Search for: All records

ABSTRACT The water quality of drinking water reservoirs is critical for human and ecosystem health. In this study, we examined the drivers of three metals, aluminum (Al), barium (Ba), and copper (Cu), across two drinking water reservoirs in southwestern Virginia, USA, over 4 years. One reservoir has a hypolimnetic oxygenation system; the other does not. We used time series modeling and multivariate analysis of water column chemistry, suspended sediment, inflow, and precipitation data to assess the relative roles of hydrologic and geochemical drivers of metal behaviors in the two reservoirs. Results suggest that Al concentrations were primarily influenced by high-flow events, consistent with the mobilization of clays from physical weathering. In contrast, Ba showed stronger sensitivity to geochemical drivers, specifically redox conditions. Drivers of Cu behavior were obscured by low Cu concentrations. For all metals, patterns varied among years. Our findings highlight the importance of long-term monitoring and integrated approaches to evaluate the drivers of metal dynamics in reservoir ecosystems and inform strategies for maintaining safe drinking water supplies. 

ABSTRACT Ecosystem states are often influenced by both concurrent and antecedent environmental drivers. However, the relative importance of antecedent conditions varies within and among ecosystems. Here, we analysed long‐term depth‐profile data from 382 temperate lakes across 10 countries to assess how differential changes in spring versus summer air temperature mediate summer water quality. We found that summer bottom‐water conditions were more associated with spring air temperatures, while surface‐water conditions were more associated with summer air temperatures. The relative influence of spring versus summer air temperature was mediated by lake morphometry, stratification and latitude. Across these lakes, summer air temperatures have increased more rapidly than spring air temperatures, potentially contributing to a growing thermal difference between surface and bottom waters (median = +0.5°C/decade). Consequently, our results demonstrate that predicting the ecological impacts of climate change may require considering spatial differences in ecological memory within ecosystems. 

Abstract Dissolved organic matter (DOM) plays an important role in aquatic carbon cycling and is a valuable metric of ecosystem functioning and water quality in freshwater ecosystems. Despite its importance for biogeochemical cycling and water quality, no near‐term iterative forecasts have previously been developed for freshwater DOM concentrations. To advance both our understanding of freshwater DOM dynamics and management, we developed 1–34 days‐ahead forecasts of fluorescent DOM (fDOM) in three drinking water reservoirs. These temperate reservoirs are co‐located in Virginia, USA and experience variable DOM dynamics (range: 5–27 QSU (quinine sulfate units)). We developed six different forecasting models to predict fDOM in each reservoir. Three models were time series models based on forecasted drivers (water temperature and meteorology) that were updated daily from high‐frequency fDOM sensors. The other forecast models included a neural network machine learning model and two baseline reference models (day‐of‐year mean and persistence). Altogether, our forecasts were able to capture observed dynamics over a year in all three reservoirs, with one time series model outperforming the baseline models across the full 34‐day forecast horizon. Aggregated across reservoirs and models over a year, forecast RMSE increased from 0.7 to 4.1 QSU over the 1–34 days‐ahead forecast horizon. Forecast skill varied substantially across seasons, with greatest accuracy in the spring and winter compared to the summer and fall across reservoirs. These forecasts can help improve our understanding of the predictability of DOM and inform management in freshwater ecosystems as carbon dynamics become more variable due to global change. 

Abstract Lakes and reservoirs play a key role in the global carbon cycle, representing important carbon sinks and sources within the terrestrial landscape under different environmental conditions. Changes in climate and land use have led to increased air and surface water temperatures; increased occurrence and duration of hypolimnetic anoxia; and altered hydrology and nutrient loading, which have the potential to affect how these freshwater ecosystems receive and process carbon. To assess how interacting environmental drivers influence carbon cycling in lakes and reservoirs, we used a 5-year whole-ecosystem experiment to investigate the effects of variable catchment, meteorology, and in-lake drivers on epilimnetic and hypolimnetic dissolved organic carbon in a small reservoir. Using a combination of whole-ecosystem models and time-series analyses, we found that primary production and other internal sources contributed a mean of 29% (range: 7–49%) of the dissolved organic carbon in the reservoir’s epilimnion over the 5-year period. We also found that sinking epilimnetic primary production, dissolved organic carbon from the sediments, and other factors were likely important sources of hypolimnetic dissolved organic carbon, especially during periods of anoxia. Both the epilimnion and hypolimnion were found to be intermittent sinks, yet net sources, of dissolved organic carbon. Overall, water temperature was identified as the most important environmental predictor for water-column dissolved organic carbon, with higher concentrations observed under seasonally elevated temperatures during the late summer and early fall. Our results suggest that lakes and reservoirs may become larger sources of dissolved organic carbon to downstream ecosystems in a warmer, more anoxic future. 

