High riverine CO2 emissions at the permafrost

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for understanding and predicting high-latitude river CO2 emissions in a changing climate. NATuRe GeOSCIeNCe | www.nature.com/naturegeoscience ...
Articles https://doi.org/10.1038/s41561-018-0218-1

High riverine CO2 emissions at the permafrost boundary of Western Siberia S. Serikova   1*, O. S. Pokrovsky   2, P. Ala-Aho3,4, V. Kazantsev5, S. N. Kirpotin6, S. G. Kopysov7, I. V. Krickov6, H. Laudon   8, R. M. Manasypov6,9, L. S. Shirokova2,9, C. Soulsby3, D. Tetzlaff   3,10,11 and J. Karlsson1* The fate of the vast stocks of organic carbon stored in permafrost of the Western Siberian Lowland, the world’s largest peatland, is uncertain. Specifically, the amount of greenhouse gas emissions from rivers in the region is unknown. Here we present estimates of annual CO2 emissions from 58 rivers across all permafrost zones of the Western Siberian Lowland, between 56 and 67° N. We find that emissions peak at the permafrost boundary, and decrease where permafrost is more prevalent and in colder climatic conditions. River CO2 emissions were high, and on average two times greater than downstream carbon export. We suggest that high emissions and emission/export ratios are a result of warm temperatures and the long transit times of river water. We show that rivers in the Western Siberian Lowland play an important role in the carbon cycle by degassing terrestrial carbon before its transport to the Arctic Ocean, and suggest that changes in both temperature and precipitation are important for understanding and predicting high-latitude river CO2 emissions in a changing climate.

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arge quantities of organic carbon (OC) are stored in permafrost soils in high-latitude regions1–3. Recent climate scenarios predict amplified warming of these regions that results in a substantial increase in mean annual air temperatures (MAAT). Such an increase will induce widespread permafrost thaw, accelerate the release of OC4 and stimulate its breakdown to carbon dioxide (CO2) and methane (CH4) in soils and wetlands5–7. Permafrost thawing also increases both the depth of the active layer and the associated release of OC to adjacent running waters6, where it is partly mineralized and evaded (mainly as CO2) to the atmosphere. Outgassing of CO2 from running waters is of significance in the global C cycle6,8,9. Yet, the magnitude of river CO2 emissions is often overlooked, especially in permafrost-affected landscapes where the consequences of climate warming are predicted to be the most severe3. Ignoring high-latitude river CO2 emissions may therefore cause errors in regional and global C budgets and bias assessments of concurrent changes following permafrost thaw. Measurements of C export by major Arctic rivers are relatively common10,11, whereas the direct measurements of CO2 emissions from high-latitude rivers are scarce. Available data show that highlatitude rivers are supersaturated in CO2 and are hotspots for CO2 release to the atmosphere12–14. Bioassays and small-scale field studies suggest that OC released from thawing permafrost can be degraded in recipient aquatic systems15,16. Furthermore, rivers receive and degas CO2 derived from soil respiration17, a process accelerated by permafrost thaw7,18. River CO2 emissions are therefore important not only for understanding the land–water C exchange with the atmosphere, but also in discerning the degree to which terrestrial C is lost in the aquatic network or exported to downstream coastal areas.

This lack of knowledge is particularly evident for Siberia, which has extensive permafrost coverage and associated vast C stocks1. In fact, the Western Siberian Lowland (WSL) alone contains 70 PgC in the region’s extensive peatlands19,20 and is home to the Arctic’s largest watershed, the Ob’ River, which is the second-largest freshwater contributor to the Arctic Ocean21. Moreover, permafrost in the WSL is highly vulnerable to thaw as its temperature has increased regionally by more than 1 °C during the last 30 years22. It has been shown recently that WSL permafrost is actively degrading not only within its forest–tundra subzone, but also within its northern tundra subzone22. Given the overall sensitivity of permafrost areas to warming, there is a clear need for empirical estimates of CO2 emissions from permafrost-draining rivers, not least in the WSL, to assess their role in regional and global C cycles and the climate system.

Study location and approach

To quantify and compare rates of CO2 emissions from rivers across different permafrost zones, we examined 58 rivers spanning a latitudinal gradient from 56 to 67° N and covering an area of approximately 1 million km2 in the WSL (Fig. 1). The rivers had no systematic variation in size or discharge along the latitudinal gradient (Supplementary Fig. 1). We carried out in situ measurements of the partial pressure of CO2 ( pCO2) and deployed floating chambers23 to estimate instantaneous CO2 emissions during spring and summer 2015. All rivers, across all permafrost zones, were supersaturated in pCO2 with respect to atmosphere, with similar values both in spring (2,402–5,072 µ​atm) and summer (2,187–5,328 µ​atm) (Supplementary Tables 1 and 4). The CO2 emissions varied among the zones (1.9–12 gC m−2 d−1 in spring; 2.7–7.6 gC m−2 d−1 in summer)

