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Abstract: The Gothenburg Protocol set national emission ceilings for transboundary air pollutants in 2010. These ceilings were formulated in 1999 using the Regional Air Pollution Information and Simulation (RAINS) model and national forecast data. The 2010 ceiling deadline is approaching as is a revision process which may lead to the setting of emission ceilings for 2020. This paper considers the original 1999 projections of six countries that were used within the RAINS model to inform the setting of their respective Gothenburg Protocol 2010 emission ceilings. These data are then contrast against recent inventory data and contemporary short-term forecasts out to 2010. These recent forecasts indicate that major downward shifts in the trends of pollutant emissions have been achieved, and whilst compliance challenges remain, there is a clear indication of the potential of such international agreements and their associated legislative and policy driven mechanisms. However, in a process governed by a maxim of achieving international environmental objectives at ‘least-cost’, the recent experience offers some valuable lessons. Specifically, in relation to the accuracy of energy projections and assumptions of other relevant variables in the modelling process. This paper considers these lessons and opens a discussion on the role of more adaptable mechanisms for the ongoing management of international agreements with long-term compliance horizons. [Copyright &y& Elsevier]

Abstract: Vulnerability is a term frequently used to describe the potential threat to rural communities posed by climate variability and change. Despite growing use of the term, analytical measures of vulnerability that are useful for prioritising and evaluating policy responses are yet to evolve. Demand for research capable of prioritising adaptation responses has evolved rapidly with an increasing awareness of climate change and its potential impacts on rural communities. Research into the climate-related vulnerability of Australian rural communities is only just beginning to emerge. Current research is dominated by hazard/impact modelling, drawing on a heritage of managing the risks posed by seasonal climate variability. There is a natural tendency to use the same risk management approach to understand the emergent nature of vulnerability. In this paper, we explore the consequences for policy advice of imperfectly examining vulnerability through the lens of an impact/hazard modelling approach to risk management. In a second paper in this series, we show how hazard/impact modelling can be complemented with more holistic measures of adaptive capacity to provide quantitative insights into the vulnerability of Australian rural communities to climate variability and change. [Copyright &y& Elsevier]

Abstract: This paper provides a literature review of methods and determinants relevant for modelling farm structural change within an integrated modelling chain. Environmental and economic impacts at farm level and individual farm responses to agricultural and agri-environmental policies strongly depend on characteristics like farm size, specialisation, and production intensity. Consequently, up-scaling results of corresponding farm type models in ex-ante assessment exercises requires comprehensive and valid predictions of the farm types’ future relevance under different scenarios. The paper reviews methods relevant to forecasting farm numbers in classes defined by farm typologies with the objective to identify (1) a preferable modelling approach and (2) empirically relevant determinants. Despite the literature''s considerable size, even recent studies are rather limited in scope and typically restricted to a subset of farm types and one or very few regions. With regard to data availability, computational complexity and statistical validation procedures, Markov chain models are identified as the only generally suitable method for a broadly scoped modelling approach across European regions and a differentiated farm typology. However, other research on determinants of farm growth, the number of farm holders, farm succession as well as new multi-agent based simulation approaches hint at relevant explanatory variables previously not considered in Markov chain analyses. Their impact seems testable in more ambitious cross-regional and cross-farm type setups. [Copyright &y& Elsevier]

Abstract: A major bottleneck for data-based policy making is that data sources are collected, managed, and distributed by different institutions, residing in different locations, resulting in conceptual and practical problems. The use of dispersed data for agricultural systems research requires the integration of data sources, which means to ensure consistency in data interpretations, units, spatial and temporal scales, to respect legal regulations of privacy, ownership and copyright, and to enable easy dissemination of data. This paper describes the SEAMLESS integrated database on European agricultural systems. It contains data on cropping patterns, production, farm structural data, soil and climate conditions, current agricultural management and policy information. To arrive at one integrated database, a shared ontology was developed according to a collaborative process, which facilitates interdisciplinary research. The paper details this process, which can be re-used in other research projects for integrating data sources. [Copyright &y& Elsevier]

