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Recent trends in the chemistry of major northern rivers signal widespread Arctic change

Nature Geoscience volume 16, pages 789–796 (2023)Cite this article

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Abstract

Rivers integrate processes occurring throughout their watersheds and are therefore sentinels of change across broad spatial scales. River chemistry also regulates ecosystem function across Earth’s land–ocean continuum, exerting control from the micro- (for example, local food web) to the macro- (for example, global carbon cycle) scale. In the rapidly warming Arctic, a wide range of processes—from permafrost thaw to biological uptake and transformation—might reasonably alter river water chemistry. Here we use data from major rivers that collectively drain two-thirds of the Arctic Ocean watershed to assess widespread change in biogeochemical function within the pan-Arctic basin from 2003 to 2019. While the oceanward flux of alkalinity and associated ions increased markedly over this time frame, nitrate and other inorganic nutrient fluxes declined. Fluxes of dissolved organic carbon showed no overall trend. This divergence in response indicates the perturbation of multiple processes on land, with implications for biogeochemical cycling in the coastal ocean. We anticipate that these findings will facilitate refinement of conceptual and numerical models of current and future functioning of Arctic coastal ecosystems and spur research on scale-dependent change across the river-integrated Arctic domain.

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Fig. 1: The six great Arctic rivers.
Fig. 2: Long-term discharge record for each of the six great Arctic rivers.
Fig. 3: Annual constituent flux for alkalinity, DOC and nitrate (NO3−-N), summed across the six great Arctic rivers.
Fig. 4: Annual trends for each of the six great Arctic rivers.
Fig. 5: A conceptual diagram illustrating select drivers of change of Arctic riverine chemistry.

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Data availability

Data used for our analyses and daily Kalman outputs are provided as a fixed package at the Arctic Data Center (https://doi.org/10.18739/A2VH5CK43). More recent updates of the ArcticGRO water quality and discharge datasets can be found at the project website (www.arcticgreatrivers.org) and through the Arctic Data Center61.

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Acknowledgements

Funding for the PARTNERS programme and Arctic Great Rivers Observatory has been provided via US National Science Foundation grants 0229302 and 0732985 (B.J.P.); 0732522, 1107774, 1602615 and 1913888 (R.M.H.); 0732821, 1602680, 1914215 and 2230812 (J.W.M.); 0732583 (P.A.R.); 1603149 and 1914081 (R.G.M.S.); and 1602879 and 1913962 (A.I.S.). This work would not have been possible without contributions from many individuals at the six ArcticGRO sampling locations, and we gratefully acknowledge contributions from E. Amos, B. Blais, C. Couvillion, A. Davydova, N. Dion, V. Efremov, L. Kutny, R. McLeod, R. Myers, A. Pavlov, A. Smirnov, M. Suslov, G. Zimova and support from the Environment and Climate Change Canada and Indigenous and Northern Affairs Canada offices in Inuvik, Canada. Sample collection occurred within the Gwich’in Settlement Region (Mackenzie River at Tsiigehtchic) and on the traditional territories of the Yup’ik people (Yukon River at Pilot Station) in North America and the Nenets, Dolgans, Nganasans, Evenks and Chukchi people (Ob’, Yenisey, Lena and Kolyma rivers at Salekhard, Dudinka, Zhigansk and Chersky) in Russia. S. Sylva, G. Swarr and M. Auro assisted with analyses of major and trace anion/cation data.

Author information

Authors and Affiliations

  1. Department of Biological Sciences, University of Alberta, Edmonton, Alberta, Canada

    Suzanne E. Tank

  2. Ecosystems Center, Marine Biological Laboratory, Woods Hole, MA, USA

    James W. McClelland & Bruce J. Peterson

  3. Department of Earth, Ocean and Atmospheric Science, Florida State University, Tallahassee, FL, USA

    Robert G. M. Spencer

  4. Earth Systems Research Center, University of New Hampshire, Durham, NH, USA

    Alexander I. Shiklomanov

  5. Woodwell Climate Research Center, Falmouth, MA, USA

    Anya Suslova, Lindsay Scott & Robert M. Holmes

  6. INRAE, UR RiverLy, Centre de Lyon-Villeurbanne, France

    Florentina Moatar

  7. Department of Marine and Coastal Environmental Sciences, Texas A&M University, Galveston, TX, USA

    Rainer M. W. Amon

  8. Department of Oceanography, Texas A&M University, College Station, TX, USA

    Rainer M. W. Amon

  9. Chesapeake Biological Laboratory, University of Maryland Center for Environmental Science, Solomons, MD, USA

    Lee W. Cooper

  10. Western Arctic Research Center, Inuvik, Northwest Territories, Canada

    Greg Elias

  11. Shirshov Institute of Oceanology, Russian Academy of Sciences, Moscow, Russia

    Vyacheslav V. Gordeev

  12. Mamala Research LLC, Honolulu, HI, USA

    Christopher Guay

  13. South Russia Centre for Preparation and Implementation of International Projects, Rostov-on-Don, Russia

    Tatiana Yu. Gurtovaya & Alexander V. Zhulidov

  14. Hydrochemical Institute of the Federal Service for Hydrometeorology and Environmental Monitoring, Ministry of Natural Resources and Environment of the Russian Federation, Rostov-on-Don, Russia

