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The concentration of dissolved oxygen (DO) is an important attribute of aquatic ecosystems, influencing habitat, drinking water quality, biodiversity, nutrient biogeochemistry, and greenhouse gas emissions. While average summer DO concentrations are declining in lakes across the temperate zone, much remains unknown about seasonal factors contributing to deepwater DO losses. It is unclear whether declines are related to increasing rates of seasonal DO depletion or changes in seasonal stratification that limit re-oxygenation of deep waters. Furthermore, despite the presence of important biological and ecological DO thresholds, there has been no large-scale assessment of changes in the amount of habitat crossing these thresholds, limiting the ability to understand the consequences of observed DO losses. We used a dataset from400 widely distributed lakes to identify the drivers of DO losses and quantify the frequency and volume of lake water crossing biologically and ecologically important threshold concentrations ranging from 5 to 0.5 mg/L. Our results show that while there were no consistent changes over time in seasonal DO depletion rates, over three-quarters of lakes exhibited an increase in the duration of stratification, providing more time for seasonal deepwater DO depletion to occur. As a result, most lakes have experienced summertime increases in the amount of water below all examined thresholds in deepwater DO concentration, with increases in the proportion of the water column below thresholds ranging between 0.9% and 1.7% per decade. In the 30-day period preceding the end of stratification, increases were greater at2.2% per decade and70% of analyzed lakes experienced increases in the amount of oxygen-depleted water. These results indicate ongoing climate-induced increases in the duration of stratification have already contributed to reduction of habitat for many species, likely increased internal nutrient loading, and otherwise altered lake chemistry. Future warming is likely to exacerbate these trends.

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. NSF [CNS-1737424, DEB-1753639, DGE-1651272, DBI-1933016, DBI-1933102]; Global Change Center at Virginia Tech; Virginia Tech College of Science Roundtable Make-A-Difference Scholarship; Virginia Water Resources Research Center; Western Virginia Water Authority Published version Funding was provided by NSF grants CNS--1737424, DEB--1753639, DBI-1933016, DBI-1933102, and DGE-1651272, the Western Virginia Water Authority, the Global Change Center at Virginia Tech, the Virginia Tech College of Science Roundtable Make--A--Difference Scholarship, and the Virginia Water Resources Research Center.

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. Fralin Life Sciences Institute Institute for Critical Technology and Applied Science National Science Foundation NSF: DGE-1651272 NSF: DBI-1933102 NSF: DBI-1933016 NSF: CNS-1737424 NSF: DEB-1753657 NSF: DEB-1753639 NSF: DEB-1753657 NSF: DEB-1753639 Virginia Tech Global Change Center Western Virginia Water Authority Published version

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. Published version