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Cumulative effects modeling in the mountaintop removal mining region of the central Appalachians Eric Richard Merriam Anthropogenic alteration of natural land cover is a global driver of aquatic resource impairment. It is increasingly recognized that aquatic systems are impacted by multiple land use activities that combine additively and interactively to result in unique patterns of degradation (i.e., cumulative effects). Moreover, stream networks are multi-scaled, hierarchically structured systems wherein localized impacts can have both local (e.g., stream segment) and regional (e.g., watershed) consequences. Thus, there has been a recent push to construct statistical models capable of predicting and forecasting aquatic conditions under current and future landuse scenarios (i.e., scenario analysis) and characterize local and regional processes dictating observed patterns of ecological degradation. Nowhere is there a greater need for decisive and empirically-driven aquatic resource management than within the Mountaintop Removal-Valley Fill (MTR-VF) mining region of the central Appalachians, where dramatic changes in land cover associated with large scale surface mining can produce strong measurable impacts to downstream ecosystems. However, several knowledge gaps currently limit aquatic resource management within this actively developing and socioeconomically important region. Notably, the extent to which surface mining-related stressors interact with those of other landuse activities is unclear. For example, we currently have little knowledge regarding how multiple land use activities structure and contribute to the full suite of dissolved water quality characteristics in this region. Furthermore, extensive localized physicochemical degradation may degrade regional biological integrity and diversity through disruption or alteration of vital metacommunity processes (e.g., dispersal). Such regional implications of extensive local impacts have yet to be described. I seek to fill in these critical knowledge gaps in this study. In my first chapter, I tested for additive and interactive effects of dominant landuse activities (i.e., surface mining, deep mining, and residential development) on water quality (specific conductance and Se), habitat quality, and benthic macroinvertebrates via a uniquely designed watershed-scale assessment of the Coal River, West Virginia. I derived equations for predicting in-stream response to landscape changes and predicted the outcome of a realistic future scenario involving development of 15 permitted mines. I found that surface mining, underground mining, and residential development altered physical, chemical and biological condition through additive and complex interactive effects. Scenario analysis suggested that landscape context (i.e., presence of pre-existing landuse activities) helps control impacts from construction of new surface mines owing to observed complex additive and interactive effects. My second chapter focused on constructing landscape-based cumulative effects models capable of predicting in-stream response to future surface-mine development within the context of other landuse activities throughout the MTR-VF region. Predictive models provided precise estimates of specific conductance (model R <0.77 and cross-validated R <0.74), Se (0.74 and 0.70), and benthic macroinvertebrate community composition (0.72 and 0.65) and predicted high levels of chemical (33%) and biological (67%) impairment as a result of additive and interactive effects of surface mining, underground mining, and residential development. Of this total impairment, however, <25% could be attributed to surface mining alone. Furthermore, the surface-mining level that results in exceedance of the 300 μS/cm conductivity benchmark increased from 4.4% in the presence of other stressors to 16.6% when only surface mining was present. These results underscore the importance of multistressor landuse models for reliable predictions of stream conditions, as well as the difficulty of interpreting correlations between surface mining and stream condition without fully accounting for other landuse activities. My third chapter focused on characterizing how multiple landuse activities control detailed patterns in local water chemistry. Principal component (PC) analysis identified 3 important dimensions of variation in water chemistry that were significantly correlated with contemporary surface mining (PC1, elevated dominant ions, sulfate, alkalinity, and selenium), coal geology and legacy mines (PC2, elevated trace metals), and residential development (PC3, elevated sodium and chloride). The combination of these 3 dominant sources of pollutants produced a complex stream-to-stream patchwork of contaminant mixtures. Seventy-five percent of headwater streams (catchments <5km) had water chemistries that classified as either reference (49%), development only (18%) or mining only (8%). Only 21% of larger streams (catchments >5km) were classified as having reference chemistries, and chemistries indicative of combined mining and development contaminants accounted for 47% of larger streams (compared to 26% of headwater streams). Extreme degradation of larger streams within the MTR-VF region can be attributed to the accumulation of contaminants from multiple human landuse activities that include contemporary mountaintop mining, underground mining, abandoned mines, and untreated domestic wastewater. Consequently, water quality improvements in this region will require a multi-contaminant remediation approach. My fourth chapter was focused on quantifying the extent to which pervasive physicochemical degradation throughout the MTR-VF region influences regional metacommunity structure and processes. Notably, conservation of undisturbed headwater streams is a common management activity in disturbed watersheds because of their ability to preserve regional biodiversity. However, undisturbed headwater streams are often isolated within heavily degraded regions, leaving their communities at risk of losing sensitive, poor dispersing taxa (through decreased mass and rescue effects) and gaining tolerant, widely dispersing taxa (through increased dispersal and mass effects) from nearby degraded habitats. Results of this chapter suggest that both local (observed physicochemical conditions) and neighborhood (condition of streams within a 5km buffer) conditions explain significant variation in assemblage structure across all taxa. However, the strength of neighborhood effects varied as a function of taxon-specific tolerance and dispersal characteristics. Neighborhood conditions had a significant effect on low dispersing taxa with moderate and high tolerances and on high dispersing taxa with high tolerances. Decreasing neighborhood condition was associated with decreased occurrence (Baetis, Ceratopsyche) and abundance (Maccaffertium) of several taxa, as well as associated metrics (%E, %EPT). Several taxa (Chironomidae, Hemerodromia, Chimarra) increased in occurrence and abundance with decreasing neighborhood conditions. Thus, invertebrate communities within even the most pristine streams are at risk when isolated within heavily impacted neighborhoods. Consequently, protection of regional species’ pools in heavily impacted regions will require more than simply conserving headwater catchments.