Characteristics of methane emissions from alpine thermokarst lakes on the Tibetan Plateau

Abstract

Understanding methane (CH₄) emission from thermokarst lakes is crucial for predicting the impacts of abrupt thaw on the permafrost carbon-climate feedback. However, observational evidence, especially from high-altitude permafrost regions, is still scarce. Here, by combining field surveys, radio- and stable-carbon isotopic analyses, and metagenomic sequencing, we present multiple characteristics of CH₄ emissions from 120 thermokarst lakes in 30 clusters along a 1100 km transect on the Tibetan Plateau. We find that thermokarst lakes have high CH₄ emissions during the ice-free period (13.4 ± 1.5 mmol m^-2 d^-1; mean ± standard error) across this alpine permafrost region. Ebullition constitutes 84% of CH₄ emissions, which are fueled primarily by young carbon decomposition through the hydrogenotrophic pathway. The relative abundances of methanogenic genes correspond to the observed CH₄ fluxes. Overall, multiple parameters obtained in this study provide benchmarks for better predicting the strength of permafrost carbon-climate feedback in high-altitude permafrost regions.

Fig. 1. The flow chart of the sampling campaign.

Our field sampling consists of the following three key steps. First, we choose 30 clusters of thermokarst lakes along a 1100 km transect on the Tibetan Plateau (a). Second, multiple locations within multiple lakes are selected at each cluster to eliminate spatial heterogeneity. In particular, four thermokarst lakes with different sizes are selected at each cluster (b). In each lake, 4 to 6 sampling locations are distributed from the shore to center (c), and at each location flux measurements are taken and averaged to estimate the CH₄ and CO₂ flux from the lake. Finally, each lake is sampled five times at monthly intervals during the ice-free period from mid-May to mid-October of 2021 to explore seasonal variation of CH₄ or CO₂ fluxes (d–h). In-situ CH₄ and CO₂ fluxes are determined using an opaque lightweight floating chamber equipped with a closed loop to a near-infrared laser CH₄/CO₂ analyzer (GLA231-GGA, ABB., Canada). In (a), the permafrost map of the Northern Hemisphere is obtained from the National Snow & Ice Data Center. Spatial distribution of permafrost on the Tibetan Plateau is derived from Zou et al.. The ellipses indicate the three representative permafrost regions in our study area, including the Madoi, Budongquan-Nagqu-Zadoi and Qilian sections. Photos are taken by G.Y.

Fig. 2. CH₄ fluxes in alpine thermokarst lake on the Tibetan Plateau.

Bubble size is proportional to the value of the CH₄ flux at each cluster, with a larger size representing a higher value. The background permafrost maps of the Northern Hemisphere and the Tibetan Plateau are derived from the National Snow & Ice Data Center and Zou et al., respectively. The inset shows the comparison of CH₄ fluxes in thermokarst lakes located in the three grassland types. AS, AM and SM represent alpine steppe, alpine meadow and swamp meadow, respectively. Box plots present the 25th and the 75th quartile (interquartile range), and whiskers indicate the data range among thermokarst lakes located in AS (n = 5), AM (n = 13) and SM (n = 12), respectively. The notches are the medians with 95% confidence intervals. Observed values are shown as black dots. Significant differences are denoted by different letters (one-way ANOVAs with two-sided Tukey’s HSD multiple comparisons, p = 0.049).

Fig. 3. Contribution of CH₄ to total carbon emissions from the investigated thermokarst lakes.

Panels (a, b) represent the density of carbon fluxes and CO₂-equivalent emmissions, respectively. The lines indicate the fluxes from four thermokarst lakes at each cluster during the measurement period. The pie charts show the contribution of CH₄ fluxes to total carbon emissions and CO₂-equivalent emissions. Mean CH₄ flux during the ice-free season and its CO₂-equivalent emissions are shown outside parentheses, and the corresponding contribution to total carbon emissions and CO₂-equivalent emissions are presented in parentheses, respectively.

Fig. 4. CH₄ ebullition and diffusion fluxes, radiocarbon age and production pathway in alpine thermokarst lakes on the Tibetan Plateau.

In (a), the corresponding values of light green and dark green lines represent the ebullition and diffusion CH₄ fluxes across 30 clusters, respectively. Line shows the mean CH₄ flux for the four thermokarst lakes at each cluster. In (b), line indicates the radiocarbon age of surface permafrost below the active layer at each sampling site (n = 24). In (c), the light blue and light orange lines are the apparent carbon fractionation factor (α_C) values of 1.04 and 1.055. The α_C values indicate the pathway of CH₄ production, with α_C > 1.055 suggesting that CH₄ is mainly produced by CO₂ reduction (hydrogenotrophic methanogenesis, HM), and α_C < 1.055 suggesting that CH₄ is produced increasingly by acetate fermentation (acetoclastic methanogenesis, AM). ¹⁴C and δ¹³C isotopic signatures were measured in the bubble gas from only 24 and 29 lakes respectively, due to the limited volume of gas samples that could be collected in the field.

Fig. 5. Methanogenic micoorganisms of thermokarst lakes on the Tibetan Plateau.

Panel (a) respresents the differences in the key functional gene of mcrA among thermokarst lakes located in alpine steppe (AS), alpine meadow (AM), and swamp meadow (SM). The relative abundance of mcrA gene was predicted by contigs with length ≥ 1000 bp. Box plots present the 25th and the 75th quartile (interquartile range), and whiskers indicate the data range among thermokarst lakes located in AS (n = 5), AM (n = 13) and SM (n = 12), respectively. The notches are the medians with 95% confidence intervals. Observed values are shown as black dots. Significant differences are denoted by different letters (one-way ANOVAs with two-sided Tukey’s HSD multiple comparisons, p = 0.038). Panel (b) shows methanogenic taxonomic infromation. The colors in the inner ring represent the different taxa. The triangles in the first ring indicate relative abundance with ≥ 5 per 10,000 (upper triangle) or <5 per 10,000 (lower triangle). The mean relative abundances for all samples are shown in the second ring and pillars, where color depth and height are proportional to the cubic root of relative abundance.