusion of the relevant stakeholders and decision makers at the scales considered.Different farming systems models are reviewed, including the existing dynamic and static biophysical models. Finally, procedures for upscaling and validity testing of synthesized model results at regional scales are presented. Based on a discussion of these procedures, recommendations for hot-spot analyses in farming systems with regard to integrated climate change adaptation and mitigation for a sustainable food production are synthesized, and the potentials for integration of recommended policies and farm management options into overarching models in order to assess their impact on the regional to global scales are discussed. No Label
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Dader, B. (2015). Elevated CO2 impacts bell pepper growth with consequences in the feeding behaviour and performance of the green peach aphid, Myzus persicae (Vol. 5).
Abstract: Future CO2 predictions estimate an increase up to 550 ppm within only few decades away. Among the observed effects on plants, increasing CO2 stimulates growth, reduces stomatal conductance and transpiration, improves water-use efficiency and induces photosynthesis. These changes have an indirect impact on pest biology and behaviour, e.g. altering their population growth or feeding habits.Our first aim was to study the effect of ambient (400 ppm) (aCO2) and elevated CO2 (650 ppm) (eCO2) on pepper (Capsicum annuum L.). Height, leaf area, dry weight and leaf temperature by thermal imaging were measured. Chlorophyll was measured in SPAD units as an indirect indicator of nitrogen foliar content. Peppers under eCO2 were significantly taller although they had the same number of leaves than under aCO2. SPAD was significantly lower under eCO2. Leaf, stem and above-ground dry weight were significantly higher under eCO2. There was a significant decrease in specific leaf area under eCO2. Canopy temperature was 1.2 °C higher under eCO2.Secondly, pepper plants were used to assess the development and fecundity of M. persicae. The pre-reproductive period was 11% longer in eCO2 peppers. Aphids grew significantly slower and produced fewer nymphs under eCO2. Lastly, aphid feeding behaviour was studied using the Electrical Penetration Graph (EPG) technique, which provides a live visualization and recording of plant penetration by aphid mouthparts. EPG results will be presented and discussed. No Label
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Coucheney, E. (2015). Sensitivity of crop water and N stress to soil input data in regional cropyield simulations and the implications for data aggregation effects: a case study with the COUP-model (Vol. 5).
Abstract: The effects of aggregating soil input data on modelling crop yields at regional scale have been explored within the MACSUR- Crop M – WP3 scaling exercise for an ensemble of crop models 1. The models were run for the North Rhine-Westphalia region in Germany with an average climate time-series (30 years) and soil data at resolution 1 km to 100 km. Aggregation effects showed substantial differences between the models 1. This could be linked to differences in model structure and concepts and to different procedures for the parameterization of soil properties. A further analysis of the sensitivity of the outputs to key soil properties, for each ‘model – method of parameterization’, could help in understanding differences observed within the model ensemble. In this study, we explored the relationship between winter wheat yields, water and N-stress indexes and simple key-soil properties, based on the COUP-model 2 simulations. Soils were grouped into classes according to selected parameters (i.e. soil depth, soil texture and soil organic content). Preliminary results show that some of those soil classes are clearly associated with high water and / or N-stress and lower yields or with high inter-annual variation of the yield. As such they represent key factors explaining the spatial pattern of the simulated yield at the different resolutions. In addition we identified differences in the fractional area of those soil classes between high and low spatial resolutions (‘inherent errors’ due to data aggregation). How this may influence soil data aggregation effects on simulated yields will be further analyzed. No Label
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