    Lyudmila S. Kosmenko

  15. Yukon River Inter-Tribal Watershed Council, Anchorage, AK, USA

    Edda A. Mutter

  16. Marine Chemistry and Geochemistry Department, Woods Hole Oceanographic Institution, Woods Hole, MA, USA

    Bernhard Peucker-Ehrenbrink

  17. School of Forestry and Environmental Studies, Yale University, New Haven, CT, USA

    Peter A. Raymond

  18. Earth System Processes Division, US Geological Survey, Boulder, CO, USA

    Paul F. Schuster & Robert G. Striegl

  19. Water Resources Division, Government of the Northwest Territories, Yellowknife, Northwest Territories, Canada

    Robin Staples

  20. River Estuaries and Water Resources Department, Arctic and Antarctic Research Institute, Saint Petersburg, Russia

    Mikhail Tretiakov

  21. Pacific Geographical Institute of the Far Eastern Branch of the Russian Academy of Sciences, Chersky, Russia

    Nikita Zimov & Sergey Zimov

Authors
  1. Suzanne E. Tank
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  26. Robert M. Holmes
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Contributions

Conceived of the paper and performed data analysis: S.E.T., R.M.H., J.W.M., R.G.M.S., A.S., F.M. and A.I.S. Led manuscript preparation: S.E.T. Initial design of the ArcticGRO (PARTNERS) programme: B.J.P., R.M.H., J.W.M., P.A.R., R.G.S., R.M.W.A., L.W.C., V.V.G., S.Z. and A.V.Z. Sample and data acquisition: A.V.Z., T.Yu.G., S.Z., N.Z., G.E., P.F.S., E.A.M., R.S., M.T. and L.S.K. Performed laboratory analyses: A.S., L.S., B.P.-E., C.G. and P.F.S. Read and commented on the manuscript: all authors.

Corresponding author

Correspondence to Suzanne E. Tank.

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The authors declare no competing interests.

Peer review

Peer review information

Nature Geoscience thanks Fabrice Lacroix, Ryan Toohey and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Primary Handling Editor: Xujia Jiang, in collaboration with the Nature Geoscience team.

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Extended data

Extended Data Table 1 Characteristics of the six largest Arctic watersheds
Full size table

Extended Data Fig. 1 Time-series of discharge and concentration measurements across the six great Arctic rivers.

Discharge is shown as a continuous record for all rivers. Dates of sample collection for concentration measurements used in this analysis are shown with red circles; hollow circles indicate ongoing data collection.

Extended Data Fig. 2 Correlation between constituents for the full ArcticGRO dataset.

Shading indicates the Pearson correlation coefficient, which was used as the distance metric for hierarchical clustering. Focal constituents (alkalinity, nitrate [NO3−-N], and dissolved organic carbon [DOC]) are bolded in blue. Black boxes within the correlation plot and grey shading along axes indicate clusters associated with each focal constituent. Analysis is visualized via a cluster heatmap, for correlations on individual concentration data points.

Extended Data Fig. 3 Annual trends in constituent flux across the full ArcticGRO dataset.

Trend analysis is via a Mann-Kendall analysis; the Thiel-Sen slope (numerical value) and p-value of the trend analysis (shading) are shown. Corresponding trends in concentration are provided in Extended Data Fig. 4. Grey bars illustrate groupings from Extended Data Fig. 2. Units (Gg y−1 or Mg y−1) are provided in Supplementary Table 1.

Extended Data Fig. 4 Trends for constituent concentration across the full ArcticGRO dataset.

Trend analysis is via a seasonal Mann-Kendall analysis; the Thiel-Sen slope (numerical value) and p-value of the trend analysis (shading) are shown. Corresponding trends in constituent flux are provided in Extended Data Fig. 3. Grey bars illustrate groupings from Extended Data Fig. 2. Units (mg L−1 y−1 or µg L−1 y−1) are provided in Supplementary Table 2.

Extended Data Fig. 5 Flow-normalized trends in annual constituent flux.

Trends are provided for the three focal constituents (alkalinity, dissolved organic carbon [DOC], and nitrate [NO3−-N], for each of the six great Arctic rivers. The solid line indicates the mean, and shading indicates 90% confidence interval from the block bootstrap analysis. Asterisks indicate block bootstrap-assessed trends that are: ***highly likely (posterior mean estimate \(\hat{\pi }\) <0.05 or >0.95); **very likely (\(\hat{\pi }\) 0.05–0.10 or 0.90–0.95); or *likely (\(\hat{\pi }\) 0.10–0.33 or 0.66–0.90), with percentage change in constituent flux indicated for the period of record. Where no percentage change is shown, trends were assessed to be about as likely as not (\(\hat{\pi }\) 0.33–0.66).

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Supplementary Information

Supplementary Discussion, Fig. 1 and Tables 1 and 2.

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Tank, S.E., McClelland, J.W., Spencer, R.G.M. et al. Recent trends in the chemistry of major northern rivers signal widespread Arctic change. Nat. Geosci. 16, 789–796 (2023). https://doi.org/10.1038/s41561-023-01247-7

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