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Global carbon dioxide efflux from rivers enhanced by high nocturnal emissions

Abstract

Carbon dioxide (CO2) emissions to the atmosphere from running waters are estimated to be four times greater than the total carbon (C) flux to the oceans. However, these fluxes remain poorly constrained because of substantial spatial and temporal variability in dissolved CO2 concentrations. Using a global compilation of high-frequency CO2 measurements, we demonstrate that nocturnal CO2 emissions are on average 27% (0.9 gC m−2 d−1) greater than those estimated from diurnal concentrations alone. Constraints on light availability due to canopy shading or water colour are the principal controls on observed diel (24 hour) variation, suggesting this nocturnal increase arises from daytime fixation of CO2 by photosynthesis. Because current global estimates of CO2 emissions to the atmosphere from running waters (0.65–1.8 PgC yr−1) rely primarily on discrete measurements of dissolved CO2 obtained during the day, they substantially underestimate the magnitude of this flux. Accounting for night-time CO2 emissions may elevate global estimates from running waters to the atmosphere by 0.20–0.55 PgC yr−1.

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Fig. 1: Magnitude and bias of diel variation in CO2 emission fluxes from global streams.
Fig. 2: Geographical distribution of diel variation in stream CO2 emission fluxes.
Fig. 3: Seasonal pattern of diel changes in CO2 emission fluxes from streams.
Fig. 4: Night versus day differences in CO2 emission fluxes along the river size and colour continuum.

Data availability

Data are freely available at Zenodo (https://doi.org/10.5281/zenodo.4321623). Data can be explored interactively at: https://gmrocher.shinyapps.io/night_co2_emissions_streams/.

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Acknowledgements

We thank S. Blackburn, J. Crawford, the Krycklan Catchment study and the Swedish Infrastructure for Ecosystem Science for sharing data used in this study. This study was largely supported by a Formas grant to R.A.S. Datasets provided by the StreamPULSE Network were funded by the National Science Foundation Macrosystems program (NSF Grant EF-1442439). D.A.R.-I. acknowledges support from the National Science Foundation (Grant EAR-1847331).

Author information

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Authors

Contributions

L.G.-G., G.R.-R. and R.A.S designed the study and wrote the paper with input from M.J.C. L.G.-G. and G.R.-R. compiled, processed and analysed the data. Å.H. provided remote sensing estimates. All authors contributed with data and commented on the earlier versions of this manuscript.

Corresponding authors

Correspondence to Lluís Gómez-Gener or Gerard Rocher-Ros.

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Competing interests

The authors declare no competing interests.

Additional information

Peer review information Nature Geoscience thanks Alberto Borges, Pierre Regnier and Jun Xu for their contribution to the peer review of this work. Primary Handling Editor: Xujia Jiang.

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data

Extended Data Fig. 1 Geographical and size distribution of the dataset.

a) Global distribution of the stream and river sites colored by canopy cover category. b) Distribution and relationship between catchment area and median annual discharge, colored by canopy cover category. Symbols indicate the origin of the data (see Supplementary Table 1 and Supplementary Table 5 for more information).

Extended Data Fig. 2 Drivers of night-day differences of CO2 emissions from streams.

Structural equation model (SEM) representing connections between reach-scale physical and biological parameters contributing to the relative night-day variation in summertime CO2 emissions (%). The SEM consisted of two dependent levels of factor interaction or metamodels. Metamodel 1 assessed the influence of kCO2 and stream water pCO2 on night-day differences of CO2 emissions. Metamodel 2 assessed relationships between environmental variables and diel changes in stream water pCO2. Blue arrows represent statistically significant effects (p < 0.05). Numbers adjacent to arrows are the standardized effect sizes of each relationship. Arrow width is proportional to the effect size. SEM goodness of fit was evaluated based on variance explained by each of the two models (r2). A summary of statistical outputs from the SEM model is provided in Supplementary Table 4. Reach-scale properties for each site used in the SEM model are presented in Supplementary Table 2.

Extended Data Fig. 3 Effect of water colour on the night-day differences in riverine CO2 emission fluxes.

Comparison of night-day differences in CO2 emission fluxes averaged by watercourse and grouped by canopy level and dissolved organic carbon concentration (DOC; mg L−1) level (lower than 10 mg L−1, between 10 and 20 mg L−1, and higher than 20 mg L−1). Box plots display the 25th, 50th, and 75th percentiles whiskers display minimum and maximum values.

Extended Data Fig. 4 Distribution of dissolved organic carbon (DOC) in the GLORICH dataset and in this study.

Inset table shows a selection of summary statistics. In the GLORICH database12, 92.6 and 98.5 % of the samples were below 10 and 20 mg L−1 respectively. 15 observations from the GLORICH database (out of 6,771) had DOC > 50 mg L−1 and are not represented in the density plot for better visualization (max. value 839 mg L−1).

Extended Data Fig. 5 Distribution of stream canopy cover and DOC concentrations by biome.

Panel a shows the canopy cover distribution for each biome (note that canopy category can only be 0, 1 or 2). Panel b represents the ranges in DOC for each biome.

Supplementary information

Supplementary Information

Supplementary methods, Figs. 1–3 and Tables 1–5.

Supplementary Tables

Supplementary Tables 1–5 as an excel file.

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Gómez-Gener, L., Rocher-Ros, G., Battin, T. et al. Global carbon dioxide efflux from rivers enhanced by high nocturnal emissions. Nat. Geosci. 14, 289–294 (2021). https://doi.org/10.1038/s41561-021-00722-3

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