Application of an Integrative Decision Support Tool and Spatial Modeling to Assess the Implications of Future Growth Scenarios on Sensitive Aquatic Resources in Maine
University of Maine, University of Maine School of Law
Abstract. The influence of urbanization on hydrologic systems is well documented, with stream impairment resulting from a diverse set of physical and chemical drivers including hydrology, chemical and nutrient pollution, and thermal stress. These drivers are emergent properties of social and economic processes that are in turn influenced by ecosystem processes, resulting in a complex set of linkages among social and ecological factors. Given these complex interactions, it is difficult to predict how landscape changes will differentially affect stream resources, and which impaired streams are most likely to respond to restoration efforts. However, it may be possible to identify the likelihood that a stream will be at risk for degradation, thereby providing a proactive means of preventing and managing future urban stream degradation. Such an approach is likely to produce positive environmental outcomes at much lower cost than restoration efforts begun after degradation has substantially progressed.
The goal of this project is to develop a decision-support framework that can be used to integrate spatial data, expert knowledge, and stakeholder values into a planning process aimed at identifying aquatic resources at-risk from future development. Our approach uses Bayesian Belief Network (BBN) models to combine these disparate sources of data, and integrates work conducted under two SSI projects – Maine Conservation Futures and Urban Streams. Our specific objectives are to develop: (1) a BBN model to explore different development scenarios around major urban areas that can be used to identify aquatic resources likely to experience significant levels of new residential and commercial development; and (2) a pilot municipal-scale BBN development model in one or more towns to identify at-risk smaller streams and wetlands (e.g., Hampden). In both cases, future development scenarios will explore varying assumptions regarding population growth, zoning and land use policies, and settlement density. The Team also will concurrently evaluate opportunities for prioritizing policy and regulatory responses within existing legal frameworks, and the potential opportunities and pitfalls arising from reforms designed to allow such prioritization.
Figure 2. BBN-derived land suitability map for residential and amenity-based development in the Lower Penobscot River Watershed. Note that only land suitability – not future population projections – is depicted. Actual area under development threat would be determined by population forecasts, settlement density assumptions, and scenarios depicting the mix of residential and amenity-based development.