Grazing exclusion alters soil methane flux and methanotrophic and methanogenic communities in alpine meadows on the Qinghai-Tibet Plateau

Abstract

Grazing exclusion (GE) is an effective measure for restoring degraded grassland ecosystems. However, the effect of GE on methane (CH₄) uptake and production remains unclear in dominant bacterial taxa, main metabolic pathways, and drivers of these pathways. This study aimed to determine CH₄ flux in alpine meadow soil using the chamber method. The in situ composition of soil aerobic CH₄-oxidizing bacteria (MOB) and CH₄-producing archaea (MPA) as well as the relative abundance of their functional genes were analyzed in grazed and nongrazed (6 years) alpine meadows using metagenomic methods. The results revealed that CH₄ fluxes in grazed and nongrazed plots were -34.10 and -22.82 μg‧m^-2‧h^-1, respectively. Overall, 23 and 10 species of Types I and II MOB were identified, respectively. Type II MOB comprised the dominant bacteria involved in CH₄ uptake, with Methylocystis constituting the dominant taxa. With regard to MPA, 12 species were identified in grazed meadows and 3 in nongrazed meadows, with Methanobrevibacter constituting the dominant taxa. GE decreased the diversity of MPA but increased the relative abundance of dominated species Methanobrevibacter millerae from 1.47 to 4.69%. The proportions of type I MOB, type II MOB, and MPA that were considerably affected by vegetation and soil factors were 68.42, 21.05, and 10.53%, respectively. Furthermore, the structural equation models revealed that soil factors (available phosphorus, bulk density, and moisture) significantly affected CH₄ flux more than vegetation factors (grass species number, grass aboveground biomass, grass root biomass, and litter biomass). CH₄ flux was mainly regulated by serine and acetate pathways. The serine pathway was driven by soil factors (0.84, p < 0.001), whereas the acetate pathway was mainly driven by vegetation (-0.39, p < 0.05) and soil factors (0.25, p < 0.05). In conclusion, our findings revealed that alpine meadow soil is a CH₄ sink. However, GE reduces the CH₄ sink potential by altering vegetation structure and soil properties, especially soil physical properties.

Keywords: alpine meadow; grazing management; greenhouse gas; methane flux; methane sink; methane-oxidizing bacteria.

Figure 1

Experimental design and steps. Grazed and nongrazed plots were established in alpine meadows on the eastern Qinghai-Tibet Plateau in May 2014 (A), with six replicates in grazed and nongrazed plots (B). (C) Shows the sampling diagram of vegetation survey and soil sampling in August 2020, and blue dots indicate sampling points. (D) Shows the vegetation landscape of grazed and nongrazed plots. (E) Shows the experimental steps, soil was collected at a depth of 0–10 cm at each sampling point (five collections) and mixed into one sample. The pooled soil samples were divided into four parts using the tetrad method: One part was used to measure moisture, one part was cryopreserved (−80°C) for DNA extraction and sequencing, one part was used to determine total nutrient content, and one part was used to determine available nutrient content. Further details are provided in the main text.

Figure 2

Plant community composition at the family level and its importance values at the experimental site. (A) Grass species number at the family level. (B) Response of the importance values of the plant functional group to GE. **p < 0.01.

Figure 3

Response of microbial communities associated with CH₄ metabolism to GE. (A) Relative abundance of type I MOB, type II MOB, and MPA at the species level (six repetitions). (B) Effect of GE on the relative abundance of type I MOB, type II MOB, and MPA. (C) A ternary diagram illustrating the compositions of type I MOB, type II MOB, and MPA. The size of the bubbles indicates the sum of the relative abundance of type I MOB, type II MOB, and MPA taxa. (D) Microbial biomarkers for CH₄ metabolism at different taxonomic levels according to the linear discriminant analysis (LDA) effect size method (LDA score of >2). Uppercase letters indicate biomarkers, whereas lowercase letters indicate microbial taxa at different levels: c, class; o, order; f, family; g, genus; s, species. (E) Co-occurrence networks of soil microbial species. Visualization of the connectivity in type I MOB, type II MOB, and MPA taxa. Nodes indicate individual microbial species, and edges represent significant Spearman correlations (ρ > 0.7; p < 0.05). The size of the nodes indicates the relative abundance of species. Dark cyan edges indicate positive correlations, and light cyan edges indicate negative correlations. *p < 0.05, **p < 0.01.

Figure 4

Response of the relative abundance of functional genes related to CH₄ uptake (A) and production (B) to GE in GPs and NPs (six repetitions). (C) Relative abundance of genes involved in the different pathways of CH₄ uptake and production. (D) Biomarker genes for CH₄ metabolism according to the linear discriminant analysis effect size method (LDA score of >2). *p < 0.05, **p < 0.01, ***p < 0.001.

Figure 5

Redundancy analysis of vegetation features, soil properties, and CH₄ metabolism-related taxa at the genus (A) and species (B) levels; type I MOB, type II MOB, and MPA (C); CH₄ uptake and production pathways (D); and functional genes (E). Red dots represent the top five genera in (A), species in (B), and functional genes in (D) in terms of relative abundance. The size of the points reflects the relative abundance. GSN, grass species number; GAB, grass aboveground biomass; GRB, grass root biomass; LB, litter biomass; SBD, soil bulk density; SAs, soil aggregates; ST, soil temperature; SM, soil moisture; SOM, soil organic matter; AN, available nitrogen; AP, available phosphorus; AK, available potassium; TN, total nitrogen; TP, total phosphorus; TK, total potassium. The same as below.

Figure 6

Correlation analysis including MOB and MPA at the species level and environmental factors. Red indicates a positive relationship and blue indicates a negative relationship. Features with no significant correlation were removed. *p < 0.05, **p < 0.01, ***p < 0.001.

Figure 7

Response of CH₄ flux to vegetation and soil factors. GE affects CH₄ flux by altering different soil microbial taxa (A) and pathways (B). The solid line indicates a significant level (p < 0.05), whereas the dotted line indicates a nonsignificant level. The size of the line indicates the value of the influence coefficient. *p < 0.05, **p < 0.01, ***p < 0.001. The line with an arrow indicates that the response of the indicator to grazing is increasing or decreasing in (B). Global goodness of fit: Fisher’s C = 5.02, p = 0.081, AIC = 33.02, BIC = 72.05 in (A); Fisher’s C = 11.37, p = 0.078, AIC = 49.37, BIC = 102.33 in (B).