دانلود رایگان مقاله انگلیسی پیش بینی آسیب پذیری جریان به تنش شهرسازی با مدل های شبکه بیزی - الزویر 2018

ABSTRACT

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.

6. Conclusion

A major research theme in sustainability science is the analysis of vulnerability in coupled social-ecological systems. Communities and ecosystems with high vulnerability and low resilience are regarded as important targets for conservation protection and management for long-term sustainability (Kates et al., 2001; Wu 2013). Turner et al. (2003) have argued that vulnerability analyses must use a place-based approach that incorporates multiple interacting stressors, accounts for the sensitivity of the system to those stressors, and results in development of metrics and models for measuring vulnerability. Our study used expert knowledge and a BN modeling framework to assess the complex relationships influencing stream responses to catchment urbanization in the northern temperate landscape of Maine. By combining a BN model for stream vulnerability to urbanization stress with a complementary BN model of development suitability, we developed a process for predicting the spatial distribution of streams that are at higher risk of impairment from future land use changes. Our analysis identified over 400 streams and associated small watersheds in the Maine landscape that are at increased risk of degradation from future human development activities. Further, we developed a framework that can be used to identify catchments where aquatic ecosystem services may be less vulnerable to development pressure. This information provides a probabilistic basis for more informed decision-making and proactive watershed management focused on sustaining aquatic resources. Overall, our BN vulnerability model provides a new application of spatial land use planning aimed at mitigating human development impacts on both natural ecosystems and ecosystem services.