Abstract: Biofuels are promoted worldwide as an alternative for the replacement of fossil fuels, especially in the transportation sector, although the extent to which biofuels can meet this need is unclear. Currently, oil palm is the most important crop used for biodiesel production in the world. The growth of oil palm plantations in Asia has often occurred at the expense of forest areas creating environmental concerns. Colombia is the fifth largest oil palm grower worldwide, and policies that provide subsidies have been enacted to ensure that Colombia plays an important role in future biodiesel markets. At that same time, many sectors of society are concerned that the negative effects of biofuels may be worse than the benefits. In this paper we analyze the land use transitions generated by the expansion of oil palm crops between 2002 and 2008; we identify the factors associated with the expansion and project the future expansion of plantations in Colombia by applying spatial regression analysis and econometric models. To model future expansion, we started with a map of oil palm plantations in 2008. An econometric model that incorporates the impact of governmental policies (normative and economic that support the biofuel sector) through a Time Series Intervention Model Analysis was used to estimate the cultivated area in 2020. To spatially project these estimates a spatial logistic regression model that incorporates biophysical and socioeconomic variables was used. Finally, future land use transitions associated with the expansion of oil palm plantations were analyzed. The results show that present and future oil palm expansion is concentrated in areas dominated by pastures, and to a lesser extent areas that are a mix of agricultural land and natural forests. Our results also suggest that it is highly unlikely that the government will reach its goal of over 3 million hectares of oil palm plantations by 2020 and the goal of biodiesel blends supplying 20% of the national fuel needs. [Copyright &y& Elsevier]

Abstract: I argue in this paper that transaction cost is central to the analytics of climate adaptation in the local commons. I illustrate this by bringing together insights from Coase on tradability of property rights, Ostrom on institutional design principles for long lived commons and Williamson on transaction cost and governance mechanisms. I call this the COW model on the analytics of climate adaptation, which I illustrate using grounded theory in the case of the 400-year old zangjera irrigation societies in Northern Philippines. The zangjeras are highly vulnerable to climatic risks but has successfully managed to adapt steadily overtime. I argue that their ability to adapt is a function of transaction cost which is associated with some ingenious principles of institutional design such as: (1) clear allocation and tradability of rights and obligations; (2) fairness in the allocation of risks, costs and benefits; (3) reliance on prices and incentives as adaptation mechanisms; (4) adaptive efficiency, i.e. maximization of welfare at least adaptation cost; (5) reliable enforcement mechanisms; and (6) a polycentric structure of governance. I conclude that the COW model can provide a useful foundation for the analytics of climate adaptation. [Copyright &y& Elsevier]

Abstract: Addressing the conflict between biodiversity conservation and enhancing human well-being is a complex exercise that must draw upon social, economic, cultural and biophysical perspectives. Project interventions seeking to achieve a ‘balance’ between conservation and development whereby biodiversity is conserved and people''s livelihoods improve need to address these broad contextual issues. However, most attempts fail because they are not based upon understanding of system complexity, they assume “win-win” situations, they fail to plan for the impacts of society-wide changes happening beyond the project landscapes, and they use top-down – planning – approaches. In this paper we explore the use of system dynamics modelling for investigating trade-offs and synergies in landscape-scale approaches to conservation and development. We advocate the use of ‘scoping models’ because of their ability to incorporate complexity and promote social-learning in a participatory environment, while increasing the capacity of local actors to manage social-ecological complexity. We discuss their role in facilitating change in policies and practice in three landscapes in the tropics. Models do not provide a magic bullet solution and should not be used in isolation. They must be deployed along side other participatory and technical tools appropriate to local conditions. [Copyright &y& Elsevier]

