Accounting for multiple impacts of the Common agricultural policies in rural areas: an analysis using a Bayesian networks approach

In evaluating the potential effects of the reforms of the Common Agricultural Policy, a particularly challenging issue is the representation of the complexity of rural systems either in a static or dynamic framework. In this paper we use Bayesian networks, to the best knowledge of the authors, basically ignored by the literature on rural development. The objective of this paper is to discuss the potential use of Bayesian Networks tools to represent the multiple determinants and impacts of the Common Agricultural Policies in rural areas across Europe. The analysis shows the potential use of BNs in terms of representation of the multiple linkages between different components of rural areas and farming systems, though its use as a simulation tool still requires further improvements.Bayesian Networks (BNs), farm-household, multiple outcomes, Agricultural and Food Policy, Q1, Q18,

Integrating economic values and catchment modelling

Integrated catchment policies are widely used to manage natural resources in Australian catchments. Decision support tools available to aid integrated catchment management are often limited in their integration of environmental processes with socio-economic systems. Fully integrated models are required to support assessments of the environmental and economic trade-offs of catchment management changes. A Bayesian Network (BN) model is demonstrated to provide a suitable approach to integrate environmental modelling with economic valuation. The model incorporates hydrological, ecological and economic models for the George catchment in Tasmania. Information about the non-market costs and benefits of environmental changes is elicited using Choice Experiments, allowing an assessment of the efficiency of alternative management scenarios.Integrated catchment modelling, Bayesian networks, Uncertainty, Environmental values, Non-market valuation, Choice Modelling.,

Integrated Hydro-Economic Modelling: Challenges and Experiences in an Australian Catchment

Integrated catchment policies are widely used to manage natural resources in Australian catchments. Integration of environmental processes with socio-economic systems is often difficult due to the limitations of decision support tools. To support assessments of the environmental and economic trade-offs of changes in catchment management, fully integrated models are needed. This research demonstrates a Bayesian Network (BN) approach to integrating environmental modelling with economic valuation. The model incorporates hydrological, ecological and economic models for the George catchment in Tasmania. Choice experiments were used to elicit information about the non-market costs and benefits of environmental changes. This allows the efficiency of alternative management scenarios to be assessed.Hydro-economic modelling, Integrated catchment modelling, Ecological modelling, Valuation, Bayesian networks, Water quality, Community/Rural/Urban Development, Environmental Economics and Policy, Land Economics/Use,

An Integrated Assessment approach to linking biophysical modelling and economic valuation tools

Natural resource management (NRM) typically involves complex decisions that affect a variety of stakeholder values. Efficient NRM, which achieves the greatest net environmental, social and financial benefits, needs to integrate the assessment of environmental impacts with the costs and benefits of investment. Integrated assessment (IA) is one approach that incorporates the several dimensions of catchment NRM, by considering multiple issues and knowledge from various disciplines and stakeholders. Despite the need for IA, there are few studies that integrate biophysical modelling tools with economic valuation. In this paper, we demonstrate how economic non-market valuation tools can be used to support an IA of catchment NRM changes. We develop a Bayesian Network model that integrates: a process-based water quality model; ecological assessments of native riparian vegetation; estimates of management costs; and non-market (intangible) values of changes in riparian vegetation. This modelling approach illustrates how information from different sources can be integrated in one framework to evaluate the environmental and economic impacts of NRM actions. It also shows the uncertainties associated with the estimated welfare effects. By estimating the marginal social costs and benefits, a cost-benefit analysis of alternative management intervention can be gained and provides more economic rationality to NRM decisions.Bayesian networks, bio-economic modelling, catchment management, cost-benefit analysis, environmental values, integrated assessment and modelling, non-market valuation, riparian vegetation, Environmental Economics and Policy, Research Methods/ Statistical Methods,

Development of scenarios for land cover, population density, impervious cover, and conservation in New Hampshire, 2010–2100

Future changes in ecosystem services will depend heavily on changes in land cover and land use, which, in turn, are shaped by human activities. Given the challenges of predicting long-term changes in human behaviors and activities, scenarios provide a framework for simulating the long-term consequences of land-cover change on ecosystem function. As input for process-based models of terrestrial and aquatic ecosystem function, we developed scenarios for land cover, population density, and impervious cover for the state of New Hampshire for 2020–2100. Key drivers of change were identified through information gathered from six sources: historical trends, existing plans relating to New Hampshire’s land-cover future, surveys, existing population scenarios, key informant interviews with diverse stakeholders, and input from subject-matter experts. Scenarios were developed in parallel with information gathering, with details added iteratively as new questions emerged. The final scenarios span a continuum from spatially dispersed development with a low value placed on ecosystem services (Backyard Amenities) to concentrated development with a high value placed on ecosystem services (the Community Amenities family). The Community family includes two population scenarios (Large Community and Small Community), to be combined with two scenarios for land cover (Protection of Wildlands and Promotion of Local Food), producing combinations that bring the total number of scenarios to six. Between Backyard Amenities and Community Amenities is a scenario based on linear extrapolations of current trends (Linear Trends). Custom models were used to simulate decadal change in land cover, population density, and impervious cover. We present raster maps and proportion of impervious cover for HUC10 watersheds under each scenario and discuss the trade-offs of our translation and modeling approach within the context of contemporary scenario projects