Soil Microbial Adaptation and Biogeochemical Feedback in Degraded Alpine Meadows of the Qinghai-Tibetan Plateau

Abstract

Alpine meadows on the Qinghai-Tibetan Plateau are experiencing rapid degradation due to climate change and anthropogenic disturbances, leading to severe ecological consequences. In this study, we investigated the response of soil microbial communities and their metabolic functions across a degradation gradient using metagenomic sequencing and comprehensive soil physicochemical analysis in the city of Lhasa, China. Results showed that soil pH increased with degradation, while most nutrients, including different forms of nitrogen, phosphorus, and potassium, declined. pH, ammonium nitrogen, and organic matter were identified as key factors driving degradation dynamics. Microbial community composition shifted markedly, with distinct biomarker taxa emerging at different degradation levels. Network analysis revealed a progressive loss of microbial connectivity, with Actinobacteria dominance increasing in heavily degraded soils, while cross-phylum interactions weakened. Functional analysis of biogeochemical cycling genes showed that carbon, nitrogen, and phosphorus cycling were all disrupted by degradation, but each exhibited unique response patterns. These findings will extend our understanding of microbial-mediated soil processes under degradation and provide a scientific foundation for ecosystem management, conservation, and targeted restoration strategies in alpine meadows.

Keywords: alpine meadow degradation; biogeochemical cycling; metagenomic sequencing; microorganism community; soil physicochemical properties.

Figure 1

Vegetation characteristics of alpine meadows at different degradation levels. Different lowercase letters indicate significant differences at p < 0.05. Abbreviations: ND—non-degraded meadow; MD—moderately degraded meadow; HD—heavily degraded meadow. (A) Aboveground biomass; (B) Plant coverage; (C) Plant diversity (Simpson).

Figure 2

Soil physicochemical properties of alpine meadows at different degradation levels. Different lowercase letters indicate significant differences at p < 0.05. Abbreviations: ND—non-degraded meadow; MD—moderately degraded meadow; HD—heavily degraded meadow. (A) pH; (B) Organic matter (OM); (C) Total nitrogen (TN); (D) Total phosphorus (TP); (E) Total potassium (TK); (F) Ammonium nitrogen (NH₄-N); (G) Nitrate nitrogen (NO₃-N); (H) Available phosphorus (AP); (I) Available potassium (AK).

Figure 3

Influence of soil physicochemical properties on aboveground biomass. (A) Variable importance scores for soil physicochemical factors calculated by the random forest model; (B) partial dependence plots showing the relationships between individual soil physicochemical factors and AGB. In panel (B), the blue line represents the partial dependence estimates, the green line depicts a locally weighted polynomial regression trend, and the red shaded area indicates the 95% confidence interval. These partial dependence plots illustrate how changes in soil physicochemical properties affect the aboveground biomass.

Figure 4

Microbial community profiles of alpine meadow soils at different degradation levels. (A) Principal coordinate analysis (PCoA) analysis based on Bray–Curtis distances, with ANOSIM results (R and p values) shown. (B,C) Microbial diversity indices including Shannon and Chao1, where different lowercase letters indicate significant differences at p < 0.05. (D,E) Taxonomic composition at the phylum and genus levels. (F) Key taxa enriched in different degradation levels as identified using LEfSe analysis.

Figure 5

Network analysis of soil microorganisms across alpine meadows at different degradation levels. (A–C) Co-occurrence networks, with nodes representing microbial taxa and edges indicating strong and statistically significant interactions. Node colors correspond to taxonomic groups, and node size indicates the number of connections. (D–F) Zi-Pi plots showing different ecological roles of nodes. Microorganisms are categorized into four groups based on their within-module connectivity (Zi) and among-module connectivity (Pi).

Figure 6

Heatmap depicting the relative distribution of functional genes involved in biogeochemical cycles that differ significantly across degradation levels. Panels (A–C) correspond to genes associated with carbon, nitrogen, and phosphorus cycling, respectively.