Browsing by Author "Howard, Dexter W."

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    Advancing lake and reservoir water quality management with near-term, iterative ecological forecasting
    Carey, Cayelan C.; Woelmer, Whitney M.; Lofton, Mary E.; Figueiredo, Renato J.; Bookout, Bethany J.; Corrigan, Rachel S.; Daneshmand, Vahid; Hounshell, Alexandria G.; Howard, Dexter W.; Lewis, Abigail S. L.; McClure, Ryan P.; Wander, Heather L.; Ward, Nicole K.; Thomas, R. Quinn (2021-01-18)
    Near-term, iterative ecological forecasts with quantified uncertainty have great potential for improving lake and reservoir management. For example, if managers received a forecast indicating a high likelihood of impending impairment, they could make decisions today to prevent or mitigate poor water quality in the future. Increasing the number of automated, real-time freshwater forecasts used for management requires integrating interdisciplinary expertise to develop a framework that seamlessly links data, models, and cyberinfrastructure, as well as collaborations with managers to ensure that forecasts are embedded into decision-making workflows. The goal of this study is to advance the implementation of near-term, iterative ecological forecasts for freshwater management. We first provide an overview of FLARE (Forecasting Lake And Reservoir Ecosystems), a forecasting framework we developed and applied to a drinking water reservoir to assist water quality management, as a potential open-source option for interested users. We used FLARE to develop scenario forecasts simulating different water quality interventions to inform manager decision-making. Second, we share lessons learned from our experience developing and running FLARE over 2 years to inform other forecasting projects. We specifically focus on how to develop, implement, and maintain a forecasting system used for active management. Our goal is to break down the barriers to forecasting for freshwater researchers, with the aim of improving lake and reservoir management globally.
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    Anoxia begets anoxia: A positive feedback to the deoxygenation of temperate lakes
    Lewis, Abigail S. L.; Lau, Maximilian P.; Jane, Stephen F.; Rose, Kevin C.; Be'eri-Shlevin, Yaron; Burnet, Sarah H.; Clayer, François; Feuchtmayr, Heidrun; Grossart, Hans-Peter; Howard, Dexter W.; Mariash, Heather; Delgado Martin, Jordi; North, Rebecca L.; Oleksy, Isabella; Pilla, Rachel M.; Smagula, Amy P.; Sommaruga, Ruben; Steiner, Sara E.; Verburg, Piet; Wain, Danielle; Weyhenmeyer, Gesa A.; Carey, Cayelan C. (Wiley, 2023)
    Declining oxygen concentrations in the deep waters of lakes worldwide pose a pressing environmental and societal challenge. Existing theory suggests that low deep-water dissolved oxygen (DO) concentrations could trigger a positive feedback through which anoxia (i.e., very low DO) during a given summer begets increasingly severe occurrences of anoxia in following summers. Specifically, anoxic conditions can promote nutrient release from sediments, thereby stimulating phytoplankton growth, and subsequent phytoplankton decomposition can fuel heterotrophic respiration, resulting in increased spatial extent and duration of anoxia. However, while the individual relationships in this feedback are well established, to our knowledge, there has not been a systematic analysis within or across lakes that simultaneously demonstrates all of the mechanisms necessary to produce a positive feedback that reinforces anoxia. Here, we compiled data from 656 widespread temperate lakes and reservoirs to analyze the proposed anoxia begets anoxia feedback. Lakes in the dataset span a broad range of surface area (1–126,909 ha), maximum depth (6–370 m), and morphometry, with a median time-series duration of 30 years at each lake. Using linear mixed models, we found support for each of the positive feedback relationships between anoxia, phosphorus concentrations, chlorophyll a concentrations, and oxygen demand across the 656-lake dataset. Likewise, we found further support for these relationships by analyzing time-series data from individual lakes. Our results indicate that the strength of these feedback relationships may vary with lake-specific characteristics: For example, we found that surface phosphorus concentrations were more positively associated with chlorophyll a in high-phosphorus lakes, and oxygen demand had a stronger influence on the extent of anoxia in deep lakes. Taken together, these results support the existence of a positive feedback that could magnify the effects of climate change and other anthropogenic pressures driving the development of anoxia in lakes around the world.
