Abstract
An explosion in high frequency dissolved oxygen (DO) observations at river network scales is creating new opportunities to understand dynamic signals in streams and rivers. Among the most informative metrics obtained from DO time series is stream metabolism—comprising gross primary production (GPP) and ecosystem respiration (ER)—but its estimation is non-trivial. There is thus interest in simpler metrics that can capture spatiotemporal patterns in stream metabolism and their consequences for critical ecosystem processes. Using hourly DO time series from 43 agricultural headwater streams reaches (Strahler order 1–5) across five watersheds and two years, we tested the hypothesis that simple DO metrics are useful proxies of stream metabolism, capturing key features of its spatiotemporal variation, and predicting attendant patterns in dissolved organic matter quality and catchment nitrogen processing via denitrification. Our results suggest the diel DO range scaled by stream depth is an excellent proxy for GPP throughout the network, accurately describing its spatial and temporal patterns. In contrast, we found that DO metrics were less successful as proxies for ER, with the maximum daily DO deficit scaled by depth being a good proxy for ER only in higher order streams. We also observed that DO metrics were strongly related to variation in dissolved organic matter quality and denitrification far better than GPP or ER. Finally, we found that DO metrics, GPP, and to a lesser extent ER, had power-law relationships with watershed area (scaling exponents, β = 0.2–0.5), implying increasing downstream metabolic activity. However, because lower order streams occupy ∼75% of network benthic area, total network GPP and ER (g O2 d−1) were disproportionately provided by lower order streams, consistent with recent theoretical modeling. These findings reveal the rich inference space that simple DO metrics can provide, and support their use as proxies for stream metabolism and for inferring network patterns of biogeochemical function.
Highlights
Dissolved oxygen (DO) in flowing waters is an information-rich ecosystem indicator, at once integrating energy dynamics, describing aquatic habitat suitability, and constraining biogeochemical processes
Despite the often dispiriting un certainties associated with metabolism inferences, much can be learned from simple DO metrics (Moatar et al, 2001; Mulholland et al, 2005; Wang et al, 2003) that obviate the necessity of modeling assumptions
For data that passed quality control (n = 222,339), we calculated hourly DO saturation (DOsat) using water temperature and barometric pressure at sea level corrected for site elevation, and derived hourly DO saturation deficit (=DO minus DOsat), with a negative deficit indicating measured DO is below saturation
Summary
Dissolved oxygen (DO) in flowing waters is an information-rich ecosystem indicator, at once integrating energy dynamics, describing aquatic habitat suitability, and constraining biogeochemical processes. The first prediction, which is borne out of theoretical (Koenig et al, 2019; Vannote et al, 1980) and empirical evidence (Finlay, 2011; McTammany et al, 2003; Mejia et al, 2019), is that GPP increases along river networks as light availability increases with increasing channel widths and reduced shading This prediction implies that the diel range in DO (sometimes called DO flux, Jankowski et al, 2021 and references therein) increases in similar fashion as light inputs (Wang et al, 2003). Large DO deficits affect the balance between oxic and anoxic respiration pathways, and are linked to increased potential for in-stream denitrification (Christensen et al, 1990), which requires low DO This process inte gration of oxygen, DOM quality, and denitrification suggests that changes in DO concentrations along the stream should both control and result from in-stream biogeochemical processes and by-products. We expected strong relationships between DO proxies of stream metabolism and both DOM quality and denitrification isotopic N signatures
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