Anoxia begets anoxia: A positive feedback to the deoxygenation of temperate lakes

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.

Uncertainty in projections of future lake thermal dynamics is differentially driven by lake and global climate models

Freshwater ecosystems provide vital services, yet are facing increasing risks from global change. In particular, lake thermal dynamics have been altered around the world as a result of climate change, necessitating a predictive understanding of how climate will continue to alter lakes in the future as well as the associated uncertainty in these predictions. Numerous sources of uncertainty affect projections of future lake conditions but few are quantified, limiting the use of lake modeling projections as management tools. To quantify and evaluate the effects of two potentially important sources of uncertainty, lake model selection uncertainty and climate model selection uncertainty, we developed ensemble projections of lake thermal dynamics for a dimictic lake in New Hampshire, USA (Lake Sunapee). Our ensemble projections used four different climate models as inputs to five vertical one-dimensional (1-D) hydrodynamic lake models under three different climate change scenarios to simulate thermal metrics from 2006 to 2099. We found that almost all the lake thermal metrics modeled (surface water temperature, bottom water temperature, Schmidt stability, stratification duration, and ice cover, but not thermocline depth) are projected to change over the next century. Importantly, we found that the dominant source of uncertainty varied among the thermal metrics, as thermal metrics associated with the surface waters (surface water temperature, total ice duration) were driven primarily by climate model selection uncertainty, while metrics associated with deeper depths (bottom water temperature, stratification duration) were dominated by lake model selection uncertainty. Consequently, our results indicate that researchers generating projections of lake bottom water metrics should prioritize including multiple lake models for best capturing projection uncertainty, while those focusing on lake surface metrics should prioritize including multiple climate models. Overall, our ensemble modeling study reveals important information on how climate change will affect lake thermal properties, and also provides some of the first analyses on how climate model selection uncertainty and lake model selection uncertainty interact to affect projections of future lake dynamics.

High-frequency sensor data capture short-term variability in Fe and Mn concentrations due to hypolimnetic oxygenation and seasonal dynamics in a drinking water reservoir

The biogeochemical cycles of iron (Fe) and manganese (Mn) in lakes and reservoirs have predictable seasonal trends, largely governed by stratification dynamics and redox conditions in the hypolimnion. However, short-term (i.e., sub-weekly) trends in Fe and Mn cycling are less well-understood, as most monitoring efforts focus on longer-term (i.e., monthly to yearly) time scales. The potential for elevated Fe and Mn to degrade water quality and impact ecosystem functioning, coupled with increasing evidence for high spatiotemporal variability in other biogeochemical cycles, necessitates a closer evaluation of the short-term Fe and Mn dynamics in lakes and reservoirs. We adapted a UV-visible spectrophotometer coupled with a multiplexor pumping system and partial least squares regression (PLSR) modeling to generate high spatiotemporal resolution predictions of Fe and Mn concentrations in a drinking water reservoir (Falling Creek Reservoir, Vinton, VA, USA) equipped with a hypolimnetic oxygenation (HOx) system. We quantified hourly Fe and Mn concentrations during two transitional periods: reservoir turnover (Fall 2020) and HOx initiation (Summer 2021). Our sensor system successfully predicted mean Fe and Mn concentrations and trends, ground-truthed by grab sampling and laboratory analysis. During fall turnover, hypolimnetic Fe and Mn concentrations began to decrease more than two weeks before complete mixing of the reservoir, with rapid equalization of epilimnetic and hypolimnetic Fe and Mn concentrations in less than 48 h after full water column mixing. During the initiation of HOx in Summer 2021, Fe and Mn displayed distinctly different responses to oxygenation, as indicated by the rapid oxidation of soluble Fe but not soluble Mn. This study demonstrates that Fe and Mn concentrations are sensitive to changes in redox conditions induced by stratification and oxygenation, although their responses to these changes differ. We also show that high spatio-temporal resolution predictions of Fe and Mn can improve drinking water monitoring programs and reservoir management practices.

Assessing opportunities and inequities in undergraduate ecological forecasting education

Conducting ecological research in a way that addresses complex, real-world problems requires a diverse, interdisciplinary and quantitatively trained ecology and environmental science workforce. This begins with equitably training students in ecology, interdisciplinary science, and quantitative skills at the undergraduate level. Understanding the current undergraduate curriculum landscape in ecology and environmental sciences allows for targeted interventions to improve equitable educational opportunities. Ecological forecasting is a sub-discipline of ecology with roots in interdisciplinary and quantitative science. We use ecological forecasting to show how ecology and environmental science undergraduate curriculum could be evaluated and ultimately restructured to address the needs of the 21^st century workforce. To characterize the current state of ecological forecasting education, we compiled existing resources for teaching and learning ecological forecasting at three curriculum levels: online resources; US university courses on ecological forecasting; and US university courses on topics related to ecological forecasting. We found persistent patterns (1) in what topics are taught to US undergraduate students at each of the curriculum levels; and (2) in the accessibility of resources, in terms of course availability at higher education institutions in the United States. We developed and implemented programs to increase the accessibility and comprehensiveness of ecological forecasting undergraduate education, including initiatives to engage specifically with Native American undergraduates and online resources for learning quantitative concepts at the undergraduate level. Such steps enhance the capacity of ecological forecasting to be more inclusive to undergraduate students from diverse backgrounds and expose more students to quantitative training.

