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Summary: A majority of environmental studies describe microbiomes at coarse scales of taxonomic resolution (bacterial community, phylum), ignoring key ecological knowledge gained from finer‐scales and microbial indicator taxa. Here, we characterized the distribution of 940 bacterial taxa from 41 streams along an urbanization gradient (0%–83% developed watershed area) in the Raleigh‐Durham area of North Carolina (USA). Using statistical approaches derived from macro‐organismal ecology, we found that more bacterial taxa were classified as intolerant than as tolerant to increasing watershed urbanization (143 vs 48 OTUs), and we identified a threshold of 12.1% developed watershed area beyond which the majority of intolerant taxa were lost from streams. Two bacterial families strongly decreased with urbanization: Acidobacteriaceae (Acidobacteria) and Xanthobacteraceae (Alphaproteobacteria). Tolerant taxa were broadly distributed throughout the bacterial phylogeny, with members of the Comamonadaceae family (Betaproteobacteria) presenting the highest number of tolerant taxa. Shifts in microbial community structure were strongly correlated with a stream biotic index, based on macroinvertebrate composition, suggesting that microbial assemblages could be used to establish biotic criteria for monitoring aquatic ecosystems. In addition, our study shows that classic methods in community ecology can be applied to microbiome datasets to identify reliable microbial indicator taxa and determine the environmental constraints on individual taxa distributions along environmental gradients. [ABSTRACT FROM AUTHOR]

Land cover change often alters the chemical regime and reduces the diversity of sensitive taxa in downstream aquatic ecosystems. The consistently elevated ionic strength associated with surface coal mines has been implicated in extirpating sensitive taxa throughout many Appalachian streams. We quantified secondary production at three sites spanning a gradient of mining impacts in the Mud River (West Virginia, U.S.A.) by sampling macroinvertebrates monthly from 2012 to 2013. Not only do we observe significant changes in aquatic insect community structure driven by the loss of sensitive taxa in mined watersheds, but we show that these losses translate directly to depressed biomass throughout the year becoming most apparent when pollutant concentrations rise during summer baseflow. These distinct seasonal patterns result in threefold decreases in total insect production and EPT production ∼1-km downstream of an unmined reach. Farther downstream, where pollutant concentrations are much higher, total annual productivity is similar to the unmined reach, but suffers from a 31% loss of taxa comprising production and altered timing of that production. Mayflies were the insects most notably affected by the chemical alteration. Whereas mayflies accounted for ∼14% of total production in our upstream, unmined site, they only accounted for 0.2% of production at the most impacted site. We conclude that elevated ionic strength depresses insect production by preventing sensitive taxa from completing their life cycles in mining-impacted streams. Because surface coal mining dominates the Central Appalachian landscape, such altered production patterns are likely a common landscape feature impacting regional food webs. [ABSTRACT FROM AUTHOR]

When setting water quality criteria, managers must choose thresholds for stressors that are protective of aquatic biodiversity. Setting such thresholds requires making implicit judgments about the degree of biodiversity loss that managers are willing to accept., We present a new modelling approach, the hierarchical diversity decision framework ( Hi DDe F) that explicitly communicates the sensitivity of water quality benchmarks to these implicit judgments. We apply Hi DDe F to a data set of stream macroinvertebrate abundances across 218 sites in south-western West Virginia, USA, where alkaline mine drainage increases streamwater conductivity and leads to the loss of sensitive taxa throughout regional river networks., By integrating responses of individual taxa within a flexible hierarchical framework, Hi DDe F reliably predicts macroinvertebrate assemblages across the full range of conductivities observed in the training data set but requires only a fraction (~10%) of the sites required in previous studies. Hi DDe F results suggest that the current conductivity benchmark (300 μS cm−1) for regional streams translates to 50% loss in abundance for at least one-quarter of regional macroinvertebrate taxa., Hi DDeF produces a 'decision landscape' that allows decision-makers to assess sensitivity of proposed benchmarks to their choice of protective level. Hi DDeF allows users to investigate both individual- and community-level responses to environmental gradients and generates output that includes a comprehensive summary of uncertainty in model parameters. [ABSTRACT FROM AUTHOR]