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Reach-scale river metabolism across contrasting sub-catchment geologies: Effect of light and hydrology

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Published
  • Lorenzo Rovelli
  • Karl M. Attard
  • Andrew Mark Binley
  • Catherine M. Heppell
  • Henrik Stahl
  • Mark Trimmer
  • Ronnie N. Glud
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<mark>Journal publication date</mark>11/2017
<mark>Journal</mark>Limnology and Oceanography
Issue numberSuppl. 1
Volume62
Number of pages19
Pages (from-to)S381-S399
Publication StatusPublished
Early online date5/07/17
<mark>Original language</mark>English

Abstract

We investigated the seasonal dynamics of in-stream metabolism at the reach scale (∼ 150 m) of headwaters across contrasting geological sub-catchments: clay, Greensand, and Chalk of the upper River Avon (UK). Benthic metabolic activity was quantified by aquatic eddy co-variance while water column activity was assessed by bottle incubations. Seasonal dynamics across reaches were specific for the three types of geologies. During the spring, all reaches were net autotrophic, with rates of up to 290 mmol C m-2 d-1 in the clay reach. During the remaining seasons, the clay and Greensand reaches were net heterotrophic, with peak oxygen consumption of 206 mmol m-2 d-1 during the autumn, while the Chalk reach was net heterotrophic only in winter. Overall, the water column alone still contributed to ∼ 25% of the annual respiration and primary production in all reaches. Net ecosystem metabolism (NEM) across seasons and reaches followed a general linear relationship with increasing stream light availability. Sub-catchment specific NEM proved to be linearly related to the local hydrological connectivity, quantified as the ratio between base flow and stream discharge, and expressed on a timescale of 9 d on average. This timescale apparently represents the average period of hydrological imprint for carbon turnover within the reaches. Combining a general light response and sub-catchment specific base flow ratio provided a robust functional relationship for predicting NEM at the reach scale. The novel approach proposed in this study can help facilitate spatial and temporal upscaling of riverine metabolism that may be applicable to a broader spectrum of catchments.