Documenting responses of biotic assemblages to coal-mining impacts is crucial to informing regulatory and reclamation actions. However, attributing biotic patterns to specific stressors is difficult given the dearth of preimpact studies and prevalence of confounding factors. Analysing species distributions and abundances, especially stratified by species traits, provides insights into how assemblage composition | 5 MARTIN eT Al. region has been intensely mined over the past four decades, some coal-bearing areas remain forested and unmined (VDMME, 2015; Zipper et al., 2016). This spatial variance, as well as high historical fish diversity, makes these drainages well-suited for examining physicochemical conditions and assemblage composition among headwater watersheds along a mining-intensity gradient. 2.2 | Site selection and mining-intensity gradient We used existing data to construct a mining-intensity gradient and choose representative sites. Known fish and habitat sampling localities from state and federal agencies, and researchers at Virginia Tech, were overlaid on our study area with geospatial layers of stream networks and topography from the National Hydrography Dataset Plus Version 2 (NHDPlusV2), and coal mining permits and features (Martin et al., 2018; Moore et al., 2017; Timpano et al., 2015). All geospatial analyses were conducted in ArcMap 10.3 (ESRI, Inc., Redlands, CA). Geospatial data on the areal extents (e.g., km 2) of active surface-mine permits, active deep-mine permits and valley fills (pre-and postbond release) were obtained from Virginia Department of Mines, Minerals, and Energy, Division of Mined Land Reclamation (VDMME, 2015) (Figure 2). Sites and NHDPlusV2 flowlines were assigned a Strahler stream order according to NHDPlusV2 FlowlineVAA table data (McKay et al., 2012). Our candidate headwater (i.e., 2nd-and 3rd-order) streams included all flowlines at least two fluvial kilometres upstream of mainstem flowlines (i.e., ≥5th-order). We focused on headwaters to isolate mining effects and minimise confounding, cumulative watershed effects. Ultimately, the 83 selected sites represented watersheds of varying intensities of mining-related disturbance throughout our study area. Our samples drew from data collected in a separate study during the summer and