Progress and opportunities in advancing near-term forecasting of freshwater quality

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.

Near-term phytoplankton forecasts reveal the effects of model time step and forecast horizon on predictability

As climate and land use increase the variability of many ecosystems, forecasts of ecological variables are needed to inform management and use of ecosystem services. In particular, forecasts of phytoplankton would be especially useful for drinking water management, as phytoplankton populations are exhibiting greater fluctuations due to human activities. While phytoplankton forecasts are increasing in number, many questions remain regarding the optimal model time step (the temporal frequency of the forecast model output), time horizon (the length of time into the future a prediction is made) for maximizing forecast performance, as well as what factors contribute to uncertainty in forecasts and their scalability among sites. To answer these questions, we developed near-term, iterative forecasts of phytoplankton 1-14 days into the future using forecast models with three different time steps (daily, weekly, fortnightly), that included a full uncertainty partitioning analysis at two drinking water reservoirs. We found that forecast accuracy varies with model time step and forecast horizon, and that forecast models can outperform null estimates under most conditions. Weekly and fortnightly forecasts consistently outperformed daily forecasts at 7-day and 14-day horizons, a trend that increased up to the 14-day forecast horizon. Importantly, our work suggests that forecast accuracy can be increased by matching the forecast model time step to the forecast horizon for which predictions are needed. We found that model process uncertainty was the primary source of uncertainty in our phytoplankton forecasts over the forecast period, but parameter uncertainty increased during phytoplankton blooms and when scaling the forecast model to a new site. Overall, our scalability analysis shows promising results that simple models can be transferred to produce forecasts at additional sites. Altogether, our study advances our understanding of how forecast model time step and forecast horizon influence the forecastability of phytoplankton dynamics in aquatic systems and adds to the growing body of work regarding the predictability of ecological systems broadly.

Towards critical white ice conditions in lakes under global warming

The quality of lake ice is of uppermost importance for ice safety and under-ice ecology, but its temporal and spatial variability is largely unknown. Here we conducted a coordinated lake ice quality sampling campaign across the Northern Hemisphere during one of the warmest winters since 1880 and show that lake ice during 2020/2021 commonly consisted of unstable white ice, at times contributing up to 100% to the total ice thickness. We observed that white ice increased over the winter season, becoming thickest and constituting the largest proportion of the ice layer towards the end of the ice cover season when fatal winter drownings occur most often and light limits the growth and reproduction of primary producers. We attribute the dominance of white ice before ice-off to air temperatures varying around the freezing point, a condition which occurs more frequently during warmer winters. Thus, under continued global warming, the prevalence of white ice is likely to substantially increase during the critical period before ice-off, for which we adjusted commonly used equations for human ice safety and light transmittance through ice.

Anoxia decreases the magnitude of the carbon, nitrogen, and phosphorus sink in freshwaters

Oxygen availability is decreasing in many lakes and reservoirs worldwide, raising the urgency for understanding how anoxia (low oxygen) affects coupled biogeochemical cycling, which has major implications for water quality, food webs, and ecosystem functioning. Although the increasing magnitude and prevalence of anoxia has been documented in freshwaters globally, the challenges of disentangling oxygen and temperature responses have hindered assessment of the effects of anoxia on carbon, nitrogen, and phosphorus concentrations, stoichiometry (chemical ratios), and retention in freshwaters. The consequences of anoxia are likely severe and may be irreversible, necessitating ecosystem-scale experimental investigation of decreasing freshwater oxygen availability. To address this gap, we devised and conducted REDOX (the Reservoir Ecosystem Dynamic Oxygenation eXperiment), an unprecedented, 7-year experiment in which we manipulated and modeled bottom-water (hypolimnetic) oxygen availability at the whole-ecosystem scale in a eutrophic reservoir. Seven years of data reveal that anoxia significantly increased hypolimnetic carbon, nitrogen, and phosphorus concentrations and altered elemental stoichiometry by factors of 2-5× relative to oxic periods. Importantly, prolonged summer anoxia increased nitrogen export from the reservoir by six-fold and changed the reservoir from a net sink to a net source of phosphorus and organic carbon downstream. While low oxygen in freshwaters is thought of as a response to land use and climate change, results from REDOX demonstrate that low oxygen can also be a driver of major changes to freshwater biogeochemical cycling, which may serve as an intensifying feedback that increases anoxia in downstream waterbodies. Consequently, as climate and land use change continue to increase the prevalence of anoxia in lakes and reservoirs globally, it is likely that anoxia will have major effects on freshwater carbon, nitrogen, and phosphorus budgets as well as water quality and ecosystem functioning.

