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1.
  • Alkan Olsson, Johanna, et al. (författare)
  • A goal oriented indicator framework to support integrated assessment of new policies for agri-environmental systems
  • 2009
  • Ingår i: Environmental Science and Policy. - : Elsevier BV. - 1462-9011. ; 12:5, s. 562-572
  • Tidskriftsartikel (refereegranskat)abstract
    • The goal oriented framework (GOF) for indicators has been developed as part of a comprehensive research project developing computerised tools for integrated assessment of the effects of new policies or technologies on agricultural systems (SEAMLESS-IF). The ambition has therefore been to create an indicator framework where the environmental, economic and social dimensions of sustainable development can be related to each other in a consistent way. Integrated assessment tools rely on such frameworks to capture and visualise trade-offs (antagonisms or synergies) among indicators between and within the three dimensions of sustainable development. The specific aims of this paper are to (i) present the GOF (ii) present how the GOF can be used to select indicators within the integrated assessment framework SEAMLESS-IF and (iii) discuss the advantages and limitations with the proposed approach. We show that the GOF has several advantages. Its major rewards are its relative simplicity and the possibility to link indicators to policy goals of each dimension of sustainability and thereby facilitate the comparison of the impacts of the new policy on the different dimensions. Another important feature of the GOF is its multi-scale perspective, which will enable the comparison of effects of a new policy between scales. Yet, as typical for all indicator frameworks, the GOF has also biases either instigated by the issues the included models cover or by the stakeholders' selection of indicators. However, due to the way the GOF and its indicators are technically implemented in SEAMLESS-IF, it can easily be extended and include new indicators to increase and update its policy relevance. (C) 2009 Elsevier Ltd. All rights reserved.
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  • Ewert, Frank, et al. (författare)
  • A methodology for enhanced flexibility of integrated assessment in agriculture
  • 2009
  • Ingår i: Environmental Science and Policy. - : Elsevier BV. - 1462-9011. ; 12:5, s. 546-561
  • Tidskriftsartikel (refereegranskat)abstract
    • Agriculture is interrelated with the socio-economic and natural environment and faces increasingly the problem of managing its multiple functions in a sustainable way. Growing emphasis is on adequate policies that can support both agriculture and sustainable development. Integrated Assessment and Modelling (IAM) can provide insight into the potential impacts of policy changes. An increasing number of Integrated Assessment (IA) models are being developed, but these are mainly monolithic and are targeted to answer specific problems. Approaches that allow flexible IA for a range of issues and functions are scarce. Recently, a methodology for policy support in agriculture has been developed that attempts to overcome some of the limitations of earlier IA models. The proposed framework (SEAMLESS-IF) integrates relationships and processes across disciplines and scales and combines quantitative analysis with qualitative judgments and experiences. It builds on the concept of systems analysis and attempts to enable flexible coupling of models and tools. The present paper aims to describe progress in improving flexibility of IAM achieved with the methodology developed for SEAMLESS-IF. A brief literature review identifying limitations in the flexibility of IAM is followed by a description of the progress achieved with SEAMLESS-IF. Two example applications are used to illustrate relevant capabilities of SEAMLESS-IF. The examples refer to (i) the impacts on European agriculture of changes in world trade regulations and (ii) regional impacts of the EU Nitrates Directive in combination with agro-management changes. We show that improving the flexibility of IAM requires flexibility in model linking but also a generic set up of all IA steps. This includes problem and scenario definition, the selection and specification of indicators and the indicator framework, the structuring of the database, and the visualization of results. Very important is the flexibility to integrate, select and link models, data and indicators depending on the application. Technical coupling and reusability of model components is greatly improved through adequate software architecture (SEAMLESS-IF uses OpenMI). The use of ontology strongly supports conceptual consistency of model linkages. However, the scientific basis for linking models across disciplines and scales is still weak and requires specific attention in future research. We conclude that the proposed framework significantly advances flexibility in IAM and that it is a good basis to further improve integrated modelling for policy impact assessment in agriculture. (C) 2009 Elsevier Ltd. All rights reserved.
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4.
  • van Ittersum, Martin, et al. (författare)
  • Integrated Assessment of Agricultural and Environmental Policies – A Modular Framework for the EU (SEAMLESS)
  • 2008
  • Ingår i: Agricultural Systems. - : Elsevier BV. - 0308-521X. ; 96:1-3, s. 150-165
  • Tidskriftsartikel (refereegranskat)abstract
    • Abstract in UndeterminedAgricultural systems continuously evolve and are forced to change as a result of a range of global and local driving forces. Agricultural technologies and agricultural, environmental and rural development policies are increasingly designed to contribute to the sustainability of agricultural systems and to enhance contributions of agricultural systems to sustainable development at large. The effectiveness and efficiency of such policies and technological developments in realizing desired contributions could be greatly enhanced if the quality of their ex-ante assessments were improved. Four key challenges and requirements to make research tools more useful for integrated assessment in the European Union were defined in interactions between scientists and the European Commission (EC), i.e., overcoming the gap between micro-macro level analysis, the bias in integrated assessments towards either economic or environmental issues, the poor re-use of models and hindrances in technical linkage of models. Tools for integrated assessment must have multi-scale capabilities and preferably be generic and flexible such that they can deal with a broad variety of policy questions. At the same time, to be useful for scientists, the framework must facilitate state-of-the-art science both on aspects of the agricultural systems and on integration. This paper presents the rationale, design and illustration of a component-based framework for agricultural systems (SEAMLESS Integrated Framework) to assess, ex-ante, agricultural and agri-environmental policies and technologies across a range of scales, from field-farm to region and European Union, as well as some global interactions. We have opted for a framework to link individual model and data components and a software infrastructure that allows a flexible (re-)use and linkage of components. The paper outlines the software infrastructure, indicators and model and data components. The illustrative example assesses effects of a trade liberalisation proposal on EU's agriculture and indicates how SEAMLESS addresses the four identified challenges for integrated assessment tools, i.e., linking micro and macro analysis, assessing economic, environmental, social and institutional indicators, (re-)using standalone model components for field, farm and market analysis and their conceptual and technical linkage.
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