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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 Measurements of riverine dissolved inorganic carbon, total alkalinity (A_T), pH, and the partial pressure of carbon dioxide (pCO₂) can provide insights into the biogeochemical function of rivers, including the processes that control biological production, chemical speciation, and air‐water CO₂fluxes. The complexity created by these combined processes dictates that studies of inorganic carbon be made over broad spatial and temporal scales. Time‐series data like these are relatively rare, however, because sampling and measurements are labor intensive and, for some variables, good measurement quality is difficult to achieve (e.g., pH). In this study, spectrophotometric pH and A_Twere quantified with high precision and accuracy at biweekly to monthly intervals over a four‐year period (2018–2021) along 216 km of the Upper Clark Fork River (UCFR) in the northern Rocky Mountains, USA. We use these and other time‐series data to provide insights into the processes that control river inorganic carbon, with a focus onpCO₂and air‐water CO₂fluxes. We found that seasonal snowmelt runoff increasedpCO₂and that expected increase and decrease ofpCO₂due to seasonal heating and cooling were likely offset by an increase and loss of algal biomass, respectively. Overall, the UCFR was a small net source (0.08 ± 0.14 mol m⁻² d⁻¹) of CO₂to the atmosphere over the four‐year study period with highly variable annual averages (0.0–0.10 mol m⁻² d⁻¹). The seasonally correlated, offsetting mechanisms highlight the challenges in predictingpCO₂and air‐water CO₂fluxes in rivers. 

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. 

Abstract The Upper Clark Fork River (UCFR), Montana, a mid-order well-lit system with contemporary anthropogenic nitrogen (N) enrichment and natural geogenic sources of phosphorus (P), experiences annual algal blooms that influence ecosystem structure and function. This study was designed to assess the occurrence of riverine algal blooms (RABs) in the UCFR by characterizing the succession of periphyton and biogeochemical conditions following annual snowmelt runoff through autumnal baseflow conditions, and to provide a framework for assessing RAB progression in montane mid-order rivers more broadly. Using a 21-year database (2000–2020) collected over the growing season at three sites, historical assessment of the persistent and recurrent character of RABs in the UCFR showed that the magnitude of the summer bloom was, in part, moderated by snowmelt disturbance. Abundance and growth forms of benthic algae, along with river physicochemistry (e.g., temperature) and water chemistry (N and P concentration), were measured over the course of snowmelt recession for three years (2018–2020) at the same three sites. Results documented the onset of major blooms of the filamentous green algaeCladophoraacross all sites, commensurate with declines in dissolved inorganic N. Atomic N:P ratios of river water suggest successional transitions from P- to N-limitation associated with mid-season senescence ofCladophoraand development of a secondary bloom of N-fixing cyanobacteria, dominated byNostoc cf. pruniforme. Rates of N-fixation, addressed at one of the sites during the 2020 snowmelt recession, increased uponCladophorasenescence to a maximal value among the highest reported for lotic systems (5.80 mg N/m²/h) before decreasing again to background levels at the end of the growing season. Based on these data, a heuristic model for mid-order rivers responding to snowmelt disturbance suggests progression from phases of physical stress (snowmelt) to optimal growth conditions, to conditions of biotic stress later in the growing season. Optimal growth is observed as green algal blooms that form shortly after peak snowmelt, then transition to stages dominated by cyanobacteria and autochthonous N production later in the growing season. Accordingly, interactions among algal composition, reactive N abundance, and autochthonous N production, suggest successional progression from reliance on external nutrient sources to increased importance of autochthony, including N-fixation that sustains riverine productivity during late stages of snowmelt recession.