Anoxia decreases the magnitude of the carbon, nitrogen, and phosphorus sink in freshwaters

Oxygen availability is decreasing in many lakes and reservoirs worldwide, raising the urgency for understanding how anoxia (low oxygen) affects coupled biogeochemical cycling, which has major implications for water quality, food webs, and ecosystem functioning. Although the increasing magnitude and prevalence of anoxia has been documented in freshwaters globally, the challenges of disentangling oxygen and temperature responses have hindered assessment of the effects of anoxia on carbon, nitrogen, and phosphorus concentrations, stoichiometry (chemical ratios), and retention in freshwaters. The consequences of anoxia are likely severe and may be irreversible, necessitating ecosystem-scale experimental investigation of decreasing freshwater oxygen availability. To address this gap, we devised and conducted REDOX (the Reservoir Ecosystem Dynamic Oxygenation eXperiment), an unprecedented, 7-year experiment in which we manipulated and modeled bottom-water (hypolimnetic) oxygen availability at the whole-ecosystem scale in a eutrophic reservoir. Seven years of data reveal that anoxia significantly increased hypolimnetic carbon, nitrogen, and phosphorus concentrations and altered elemental stoichiometry by factors of 2-5× relative to oxic periods. Importantly, prolonged summer anoxia increased nitrogen export from the reservoir by six-fold and changed the reservoir from a net sink to a net source of phosphorus and organic carbon downstream. While low oxygen in freshwaters is thought of as a response to land use and climate change, results from REDOX demonstrate that low oxygen can also be a driver of major changes to freshwater biogeochemical cycling, which may serve as an intensifying feedback that increases anoxia in downstream waterbodies. Consequently, as climate and land use change continue to increase the prevalence of anoxia in lakes and reservoirs globally, it is likely that anoxia will have major effects on freshwater carbon, nitrogen, and phosphorus budgets as well as water quality and ecosystem functioning.

Using near-term forecasts and uncertainty partitioning to inform prediction of oligotrophic lake cyanobacterial density

Near-term ecological forecasts provide resource managers advance notice of changes in ecosystem services, such as fisheries stocks, timber yields, or water quality. Importantly, ecological forecasts can identify where there is uncertainty in the forecasting system, which is necessary to improve forecast skill and guide interpretation of forecast results. Uncertainty partitioning identifies the relative contributions to total forecast variance introduced by different sources, including specification of the model structure, errors in driver data, and estimation of current states (initial conditions). Uncertainty partitioning could be particularly useful in improving forecasts of highly variable cyanobacterial densities, which are difficult to predict and present a persistent challenge for lake managers. As cyanobacteria can produce toxic and unsightly surface scums, advance warning when cyanobacterial densities are increasing could help managers mitigate water quality issues. Here, we fit 13 Bayesian state-space models to evaluate different hypotheses about cyanobacterial densities in a low nutrient lake that experiences sporadic surface scums of the toxin-producing cyanobacterium, Gloeotrichia echinulata. We used data from several summers of weekly cyanobacteria samples to identify dominant sources of uncertainty for near-term (1- to 4-week) forecasts of G. echinulata densities. Water temperature was an important predictor of cyanobacterial densities during model fitting and at the 4-week forecast horizon. However, no physical covariates improved model performance over a simple model including the previous week's densities in 1-week-ahead forecasts. Even the best fit models exhibited large variance in forecasted cyanobacterial densities and did not capture rare peak occurrences, indicating that significant explanatory variables when fitting models to historical data are not always effective for forecasting. Uncertainty partitioning revealed that model process specification and initial conditions dominated forecast uncertainty. These findings indicate that long-term studies of different cyanobacterial life stages and movement in the water column as well as measurements of drivers relevant to different life stages could improve model process representation of cyanobacteria abundance. In addition, improved observation protocols could better define initial conditions and reduce spatial misalignment of environmental data and cyanobacteria observations. Our results emphasize the importance of ecological forecasting principles and uncertainty partitioning to refine and understand predictive capacity across ecosystems.

Increased adoption of best practices in ecological forecasting enables comparisons of forecastability

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.

Granular measures of agricultural land use influence lake nitrogen and phosphorus differently at macroscales

Agricultural land use is typically associated with high stream nutrient concentrations and increased nutrient loading to lakes. For lakes, evidence for these associations mostly comes from studies on individual lakes or watersheds that relate concentrations of nitrogen (N) or phosphorus (P) to aggregate measures of agricultural land use, such as the proportion of land used for agriculture in a lake's watershed. However, at macroscales (i.e., in hundreds to thousands of lakes across large spatial extents), there is high variability around such relationships and it is unclear whether considering more granular (or detailed) agricultural data, such as fertilizer application, planting of specific crops, or the extent of near-stream cropping, would improve prediction and inform understanding of lake nutrient drivers. Furthermore, it is unclear whether lake N and P would have different relationships to such measures and whether these relationships would vary by region, since regional variation has been observed in prior studies using aggregate measures of agriculture. To address these knowledge gaps, we examined relationships between granular measures of agricultural activity and lake total phosphorus (TP) and total nitrogen (TN) concentrations in 928 lakes and their watersheds in the Northeastern and Midwest U.S. using a Bayesian hierarchical modeling approach. We found that both lake TN and TP concentrations were related to these measures of agriculture, especially near-stream agriculture. The relationships between measures of agriculture and lake TN concentrations were more regionally variable than those for TP. Conversely, TP concentrations were more strongly related to lake-specific measures like depth and watershed hydrology relative to TN. Our finding that lake TN and TP concentrations have different relationships with granular measures of agricultural activity has implications for the design of effective and efficient policy approaches to maintain and improve water quality.

