Cumulative Effects Assessment in an Intensively Mined Central Appalachian Watershed

Large scale surface mining in southern West Virginia results in significant impacts to downstream ecosystems.  However, research suggests current permitting and mitigation strategies are insufficient and must account for other factors on the landscape (i.e. geography, geology, residential land use). Through a watershed-scale assessment of the Coal River (south-central West Virginia), the specific objectives of this study were to:  1) construct predictive models linking landscape indicators to current in-stream conditions; 2) project cumulative effects at the watershed scale.  Boosted regression tree (BRT) models explained up to 88% of the deviance in specific conductance using % surface mining, # of deep mine permits, and # of structures within 200m of the stream channel as predictor variables.  Models of biological impairment offered similar results.  By integrating these models within a spatially explicit modeling framework, we were able to project current conditions and cumulative effects at the watershed scale with a high degree of accuracy.  Our results provide knowledge and technical tools that can be used to support management decisions (permitting, mitigation, and restoration) in mined Appalachian watersheds.  The framework outlined here is transferrable to other regions and provides a necessary next step in the science and practice of cumulative effects assessment.