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Abstract River metabolism and, thus, carbon cycling are governed by gross primary production and ecosystem respiration. Traditionally river metabolism is derived from diel dissolved oxygen concentrations, which cannot resolve diel changes in ecosystem respiration. Here, we compare river metabolism derived from oxygen concentrations with estimates from stable oxygen isotope signatures (δ¹⁸O₂) from 14 sites in rivers across three biomes using Bayesian inverse modeling. We find isotopically derived ecosystem respiration was greater in the day than night for all rivers (maximum change of 113 g O₂ m⁻² d⁻¹, minimum of 1 g O₂ m⁻² d⁻¹). Temperature (20 °C) normalized rates of ecosystem respiration and gross primary production were 1.1 to 87 and 1.5 to 22-fold higher when derived from oxygen isotope data compared to concentration data. Through accounting for diel variation in ecosystem respiration, our isotopically-derived rates suggest that ecosystem respiration and microbial carbon cycling in rivers is more rapid than predicted by traditional methods. 

Abstract Headwater stream networks contribute substantially to the global carbon dioxide terrestrial flux because of high turbulence and coupling with terrestrial environments. Heterogeneity within headwater stream networks, both spatially and temporally, makes measuring and upscaling these emissions challenging because measurements of carbon dioxide in streams are often limited to a few monitoring points. We modified a stream network model to reflect real measurements made under base flow and high flow conditions at Martha Creek in Stabler, WA in the US Pacific Northwest. We found that under high flow conditions, the stream network had much greater total carbon emissions than during low flow conditions (1.22 Mg C day⁻¹vs. 0.034 Mg C day⁻¹). We attribute this increase to a larger overall stream network area (0.04 vs. 0.01 km²) and discharge (1.9 m³ s⁻¹vs. 0.005 m³ s⁻¹) in November versus August. Our results demonstrate the need to understand the nonperennial stream reaches when calculating carbon emissions. We compared the stream network emissions with the terrestrial net ecosystem exchange (NEE) estimated by local eddy covariance measurements per watershed area (−5.5 Mg C day⁻¹in August and −2.2 Mg C day⁻¹in November). Daily stream emissions in November accounted for a much larger percentage of NEE than in August (54% vs. 0.62%). We concluded that the stream network can emit a large percentage of the forest NEE in the winter months, and annual estimates of stream network emissions must consider the flow regime throughout the year. 

Abstract Streams and rivers are major sources of greenhouse gases (GHGs) to the atmosphere, as carbon and nitrogen are converted and outgassed during transport. Although our understanding of drivers of individual GHG fluxes has improved with numerous site‐specific studies and global‐scale compilations, our ability to parse out interrelated physical and biogeochemical drivers of gas concentrations is limited by a lack of consistently collected, temporally continuous samples of GHGs and their associated drivers. We present a first analysis of such a dataset collected by the National Ecological Observatory Network across 27 streams and rivers across ecoclimatic domains of the United States. Average concentrations of CO₂ranged from 36.9 ± 0.88 to 404 ± 33 μmol L⁻¹, CH₄from 0.003 ± 0.0003 to 4.99 ± 0.72 μmol L⁻¹, and N₂O from 0.015 to 0.04 μmol L⁻¹and spanned ranges of previous global compilations. Both CO₂and CH₄were strongly affected by physical drivers including mean air temperature and stream slope, as well as by dissolved oxygen and total nitrogen concentrations. N₂O was exclusively correlated with total nitrogen concentrations. Results suggested that potential for gas exchange dominated patterns in gas concentrations at the site level, but contributions of in‐stream aerobic and anaerobic metabolism, and groundwater also likely varied across sites. The highest gas concentrations as well as highest variability occurred in low‐gradient, warmer, and nonperennial systems. These results are a first step in providing unprecedented, continuous estimates of GHG flux constrained by temporally variable physical and biogeochemical drivers of GHG production. 

Abstract Hydrologic controls on carbon processing and export are a critical feature of wetland ecosystems. Hydrologic response to climate variability has important implications for carbon‐climate feedbacks, aquatic metabolism, and water quality. Little is known about how hydrologic processes along the terrestrial‐aquatic interface in low‐relief, depressional wetland catchments influence carbon dynamics, particularly regarding soil‐derived dissolved organic matter (DOM) transport and transformation. To understand the role of different soil horizons as potential sources of DOM to wetland systems, we measured water‐soluble organic matter (WSOM) concentration and composition in soils collected from upland to wetland transects at four Delmarva Bay wetlands in the eastern United States. Spectral metrics indicated that WSOM in shallow organic horizons had increased aromaticity, higher molecular weight, and plant‐like signatures. In contrast, WSOM from deeper, mineral horizons had lower aromaticity, lower molecular weights, and microbial‐like signatures. Organic soil horizons had the highest concentrations of WSOM, and WSOM decreased with increasing soil depth. WSOM concentrations also decreased from the upland to the wetland, suggesting that continuous soil saturation reduces WSOM concentrations. Despite wetland soils having lower WSOM, these horizons are thicker and continuously hydrologically connected to wetland surface and groundwater, leading to wetland soils representing the largest potential source of soil‐derived DOM to the Delmarva Bay wetland system. Knowledge of which soil horizons are most biogeochemically significant for DOM transport in wetland ecosystems will become increasingly important as climate change is expected to alter hydrologic regimes of wetland soils and their resulting carbon contributions from the landscape.