The Role of Thermokarst Lake Expansion in Altering the Microbial Community and Methane Cycling in Beiluhe Basin on Tibetan Plateau

Abstract

One of the most significant environmental changes across the Tibetan Plateau (TP) is the rapid lake expansion. The expansion of thermokarst lakes affects the global biogeochemical cycles and local climate regulation by rising levels, expanding area, and increasing water volumes. Meanwhile, microbial activity contributes greatly to the biogeochemical cycle of carbon in the thermokarst lakes, including organic matter decomposition, soil formation, and mineralization. However, the impact of lake expansion on distribution patterns of microbial communities and methane cycling, especially those of water and sediment under ice, remain unknown. This hinders our ability to assess the true impact of lake expansion on ecosystem services and our ability to accurately investigate greenhouse gas emissions and consumption in thermokarst lakes. Here, we explored the patterns of microorganisms and methane cycling by investigating sediment and water samples at an oriented direction of expansion occurred from four points under ice of a mature-developed thermokarst lake on TP. In addition, the methane concentration of each water layer was examined. Microbial diversity and network complexity were different in our shallow points (MS, SH) and deep points (CE, SH). There are differences of microbial community composition among four points, resulting in the decreased relative abundances of dominant phyla, such as Firmicutes in sediment, Proteobacteria in water, Thermoplasmatota in sediment and water, and increased relative abundance of Actinobacteriota with MS and SH points. Microbial community composition involved in methane cycling also shifted, such as increases in USCγ, Methylomonas, and Methylobacter, with higher relative abundance consistent with low dissolved methane concentration in MS and SH points. There was a strong correlation between changes in microbiota characteristics and changes in water and sediment environmental factors. Together, these results show that lake expansion has an important impact on microbial diversity and methane cycling.

Keywords: Tibetan Plateau; co-occurrence network; lake expansion; microbial community; sediment-water; thermokarst lake.

Figure 1

(A) Location of the study site in the continuous permafrost of the TP. The frozen-ground map of the TP was plotted with referring to the study of Zou [48]. (B) Four sampling points: shallow points (MS, SH), deep points (MC, CE). (C) The thermokarst lake in spring.

Figure 2

Bacterial and archaeal diversity of water and sediment at different sampling points. (A) Bacteria Shannon index in different points; (B) Archaea Shannon index in different points; (C) Bacterial CPCoA plot using Bray–Curtis dissimilarity based on OTUs in different points (D) Archaeal diversity CPCoA plot using Bray–Curtis dissimilarity based on OTUs in different points. Four sampling points: SH (SH in water), SH_S (SH in sediment), MS (MS in water), MS_S (MS in sediment), MC (MC in water), MC_S (MC in sediment), CE (CE in water), and CE_S (CE in sediment).

Figure 3

Bacterial and archaeal composition of water and sediment samples from four different sampling points. (A) Sediment bacterial composition at the phylum level; (B) Water bacterial composition at the phylum level; (C) sediment archaeal composition at the phylum level; (D) Water archaeal composition at the phylum level. Four sampling points: SH, MS, MC, and CE.

Figure 4

Microorganisms with significant differences among points, (A) Bacterial phyla in sediment; (B,C) Bacterial phyla in water; (D) Archaeal phyla in sediment; (E,F) Archaeal phyla in water. Statistical significance is denoted by differing letters (p = 0.05). Columns with the same letters are not significantly different. Different letters meant there was significant difference among points (p < 0.05).

Figure 5

Microorganisms involved in methane cycling. (A) Methanogens in sediment at the genus level; (B) Methanogens in water at the genus level; (C) Methanotrophs in sediment at the genus level; (D) Methanotrophs in water at the genus level. Four sampling points: SH, MS, MC, and CE.

Figure 6

Relationship between the dissolved CH₄ concentration and alpha diversity of the functional gene mcrA and pmoA. (A,B) show the relationship between the dissolved CH₄ concentration and alpha diversity of functional gene mcrA in sediment and water. (C,D) show the relationship between the dissolved CH₄ concentration and alpha diversity of functional gene pmoA in sediment and water. Significant correlations are shown with a regression line.

Figure 7

Co-occurrence networks for bacterial and archaeal communities based on pairwise Spearman’s correlations between microbial OTUs water and sediments. The connection edge presents a strong correlation coefficient r > |0.75| and p < 0.05. The modules are shown in different colors. (A) Co-occurrence networks for bacteria in sediment; (B) Co-occurrence networks for bacteria in water; (C) co-occurrence networks for archaea in sediment; (D) co-occurrence networks for archaea in water. (E,F) The numbers of betweenness and closeness of bacteria co-occurrence patterns; (G,H) The numbers of betweenness and closeness of archaea co-occurrence patterns; (I,J) The numbers of nodes and edges of bacteria co-occurrence patterns; (K,L) The numbers of nodes and edges of archaea co-occurrence patterns. Statistical significance is denoted by differing letters (p = 0.05). Columns with the same letters are not significantly different. Different letters meant there was significant difference among points (p < 0.05).