Vermont EPSCoR Publications and Products
Use of machine learning to extract patterns from long-term monitoring data across the US. ESA2020 (Harnessing the Ecological Data Revolution) [Internet]. 2020 . Available from: https://eco.confex.com/eco/2020/meetingapp.cgi/Paper/86651
. Temperature controls production but hydrology regulates export of dissolved organic carbon at the catchment scale. Hydrology and Earth System Sciences [Internet]. 2020 ;24(2):945 - 966. Available from: https://www.hydrol-earth-syst-sci.net/24/945/2020/hess-24-945-2020.html
Streams as Mirrors: Reading Subsurface Water Chemistry From Stream Chemistry. Water Resources Research [Internet]. 2022 ;58(1). Available from: https://onlinelibrary.wiley.com/doi/10.1029/2021WR029931
Machine‐Learning Reveals Equifinality in Drivers of Stream DOC Concentration at Continental ScalesAbstractKey Points. Water Resources Research [Internet]. 2023 ;59(3). Available from: https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2021WR030551
. Drivers of Dissolved Organic Carbon Mobilization From Forested Headwater Catchments: A Multi Scaled Approach. Frontiers in Water [Internet]. 2021 ;3. Available from: https://www.frontiersin.org/articles/10.3389/frwa.2021.578608/full
Critical Zone network cluster research: Using Big Data approaches to assess ecohydrological resilience across scales. In: 2020 AGU (American Geophysical Union) Fall Meeting. 2020 AGU (American Geophysical Union) Fall Meeting. Virtual: American Geophysical Union (AGU); 2020. Available from: https://agu.confex.com/agu/fm20/webprogram/Paper748076.html
Combining long-term observations with experiments to test hypotheses on stream water dissolved organic carbon dynamics at the Sleepers River Research Watershed. In: 2018 AGU (American Geophysical Union) Fall Meeting. 2018 AGU (American Geophysical Union) Fall Meeting. Washington, DC: American Geophysical Union (AGU); 2018. Available from: https://agu.confex.com/agu/fm18/meetingapp.cgi/Paper/407615
Combining complex systems analyses with process observations to understand stream dissolved organic carbon across scales. Goldschmidt 2020 [Internet]. 2020 . Available from: https://goldschmidtabstracts.info/2020/2060.pdf
. Application of machine-learning tools to extract patterns in long-term DOC monitoring data: an integrated, multi-scale approach. In: 2018 AGU (American Geophysical Union) Fall Meeting. 2018 AGU (American Geophysical Union) Fall Meeting. Washington, DC: American Geophysical Union (AGU); 2018. Available from: https://agu.confex.com/agu/fm18/meetingapp.cgi/Paper/411757
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