Sandars, D., Audsley, E., & Holman, I. (2014). Predicting the optimum land use at any location for any future scenario (CLIMSAVE/IMPRESSIONS). FACCE MACSUR Mid-term Scientific Conference, 3(S) Sassari, Italy.
Abstract: Given any socio-, techno-, economic scenario and location specific soil and climate scenario, the farm model predicts the most profitable land use at that location. This model is encapsulated within a Europe-wide interactive interface, to allow adaptation and mitigation options to be explored by any user. With 5 climate models and 19 parameters, the user can study the sensitivity of the results to the chosen scenario settings. A scenario’s land use can be classified as intensive arable, intensive grassland, extensive grassland, forestry, or abandoned depending on potential profitability.
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Helming, K., Podhora, A., & König, H. (2014). Policy impact assessment – a venue for the science policy interface. FACCE MACSUR Mid-term Scientific Conference, 3(S) Sassari, Italy.
Abstract: Policy making aims to align agricultural production with multifunctional services such as environmental conservation, rural development, and economic competitiveness. Policies counteract or reinforce external driving forces such as climate change, global economic developments, demography, consumption patterns. They considerably affect decision making of farmers. Because of the interaction and non-linear feedback loops with socio-economic and geophysical processes of the land use systems, policies are difficult to design, and their impacts are difficult to anticipate. The policy making community articulates an emerging demand for science based evidence in support of the policy process. Ex-ante impact assessment of policy making provides the legal basis to fuel scientific evidence into the policy process. For researchers, impact assessment is a means to structure the analysis of human-environment interactions. For policy makers, impact assessment is a means to better target policy decisions towards sustainable development. The integration of both requires a mutual understanding of the respective objectives and operational restrictions within the scientific and policy-making domains. This paper provides insight into the process of policy impact assessment and how research based methods and tools can best feed into it. Three aspects are outlined: the co-design of the assessment between policy makers and researchers; the integration of quantitative analysis with participatory valuation methods; and the robustness and transparency of the analytical methods.
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Haas, E., Klatt, S., Kiese, R., Santa Barbara Ruiz, I., & Kraus, D. (2014). Parameter-induced uncertainty quantification of a regional N2O and NO3 inventory using the biogeochemical model LandscapeDNDC. FACCE MACSUR Mid-term Scientific Conference, 3(S) Sassari, Italy.
Abstract: In this study we quantify regional parameter-induced model uncertainty on nitrous oxide (N2O) emissions and nitrate (NO3) leaching from arable soils of Saxony (Germany) using the biogeochemical model LandscapeDNDC. For this we calculate a regional inventory using a joint parameter distribution for key parameters describing microbial C and N turnover processes as obtained by a Bayesian calibration study. We representatively sampled 400 different parameter vectors from the discrete joint parameter distribution comprising approximately 400,000 parameter combinations and used these to calculate 400 individual realizations of the regional inventory. The spatial domain (represented by 4042 polygons) is set up with spatially explicit soil and climate information and a region-typical 3-year crop rotation consisting of winter wheat, rape- seed, and winter barley. Average N2O emission from arable soils in the state of Saxony across all 400 realizations was 1.43 ± 1.25 [kg N / ha] with a median value of 1.05 [kg N / ha]. Using the default IPCC emission factor approach (Tier 1) for direct emissions reveal a higher average N2O emission of 1.51 [kg N / ha] due to fertilizer use. In the regional uncertainty quantification the 20% likelihood range for N2O emissions is 0.79 – 1.37 [kg N / ha] (50% likelihood: 0.46 – 2.05 [kg N / ha]; 90% likelihood: 0.11 – 4.03 [kg N / ha]). Respective quantities were calculated for nitrate leaching.
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König, H. J. (2014). Operationalising sustainability impact assessment of land use scenarios in developing countries: A stakeholder-based approach with case studies in China, India, Indonesia, Kenya, and Tunisia. FACCE MACSUR Mid-term Scientific Conference, 3(S) Sassari, Italy.
Abstract: Growing populations, continued economic development, and limited natural resources are critical factors affecting sustainable development. Ex-ante impact assessment is an emerging field poised at the science-policy interface and is used to assess the potential impacts of policy while also exploring trade-offs between economic, social and environmental sustainability targets. The Framework for Participatory Impact Assessment (FoPIA) was selected for this study because it allows for the integration of various sustainability dimensions, the handling of complexity, and the incorporation of local stakeholder perceptions. FoPIA was adapted to the conditions of developing countries, and its implementation was demonstrated in five selected case studies. Based on the findings from the five case studies, FoPIA was found to be suitable for implementing the impact assessment at case study level while ensuring a high level of transparency. FoPIA supports the identification of causal relationships underlying regional land use problems, facilitates communication among stakeholders and illustrates the effects of alternative decision options with respect to all three dimensions of sustainable development.
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Gøtke, N. (2014). Opening remarks by the chair of the FACCE JPI Governing Board. FACCE MACSUR Mid-term Scientific Conference, 3(S) Sassari, Italy.
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