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Abstract Aquatic ecosystems are subjected to many chemical stressors, including nutrients and emerging contaminants like pharmaceuticals. While pharmaceutical concentrations in streams and rivers are often below the thresholds for acute toxicity, they nonetheless disrupt ecology through changes to organisms' physiology, metabolism, and behavior. However, analyzing samples for the wide range of manufactured pharmaceuticals is often prohibitively expensive for many monitoring efforts. As such, the ability to predict pharmaceutical concentrations over space and time using easier‐to‐monitor water quality parameters would expand our understanding of the scope and consequences of pharmaceutical contamination in aquatic ecosystems. We applied random forest models to data from the Baltimore Ecosystem Study to investigate how well routinely monitored water quality parameters could be used to predict concentrations of nutrients and pharmaceuticals. We found that concentrations of nutrients were accurately predicted by these models, but models for predicting concentrations of pharmaceuticals had high error rates and low predictive ability. Differences in our ability to predict concentrations of nutrients as opposed to pharmaceuticals could be due to differences in their sources, chemistries, or behavior in the environment. More concerted efforts to monitor pharmaceutical concentrations over time in aquatic ecosystems may help to resolve environmental drivers of their concentration and improve our ability to predict them. 

Abstract Nutrient impacts on productivity in stream ecosystems can be obscured by light limitation imposed by canopy cover and water turbidity, thereby creating uncertainties in linking nutrient and productivity regimes. Evaluations of nutrient limitations are often based on a response ratio (RR) quantifying productivity stimulation above ambient levels given augmented nutrient supply. This metric neglects the primacy of light effects on productivity. We propose an alternative approach to quantify nutrient limitations using a “decline ratio” (DR), which quantifies the productivity decline from the maximum established by light availability. The DR treats light as the first‐order control and nutrient depletion as a disturbance causing productivity decline, allowing separation of nutrient and light influences. We used DR to assess nutrient diffusing substrate (NDS) experiments with three nutrients (nitrogen [N], phosphorus [P], iron [Fe]) from five Greenland streams during summer, where light is not limited due to the lack of canopy and low turbidity. We tested two hypotheses: (a) productivity maximum (i.e., highest chlorophyll‐aamong NDS treatments) is controlled by light and (b) DR depends on both light and nutrients. The productivity maximum was strongly predicted by light (R² = 0.60). The productivity decline induced by N limitation (i.e., DR_N) was best explained by light availability when parameterized with either dissolved inorganic nitrogen concentration (R² = 0.79) or N:Fe ratio (R² = 0.87). These predictions outperformed predictions of RR for which light was not a significant factor. Reversing the perspective on nutrient limitation from “stimulation above ambient” to “decline below maximum” provides insights into both light and nutrient impacts on stream productivity. 

ABSTRACT Emerging aquatic insects can be an important resource subsidy for a variety of terrestrial consumers, including spiders, birds, bats and lizards. Emergence flux is influenced by a variety of abiotic and biotic variables, such as temperature, drying, and predators and these variables can also control the body size of emergent insects. Despite their importance, these variables can change rapidly during drought conditions as water temperatures rise, surface area decreases and predator densities increase.During 2018, the Konza Prairie Biological Station experienced a record drought: flow ceased in the lower reaches of Kings Creek for the first time in over 40 years of observation, leaving a series of isolated pools. We studied how the drought affected aquatic insect emergence in 12 of these pools via elevated temperatures, decreased surface area, and concentration of predators (e.g. fishes and crayfish) over a four‐week period. We returned in 2020 and sampled emergence in the same pools over 2 weeks under non‐drought conditions to compare emergence between drought and non‐drought conditions.We found three overall patterns: (1) rates of areal emergence abundance and biomass (number or mg DM m⁻²d⁻¹) did not differ between drought and non‐drought conditions. In contrast, pool‐scale emergence abundance, but not biomass (number or mg DM pool⁻¹d⁻¹), was lower during drought conditions; (2) average midge body size was larger during the drought relative to the non‐drought conditions; (3) environmental variables (e.g. temperature, pool surface area, predator biomass) were not predictive of emergence during drought and non‐drought conditions.Fewer, but larger emergent midges (as seen under drought conditions) may represent a higher quality resource for terrestrial consumers than many smaller midges due to increased per‐capita energy yield. However, due to the overall decrease in water availability throughout the stream network, the overall emergence flux was concentrated in reaches with remaining water during the drought, making pools emergence subsidy hotspots. Overall, these contrasting responses underscore the complex nature of community responses to shifting climatic conditions.