Macrosystems EDDIE teaching modules significantly increase ecology students' proficiency and confidence working with ecosystem models and use of systems thinking

Simulation models are increasingly used by ecologists to study complex, ecosystem-scale phenomena, but integrating ecosystem simulation modeling into ecology undergraduate and graduate curricula remains rare. Engaging ecology students with ecosystem simulation models may enable students to conduct hypothesis-driven scientific inquiry while also promoting their use of systems thinking, but it remains unknown how using hands-on modeling activities in the classroom affects student learning. Here, we developed short (3-hr) teaching modules as part of the Macrosystems EDDIE (Environmental Data-Driven Inquiry & Exploration) program that engage students with hands-on ecosystem modeling in the R statistical environment. We embedded the modules into in-person ecology courses at 17 colleges and universities and assessed student perceptions of their proficiency and confidence before and after working with models. Across all 277 undergraduate and graduate students who participated in our study, completing one Macrosystems EDDIE teaching module significantly increased students' self-reported proficiency, confidence, and likely future use of simulation models, as well as their perceived knowledge of ecosystem simulation models. Further, students were significantly more likely to describe that an important benefit of ecosystem models was their "ease of use" after completing a module. Interestingly, students were significantly more likely to provide evidence of systems thinking in their assessment responses about the benefits of ecosystem models after completing a module, suggesting that these hands-on ecosystem modeling activities may increase students' awareness of how individual components interact to affect system-level dynamics. Overall, Macrosystems EDDIE modules help students gain confidence in their ability to use ecosystem models and provide a useful method for ecology educators to introduce undergraduate and graduate students to ecosystem simulation modeling using in-person, hybrid, or virtual modes of instruction.

Iron and manganese fluxes across the sediment-water interface in a drinking water reservoir

The development of low dissolved oxygen (DO) concentrations in the hypolimnion of drinking water reservoirs during thermal stratification can lead to the reduction of oxidized, insoluble iron (Fe) and manganese (Mn) in sediments to soluble forms, which are then released into the water column. As metals degrade drinking water quality, robust measurements of metal fluxes under changing oxygen conditions are critical for optimizing water treatment. In this study, we conducted benthic flux chamber experiments in summer 2018 to directly quantify Fe and Mn fluxes at the sediment-water interface under different DO and redox conditions of a eutrophic drinking water reservoir with an oxygenation system (Falling Creek Reservoir, Vinton, VA, USA). Throughout the experiments, we monitored DO, oxidation-reduction potential (ORP), water temperature, and pH in the chambers and compared the metal fluxes in the chambers with time-series of fluxes calculated using a hypolimnetic mass balance method. Our results showed that metal fluxes were highly variable during the monitoring period and were sensitive to redox conditions in the water column at the sediment-water interface. The time-series changes in fluxes and relationship to redox conditions are suggestive of "hot moments", short time periods of intense biogeochemical cycling. Although the metal concentrations and fluxes are specific to this site, the approaches for examining relationships between metals, oxygen concentrations and overall redox conditions can be applied by water utilities to improve water quality management of Fe and Mn.

Storm impacts on phytoplankton community dynamics in lakes

In many regions across the globe, extreme weather events such as storms have increased in frequency, intensity, and duration due to climate change. Ecological theory predicts that such extreme events should have large impacts on ecosystem structure and function. High winds and precipitation associated with storms can affect lakes via short-term runoff events from watersheds and physical mixing of the water column. In addition, lakes connected to rivers and streams will also experience flushing due to high flow rates. Although we have a well-developed understanding of how wind and precipitation events can alter lake physical processes and some aspects of biogeochemical cycling, our mechanistic understanding of the emergent responses of phytoplankton communities is poor. Here we provide a comprehensive synthesis that identifies how storms interact with lake and watershed attributes and their antecedent conditions to generate changes in lake physical and chemical environments. Such changes can restructure phytoplankton communities and their dynamics, as well as result in altered ecological function (e.g., carbon, nutrient and energy cycling) in the short- and long-term. We summarize the current understanding of storm-induced phytoplankton dynamics, identify knowledge gaps with a systematic review of the literature, and suggest future research directions across a gradient of lake types and environmental conditions.

