The rapid rate of urbanization within the Upper Chattahoochee Watershed (UCW) is threatening the provision of ecosystem services (ESs) for six million residents of the Atlanta Metropolitan Area. This study uses the land cover change model TerrSet to project future land cover from 2016 to 2040. The modular toolset InVEST (Integrated Valuation of Ecosystem Services and Tradeoffs) is used to assess the efficacy of four land use policies in maintaining the provision of three ESs (carbon storage, wildlife habitat, and water quality) within the UCW. The Baseline scenario represents past urbanization trends, whereas the Urbanization scenario accounts for a higher urban growth rate. The Plan 2040 scenario includes existing policy guidelines, and the Conservation scenario adds forested riparian buffer areas. Two integrated indexes and an economic valuation of ESs were used to combine all ESs and analyze the overall performance of each policy. The first index uses unequal weights for ESs based on the Analytical Hierarchical Process, whereas the second index uses equal weights. The values of both integrated indexes and economic values were highest in the Conservation scenario and lowest in the Urbanization scenario. No significant differences in the provision of ESs were found between the Baseline and the Plan 2040 scenarios. However, the integrated indexes and economic values for both land use policies declined over time. Our study will feed into the ongoing movement of sustainable watershed management for ensuring the provision of ESs, especially for rapidly urbanizing cities worldwide, in general, and in the United States, in particular.
Modeling ecosystem services (ESs) intrinsically involves the use of spatial and temporal data. Correct estimates of ecosystem services are inherently dependent upon the scale (resolution and extent) of the input spatial data. Sensitivity of modeling platforms typically used for quantifying ESs to simultaneous changes in the resolution and extent of spatial data is not particularly clear at present. This study used the Nutrient Delivery Ratio (NDR) model embedded in InVEST (Integrated Valuation of Ecosystem Services and Tradeoffs) for ascertaining the sensitivity of the outputs to three digital elevation models (DEM), two land cover datasets, and three precipitation grids for 57 watersheds located in Georgia, United States. Multivariate regression models were developed to verify the influence of the spatial resolution of input data on the NDR model output at two spatial extents (the state of Georgia and six physiographical regions within the state). Discrepancies in nutrient exports up to 77.4% and 168.1% were found among scenarios at the state level for nitrogen and phosphorus, respectively. Land cover datasets differing in resolution were responsible for the highest differences in nutrient exports. Significance (at 5% level) of spatial variables on the model outputs were different for the two spatial extents, demonstrating the influence of scale when modeling nutrient runoff and its importance for better policy prescriptions.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.