Climate Impacts Research Centre, Department of Ecology and Environmental Science, Umeå University, Umeå, Sweden. 2GET UMR 5563 CNRS, Geoscience and Environment, University of Toulouse, Toulouse, France. 3University of Aberdeen, Kings College, Aberdeen, Scotland. 4Water Resources and Environmental Engineering Research Unit, Faculty of Technology, University of Oulu, Oulu, Finland. 5Organization of the Russian Academy of Sciences A.M. Obukhov Institute of Atmospheric Physics RAS, Moscow, Russia. 6BIO-GEO-CLIM Laboratory, Tomsk State University, Tomsk, Russia. 7Institute of Monitoring of Climatic and Ecological Systems SB RAS, Tomsk, Russia. 8Department of Forest Ecology and Management, The Swedish University of Agricultural Sciences, Umeå, Sweden. 9N. Laverov Federal Center for Integrated Arctic Research, IEPS, RAS, Arkhangelsk, Russia. 10IGB Leibniz Institute of Freshwater Ecology and Inland Fisheries, Berlin, Germany. 11Humboldt University Berlin, Berlin, Germany. *e-mail: [email protected]; [email protected] 1

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Fig. 1 | Map of the study sites in the WSL, Russia. The blue shading represents permafrost extent in the WSL based on published data6,37, while the size of the orange circles represents the magnitude of the annual CO2 emissions (per unit of water area) from the studied rivers.

and showed seasonal differences in the permafrost-free and sporadic permafrost zones (Supplementary Fig. 2, Supplementary Tables 1 and 5). We also estimated diffusive CH4 emissions from the studied rivers. Although all rivers were net sources of CH4 to the atmosphere, these emissions were low and constituted only a minor contribution to total atmospheric C emissions, which were dominated by CO2 (98%).

Annual river CO2 emissions across permafrost zones

We found strong patterns in annual CO2 emissions among rivers located in different permafrost zones (F3,54 =​  6.808, P ​ 0.80, 8% of the measurements had a linear increase with r2 ​65°  N, n =​  6). We merged isolated and sporadic permafrost zones together under sporadic permafrost group as done elsewhere6. We also grouped the sampled sites into four different classes that represent watershed sizes: (1) small (​10,000  km2, n =​ 9). All statistical analyses were performed in RStudio statistical software (Version 1.0.44, RStudio, Inc.; www.r-project.org). To meet the normality assumption, all variables were log-transformed when necessary. The normality of data distribution was assessed by Shapiro–Wilk normality test. We further checked for the homogeneity of variances between the groups by using the parametric Bartlett test. We used one-way analysis of variance

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(ANOVA) with Tukey’s HSD post-hoc comparisons to investigate differences in annual river CO2 emissions among permafrost zones. All variables and their residuals followed normal distributions after transformation. We further used linear mixed effects models (lme4 package) when analysing two-way interactions of seasons and permafrost zones on the transformed per unit area daily CO2 emissions and surface water pCO2 . We used permafrost zones and seasons as fixed factors that are expected to have a systematic influence on the data, while we allowed our sampled streams to randomly vary inside permafrost zone groups and watershed classes, as well as months inside permafrost zone groups, to correct for the nested design of the study and resolve interdependency issues. In that way, we assumed that whatever the effects of permafrost extent and seasons are, they are going to be the same for all rivers sampled within the permafrost zone group. The best model fit was selected based on Akaike information criterion (AIC). We also performed contrast analyses on respective mixed effects models by constructing orthogonal contrasts to compare seasons between each other and to avoid multiple comparisons (lsmeans package). We used linear regression when analysing the relationship between annual CO2 emissions and MAAT. We also run multiple regression analysis on the dataset to see which of the variables (discharge, annual runoff, proportion of bogs, lakes, forest coverage, permafrost extent and so on) might be good predictors of the seasonal and annual CO2 emissions. No linear combination of the variables gave an r2 value greater than 50%. We further tested the variation in watershed size, discharge or landscape characteristics such as the proportion of bogs and forest coverage among different permafrost zones groups by using ANOVA with Tukey’s HSD post-hoc comparison or a non-parametric alternative of the Pairwise Wilcox test with the Holm adjustment. None of the variables exhibited significant differences between permafrost zones. We also used parametric Levene’s test on homogeneity of variances when assessing the variability in δ​2H and δ​18O between permafrost zones as well as pairwise Wilcox test with the Holm adjustment when examining differences in terrestrial C export between permafrost zones. Note that we report untransformed data in the text, figures and tables. Because of the non-normal distribution of the data, we use mean ±​ IQR when reporting uncertainty. All statistical tests used a significance level of 5% (α =​ 0.05) and were run on the complete dataset that includes all rivers. We removed outliers in Fig. 2 to visually improve the graph. Data availability. A summary of data generated and analysed during this study is available in the Supplementary Information Files. Water chemistry parameters and watershed characteristics for each of the sampled rivers are available as a separate Excel file. Additional pCO and CO2 emission data for each of the studied rivers are available upon request. 2

References

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