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    Experimental thermocline deepening alters vertical distribution and community structure of phytoplankton in a 4-year whole-reservoir manipulation
    Lofton, Mary E.; Howard, Dexter W.; McClure, Ryan P.; Wander, Heather L.; Woelmer, Whitney M.; Hounshell, Alexandria G.; Lewis, Abigail S. L.; Carey, Cayelan C. (Wiley, 2022-11)
    Freshwater phytoplankton communities are currently experiencing multiple global change stressors, including increasing frequency and intensity of storms. An important mechanism by which storms affect lake and reservoir phytoplankton is by altering the water column's thermal structure (e.g., changes to thermocline depth). However, little is known about the effects of intermittent thermocline deepening on phytoplankton community vertical distribution and composition or the consistency of phytoplankton responses to varying frequency of these disturbances over multiple years. We conducted whole-ecosystem thermocline deepening manipulations in a small reservoir. We used an epilimnetic mixing system to experimentally deepen the thermocline via five short (24-72 hr) mixing events across two summers, inducing potential responses to storms. For comparison, we did not manipulate thermocline depth in two succeeding summers. We collected weekly depth profiles of water temperature, light, nutrients, and phytoplankton biomass as well as bottle samples to assess phytoplankton community composition. We then used time-series analysis and multivariate ordination to assess the effects of intermittent thermocline deepening due to both our experimental manipulations and naturally occurring storms on phytoplankton community structure. We observed inter-annual and intra-annual variability in phytoplankton community response to thermocline deepening. We found that peak phytoplankton biomass was significantly deeper in years with a higher frequency of thermocline deepening events (i.e., years with both manipulations and natural storms) due to altered thermal stratification and more variable depth distributions of soluble reactive phosphorus. Furthermore, we found that the depth of peak phytoplankton biomass was linked to phytoplankton community composition, with certain taxa being associated with deep or shallow biomass peaks, often according to functional traits such as optimal growth temperature, mixotrophy, and low-light tolerance. For example, Cryptomonas taxa, which are low-light tolerant and mixotrophic, were associated with deep peaks, while the cyanobacterial taxon Dolichospermum was associated with shallow peaks. Our results demonstrate that abrupt thermocline deepening due to water column mixing affects both phytoplankton depth distribution and community structure via alteration of physical and chemical gradients. In addition, our work supports previous research that phytoplankton depth distributions are related to phytoplankton community composition at inter-annual and intra-annual timescales. Variability in the inter-annual and intra-annual responses of phytoplankton to abrupt thermocline deepening indicates that antecedent conditions and the seasonal timing of surface water mixing may mediate these responses. Our findings emphasise that phytoplankton depth distributions are sensitive to global change stressors and effects on depth distributions should be taken into account when predicting phytoplankton responses to increased storms under global change.
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    Geochemical drivers of manganese removal in drinking water reservoirs under hypolimnetic oxygenation
    Ming, Cissy L.; Breef-Pilz, Adrienne; Howard, Dexter W.; Schreiber, Madeline E. (Elsevier, 2024-07)
    Manganese (Mn) is a naturally occurring contaminant commonly found in drinking water supplies. In lakes and reservoirs, water authorities increasingly use in situ treatment by hypolimnetic oxygenation (HOx) systems to remove metals such as Mn from the water column. HOx systems introduce dissolved oxygen (DO) to the bottom waters (hypolimnion) to promote oxidation and subsequent removal of metals from the water column. Previous laboratory studies have shown the importance of individual geochemical drivers (pH, alkalinity, mineral surfaces) on Mn oxidation, but few studies have examined the influence of these drivers of Mn removal in concert. In this study, we conducted field monitoring and laboratory experiments to examine how pH, alkalinity and the presence of mineral particles influence Mn removal at two drinking water reservoirs in southwest Virginia, both with HOx systems: Falling Creek Reservoir (FCR) and Carvins Cove Reservoir (CCR). Both reservoirs have had historical issues with elevated (>0.05 mg/L) Mn concentrations during seasonal stratification (May–October). Watershed geology contributes to differences in pH and alkalinity between the reservoirs, with FCR having lower historical medians of hypolimnetic pH and alkalinity (6.6 and 18 mg/L CaCO3, respectively) than CCR (7.2 and 62 mg/L CaCO3, respectively). Results of laboratory experiments examining the influence of pH on Mn removal showed substantial Mn loss within 14 days only under high pH (10) conditions. Mn removal did not occur at pH 6 or 8 over the same 14-day period. In experiments with pH 10 and alkalinity >70 mg/L CaCO3, near-total Mn removal occurred within 2 h. Mn removal occurred concurrently with precipitation of microscopic (<5 μm) particles, followed by formation of macroscopic (>100 μm) particles. Particles of both size classes were identified as Mn oxides (MnOx). These observations suggest that increasing pH and alkalinity promotes Mn oxidation and subsequent removal from solution. Results of experiments with pH 10 and alkalinity >70 mg/L CaCO3 suggest that heterogeneous oxidation by MnOx partially drives rapid Mn removal. Thus, initial formation of MnOx creates a positive feedback loop that can enhance additional Mn loss. In experiments using water collected from FCR and CCR, we observed rapid Mn removal in unfiltered water (0.002–0.05 d−1) but no significant removal of Mn in filtered water. These results, in combination with results of analysis of particles collected from reservoir water, suggest that minerals present in the water column likely catalyze MnOx formation. Together, our experimental results suggest that heterogenous oxidation is an important process of Mn removal, while pH and alkalinity variations of the range expected in natural freshwaters contribute less to differential Mn removal. The formation of MnOx particles during in situ oxygenation, as well as the presence of suspended minerals that occur naturally in water columns, play an important role in promoting Mn oxidation and should be accounted for in Mn removal treatment strategies.
