Institute of Ecosystem Studies

2007 BES Annual Meeting Presentation and Poster Abstracts

Developing a model-based approach for assessing landscape restoration activities in Watershed 263, Baltimore, MD
voigt, brian
Co-Authors: Brian Voigt
Abstract: Recent household-level survey data (2006) in Watershed 263 (W263) has demonstrated that a majority of residents would prefer to live elsewhere if they could due to ambivalent or negative perceptions of their quality of life (QOL) resulting from neighborhood disamenities such as crime, trash, and building abandonment. To improve both ecosystem function and QOL within the watershed, landscape interventions including tree planting, asphalt removal, development of community gardens and public awareness and education campaigns, have been initiated by the Parks and People Foundation. This poster documents the ongoing development of a dynamic, spatially explicit modeling tool designed to facilitate learning about the interactions among the biophysical and socio-economic components of W263 and quantitatively assess landscape restoration activities within the watershed. A combination of linear regression and logit choice models are used to define the watershed’s social and economic systems. Based on our understanding of the relationships and feedbacks among system components, modeling "what-if" scenarios that control the frequency and magnitude of specific interventions allows us to test their effects on household-level decision making and environmental conditions while defining the range of system response(s) to such interventions. Model outputs will necessarily address the primary concerns of the W263 council through the development of a set of indicators that describe resulting neighborhood-level conditions (e.g., number of residents that wish to leave, numbers of vacant and abandoned lots, gentrification, property values, etc.), enabling project stakeholders to make informed decisions towards planning for equitable, effective and sustainable landscape intervention strategies aimed at QOL improvements.