Perspective: Advancing the research agenda for improving understanding of cyanobacteria in a future of global change

Harmful cyanobacterial blooms (=cyanoHABs) are an increasing feature of many waterbodies throughout the world. Many bloom-forming species produce toxins, making them of particular concern for drinking water supplies, recreation and fisheries in waterbodies along the freshwater to marine continuum. Global changes resulting from human impacts, such as climate change, over-enrichment and hydrological alterations of waterways, are major drivers of cyanoHAB proliferation and persistence. This review advocates that to better predict and manage cyanoHABs in a changing world, researchers need to leverage studies undertaken to date, but adopt a more complex and definitive suite of experiments, observations, and models which can effectively capture the temporal scales of processes driven by eutrophication and a changing climate. Better integration of laboratory culture and field experiments, as well as whole system and multiple-system studies are needed to improve confidence in models predicting impacts of climate change and anthropogenic over-enrichment and hydrological modifications. Recent studies examining adaptation of species and strains to long-term perturbations, e.g. temperature and carbon dioxide (CO₂) levels, as well as incorporating multi-species and multi-stressor approaches emphasize the limitations of approaches focused on single stressors and individual species. There are also emerging species of concern, such as toxic benthic cyanobacteria, for which the effects of global change are less well understood, and require more detailed study. This review provides approaches and examples of studies tackling the challenging issue of understanding how global changes will affect cyanoHABs, and identifies critical information needs for effective prediction and management.

Integrating fast and slow processes is essential for simulating human-freshwater interactions

Integrated modeling is a critical tool to evaluate the behavior of coupled human-freshwater systems. However, models that do not consider both fast and slow processes may not accurately reflect the feedbacks that define complex systems. We evaluated current coupled human-freshwater system modeling approaches in the literature with a focus on categorizing feedback loops as including economic and/or socio-cultural processes and identifying the simulation of fast and slow processes in human and biophysical systems. Fast human and fast biophysical processes are well represented in the literature, but very few studies incorporate slow human and slow biophysical system processes. Challenges in simulating coupled human-freshwater systems can be overcome by quantifying various monetary and non-monetary ecosystem values and by using data aggregation techniques. Studies that incorporate both fast and slow processes have the potential to improve complex system understanding and inform more sustainable decision-making that targets effective leverage points for system change.

Calanoid copepod zooplankton density is positively associated with water residence time across the continental United States

Inherent differences between naturally-formed lakes and human-made reservoirs may play an important role in shaping zooplankton community structure. For example, because many reservoirs are created by impounding and managing lotic systems for specific human purposes, zooplankton communities may be affected by factors that are unique to reservoirs, such as shorter water residence times and a reservoir’s management regime, compared to natural lakes. However, the environmental factors that structure zooplankton communities in natural lakes vs. reservoirs may vary at the continental scale and remain largely unknown. We analyzed data from the 2007 U.S. Environmental Protection Agency’s National Lakes Assessment and the U.S. Army Corps of Engineers’ National Inventory of Dams to compare large-bodied crustacean zooplankton communities (defined here as individuals retained by 0.243 mm mesh size) in natural lakes and reservoirs across the continental U.S. using multiple linear regressions and regression tree analyses. We found that large-bodied crustacean zooplankton density was overall higher in natural lakes compared to reservoirs when the effect of latitude was controlled. The difference between waterbody types was driven by calanoid copepods, which were also more likely to be dominant in the >0.243 mm zooplankton community in natural lakes than in reservoirs. Regression tree analyses revealed that water residence time was not a major driver of calanoid copepod density in natural lakes but was one of the most important drivers of calanoid copepod density in reservoirs, which had on average 0.5-year shorter water residence times than natural lakes. Reservoirs managed for purposes that resulted in shorter residence times (e.g., hydroelectric power) had lower zooplankton densities than reservoirs managed for purposes that resulted in longer residence times (e.g., irrigation). Consequently, our results indicate that water residence time may be an important characteristic driving differing large-bodied zooplankton dynamics between reservoirs and natural lakes.

Metalimnetic oxygen minima alter the vertical profiles of carbon dioxide and methane in a managed freshwater reservoir

Metalimnetic oxygen minimum zones (MOMs) commonly develop during the summer stratified period in freshwater reservoirs because of both natural processes and water quality management. While several previous studies have examined the causes of MOMs, much less is known about their effects, especially on reservoir biogeochemistry. MOMs create distinct redox gradients in the water column which may alter the magnitude and vertical distribution of dissolved methane (CH₄) and carbon dioxide (CO₂). The vertical distribution and diffusive efflux of CH₄ and CO₂ was monitored for two consecutive open-water seasons in a eutrophic reservoir that develops MOMs as a result of the operation of water quality engineering systems. During both summers, elevated concentrations of CH₄ accumulated within the anoxic MOM, reaching a maximum of 120 μM, and elevated concentrations of CO₂ accumulated in the oxic hypolimnion, reaching a maximum of 780 μM. Interestingly, the largest observed diffusive CH₄ effluxes occurred before fall turnover in both years, while peak diffusive CO₂ effluxes occurred both before and during turnover. Our data indicate that MOMs can substantially change the vertical distribution of CH₄ and CO₂ in the water column in reservoirs, resulting in the accumulation of CH₄ in the metalimnion (vs. at the sediments) and CO₂ in the hypolimnion.

