In the era of big data, ecologists are increasingly relying on computational approaches and tools to answer existing questions and pose new research questions. These include both software applications (e.g., simulation models, databases and machine learning algorithms) and hardware systems (e.g., wireless sensor networks, supercomputing, drones and satellites), motivating the need for greater collaboration between computer scientists and ecologists. Here, we outline some synergistic opportunities for scientists in both disciplines that can be gained by building collaborations between the computer science and ecology research communities, with a focus on the benefits to ecology specifically. We also identify past contributions of computer science to ecology, including high-frequency environmental sensor technology, advanced supercomputing capacity for ecological modeling, databases for long-term and high-frequency datasets, and software programs for ecological analyses, to anticipate future potential contributions. These examples highlight the power and potential for further integration of computer science technology and ideas into the ecological research community. Finally, we translate our own experiences working together as a team of computer scientists and ecologists over the past decade into a conceptual framework with recommendations for supporting productive collaborations at the interface of the two disciplines. We specifically focus on how to apply best practices of team science for bridging computer science and ecology, which we advocate will substantially benefit ecology long-term.

Munger ZW, Carey CC, Gerling AB, Doubek JP, Hamre KD, McClure RP, Schreiber ME. 2018. Oxygenation and hydrologic controls on iron and manganese mass budgets in a drinking-water reservoir. Lake Reserv Manage. 35:277-291. In seasonally stratified lakes and reservoirs, fluctuating hypolimnetic oxygen and hydrologic conditions in the watershed can influence the retention of metals and their exchange between the sediments and water column. In particular, iron (Fe) and manganese (Mn) cycling at the sediment-water interface can be dynamic in response to variability in the watershed and within the waterbody, which has substantial implications for drinking water quality. We calculated a mass budget for Fe and Mn in a shallow drinking-water reservoir over a 2-year period in which we manipulated the tributary inflow rate and dissolved oxygen (DO) concentrations in the hypolimnion at the reservoir scale. We found that the net Fe and Mn release from the sediments into the water column was suppressed during oxygenation; however, both metals continued to be released from the sediments, even during well-oxygenated conditions. Oxygenation in the hypolimnion had no effect on the net export of metals from the reservoir to downstream. Instead, the overall net export of Fe and Mn during the stratified period was influenced by hydrologic inflows. In summary, we found that manipulating hypolimnetic oxygenation had an important effect on the cycling of Fe and Mn within the hypolimnion, but that the net retention of metals in the reservoir was driven primarily by hydrology.

Cyanobacterial blooms are increasing in waterbodies worldwide because of anthropogenic forcing. Most blooms occur at the water's surface, but some cyanobacterial taxa, such as Planktothrix, are able to modify their buoyancy to access more favorable growing conditions in deeper waters. Here, we used in situ fluorometry to examine the vertical distribution and biomass of Planktothrix in a seasonally anoxic reservoir for 3 consecutive summers. We also collected depth profiles of photosynthetically active radiation, temperature, and nutrients to evaluate which environmental drivers were most important for predicting Planktothrix biomass. In all 3 summers, Planktothrix dominated the phytoplankton community, exhibiting a large (concentrations similar to 100 mu g/L), persistent (lasting similar to 100 d) bloom below the thermocline. The bloom consistently exhibited maximum biomass at or below the depth reached by 1% of surface light. Light availability probably was the most important factor driving the vertical distribution of the stratified Planktothrix bloom, and light, temperature, and nutrients together were strong predictors of cyanobacterial biomass in the hypolimnion, explaining 71 to 93% of the variation in biomass. Our data suggest that Planktothrix remained in the hypolimnion where nutrient availability was maximized, while progressing slightly upward in the water column through each summer in response to light limitation. Our findings demonstrate that Planktothrix can dominate in low light and anoxic conditions and can form persistent blooms that last for multiple months. As cyanobacterial blooms become more prevalent, monitoring cyanobacteria at the surface and at depth will become critically important in freshwater ecosystems.

In freshwater lakes and reservoirs, climate change and eutrophication are increasing the occurrence of low-dissolved oxygen concentrations (hypoxia), which has the potential to alter the variability of zooplankton seasonal dynamics. We sampled zooplankton and physical, chemical and biological variables (e.g., temperature, dissolved oxygen, and chlorophyll a) in four reservoirs during the summer stratified period for three consecutive years. The hypolimnion (bottom waters) of two reservoirs remained oxic throughout the entire stratified period, whereas the hypolimnion of the other two reservoirs became hypoxic during the stratified period. Biomass variability (measured as the coefficient of the variation of zooplankton biomass) and compositional variability (measured as the community composition of zooplankton) of crustacean zooplankton communities were similar throughout the summer in the oxic reservoirs; however, biomass variability and compositional variability significantly increased after the onset of hypoxia in the two seasonally-hypoxic reservoirs. The increase in biomass variability in the seasonally-hypoxic reservoirs was driven largely by an increase in the variability of copepod biomass, while the increase in compositional variability was driven by increased variability in the dominance (proportion of total crustacean zooplankton biomass) of copepod taxa. Our results suggest that hypoxia may increase the seasonal variability of crustacean zooplankton communities.