Abstract: Water management in Uzbekistan (Central Asia) is facing tremendous challenges. They are rooted in past and present environmental degradation, the socio-economic transition after the breakup of the Soviet Union, and the impacts of climate change. The Uzbek government has initiated reforms in the agricultural and water sectors to steer the socio-economic transition and address the threats of increasing water scarcity and decreasing agricultural productivity. However, despite the urgency of the problems and massive international assistance changes to the water management regime have only been minimal so far. In this paper we identify major structural barriers for adaptation of the water management regime through an analysis of two recent policy processes. Both processes address pressing water management issues such as “coping with extreme events” and “providing water for ecosystems”. They were analyzed using the Management and Transition Framework as well as a group model building exercises with stakeholders on the national, regional and local levels. The analyses reveal a lack of vertical integration across administrative levels of the formal system and a still prevailing strong centralization of water management. Moreover the water management regime is strongly influenced by informal institutions that shape the outcomes of policy processes. The interactions guided by informal institutions provide an informal link between different administrative levels of the regime. However, those informal networks and the social capital embedded in them rather prevent needed changes. The resulting combination of top down institutional change initiated by socio-economic transition and bottom-up consolidation of the existing status quo via informal processes and networks prevents social learning. It also slows down an adaptation process that potentially could lead to a transition towards a more adaptive regime. [ABSTRACT FROM AUTHOR]

Abstract: The benefits of utilizing intermediaries to broker understanding between environmental scientists and policy makers have become widely touted. Yet little is known about the tasks boundary spanners undertake to develop environmental policy solutions and how these tasks fit into frameworks intended to advance public policy decision making. Such frameworks may be constructed to aid decision makers in differentiating between the types of environmental policy issues that confront them or the policy settings in which they are operating. Consequently, this paper examines how six different knowledge brokering strategies; informing, consulting, matchmaking, engaging, collaborating and building capacity might be employed in responding to different types of environmental policy problems or policy settings identified in decision aiding frameworks. Using real world examples, four frameworks are reviewed. They are; Lindquist''s [Lindquist, E.A., 1988. What do decision models tell us about information use? Knowledge in Society 1 (2), 86–111; Lindquist, E.A., 1990. The third community, policy inquiry, and social scientists. In: Stephen Brooks, S., Gagnon, A. (Eds.), Social Scientists, Policy and the State. Praeger, New York; Lindquist, E.A., 2001. Discerning policy influence: framework for a strategic evaluation of IDRC-Supported research] decision regimes, Turnhout et al.’s [Turnhout, E., Hisschemoller, M., Eijsackers, H., 2007. Ecological indicators: between the two fires of science and policy. Ecological Indicators 7 (2), 215–228] science policy typology, Holling''s [Holling, C.S., 1995. What barriers? What bridges? In: Gunderson, L.H., Holling, C.S. (Eds.), Barriers and Bridges to the Renewal of Ecosystems and Institutions. Columbia University Press, New York, pp. 3–34] adaptive cycle and Kurtz and Snowden''s [Kurtz, C.F., Snowden, D.J., 2003. The new dynamics of strategy: sense-making in a complex and complicated world. IBM Systems Journal 42 (3), 462–483] Cynefin domains. For the different problem types or policy settings described in the decision aiding frameworks primary knowledge brokering strategies are identified. While the frameworks differ in their conceptual constructions, the applicability of specific knowledge brokering strategies serve as a commonality across particular problem types and policy settings. [Copyright &y& Elsevier]

Abstract: Environmental compliance assessment and enforcement are complex, labor intensive tasks that would benefit from some form of decision support. Despite the well-documented application of remote sensing in environmental analysis and assessment, the operational use of this technology for environmental compliance enforcement remains in its infancy. Because the majority of environmental laws and regulations in the United States were enacted prior to the emergence of a mature science of remote sensing, there exists a degree of skepticism regarding the operational utility and reliability of remotely sensed data as an environmental compliance tool. This paper provides a review of the role of remote sensing in environmental compliance assessment and introduces a framework to guide the application of this technology based on the use of artificial neural networks. The customized neural networks developed in this study serve as a simplifying strategy to assist the process of compliance monitoring. Functioning as “intelligent” classifiers, the network models provide a spatial characterization of activities likely to cause damage; achieving mapping accuracies that ranged from 68 to 90% for the test case samples selected for investigation. [Copyright &y& Elsevier]

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. [Copyright &y& Elsevier]

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. [Copyright &y& Elsevier]