Power, pitfalls, and potential for integrating computational literacy into undergraduate ecology courses

Environmental research requires understanding nonlinear ecological dynamics that interact across multiple spatial and temporal scales. The analysis of long-term and high-frequency sensor data combined with simulation modeling enables interpretation of complex ecological phenomena, and the computational skills needed to conduct these analyses are increasingly being integrated into graduate student training programs in ecology. Despite its importance, however, computational literacy-that is, the ability to harness the power of computer technologies to accomplish tasks-is rarely taught in undergraduate ecology classrooms, representing a major gap in training students to tackle complex environmental challenges. Through our experience developing undergraduate curricula in long-term and high-frequency data analysis and simulation modeling for two environmental science pedagogical initiatives, Project EDDIE (Environmental Data-Driven Inquiry and Exploration) and Macrosystems EDDIE, we have found that students often feel intimidated by computational tasks, which is compounded by the lack of familiarity with software (e.g., R) and the steep learning curves associated with script-based analytical tools. The use of prepackaged, flexible modules that introduce programming as a mechanism to explore environmental datasets and teach inquiry-based ecology, such as those developed for Project EDDIE and Macrosystems EDDIE, can significantly increase students' experience and comfort levels with advanced computational tools. These types of modules in turn provide great potential for empowering students with the computational literacy needed to ask ecological questions and test hypotheses on their own. As continental-scale sensor observatory networks rapidly expand the availability of long-term and high-frequency data, students with the skills to manipulate, visualize, and interpret such data will be well-prepared for diverse careers in data science, and will help advance the future of open, reproducible science in ecology.

Temperature Effects Explain Continental Scale Distribution of Cyanobacterial Toxins

Insight into how environmental change determines the production and distribution of cyanobacterial toxins is necessary for risk assessment. Management guidelines currently focus on hepatotoxins (microcystins). Increasing attention is given to other classes, such as neurotoxins (e.g., anatoxin-a) and cytotoxins (e.g., cylindrospermopsin) due to their potency. Most studies examine the relationship between individual toxin variants and environmental factors, such as nutrients, temperature and light. In summer 2015, we collected samples across Europe to investigate the effect of nutrient and temperature gradients on the variability of toxin production at a continental scale. Direct and indirect effects of temperature were the main drivers of the spatial distribution in the toxins produced by the cyanobacterial community, the toxin concentrations and toxin quota. Generalized linear models showed that a Toxin Diversity Index (TDI) increased with latitude, while it decreased with water stability. Increases in TDI were explained through a significant increase in toxin variants such as MC-YR, anatoxin and cylindrospermopsin, accompanied by a decreasing presence of MC-LR. While global warming continues, the direct and indirect effects of increased lake temperatures will drive changes in the distribution of cyanobacterial toxins in Europe, potentially promoting selection of a few highly toxic species or strains.

Chaoborus spp. Transport CH4 from the Sediments to the Surface Waters of a Eutrophic Reservoir, But Their Contribution to Water Column CH4 Concentrations and Diffusive Efflux Is Minor

Chaoborus spp. (midge larvae) live in the anoxic sediments and hypolimnia of freshwater lakes and reservoirs during the day and migrate to the surface waters at night to feed on plankton. It has recently been proposed that Chaoborus take up methane (CH₄) from the sediments in their tracheal gas sacs, use this acquired buoyancy to ascend into the surface waters, and then release the CH₄, thereby serving as a CH₄ "pump" to the atmosphere. We tested this hypothesis using diel surveys and seasonal monitoring, as well as incubations of Chaoborus to measure CH₄ transport in their gas sacs at different depths and times in a eutrophic reservoir. We found that Chaoborus transported CH₄ from the hypolimnion to the lower epilimnion at dusk, but the overall rate of CH₄ transport was minor, and incubations revealed substantial variability in CH₄ transport over space and time. We calculated that Chaoborus transport ∼0.1 mmol CH₄ m^-2 yr^-1 to the epilimnion in our study reservoir, a very low proportion (<1%) of total CH₄ diffusive flux during the summer stratified period. Our data further indicate that CH₄ transport by Chaoborus is sensitive to water column mixing, Chaoborus density, and Chaoborus species identity.

Effectiveness of hypolimnetic oxygenation for preventing accumulation of Fe and Mn in a drinking water reservoir

The accumulation of Fe and Mn in seasonally stratified drinking water reservoirs adversely impacts water quality. To control issues with Fe and Mn at the source, some drinking water utilities have deployed hypolimnetic oxygenation systems to create well-oxygenated conditions in the water column that are favorable for the oxidation, and thus removal, of Fe and Mn. However, in addition to being controlled by dissolved oxygen (DO), Fe and Mn concentrations are also influenced by pH and metal-oxidizing microorganisms. We studied the response of Fe and Mn concentrations to hypolimnetic oxygenation in a shallow drinking water reservoir in Vinton, Virginia, USA by sequentially activating and deactivating an oxygenation system over two summers. We found that maintaining well-oxygenated conditions effectively prevented the accumulation of soluble Fe in the hypolimnion. However, while the rate of Mn oxidation increased under well-oxygenated conditions, soluble Mn still accumulated in the slightly acidic to neutral (pH 5.6 to 7.5) hypolimnion. In parallel, we conducted laboratory incubation experiments, which showed that the presence of Mn-oxidizing microorganisms increased the rate of Mn oxidation in comparison with rates under oxic, abiotic conditions. Combined, our field and laboratory results demonstrate that increasing DO concentrations in the water column is important for stimulating the oxidation of Fe and Mn, but that the successful management of Mn is also tied to the activity of Mn-oxidizing organisms in the water column and favorable (neutral to alkaline) pH.

