As human development and urbanization expand across the landscape, increasing numbers of streams are threatened with impairment from disturbance and stresses associated with land use changes. In this investigation, a Bayesian Network (BN) with an expert-informed model structure was developed to predict stream vulnerability to urbanization across a range of biophysical conditions. Primary factors affecting vulnerability were stream buffers, colonization connectivity, agriculture, watershed area, and sand/gravel aquifers. On a scale from 0 to 100 (lowest to highest probability), BN model vulnerability scores ranged from a minimum of 20 to a maximum of 87.5 across the 23,554 stream catchments in our statewide study area. Catchment vulnerability scores were linked with predictions of land development suitability from a second BN model in order to map the locations of streams at risk of impairment from projected future urbanization in two large watersheds in Maine, USA. Our BN synthesis identified 5% of the streams that are at risk based on two assessment criteria: (1) their catchments have projected future impervious cover (IC) levels greater than 6% and (2) the stream catchments have predicted vulnerability scores in the highest quartile of the BN model probability distribution. These at-risk streams represent priority targets for proactive monitoring, management, and conservation efforts to avoid future degradation and expensive restoration costs. This study laid the conceptual groundwork for using BN spatial models to identify streams that are not only vulnerable to urbanization, but are also located in catchments classified with a high probability of development suitability and future urbanization.

Introduction

An undeveloped forested watershed can tolerate only a limited amount of urbanization and human development activity before symptoms of stress and degradation begin to appear in downstream aquatic ecosystems. However, the response of streams to anthropogenic land use changes can vary as a function of watershed biophysical conditions that influence resistance or resilience properties of the coupled catchment and stream system (Alberti and Marzluff 2004; McCluney et al., 2014; Utz et al., 2016). In general, one would expect the streams at highest risk of impairment from development to be those with watershed characteristics that confer low resistance or high vulnerability to changing land use conditions or urbanization. Here, resistance refers to the ability of an ecosystem to resist change and to maintain structure and function despite increased exposure to stressors (Pearsons and Li 1992; Vieira, Clements, Guevara, & Jacobs, 2004). Conversely, vulnerability describes the sensitivity of a system to a stress and the degree to which the system will experience harm due to exposure to a stressor or perturbation (Besaw et al., 2009; Turner et al., 2003). Resilience describes the ability of a system to recover from disturbance or stress. Under authority of the federal Clean Water Act (CWA) and state water quality standards, the U.S. Environmental Protection Agency (US EPA) and state regulatory agencies endeavor to sustain healthy aquatic resources and to restore the chemical, physical, and biological integrity of waters that have been impaired by urbanization, non-point pollution, or other stressors. In Maine, the Department of Environmental Protection (Maine DEP) monitors the health of streams and determines if they attain water quality standards and criteria associated with four state-defined statutory classes (Courtemanch, Davies, & Laverty, 1989; Danielson et al., 2012; Davies, Drummond, Courtemanch, Tsomides, & Danielson, 2016). If a stream does not attain water quality standards or criteria associated with its designated class, then it may be listed as impaired in the CWA 303(d) inventory of impaired waters (Maine DEP, 2012a). Unfortunately, the economic cost of restoring impaired streams can be substantial − as one example, ongoing restoration of the impaired Long Creek ecosystem in Portland, Maine is projected to cost $14 million (FB Environmental Associates 2009).