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This paper examines the biogeochemical basis of forest recovery following harvest across a backdrop of acid precipitation to show how plant-driven mineral weathering can drive long-term change in watershed cation export. 

Abstract Concentrations of total dissolved inorganic carbon (DIC) in freshwater ecosystems are controlled by terrestrial inputs and a myriad of in situ processes, such as aquatic metabolism. Dissolved CO₂is one of the components of DIC, and its dynamics are also regulated by chemical equilibrium with the DIC pool, so‐called carbonate buffering. Although its importance is generally recognized, carbonate buffering is still not consistently accounted for in freshwater studies. Here, we review key concepts in freshwater carbonate buffering, perform simulation experiments, and provide a case study of an alkaline river to illustrate calculations of DIC from CO₂. These analyses demonstrate that carbonate buffering can alter common interpretations of CO₂data, including carbon–oxygen coupling through production and respiration. As direct measurements of dissolved CO₂are increasingly common, accounting for CO₂equilibria with DIC is critical to understanding its role in carbon cycling within most freshwater systems. 

Abstract Gas transfer velocity () controls gas fluxes between aquatic ecosystems and the atmosphere. In streams, is controlled by turbulence and, thus, local hydrology and geomorphology. Resultantly, variability in can be large and modeling from physical parameters can have large uncertainty. Here, we leverage a large dataset of estimates derived from tracer‐gas experiments in 22 US streams across a range of discharges. Our analysis shows that was highly variable both spatially across and temporally within streams, with estimates of spanning three orders of magnitude. Overall, scaled with discharge in steep streams due to relatively high stream power, but not in low‐slope streams, where stream power was relatively low even at high flows. Understanding how responds to stream discharge in a wide variety of streams is key to creating temporally and spatially resolved estimates of biogeochemical processes in streams. 

Stream metabolism, encompassing gross primary production and ecosystem respiration, reflects the fundamental energetic dynamics of freshwater ecosystems. These processes regulate the concentrations of dissolved gases like oxygen and carbon dioxide, which in turn shape aquatic food webs and ecosystem responses to stressors such as floods, drought, and nutrient loading. Historically difficult to quantify, stream metabolism is now measurable at high temporal resolution thanks to advances in sensor technology and modeling. The StreamPULSE dataset includes high-frequency sensor data, metadata, and modeled estimates of ecosystem metabolism. This living dataset contributes to a growing body of open-access data characterizing the metabolic pulse of stream ecosystems worldwide. To contribute to StreamPULSE, visit data.streampulse.org. All data contributed to StreamPULSE become public after an optional embargo period. Use this publication to access annual data releases, or use data.streampulse.org to download new data as they become available. 

Abstract Rivers efficiently collect, process, and transport terrestrial‐derived carbon. River ecosystem metabolism is the primary mechanism for processing carbon. Diel cycles of dissolved oxygen (DO) have been used for decades to infer river ecosystem metabolic rates, which are routinely used to predict metabolism of carbon dioxide (CO₂) with uncertainties of the assumed stoichiometry ranging by a factor of 4. Dissolved inorganic carbon (DIC) has been less used to directly infer metabolism because it is more difficult to quantify, involves the complexity of inorganic carbon speciation, and as shown in this study, likely requires a two‐station approach. Here, we developed DIC metabolism models using single‐ and two‐station approaches. We compared metabolism estimates based on simultaneous DO and DIC monitoring in the Upper Clark Fork River (USA), which also allowed us to estimate ecosystem‐level photosynthetic and respiratory quotients (PQ_Eand RQ_E). We observed that metabolism estimates from DIC varied more between single‐ and two‐station approaches than estimates from DO. Due to carbonate buffering, CO₂is slower to equilibrate with the atmosphere compared to DO, likely incorporating a longer distance of upstream heterogeneity. Reach‐averaged PQ_Eranged from 1.5 to 2.0, while RQ_Eranged from 0.8 to 1.5. Gross primary production from DO was larger than that from DIC, as was net ecosystem production by . The river was autotrophic based on DO but heterotrophic based on DIC, complicating our understanding of how metabolism regulated CO₂production. We suggest future studies simultaneously model metabolism from DO and DIC to understand carbon processing in rivers. 