Assessing and Enhancing Environmental Sustainability: A Conceptual Review

While sustainability is an essential concept to ensure the future of humanity and the integrity of the resources and ecosystems on which we depend, identifying a comprehensive yet realistic way to assess and enhance sustainability may be one of the most difficult challenges of our time. We review the primary environmental sustainability assessment approaches, categorizing them as either being design-based or those that employ computational frameworks and/or indicators. We also briefly review approaches used for assessing economic and social sustainability because sustainability necessitates integrating environmental, economic, and social elements. We identify the collective limitations of the existing assessment approaches, showing that there is not a consistent definition of sustainability, that the approaches are generally not comprehensive and are subject to unintended consequences, that there is little to no connection between bottom-up and top-down approaches, and that the field of sustainability is largely fragmented, with a range of academic disciplines and professional organizations pursuing similar goals, but without much formal coordination. We conclude by emphasizing the need for a comprehensive definition of sustainability (that integrates environmental, economic, and social aspects) with a unified system-of-systems approach that is causal, modular, tiered, and scalable, as well as new educational and organizational structures to improve systems-level interdisciplinary integration.

Fish and phytoplankton exhibit contrasting temporal species abundance patterns in a dynamic north temperate lake

Temporal patterns of species abundance, although less well-studied than spatial patterns, provide valuable insight to the processes governing community assembly. We compared temporal abundance distributions of two communities, phytoplankton and fish, in a north temperate lake. We used both 17 years of observed relative abundance data as well as resampled data from Monte Carlo simulations to account for the possible effects of non-detection of rare species. Similar to what has been found in other communities, phytoplankton and fish species that appeared more frequently were generally more abundant than rare species. However, neither community exhibited two distinct groups of “core” (common occurrence and high abundance) and “occasional” (rare occurrence and low abundance) species. Both observed and resampled data show that the phytoplankton community was dominated by occasional species appearing in only one year that exhibited large variation in their abundances, while the fish community was dominated by core species occurring in all 17 years at high abundances. We hypothesize that the life-history traits that enable phytoplankton to persist in highly dynamic environments may result in communities dominated by occasional species capable of reaching high abundances when conditions allow. Conversely, longer turnover times and broad environmental tolerances of fish may result in communities dominated by core species structured primarily by competitive interactions.

First report of the successful operation of a side stream supersaturation hypolimnetic oxygenation system in a eutrophic, shallow reservoir

Controlling hypolimnetic hypoxia is a key goal of water quality management. Hypoxic conditions can trigger the release of reduced metals and nutrients from lake sediments, resulting in taste and odor problems as well as nuisance algal blooms. In deep lakes and reservoirs, hypolimnetic oxygenation has emerged as a viable solution for combating hypoxia. In shallow lakes, however, it is difficult to add oxygen into the hypolimnion efficiently, and a poorly designed hypolimnetic oxygenation system could potentially result in higher turbidity, weakened thermal stratification, and warming of the sediments. As a result, little is known about the viability of hypolimnetic oxygenation in shallow bodies of water. Here, we present the results from recent successful tests of side stream supersaturation (SSS), a type of hypolimnetic oxygenation system, in a shallow reservoir and compare it to previous side stream deployments. We investigated the sensitivity of Falling Creek Reservoir, a shallow (Zmax = 9.3 m) drinking water reservoir located in Vinton, Virginia, USA, to SSS operation. We found that the SSS system increased hypolimnetic dissolved oxygen concentrations at a rate of ∼1 mg/L/week without weakening stratification or warming the sediments. Moreover, the SSS system suppressed the release of reduced iron and manganese, and likely phosphorus, from the sediments. In summary, SSS systems hold great promise for controlling hypolimnetic oxygen conditions in shallow lakes and reservoirs.

A syndrome of mutualism reinforces the lifestyle of a sloth

Arboreal herbivory is rare among mammals. The few species with this lifestyle possess unique adaptions to overcome size-related constraints on nutritional energetics. Sloths are folivores that spend most of their time resting or eating in the forest canopy. A three-toed sloth will, however, descend its tree weekly to defecate, which is risky, energetically costly and, until now, inexplicable. We hypothesized that this behaviour sustains an ecosystem in the fur of sloths, which confers cryptic nutritional benefits to sloths. We found that the more specialized three-toed sloths harboured more phoretic moths, greater concentrations of inorganic nitrogen and higher algal biomass than the generalist two-toed sloths. Moth density was positively related to inorganic nitrogen concentration and algal biomass in the fur. We discovered that sloths consumed algae from their fur, which was highly digestible and lipid-rich. By descending a tree to defecate, sloths transport moths to their oviposition sites in sloth dung, which facilitates moth colonization of sloth fur. Moths are portals for nutrients, increasing nitrogen levels in sloth fur, which fuels algal growth. Sloths consume these algae-gardens, presumably to augment their limited diet. These linked mutualisms between moths, sloths and algae appear to aid the sloth in overcoming a highly constrained lifestyle.

