A multi-scale approach to prioritize wetland restoration for watershed-level water quality improvement

Wetland restoration is commonly presented as an important strategy for maintaining and enhancing the water quality and ecological capital of watershed-scale ecosystems. Prioritizing restoration sites on the landscape is often a haphazard process based on widely held, though often untested, assumptions about relationships between watershed characteristics and water quality. We present a framework to target and prioritize wetland restoration locations using both regional and watershed-level screening models. The regression-tree and random forest models presented in this paper identify watershed variables with the strongest relationships to a given water quality parameter, present a clear hierarchy of variable importance, and present approximate thresholds in watershed area where these variables express the greatest impact on water quality. The proportion of watersheds classified as prior-converted agricultural land was an important predictor of both ortho and total phosphorus. Fortunately because prior-converted agricultural lands were historically wetlands, they are often very suitable for wetland restoration. These sites often have poorly-drained soils requiring artificial drainage to be suitable for agriculture. These drainage systems become conduits for transporting phosphorus from agricultural field and to area streams and rivers. Maintaining natural land-cover within stream buffers is identified as another important predictor of water quality. This seems to be especially true with regard to NO₃–NO₂ concentrations. Our model results support specific management recommendations including: (a) exclusion of agricultural land-uses from riparian buffers, (b) maintaining or increasing watershed-level wetland-cover and (c) reducing wetland fragmentation.