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Weakening greenhouse gas sink of pristine wetlands under warming

Nature Climate Change volume 13, pages 462–469 (2023)Cite this article

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Abstract

Pristine wetlands have high potential for mitigating climate change because of their large carbon stocks. However, whether and where wetlands will act as a greenhouse gas sink or source under warming is uncertain. Here we report the observations from 167 sites of the responses of carbon dioxide, methane and nitrous oxide emissions to experimental warming in northern wetlands between latitudes 30° N and 80° N during the period 1990–2022. We show that the 100-year global warming potential of wetlands increased by 57% in response to an average temperature increase of 1.5–2.0 °C. The difference in dominant plant functional types explains the uncertainties in emissions. Although warming increased the CO2 sink in vascular plant sites, it enhanced the CO2 source in cryptogam-dominated sites. As a net source of CH4 and N2O, the permafrost wetlands dominated by vascular plants positively responded to warming. Our results show that warming undermines the mitigation potential of pristine wetlands even for a limited temperature increase of 1.5–2.0 °C, the main goal of the Paris Agreement.

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Fig. 1: Warming experiments and wetland GHG responses.
Fig. 2: Global warming potential and sustained-flux global warming potential of wetlands.
Fig. 3: Effects of warming on GHG emissions.
Fig. 4: Spatial heterogeneity of wetland GHG emissions under warming.

Data availability

All relevant data supporting the key findings of this study are publicly available at Figshare (https://doi.org/10.6084/m9.figshare.22015664.v1)68.

Code availability

All code used can be obtained from Figshare (https://doi.org/10.6084/m9.figshare.22015742.v1)69.

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Acknowledgements

This study was funded by the National Key R&D Program of China (2022YFF0801904 to X.X.) and the Natural Science Foundation of China (42206254 to T.B.).

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Authors and Affiliations

  1. Key Laboratory of Regional Climate-Environment for Temperate East Asia, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China

    Tao Bao, Gensuo Jia & Xiyan Xu

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  1. Tao Bao
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  2. Gensuo Jia
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Contributions

T.B., X.X. and G.J. conceived and designed the study. T.B. performed the data extraction and analysis as well as figure plotting. T.B., X.X. and G.J. wrote the manuscript and contributed to the discussion of the results.

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Correspondence to Xiyan Xu.

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Extended data

Extended Data Fig. 1 Effects of warming on GPP and ER.

The mean effect size of warming on GPP and ER at vascular plant and cryptogam sites (a), and at different plant dominated sites (b) with error bars indicating 95%CI, the conceptual diagram illustrating the response of GPP and ER to warming (c and d). Different plant types mentioned here refer to the local dominant plants. The values next to the bars in parentheses are the corresponding effect size (left) and the number of sites (right) in each group. p value is shown if effect size of a group is significant (p < 0.05). p values are derived from the meta-analysis by using the inverse-variance method under a random-effects model (see Methods). The thickness of the arrow in (c) and (d) corresponds to the magnitude of the effect size. Red and gray arrows in (c) and (d) represent significantly positive and insignificant effect, respectively.

Extended Data Fig. 2 Mean effect size of warming on GHG emissions at sites of different wetland type.

Wetland warming experiments were mainly conducted in three wetland types, that is, fen, bog and wet tundra. The values next to the bars in parentheses are the corresponding effect size (left) and the number of sites (right) in each group. p value is shown if effect size of a group is significant (p < 0.05). p values are derived from the meta-analysis by using the inverse-variance method under a random-effects model. Error bars indicate 95% CIs.

Extended Data Fig. 3 Spatial heterogeneity of GPP and ER under warming.

Latitudinal variations of the effect sizes of warming on GPP (a) and ER (b). Comparison of the mean effect sizes of warming on GPP (d) and ER (e) in permafrost and non-permafrost. Hollow circles in (a) and (b) represent single pairs of data, with different size representing the relative weight. Colored lines are best-fit lines obtained from meta-regression. The p and F values of Pearson correlation (r) statistical analysis in (a) and (b) are indicated next to the corresponding fitted line. N is the sample size of each group. The shaded area in (a) and (b) and error bars in (c) and (d) stand for 95% CIs. The values next to the bars in parentheses are the corresponding effect size (left) and the number of sites (right) in each group. p values in (a) and (b) are calculated via one-way ANOVA test, and in (c) and (d) are derived from the meta-analysis by using the inverse-variance method under a random-effects model.

