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Biogeosciences An interactive open-access journal of the European Geosciences Union
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Preprints
https://doi.org/10.5194/bg-2020-304
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/bg-2020-304
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

  14 Oct 2020

14 Oct 2020

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This preprint is currently under review for the journal BG.

Resistance and resilience of stream metabolism to high flow disturbances

Brynn O'Donnell and Erin R. Hotchkiss Brynn O'Donnell and Erin R. Hotchkiss
  • Department of Biological Sciences, Virginia Polytechnic Institute and State University, Blacksburg, Virginia

Abstract. Streams are ecosystems organized by disturbance. One of the most frequent and variable disturbances in running waters is elevated flow. Yet, we still have few estimates of how ecosystem processes, such as stream metabolism (gross primary production and ecosystem respiration; GPP and ER), respond to high flow events. Furthermore, we lack a predictive frame- work for understanding controls on within-site metabolic responses to flow disturbances. Using five years of high-frequency dissolved oxygen data from an urban- and agriculturally-influenced stream, we estimated daily GPP and ER and analyzed metabolic changes across 15 isolated high flow events. Metabolism was variable from day to day, even during lower flows. Thus, we calculated metabolic resistance as the magnitude of departure from the dynamic equilibrium during antecedent lower flows and quantified resilience from the days until GPP and ER returned to the range of antecedent dynamic equilibrium. We evaluated correlations between metabolic resistance and resilience with characteristics of each high flow event, antecedent conditions, and time since last flow disturbance. ER was more resistant and resilient than GPP. GPP was typically suppressed following flow disturbances, regardless of disturbance intensity. In contrast, the ER magnitude of departure increased with disturbance intensity. Additionally, GPP was less resilient and took longer to recover (0 to > 9 days, mean = 2.2) than ER (0 to 2 days, mean = 0.6). Given the flashy nature of streams draining human-altered landscapes and the variable consequences of flow for GPP and ER, testing how ecosystem processes respond to flow disturbances is essential to an integrative understanding of ecosystem function.

Brynn O'Donnell and Erin R. Hotchkiss

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Brynn O'Donnell and Erin R. Hotchkiss

Brynn O'Donnell and Erin R. Hotchkiss

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