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    Increased adoption of best practices in ecological forecasting enables comparisons of forecastability
    Lewis, Abigail S. L.; Woelmer, Whitney M.; Wander, Heather L.; Howard, Dexter W.; Smith, John W.; McClure, Ryan P.; Lofton, Mary E.; Hammond, Nicholas W.; Corrigan, Rachel S.; Thomas, R. Quinn; Carey, Cayelan C. (Wiley, 2021-12-14)
    Near-term iterative forecasting is a powerful tool for ecological decision support and has the potential to transform our understanding of ecological predictability. However, to this point, there has been no cross-ecosystem analysis of near-term ecological forecasts, making it difficult to synthesize diverse research efforts and prioritize future developments for this emerging field. In this study, we analyzed 178 near-term (≤10-yr forecast horizon) ecological forecasting papers to understand the development and current state of near-term ecological forecasting literature and to compare forecast accuracy across scales and variables. Our results indicated that near-term ecological forecasting is widespread and growing: forecasts have been produced for sites on all seven continents and the rate of forecast publication is increasing over time. As forecast production has accelerated, some best practices have been proposed and application of these best practices is increasing. In particular, data publication, forecast archiving, and workflow automation have all increased significantly over time. However, adoption of proposed best practices remains low overall: for example, despite the fact that uncertainty is often cited as an essential component of an ecological forecast, only 45% of papers included uncertainty in their forecast outputs. As the use of these proposed best practices increases, near-term ecological forecasting has the potential to make significant contributions to our understanding of forecastability across scales and variables. In this study, we found that forecastability (defined here as realized forecast accuracy) decreased in predictable patterns over 1–7 d forecast horizons. Variables that were closely related (i.e., chlorophyll and phytoplankton) displayed very similar trends in forecastability, while more distantly related variables (i.e., pollen and evapotranspiration) exhibited significantly different patterns. Increasing use of proposed best practices in ecological forecasting will allow us to examine the forecastability of additional variables and timescales in the future, providing a robust analysis of the fundamental predictability of ecological variables.
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    Progress and opportunities in advancing near-term forecasting of freshwater quality
    Lofton, Mary E.; Howard, Dexter W.; Thomas, R. Quinn; Carey, Cayelan C. (Wiley, 2023-04)
    Near-term freshwater forecasts, defined as sub-daily to decadal future predictions of a freshwater variable with quantified uncertainty, are urgently needed to improve water quality management as freshwater ecosystems exhibit greater variability due to global change. Shifting baselines in freshwater ecosystems due to land use and climate change prevent managers from relying on historical averages for predicting future conditions, necessitating near-term forecasts to mitigate freshwater risks to human health and safety (e.g., flash floods, harmful algal blooms) and ecosystem services (e.g., water-related recreation and tourism). To assess the current state of freshwater forecasting and identify opportunities for future progress, we synthesized freshwater forecasting papers published in the past 5 years. We found that freshwater forecasting is currently dominated by near-term forecasts of water quantity and that near-term water quality forecasts are fewer in number and in the early stages of development (i.e., non-operational) despite their potential as important preemptive decision support tools. We contend that more freshwater quality forecasts are critically needed and that near-term water quality forecasting is poised to make substantial advances based on examples of recent progress in forecasting methodology, workflows, and end-user engagement. For example, current water quality forecasting systems can predict water temperature, dissolved oxygen, and algal bloom/toxin events 5 days ahead with reasonable accuracy. Continued progress in freshwater quality forecasting will be greatly accelerated by adapting tools and approaches from freshwater quantity forecasting (e.g., machine learning modeling methods). In addition, future development of effective operational freshwater quality forecasts will require substantive engagement of end users throughout the forecast process, funding, and training opportunities. Looking ahead, near-term forecasting provides a hopeful future for freshwater management in the face of increased variability and risk due to global change, and we encourage the freshwater scientific community to incorporate forecasting approaches in water quality research and management.