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1. Divergent metabolism estimates from dissolved oxygen and inorganic carbon: Implications for river carbon cycling

   https://doi.org/10.1002/lno.12666  

   Shangguan, Qipei; Payn, Robert A; Hall, Robert O; Young, Fischer L; Valett, H Maurice; DeGrandpre, Michael D (September 2024, Limnology and Oceanography)

   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. 

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2. Metabolism estimates from dissolved oxygen and inorganic carbon in the Upper Clark Fork River, MT, USA.

   https://doi.org/10.6073/pasta/7b5d1fe9a3d17847a9cf5012da2a3456  

   Shangguan, Qipei; Payn, Robert A; DeGrandpre, Michael D (January 2024, Environmental Data Initiative)

   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. 

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3. Oxygen dynamics control the burial of organic carbon in a eutrophic reservoir: Oxygen dynamics control OC burial

   https://doi.org/10.1002/lol2.10057  

   Carey, Cayelan C.; Doubek, Jonathan P.; McClure, Ryan P.; Hanson, Paul C. (December 2017, Limnology and Oceanography Letters)
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   Sambrotto, Raymond N.; Langdon, Christopher (June 1994, Continental Shelf Research)
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   Chu, Sophie N.; Wang, Zhaohui Aleck; Gonneea, Meagan Eagle; Kroeger, Kevin D.; Ganju, Neil K. (October 2018, Marine Chemistry)