Final Report 07 2008 ch03

Half of the European Union (EU) land and the livelihood of 10 million farmers is threatened by unsustainable land-use intensification, land abandonment and climate change. Policy instruments, including the EU Common Agricultural Policy (CAP) have so far failed to stop this environmental degradation. BESTMAP will: 1) Develop a behavioural theoretical modelling framework to take into account complexity of farmers' decision-making; 2) Develop, adapt and customize a suite of opensource, flexible, interoperable and customisable computer models linked to existing data e.g. LPIS/IACS and remote sensing e.g. Sentinel-2; 3) Link economic, individual-farm agent-based, biophysical ecosystem ‡ § | ¶ # ¤ « « ¤ » ˄ ˅ ¦ˀˁ ₵ © Ziv G et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. services and biodiversity and geostatistical socioeconomic models; 4) Produce a simpleto-use dashboard to compare scenarios of Agri-Environmental Schemes adoption; 5) Improve the effectiveness of future EU rural policies' design, monitoring and implementation.

2008

The goal of the TOPMARD project is to develop a model of agriculture and rural development to better understand the agronomic, ecological, economic and social dimensions of rural regions. The resulting model, (Policy Model of Multifunctional Agriculture and Rural Development) was built collaboratively and hierarchically by the research teams from the 11 countries. The model features eight subsectors (Land, Agriculture, Tourism, Region, Human Resources, Non-commodities, Capital, and Quality of Life). Imbedded in the model are a complete dynamic input-output model, and an agecohort education demographic model. The model has both supply-side and demand-side drivers. Land use is the key supply-side driver. Land use, coupled with production system choices, determine agricultural and non-commodity outputs. The Quality of Life sector incorporates the coefficients from a regression analysis of migration behaviour to develop a supply-side population response to local quality of life which is added to the demand-side response to job growth.

2020

Half of the European Union (EU) land and the livelihood of 10 million farmers is threatened by unsustainable land-use intensification, land abandonment and climate change. Policy instruments, including the EU Common Agricultural Policy (CAP) have so far failed to stop this environmental degradation. BESTMAP will: 1) Develop a behavioural theoretical modelling framework to take into account complexity of farmers' decision-making; 2) Develop, adapt and customize a suite of opensource, flexible, interoperable and customisable computer models linked to existing data e.g. LPIS/IACS and remote sensing e.g. Sentinel-2; 3) Link economic, individual-farm agent-based, biophysical ecosystem ‡ § | ¶ # ¤ « « ¤ » ˄ ˅ ¦ˀˁ ₵ © Ziv G et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. services and biodiversity and geostatistical socioeconomic models; 4) Produce a simpleto-use dashboard to compare scenarios of Agri-Environmental Schemes adoption; 5) Improve the effectiveness of future EU rural policies' design, monitoring and implementation.

Half of the European Union (EU) land and the livelihood of 10 million farmers is threatened by unsustainable land-use intensification, land abandonment and climate change. Policy instruments, including the EU Common Agricultural Policy (CAP) have so far failed to stop this environmental degradation. BESTMAP will: 1) Develop a behavioural theoretical modelling framework to take into account complexity of farmers' decision-making; 2) Develop, adapt and customize a suite of opensource, flexible, interoperable and customisable computer models linked to existing data e.g. LPIS/IACS and remote sensing e.g. Sentinel-2; 3) Link economic, individual-farm agent-based, biophysical ecosystem ‡ § | ¶ # ¤ « « ¤ » ˄ ˅ ¦ˀˁ ₵ © Ziv G et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. services and biodiversity and geostatistical socioeconomic models; 4) Produce a simpleto-use dashboard to compare scenarios of Agri-Environmental Schemes adoption; 5) Improve the effectiveness of future EU rural policies' design, monitoring and implementation.

The main aim of this paper is to discuss the concept of sustainable territorial development in rural contexts, and the modeling of environmental, economic and social components to allow simulation of the inter-connected dynamic impacts of different kinds of policy over time.

Journal of Sustainable Agriculture, 2005

In this article, we assess ecological, economic and social sustainability impacts of four alternative agricultural policy scenarios relevant to the European perspective. The analysed scenarios are: Prolonged Agenda 2000, On-going CAP reform, Integrated rural and environmental policy, and Liberalised Agricultural Trade. An economic agricultural sector model of Finnish agriculture is used in the evaluation of policy impacts up to 2020. Selected indicators representing the three dimensions of sustainability are calculated on the basis of the production variables of the model in each scenario. It is assumed that economic rationality, represented by the sector model, is a driving force directing agricultural production and land use, which, in turn, have a number of ecological, economic and social consequences. Our results show that a partial de-coupling of agricultural support from production and moderate reductions of commodity prices are likely to yield environmental benefits. In addition, there is a clear trade-off between environmental benefits and production volume and intensity. However, full de-coupling and radical price reductions are not likely to bring any additional environmental benefits but will result in a significant down-scaling and regional concentration of remaining agricultural activities. Hence the presented analysis is an interesting platform for discussion for stakeholders when implementing agricultural policy reforms.