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. (C) 2020 Elsevier Ltd. All rights reserved.

Reservoirs emit large amounts of methane (CH4) to the atmosphere relative to their small surface area globally. Among the different pathways of reservoir CH4 emissions, bubbling from the sediments (ebullition) and diffusion from the water surface are major contributors of CH4 efflux. The magnitude of ebullition and diffusion can vary substantially over space and time in large reservoirs. However, it is unclear how the drivers of ebullition and diffusion vary along a reservoir's longitudinal gradient, particularly in small reservoirs. We measured ebullition, diffusion, and eight environmental driver variables at four transects along a longitudinal gradient within a small, eutrophic reservoir. We used time series modeling to examine how the drivers of ebullition and diffusion varied among transects. Sediment-water interface temperature, inflow discharge, and wind speed were the most important drivers of CH4 ebullition in upstream transects of the reservoir, while phytoplankton biomass was the most important driver of ebullition in the downstream transect closest to the dam. Strikingly, CH4 ebullition dynamics were extremely well captured by the time series models, as the modeled rates for the furthest upstream transect closely matched the observed rates throughout the monitoring period. In contrast, CH4 diffusion dynamics were harder to model, with phytoplankton biomass as the primary driver of diffusion across all transects. Our results indicate that multiple drivers affect CH4 emissions along a small reservoir's longitudinal gradient and should be considered when upscaling site measurements to reservoir-wide CH4 emissions and ultimately regional or global estimates.

Lakes and reservoirs globally produce large quantities of methane and carbon dioxide in their sediments, which accumulate in the hypolimnia (bottom waters) during thermally stratified conditions. A key parameter controlling hypolimnetic greenhouse gas concentrations is dissolved oxygen. Land use and climate change have increased hypolimnetic anoxia worldwide in lakes and reservoirs, which is expected to affect their methane and carbon dioxide concentrations. We conducted whole-ecosystem oxygenation experiments to assess the effects of oxygen concentrations on dissolved hypolimnetic greenhouse gas concentrations in comparison to a reference reservoir and calculated the maximum hypolimnetic global warming potential in both reservoirs over three summers. We observed significantly greater hypolimnetic methane under anoxic conditions but similar carbon dioxide concentrations, leading to greater hypolimnetic global warming potential of anoxic hypolimnia. Our study indicates that the global warming potential of hypolimnetic greenhouse gas concentrations may increase as the prevalence of hypolimnetic anoxia increases due to global change.

Near-term, ecological forecasting with iterative model refitting and uncertainty partitioning has great promise for improving our understanding of ecological processes and the predictive skill of ecological models, but to date has been infrequently applied to predict biogeochemical fluxes. Bubble fluxes of methane (CH4) from aquatic sediments to the atmosphere (ebullition) dominate freshwater greenhouse gas emissions, but it remains unknown how best to make robust near-term CH4 ebullition predictions using models. Near-term forecasting workflows have the potential to address several current challenges in predicting CH4 ebullition rates, including: development of models that can be applied across time horizons and ecosystems, identification of the timescales for which predictions can provide useful information, and quantification of uncertainty in predictions. To assess the capacity of near-term, iterative forecasting workflows to improve ebullition rate predictions, we developed and tested a near-term, iterative forecasting workflow of CH4 ebullition rates in a small eutrophic reservoir throughout one open-water period. The workflow included the repeated updating of a CH4 ebullition forecast model over time with newly-collected data via iterative model refitting. We compared the CH4 forecasts from our workflow to both alternative forecasts generated without iterative model refitting and a persistence null model. Our forecasts with iterative model refitting estimated CH4 ebullition rates up to 2 weeks into the future [RMSE at 1-week ahead = 0.53 and 0.48 log(e)(mg CH4 m(-2) d(-1)) at 2-week ahead horizons]. Forecasts with iterative model refitting outperformed forecasts without refitting and the persistence null model at both 1- and 2-week forecast horizons. Driver uncertainty and model process uncertainty contributed the most to total forecast uncertainty, suggesting that future workflow improvements should focus on improved mechanistic understanding of CH4 models and drivers. Altogether, our study suggests that iterative forecasting improves week-to-week CH4 ebullition predictions, provides insight into predictability of ebullition rates into the future, and identifies which sources of uncertainty are the most important contributors to the total uncertainty in CH4 ebullition predictions.

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.

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 2-5x 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.