This dataset contains estimates of gas exchange velocity, gas exchange rate, and hydraulic parameters for streams calculated from tracer-gas experiments and conservative tracer injections collected by the National Ecological Observatory Network (NEON). All input data were collected by NEON and is available on the NEON data portal at https://data.neonscience.org. Specifically, the NEON Reaeration field and lab collection data product (DP1.20190.001) was used to calculate these estimates. Gas exchange was estimated in two ways: first, following an unpooled frequentist approach and second, following a partially pooled Bayesian approach. In addition, a salt-correction was applied to gas exchange estimates for sites where it was possible and necessary. All estimates of gas exchange are included in the file gasExchange_ds.csv. A recommended selection of these estimates is included in the dataset (best_k600_mPerDay and best_K600_mPerDay). The stanfit objects used for the partially pooled Bayesian approach are also included as site-specific model objects for gas exchange velocities and rates. In addition, water velocity was calculated from conservative tracer injections, and mean water depth was calculated from these water velocity estimates and measurements of wetted width and water discharge. All hydraulic parameters are included in the file hydraulics_ds.csv. All processing code is available in the reaRates R package. NEON is sponsored by the National Science Foundation (NSF) and operated under cooperative agreement by Battelle. This material is based in part upon work supported by NSF through the NEON Program. 

Abstract Although time series in ecosystem metabolism are well characterized in small and medium rivers, patterns in the world's largest rivers are almost unknown. Large rivers present technical difficulties, including depth measurements, gas exchange (, ) estimates, and the presence of large dams, which can supersaturate gases. We estimated reach‐scale metabolism for the Hanford Reach of the Columbia River (Washington state, USA), a free‐flowing stretch with an average discharge of 3173 . We calculated from semi‐empirical models and directly estimated it from tracer measurements. We fixed at the median value from these calculations (0.5 ), and used maximum likelihood to estimate reach‐scale, open‐channel metabolism. Both gross primary production (GPP) and ecosystem respiration (ER) were high (GPP range: 0.3–30.8 g , ER range: 0.8–30.6 g ), with peak GPP and ER occurring in the late summer or early fall. GPP increased exponentially with temperature, consistent with metabolic theory, while light was seasonally saturating. Annual average GPP, estimated at 1500 g carbon , was in the top 2% of estimates for other rivers. GPP and ER were tightly coupled and 90% of GPP was immediately respired, resulting in net ecosystem production near 0. Patterns in the Hanford Reach contrast with those in small‐medium rivers, suggesting that metabolism magnitudes and patterns in large rivers may not be simply scaled from knowledge of smaller rivers. 

Abstract Headwater stream networks contribute substantially to the global carbon dioxide terrestrial flux because of high turbulence and coupling with terrestrial environments. Heterogeneity within headwater stream networks, both spatially and temporally, makes measuring and upscaling these emissions challenging because measurements of carbon dioxide in streams are often limited to a few monitoring points. We modified a stream network model to reflect real measurements made under base flow and high flow conditions at Martha Creek in Stabler, WA in the US Pacific Northwest. We found that under high flow conditions, the stream network had much greater total carbon emissions than during low flow conditions (1.22 Mg C day⁻¹vs. 0.034 Mg C day⁻¹). We attribute this increase to a larger overall stream network area (0.04 vs. 0.01 km²) and discharge (1.9 m³ s⁻¹vs. 0.005 m³ s⁻¹) in November versus August. Our results demonstrate the need to understand the nonperennial stream reaches when calculating carbon emissions. We compared the stream network emissions with the terrestrial net ecosystem exchange (NEE) estimated by local eddy covariance measurements per watershed area (−5.5 Mg C day⁻¹in August and −2.2 Mg C day⁻¹in November). Daily stream emissions in November accounted for a much larger percentage of NEE than in August (54% vs. 0.62%). We concluded that the stream network can emit a large percentage of the forest NEE in the winter months, and annual estimates of stream network emissions must consider the flow regime throughout the year.