Water science and technology : a journal of the International Association on Water Pollution Research, 2005

Finnish agriculture is likely to undergo major changes in the near and intermediate future. The ifuture policy context can be examined at a general level by strategic scenario building. Computer-based modelling in combination with agricultural policy scenarios can in turn create a basis for the assessments of changes in environmental quality following possible changes in Finnish agriculture. The analysis of economic consequences is based on the DREMFIA model, which is applied to study effects of various agricultural policies on land use, animal production, and farmers' income. The model is suitable for an impact analysis covering an extended time span--here up to the year 2015. The changes in land use, obtained with the DREMFIA model assuming rational economic behaviour, form the basis when evaluating environmental impacts of different agricultural policies. The environmental impact assessment is performed using the field scale nutrient transport model ICECREAM. The modelled var...

Sustainability research focuses on socio-ecological systems that emerge through the interaction of a society with its natural environment. Human decision-making plays a major role in every spatial and temporal aspect of land use. Decisions are made at multiple scales with feedback from one scale to another. Agent-based modelling is currently being explored as a tool for understanding the dynamics of socio-ecological systems in which decisions of actors influence biophysical dynamics, such as socioeconomic metabolism and land use. This paper investigates how agent-based modelling can contribute to local sustainability studies by encouraging transdisciplinary research and by structuring participatory processes that involve local stakeholders. It shows that agent-based modelling requires a detailed and structured knowledge of the system and both facilitates and depends upon the integration of relevant local stakeholders in the work of analysis. The representation of a case study examining how social and political interventions, such as the EU's Common Agricultural Policy (CAP), affect patterns of land use as well as socio-economic conditions in a specific rural region in Austria illustrates the research team's experience in designing a land-use model during a participatory process lasting three years. The model combines an agent-based module used to simulate farm households with a system dynamic module that simulates changes in land use and accordingly in substance flows, such as nitrogen flows. All decisions made by farmers are strongly affected by any changes in income in terms of subsidies and market prices. However, most of the decisions also depend on the time available for agricultural work and on the preferences of the younger generation regarding how much time they are willing and able to invest in farming. This indicates that the social dimension has great importance for any decision taken on the farm. Restrictions on the available time restrict actions and decision taken by the farm.

Journal of Environmental Management, 2009

In this paper a set of criteria is proposed for the evaluation of the potential contribution of modelling tools to strengthening the multifunctionality of agriculture. The four main areas of evaluation are (1) policy relevance, (2) the temporal resolution and scope, (3) the degree to which spatial and socioinstitutional scales and heterogeneity are addressed and (4) the level of integration in the assessment of scientific dimensions and of the multiple functions of agriculture. The evaluative criteria are applied to the portfolio of modelling approaches developed and applied in a joint project of the French research institute INRA and the Dutch Wageningen University & Research Centre. The CLUE-S model focuses on prediction of changes in multifunctional land-use at regional scale, given a set of predetermined scenarios or policy variants, e.g. for ex-ante policy assessment and initiation of discussions on regional development. The two other modelling approaches are complementary and aim to address multifunctional farming activities. The Landscape IMAGES framework generates a range of static images of possible but sometimes distant futures for multifunctional farming activities in a small region or landscape. It supports the exploration of trade-offs between financial returns from agriculture, landscape quality, nature conservation and restoration, and environmental quality. Co-Viability Analysis generates trajectories of states and farming decisions fulfilling a given set of ecological and productive constraints representing a desired and sustainable future. The three modelling approaches differ in their policy relevance, in the ways that spatial and socioinstitutional scales are addressed and in their degree of explicitation of interaction between the various functions of agriculture, but jointly cover most of the desired capabilities for assessment of multifunctionality. Caveats were particularly identified in the integration of the socio-institutional dimension and the related heterogeneity. Although the model portfolio did not completely satisfy the demands of the set of evaluative criteria, it is concluded that, due to their complementarities, in combination the three models could significantly contribute to further development and strengthening of multifunctionality.

Research Ideas and Outcomes

Half of the European Union (EU) land and the livelihood of 10 million farmers is threatened by unsustainable land-use intensification, land abandonment and climate change. Policy instruments, including the EU Common Agricultural Policy (CAP) have so far failed to stop this environmental degradation. BESTMAP will: 1) Develop a behavioural theoretical modelling framework to take into account complexity of farmers’ decision-making; 2) Develop, adapt and customize a suite of opensource, flexible, interoperable and customisable computer models linked to existing data e.g. LPIS/IACS and remote sensing e.g. Sentinel-2; 3) Link economic, individual-farm agent-based, biophysical ecosystem services and biodiversity and geostatistical socio-economic models; 4) Produce a simple-to-use dashboard to compare scenarios of Agri-Environmental Schemes adoption; 5) Improve the effectiveness of future EU rural policies’ design, monitoring and implementation.