Multiple in-stream stressors degrade biological assemblages in five U.S. regions.

Biological assemblages in streams are affected by a wide variety of physical and chemical stressors associated with land-use development, yet the importance of combinations of different types of stressors is not well known. From 2013 to 2017, the U.S. Geological Survey completed multi-stressor/multi-assemblage stream ecological assessments in five regions of the United States (434 streams total). Diatom, invertebrate, and fish communities were enumerated, and five types of potential stressors were quantified: habitat disturbance, excess nutrients, high flows, basic water quality, and contaminants in water and sediment. Boosted regression tree (BRT) models for each biological assemblage and region generally included variables from all five stressor types and multiple stressors types in each model was the norm. Classification and regression tree (CART) models then were used to determine thresholds for each BRT model variable above which there appeared to be adverse effects (multi-metric index (MMI) models only). In every region and assemblage there was a significant inverse relation between the MMI and the number of stressors exerting potentially adverse effects. The number of elevated instream stressors often varied substantially for a given level of land-use development and the number of elevated stressors was a better predictor of biological condition than was development. Using the adverse effects-levels that were developed based on the BRT model results, 68% of the streams had two or more stressors with potentially adverse effects and 35% had four or more. Our results indicate that relatively small increases in the number of stressors of different types can have a large effect on a stream ecosystem.

Effects of urban multi-stressors on three stream biotic assemblages.

During 2014, the U.S. Geological Survey (USGS) National Water-Quality Assessment (NAWQA) project assessed stream quality in 75 streams across an urban disturbance gradient within the Piedmont ecoregion of southeastern United States. Our objectives were to identify primary instream stressors affecting algal, macroinvertebrate and fish assemblages in wadeable streams. Biotic communities were surveyed once at each site, and various instream stressors were measured during a 4-week index period preceding the ecological sampling. The measured stressors included nutrients; contaminants in water, passive samplers, and sediment; instream habitat; and flow variability. All nine boosted regression tree models - three for each of algae, invertebrates, and fish - had cross-validation R2 (CV R2) values of 0.41 or above, and an invertebrate model had the highest CV R2 of 0.65. At least one contaminant metric was important in every model, and minimum daytime dissolved oxygen (DO), nutrients, and flow alteration were important explanatory variables in many of the models. Physical habitat metrics such as sediment substrate were only moderately important. Flow alteration metrics were useful factors in eight of the nine models. Total phosphorus, acetanilide herbicides and flow (time since last peak) were important in all three algal models, whereas insecticide metrics (especially those representing fipronil and imidacloprid) were dominant in the invertebrate models. DO values below approximately 7 mg/L corresponded to a strong decrease in sensitive taxa or an increase in tolerant taxa. DO also showed strong interactions with other variables, particularly contaminants and sediment, where the combined effect of low DO and elevated contaminants increased the impact on the biota more than each variable individually. Contaminants and flow alteration were strongly correlated to urbanization, indicating the importance of urbanization to ecological stream condition in the region.

How Hydrologic Connectivity Regulates Water Quality in River Corridors.

Downstream flow in rivers is repeatedly delayed by hydrologic exchange with off-channel storage zones where biogeochemical processing occurs. We present a dimensionless metric that quantifies river connectivity as the balance between downstream flow and the exchange of water with the bed, banks, and floodplains. The degree of connectivity directly influences downstream water quality - too little connectivity limits the amount of river water exchanged and leads to biogeochemically inactive water storage, while too much connectivity limits the contact time with sediments for reactions to proceed. Using a metric of reaction significance based on river connectivity, we provide evidence that intermediate levels of connectivity, rather than the highest or lowest levels, are the most efficient in removing nitrogen from Northeastern United States' rivers. Intermediate connectivity balances the frequency, residence time, and contact volume with reactive sediments, which can maximize the reactive processing of dissolved contaminants and the protection of downstream water quality. Our simulations suggest denitrification dominantly occurs in riverbed hyporheic zones of streams and small rivers, whereas vertical turbulent mixing in contact with sediments dominates in mid-size to large rivers. The metrics of connectivity and reaction significance presented here can facilitate scientifically based prioritizations of river management strategies to protect the values and functions of river corridors.