Abstract Seasonality in environmental conditions plays a fundamental role in shaping lake ecosystems. However, patterns of seasonality vary worldwide, and these patterns are shifting over time amid global change. Thus, it is increasingly important to evaluate how seasons and seasonality are represented in lake ecosystem research. Here, we used a literature review and global data analysis to synthesize approaches for conceptualizing seasons and seasonality in lakes. We found that a wide range of criteria are used to delineate discrete seasons in published literature, including fixed dates (e.g., months, solstice/equinox), environmental thresholds (e.g., temperature and precipitation cutoffs), and lake‐specific indicators (e.g., ice cover, plankton phenology). Analyzing data from lakes worldwide, we found that using different criteria to define the same season resulted in divergent interpretations of ecosystem states. Based on our synthesis, we offer recommendations for how to incorporate seasonality into lake research and communications amid global change. 

Abstract PurposeHypolimnetic hypoxia has become increasingly prevalent in stratified water bodies in recent decades due to climate change. One primary sink of dissolved oxygen (DO) is sediment oxygen uptake ($${J}_{{O}_{2}}$$ $J_{O_2}$ ). On the water side of the sediment–water interface (SWI),$${J}_{{O}_{2}}$$ $J_{O_2}$ is controlled by a diffusive boundary layer (DBL), a millimeter-scale layer where molecular diffusion is the primary transport mechanism. In previous studies, the DBL was determined by visual inspection, which is subjective and time-consuming. Material and methodsIn this study, a computational procedure is proposed to determine the SWI and DBL objectively and automatically. The procedure was evaluated for more than 300 DO profiles in the sediment of three eutrophic water bodies spanning gradients of depth and surface area. Synthetic DO profiles were modeled based on sediment characteristics estimated by laboratory experiments. The procedure was further verified adopting the synthetic profiles. Results and discussionThe procedure, which was evaluated for both measured and synthetic DO profiles, determined the SWI and DBL well for both steady and non-steady state DO profiles. A negative relationship between DBL thickness and aeration rates was observed, which agrees with existing literatures. ConclusionsThe procedure is recommended for future studies involving characterizing DBL to improve efficiency and consistency. 

Abstract Zooplankton play an integral role as indicators of water quality in freshwater ecosystems, but exhibit substantial variability in their density and community composition over space and time. This variability in zooplankton community structure may be driven by multiple factors, including taxon-specific migration behavior in response to environmental conditions. Many studies have highlighted substantial variability in zooplankton communities across spatial and temporal scales, but the relative importance of space vs. time in structuring zooplankton community dynamics is less understood. In this study, we quantified spatial (a littoral vs. a pelagic site) and temporal (hours to years) variability in zooplankton community structure in a eutrophic reservoir in southwestern Virginia, USA. We found that zooplankton community structure was more variable among sampling dates over 3 years than among sites or hours of the day, which was associated with differences in water temperature, chlorophyll a, and nutrient concentrations. Additionally, we observed high variability in zooplankton migration behavior, though a slightly greater magnitude of DHM vs. DVM during each sampling date, likely due to changing environmental conditions. Ultimately, our work underscores the need to continually integrate spatial and temporal monitoring to understand patterns of zooplankton community structure and behavior in freshwater ecosystems. 

