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Regional drivers of organic carbon age in lotic systems of the conterminous United States

Faunce, Kaycee

VCU Scholars Compass 2020

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  • Title:
    Regional drivers of organic carbon age in lotic systems of the conterminous United States
  • Author: Faunce, Kaycee
  • Subjects: aquatic biogeochemistry ; biogeochemistry ; carbon ; carbon cycling ; Environmental Sciences ; Other Environmental Sciences ; radiocarbon
  • Notes: https://scholarscompass.vcu.edu/context/etd/article/7562/viewcontent/Faunce_thesis_20201109.pdf
    Theses and Dissertations
    info:doi/10.25772/MGP9-E062
    https://scholarscompass.vcu.edu/etd/6435
  • Description: Rivers play a critical role in global carbon (C) budgets despite their comparatively small surface area. A significant portion of the terrestrial C that they receive is transformed, re-mineralized, or stored during transit to the ocean. Radiocarbon (∆14C) data show that a fraction of riverine organic C (OC) has been pre-aged in the terrestrial environment. Lateral export of carbon from these aged pools may contribute to atmospheric carbon dioxide emissions through microbial and photochemical oxidation. However, little is known about the regional climatic, anthropogenic, and landscape factors that promote the mobilization of aged OC to rivers. This study examines associations between riverine OC and river basin characteristics. It leverages data from two sources: 1) a spatially extensive collection of literature-reported ∆14C measurements and 2) the U.S. Environmental Protection Agency’s Stream-Catchment (StreamCat) database. The radiocarbon data include 95 dissolved (∆14CDOC) and 54 particulate (∆14CPOC) organic C measurements after averaging by location. We used the random forest (RF) machine learning algorithm to build independent models of ∆14CDOC (MSR = 7319.51, % var explained = 17.05) and ∆14CPOC (MSR = 11254.03, % var explained = 45.36). In both RF models, the StreamCat data were used aspredictor variables. Model validation was accomplished with a random, 75:25 split where 75% of the data were used for model building and the remaining 25% were used for testing and validation (∆14CDOC RMSE = 61.23, r = 0.71; ∆14CPOC RMSE = 39.82, r = 0.94). Key predictors of ∆14CDOC were generally climactic or land cover variables affecting terrestrial primary productivity. Key predictors of ∆14CPOC were primarily factors associated with sediment transport and erosion, but also included several indicators of anthropogenic influence. Human activities appear to be destabilizing both C pools, resulting in aged C flux to the more rapidly cycled C reservoir in rivers.
  • Publisher: VCU Scholars Compass
  • Creation Date: 2020
  • Language: English
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