Eco-physiological adaptations that favour freshwater cyanobacteria in a changing climate

Climate change scenarios predict that rivers, lakes, and reservoirs will experience increased temperatures, more intense and longer periods of thermal stratification, modified hydrology, and altered nutrient loading. These environmental drivers will have substantial effects on freshwater phytoplankton species composition and biomass, potentially favouring cyanobacteria over other phytoplankton. In this Review, we examine how several cyanobacterial eco-physiological traits, specifically, the ability to grow in warmer temperatures; buoyancy; high affinity for, and ability to store, phosphorus; nitrogen-fixation; akinete production; and efficient light harvesting, vary amongst cyanobacteria genera and may enable them to dominate in future climate scenarios. We predict that spatial variation in climate change will interact with physiological variation in cyanobacteria to create differences in the dominant cyanobacterial taxa among regions. Finally, we suggest that physiological traits specific to different cyanobacterial taxa may favour certain taxa over others in different regions, but overall, cyanobacteria as a group are likely to increase in most regions in the future.

Can the black box be cracked? The augmentation of microbial ecology by high-resolution, automated sensing technologies

Automated sensing technologies, 'ASTs,' are tools that can monitor environmental or microbial-related variables at increasingly high temporal resolution. Microbial ecologists are poised to use AST data to couple microbial structure, function and associated environmental observations on temporal scales pertinent to microbial processes. In the context of aquatic microbiology, we discuss three applications of ASTs: windows on the microbial world, adaptive sampling and adaptive management. We challenge microbial ecologists to push AST potential in helping to reveal relationships between microbial structure and function.

First report of microcystin-LR in the cyanobacterium Gloeotrichia echinulata

Gloeotrichia echinulata is a bloom-forming cyanobacterium that is common in eutrophic lakes, and less prevalent but increasing in oligotrophic lakes. We used an enzyme-linked immunosorbent assay analysis to test for the presence of the hepatotoxin microcystin-LR (MC-LR) in G. echinulata collected from an oligotrophic lake in central New Hampshire, USA. We found that G. echinulata contained MC-LR at mean concentrations of 97.07 +/- 7.78 (1 s.e.) ng MC-LR g(-1) dry wt colonies. This suggests that recent outbreaks of G. echinulata in oligotrophic lakes used as water sources throughout New England (USA) may pose a health concern. The toxicity of G. echinulata reported here suggests the need for future monitoring of microcystins in oligotrophic lakes.

mediator of paramutation1 is required for establishment and maintenance of paramutation at multiple maize loci

Paramutation is the directed, heritable alteration of the expression of one allele when heterozygous with another allele. Here, the isolation and characterization of a mutation affecting paramutation, mediator of paramutation1-1 (mop1-1), are described. Experiments demonstrate that the wild-type gene Mop1 is required for establishment and maintenance of the paramutant state. The mop1-1 mutation affects paramutation at the multiple loci tested but has no effect on alleles that do not participate in paramutation. The mutation does not alter the amounts of actin and ubiquitin transcripts, which suggests that the mop1 gene does not encode a global repressor. Maize plants homozygous for mop1-1 can have pleiotropic developmental defects, suggesting that mop1-1 may affect more genes than just the known paramutant ones. The mop1-1 mutation does not alter the extent of DNA methylation in rDNA and centromeric repeats. The observation that mop1 affects paramutation at multiple loci, despite major differences between these loci in their gene structure, correlations with DNA methylation, and stability of the paramutant state, suggests that a common mechanism underlies paramutation. A protein-based epigenetic model for paramutation is discussed.

The gender issue: epidemiology of ankle injuries in athletes who participate in basketball

The increased participation of women in organized athletics has resulted in an interest in gender-related injury patterns. Previous reports have indicated an increased incidence in anterior cruciate knee injuries among female intercollegiate basketball players compared with their male counterparts. The current epidemiologic study prospectively evaluated the relative risk of ankle injuries in scholastic and collegiate basketball players during a 2-year period. Eleven thousand seven hundred eighty athletes participated in this study, 4940 females and 6840 males. There were 1052 ankle injuries. Overall, females had a 25% greater risk of sustaining a Grade I ankle sprain compared with their male counterparts. This increased risk was present in the interscholastic and intercollegiate players. There was no significant difference in the risk for Grades II and III ankle sprains, ankle fractures, or syndesmotic sprains. Male and female athletes doubled their risk for sustaining an ankle injury at the intercollegiate level compared with the interscholastic level.