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High-frequency measurements of light absorbance were collected at multiple depths in Falling Creek Reservoir (FCR; Vinton, VA, USA) using a s::can Spectrolyser UV-Visible spectrophotometer coupled with a multiplexor pumping system. The system pumps water samples from individual depths into a flow-through cuvette where the UV-vis absorbance spectra of the sample are measured by the spectrophotometer. The system used in our study collected measurements of light absorbance every 2.5 nm wavelengths from 200 nm to 732.5 nm (optical path length of 10 mm) approximately at an hourly time step for seven monitoring depths in the reservoir. Data was collected during two periods; the first deployment (16 October to 9 November 2020) was to observe changes in Fe and Mn concentrations before, during, and after reservoir fall turnover and the second deployment (26 May to 21 June 2021) was to observe the effects of engineered hypolimnetic oxygenation on Fe and Mn concentrations. Partial least squares regression models were developed to generate predictions of total and soluble Fe and Mn concentrations based on the correlation between absorbance spectra and sampling data. 

Depth profiles of total and soluble iron and manganese were sampled from 2014-2022 in three drinking-water reservoirs, Falling Creek Reservoir (FCR), Beaverdam Reservoir (BVR), and Carvins Cove Reservoir (CCR). FCR and BVR are located in Vinton, Virginia, USA and CCR is located in Roanoke, Virginia, USA. All reservoirs are owned and operated by the Western Virginia Water Authority and are managed as drinking-water sources for the city of Roanoke, Virginia, USA. The dataset includes metals samples that were collected along a depth profile taken at the deepest site of BVR and FCR. At FCR, additional samples were collected at a gauged weir located on the primary inflow tributary and at a secondary tributary. The summer 2022 sampling campaign also included inflows and a depth profile of CCR, and an upstream site at BVR. At FCR and BVR, sampling frequency was approximately weekly during the summer and fall (May - October), approximately fortnightly during the spring (March - April), and approximately monthly during the winter (November - March). At CCR, sampling frequency was approximately fortnightly during summer (May - October). 

Sediment traps were deployed to assess the mass and composition (iron, manganese, total organic carbon, and total nitrogen) of settling particulates in the water column of two drinking water reservoirs—Beaverdam Reservoir and Falling Creek Reservoir, both located in Vinton, Virginia, USA. Sediment traps were deployed at two depths in each reservoir to capture both epilimnetic and hypolimnetic (total) sediment flux. The particulates were collected from the traps approximately fortnightly from April to December from 2018 to 2022, then filtered, dried, and analyzed for either iron and manganese or total organic carbon and total nitrogen. Beaverdam and Falling Creek are owned and operated by the Western Virginia Water Authority as primary or secondary drinking water sources for Roanoke, Virginia. The sediment trap dataset consists of logs detailing the sample filtering process, the mass of dried particulates from each filter, and the raw concentration data for iron (Fe) and manganese (Mn), total organic carbon (TOC) and total nitrogen (TN). The final products are the calculated downward fluxes of solid Fe, Mn, TOC and TN during the deployment periods. 

Freshwater lakes and reservoirs play a disproportionate role in the global organic carbon (OC) budget, as active sites for carbon processing and burial. Associations between OC and iron (Fe) are hypothesized to contribute substantially to the stabilization of OC in sediment, but the magnitude of freshwater Fe‐OC complexation remains unresolved. Moreover, global declines in bottom‐water oxygen concentrations have the potential to alter OC and Fe cycles in multiple ways, and the net effects of low‐oxygen (hypoxic) conditions on OC and Fe are poorly characterized. Here, we measured the pool of Fe‐bound OC (Fe‐OC) in surficial sediments from two eutrophic reservoirs, and we paired whole‐ecosystem experiments with sediment incubations to determine the effects of hypoxia on OC and Fe cycling over multiple timescales. Our experiments demonstrated that short periods (2–4 weeks) of hypoxia can increase aqueous Fe and OC concentrations while decreasing OC and Fe‐OC in surficial sediment by 30%. However, exposure to seasonal hypoxia over multiple years was associated with a 57% increase in sediment OC and no change in sediment Fe‐OC. These results suggest that the large sediment Fe‐OC pool (∼30% of sediment OC in both reservoirs) contains both oxygen‐sensitive and oxygen‐insensitive fractions, and over multiannual timescales OC respiration rates may play a more important role in determining the effect of hypoxia on sediment OC than Fe‐OC dissociation. Consequently, we anticipate that global declines in oxygen concentrations will alter OC and Fe cycling, with the direction and magnitude of effects dependent upon the duration of hypoxia.

 

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.