The Southeastern United States is a global center of freshwater biotic diversity, but much of the region's aquatic biodiversity is at risk from stream degradation. Nonpoint pollution sources are responsible for 70% of that degradation, and controlling nonpoint pollution from agriculture, urbanization, and silviculture is considered critical to maintaining water quality and aquatic biodiversity in the Southeast. We used an ecological risk assessment framework to develop vulnerability models that can help policymakers and natural resource managers understand the impact of land cover changes on water quality in North Carolina. Additionally, we determined which landscape characteristics are most closely associated with macroinvertebrate community tolerance of stream degradation, and therefore with lower-quality water. The results will allow managers and policymakers to weigh the risks of management and policy decisions to a given watershed or set of watersheds, including whether streamside buffer protection zones are ecologically effective in achieving water quality standards. Regression analyses revealed that landscape variables explained up to 56.3% of the variability in benthic macroinvertebrate index scores. The resulting vulnerability models indicate that North Carolina watersheds with less forest cover are at most risk for degraded water quality and steam habitat conditions. The importance of forest cover, at both the watershed and riparian zone scale, in predicting macrobenthic invertebrate community assemblage varies by geographic region of the state.

No abstract

No abstract

No abstract

Forested watersheds of the Mid-Atlantic Region are an important economic resource. They are also critical for maintaining water quality, sustaining important ecological services, and providing habitat to many animal and plant species of conservation concern. These forests are vulnerable to disturbance and fragmentation from changing patterns of land use in the Mid-Atlantic Region, and from harvests of commercially mature and relatively inexpensive timber. The U.S. Department of Agriculture Forest Service (USDA-FS) Forest Inventory and Analysis (FIA) compiles data on forest condition by state and county. We have transformed these FIA data to a U.S. Geological Survey (USGS) 6-digithdrologic unit code (HUC 6) watershed base, and projected trends in timber growth, inventory, and harvest to 2025 using a timber economics forecasting model (SRTS). We consider forest sustainability from the perspective of timber production, and from the perspective of landscape stability important to conservation values. Simulation data is combined with FIA planted pine acreage data to form a more complete picture of forest extent, composition, and silvicultural practice. Early recognition of prevailing economic trends which encourage the fragmentation of mature forests due to increasing timber harvests may provide managers and policy makers with a planning tool to mitigate undesirable impacts.