Search for: All records

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. 

The Upper Clark Fork River (UCFR) Long Term Research in Environmental Biology (LTREB) umbrella monitoring project generating these data is conducted separately and complementarily to the 200-million-dollar (USD) superfund project for ecological restoration of the UCFR, associated tributaries, and head water streams including Silver Bow and Warm Springs Creeks. Restoration along the UCFR in western Montana includes removal of metal-laden floodplain soils, lowering of the floodplain to its original elevation, and re-vegetation of over 70 km of the river’s floodplain closest to contaminant sources. The UCFR LTREB project includes bi-weekly water quality monitoring across the first 200 km of the river and its major tributaries along a gradient of heavy metal contamination associated with historic mining. Monitoring includes inorganic phosphorus and nitrogen concentrations, biotic standing stocks, and dissolved and whole-water heavy metal concentrations. The monitoring program began in 2017 with funding extended through 2028. The original analytical intent for these data was to assess the response of river dissolved organic carbon to the floodplain restoration. Data are total organic carbon combustion analyses (Shimadzu Scientific Instruments) of the concentration of organic carbon dissolved in filtered samples of well-mixed river thalweg water. Data are from the 2024 water year (1 Oct 2023 to 30 Sep 2024) from samples collected on the Upper Clark Fork River (USGS HUC 17010201) at project sites distributed along the river from the vicinity of Anaconda to Missoula, Montana, USA. 

The Upper Clark Fork River (UCFR) Long Term Research in Environmental Biology (LTREB) umbrella monitoring project generating these data is conducted separately and complementarily to the 200-million-dollar (USD) superfund project for ecological restoration of the UCFR, associated tributaries, and head water streams including Silver Bow and Warm Springs Creeks. Restoration along the UCFR in western Montana includes removal of metal-laden floodplain soils, lowering of the floodplain to its original elevation, and re-vegetation of over 70 km of the river’s floodplain closest to contaminant sources. The UCFR LTREB project includes bi-weekly water quality monitoring across the first 200 km of the river and its major tributaries along a gradient of heavy metal contamination associated with historic mining. Monitoring includes inorganic phosphorus and nitrogen concentrations, biotic standing stocks, and dissolved and whole-water heavy metal concentrations. The monitoring program began in 2017 with funding extended through 2028. The original analytical intent for these data was to assess the response of river dissolved organic carbon to the floodplain restoration. Data are primarily Aurora Total Organic Carbon combustion analyses of the concentration of organic carbon dissolved in filtered samples of well-mixed river thalweg water. A few samples from the final campaign in the dataset were analyzed with a Shimadzu instrument using a similar method. Data are from the 2022 water year (1 Oct 2021 to 30 Sep 2022) from samples collected on the Upper Clark Fork River (USGS HUC 17010201) at project sites distributed along the river from the vicinity of Anaconda to Missoula, Montana, USA. 

The Upper Clark Fork River (UCFR) Long Term Research in Environmental Biology (LTREB) umbrella monitoring project generating these data is conducted separately and complementarily to the 200-million-dollar (USD) superfund project for ecological restoration of the UCFR, associated tributaries, and head water streams including Silver Bow and Warm Springs Creeks. Restoration along the UCFR in western Montana includes removal of metal-laden floodplain soils, lowering of the floodplain to its original elevation, and re-vegetation of over 70 km of the river’s floodplain closest to contaminant sources. The UCFR LTREB project includes bi-weekly water quality monitoring across the first 200 km of the river and its major tributaries along a gradient of heavy metal contamination associated with historic mining. Monitoring includes inorganic phosphorus and nitrogen concentrations, biotic standing stocks, and dissolved and whole-water heavy metal concentrations. The monitoring program began in 2017 with funding extended through 2028. The original analytical intent for these data was to assess the response of river dissolved organic carbon to the floodplain restoration. Data are total organic carbon combustion analyses (Shimadzu Scientific Instruments) of the concentration of organic carbon dissolved in filtered samples of well-mixed river thalweg water. Data are from the 2023 water year (1 Oct 2022 to 30 Sep 2023) from samples collected on the Upper Clark Fork River (USGS HUC 17010201) at project sites distributed along the river from the vicinity of Anaconda to Missoula, Montana, USA. 

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 package provides necessary supporting data and models for the manuscript titled "Divergent metabolism estimates from dissolved oxygen and inorganic carbon: implications for river carbon cycling". The entire dataset consists of sensor data collected at three reaches and metabolism estimates from different models. The sensor data include partial pressure of carbon dioxide in water, dissolved oxygen and temperature. At each reach, we established a two station approach, meaning at least one pair of sensor suits were distributed upstream and downstream. Results for metabolism estimates differ by solutes (i.e., oxygen or carbon based) and modelling approaches (i.e., single station or two station approach). In addition to data products, we also provide R packages for metabolism models.