Abstract Temperate reservoirs and lakes worldwide are experiencing decreases in ice cover, which will likely alter the net balance of gross primary production (GPP) and respiration (R) in these ecosystems. However, most metabolism studies to date have focused on summer dynamics, thereby excluding winter dynamics from annual metabolism budgets. To address this gap, we analyzed 6 years of year‐round high‐frequency dissolved oxygen data to estimate daily rates of net ecosystem production (NEP), GPP, and R in a eutrophic, dimictic reservoir that has intermittent ice cover. Over 6 years, the reservoir exhibited slight heterotrophy during both summer and winter. We found winter and summer metabolism rates to be similar: summer NEP had a median rate of −0.06 mg O₂L⁻¹ day⁻¹(range: −15.86 to 3.20 mg O₂L⁻¹ day⁻¹), while median winter NEP was −0.02 mg O₂L⁻¹ day⁻¹(range: −8.19 to 0.53 mg O₂L⁻¹ day⁻¹). Despite large differences in the duration of ice cover among years, there were minimal differences in NEP among winters. Overall, the inclusion of winter data had a limited effect on annual metabolism estimates in a eutrophic reservoir, likely due to short winter periods in this reservoir (ice durations 0–35 days), relative to higher‐latitude lakes. Our work reveals a smaller difference between winter and summer NEP than in lakes with continuous ice cover. Ultimately, our work underscores the importance of studying full‐year metabolism dynamics in a range of aquatic ecosystems to help anticipate the effects of declining ice cover across lakes worldwide. 

Abstract Water level drawdowns are increasingly common in lakes and reservoirs worldwide as a result of both climate change and water management. Drawdowns can have direct effects on physical properties of a waterbody (e.g., by altering stratification and light dynamics), which can interact to modify the waterbody's biology and chemistry. However, the ecosystem‐level effects of drawdown remain poorly characterized in small, thermally stratified reservoirs, which are common in many regions of the world. Here, we intensively monitored a small eutrophic reservoir for 2 years, including before, during, and after a month‐long drawdown that reduced total reservoir volume by 36%. During drawdown, stratification strength (maximum buoyancy frequency) and surface phosphate concentrations both increased, contributing to a substantial surface phytoplankton bloom. The peak in phytoplankton biomass was followed by cascading changes in surface water chemistry associated with bloom degradation, with sequential peaks in dissolved organic carbon, dissolved carbon dioxide, and ammonium concentrations that were up to an order of magnitude higher than the previous year. Dissolved oxygen concentrations substantially decreased in surface waters during drawdown (to 41% saturation), which was associated with increased total iron and manganese concentrations. Combined, our results illustrate how changes in water level can have cascading effects on coupled physical, chemical, and biological processes. As climate change and water management continue to increase the frequency of drawdowns in lakes worldwide, our results highlight the importance of characterizing how water level variability can alter complex in‐lake ecosystem processes, thereby affecting water quality. 

Abstract Lake water clarity, phytoplankton biomass, and hypolimnetic oxygen concentration are metrics of water quality that are highly degraded in eutrophic systems. Eutrophication is linked to legacy nutrients stored in catchment soils and in lake sediments. Long lags in water quality improvement under scenarios of nutrient load reduction to lakes indicate an apparent ecosystem memory tied to the interactions between water biogeochemistry and lake sediment nutrients. To investigate how nutrient legacies and ecosystem memory control lake water quality dynamics, we coupled nutrient cycling and lake metabolism in a model to recreate long‐term water quality of a eutrophic lake (Lake Mendota, Wisconsin, USA). We modeled long‐term recovery of water quality under scenarios of nutrient load reduction and found that the rates and patterns of water quality improvement depended on changes in phosphorus (P) and organic carbon storage in the water column and sediments. Through scenarios of water quality improvement, we showed that water quality variables have distinct phases of change determined by the turnover rates of storage pools—an initial and rapid water quality improvement due to water column flushing, followed by a much longer and slower improvement as sediment P pools were slowly reduced. Water clarity, phytoplankton biomass, and hypolimnetic dissolved oxygen differed in their time responses. Water clarity and algal biomass improved within years of nutrient reductions, but hypolimnetic oxygen took decades to improve. Even with reduced catchment loading, recovery of Lake Mendota to a mesotrophic state may require decades due to nutrient legacies and long ecosystem memory.