Extended Data Fig. 4 Effect of warming on soil water and temperature.

Effect of warming on soil moisture at different soil depths and water table (a). Relationships between the change in surface soil moisture, soil temperature and increase in air temperature (b–e). Blue lines in (a) represent the mean value of soil moisture and water table change, and numbers next to violin plots are the number of sites. Black solid lines in (b–e) are best-fit lines obtained from meta‐regression. The shaded area with dashed curves stands for 95% CIs. The p and F values of Pearson correlation statistical analysis are indicated next to the corresponding fitted line. N is the sample size of each group. p values in (b-e) are calculated via one‐way ANOVA test. The dashed red line in (d) and (e) depicts the 1:1 line.

Extended Data Fig. 5 Effect of warming on plant growth.

Effects of warming on plant height and abundance at different plant (shrub, graminoid, moss and lichen) dominated sites. Data are presented as mean values ± 95% CIs. The values next to the bars in parentheses are the corresponding effect size (left) and the number of sites (right) in each group. p values are derived from the meta-analysis by using the inverse-variance method under a random-effects model. Plant height is defined as the shortest distance between the upper boundary (the highest point) of the main photosynthetic tissues and the ground level, and plant abundance is defined by biomass, frequency, cover, or point-frame hits. Figure adapted with permission from ref. 17, Wiley.

Extended Data Fig. 6 Responses of GHG emissions under warming against local climate.

Regression analysis of responses of CO2 (a), CH4 (b) and N2O (c) emissions under warming against mean annual temperature (MAT). Regression analysis of responses of CO2 (d), CH4 (e) and N2O (f) under warming against mean annual precipitation (MAP). Hollow circles in (a–f) represent single pairs of data, with different size representing the relative weight. Colored lines are best-fit lines obtained from meta-regression. The p and F values of Pearson correlation (r) statistical analysis are indicated next to the corresponding fitted line. The shaded area stands for 95% CIs. p values are calculated via one-way ANOVA test. N is the sample size of each group.

Extended Data Fig. 7 Responses of GPP and ER under warming against local climate.

Regression analysis of responses of GPP (a) and ER (b) under warming against mean annual temperature (MAT). Regression analysis of responses of GPP (c) and ER (d) under warming against mean annual precipitation (MAP). Hollow circles in (a–d) represent single pairs of data, with different size representing the relative weight. Colored lines are best-fit lines obtained from meta‐regression. The p and F values of Pearson correlation (r) statistical analysis are indicated next to the corresponding fitted line. The shaded area stands for 95% CIs. p values are calculated via one‐way ANOVA test. N is the sample size of each group.

Extended Data Fig. 8 Responses of GHG emissions depending on warming duration.

Comparison of the mean effect sizes of warming on CO2 (a), CH4 (b) and N2O (c) emissions in the short-(<3 years) and long-term (≥3 years) warming experiments. Data are presented as mean values ± 95% CIs. The values next to the bars in parentheses are the mean effect size (left) and the number of sites (right) in each group. p value is shown if effect size of a group is significant (p < 0.05). p values are derived from the meta-analysis by using the inverse-variance method under a random-effects model.

Extended Data Fig. 9 Responses of GPP and ER depending on warming duration.

Comparison of the mean effect sizes of warming on GPP (a) and ER (b) in the short- (<3 years) and long-term (≥3 years) warming experiments. Error bars in (a) and (b) indicate 95% CIs. The values next to the bars in parentheses are the corresponding effect size (left) and the number of sites (right) in each group. p value is shown if effect size of a group is significant (p < 0.05). p values are derived from the meta-analysis by using the inverse-variance method under a random-effects model.

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Bao, T., Jia, G. & Xu, X. Weakening greenhouse gas sink of pristine wetlands under warming. Nat. Clim. Chang. 13, 462–469 (2023). https://doi.org/10.1038/s41558-023-01637-0

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