Soil Microbial Community Characteristics and Influencing Factors in Alpine Marsh Wetlands with Different Degradation Levels in Qilian Mountain National Park, Qinghai, China

The microbial community is one of the key indicators for evaluating the health of alpine marsh wetlands, and understanding the composition and health of alpine wetland communities provides a scientific rationale for conservation and restoration efforts. Taking the alpine marsh wetlands in Qilian Mountain National Park, Qinghai Province, as the research object, 27 soil samples (0-30 cm depth) were collected in July 2024 from three types of wetlands: non-degraded (ND), low-level degraded (LD), and heavily degraded (HD). Using high-throughput sequencing, PICRUSt2 functional prediction, nonmetric multidimensional scaling (NMDS), and redundancy analysis (RDA), we analyzed the bacterial community structure and functional characteristics as well as the soil physicochemical properties across different degradation levels and soil depths. Pearson correlation analysis and RDA were used to identify key soil indicators influencing microbial community characteristics. The results showed that (1) compared to ND, the relative abundance of Acidobacteriota increased from 12.3% to 23.7%, and that of Pseudomonadota increased from 28.5% to 35.1% in HD wetlands. Meanwhile, the Shannon index rose from 5.31 in ND to 6.52 in HD, indicating significantly increased microbial community diversity and complexity with wetland degradation (<i>p</i> < 0.05). (2) Vertically, the six major primary metabolic functions gradually weakened with increasing soil depth in all three types of wetlands, the relative abundance of Proteobacteria decreased from 0 to 30 cm, and the α-diversity indices of soil bacteria also declined with depth. (3) Compared to ND, LD and HD showed significantly lower soil moisture content, organic matter, and total organic carbon (<i>p</i> < 0.05), while total potassium and pH increased significantly (<i>p</i> < 0.05). With increasing depth, total nitrogen significantly decreased across all degradation types (<i>p</i> < 0.05). Bacterial diversity, as measured by the Shannon and Simpson indices, showed a significant correlation with several soil properties (moisture, organic matter, total nitrogen, total potassium, cation exchange capacity, and total organic carbon; <i>p</i> < 0.05). Furthermore, pH emerged as a primary environmental driver shaping microbial community structure across different soil depths. These findings offer technical guidance and a theoretical framework for comprehending the degradation and restoration dynamics of alpine marsh wetland ecosystems in the Qilian Mountains.

Authors

Institutions

Publication Details

Journal
Biology
Published
2025-05-24
DOI
https://doi.org/10.3390/biology14060598
Citations
3
Primary Topic
Coastal wetland ecosystem dynamics
Type
article
Field-Weighted Citation Impact
5.15

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Soil Microbial Community Characteristics and Influencing Factors in Alpine Marsh Wetlands with Different Degradation Levels in Qilian Mountain National Park, Qinghai, China

Hongyan Yu, Lele Zhang, Yunfeng Yang, Xufeng Mao et al.
3 citations
Biology
Coastal wetland ecosystem dynamics
5.15
article

Soil Microbial Community Characteristics and Influencing Factors in Alpine Marsh Wetlands with Different Degradation Levels in Qilian Mountain National Park, Qinghai, China

Hongyan Yu, Lele Zhang, Yunfeng Yang, Xufeng Mao, Xianying Wang, Kai Du, Xin Jin, Jintao Zhang, Yanxiang Jin
article en
3 citations

Abstract

The microbial community is one of the key indicators for evaluating the health of alpine marsh wetlands, and understanding the composition and health of alpine wetland communities provides a scientific rationale for conservation and restoration efforts. Taking the alpine marsh wetlands in Qilian Mountain National Park, Qinghai Province, as the research object, 27 soil samples (0-30 cm depth) were collected in July 2024 from three types of wetlands: non-degraded (ND), low-level degraded (LD), and heavily degraded (HD). Using high-throughput sequencing, PICRUSt2 functional prediction, nonmetric multidimensional scaling (NMDS), and redundancy analysis (RDA), we analyzed the bacterial community structure and functional characteristics as well as the soil physicochemical properties across different degradation levels and soil depths. Pearson correlation analysis and RDA were used to identify key soil indicators influencing microbial community characteristics. The results showed that (1) compared to ND, the relative abundance of Acidobacteriota increased from 12.3% to 23.7%, and that of Pseudomonadota increased from 28.5% to 35.1% in HD wetlands. Meanwhile, the Shannon index rose from 5.31 in ND to 6.52 in HD, indicating significantly increased microbial community diversity and complexity with wetland degradation (<i>p</i> < 0.05). (2) Vertically, the six major primary metabolic functions gradually weakened with increasing soil depth in all three types of wetlands, the relative abundance of Proteobacteria decreased from 0 to 30 cm, and the α-diversity indices of soil bacteria also declined with depth. (3) Compared to ND, LD and HD showed significantly lower soil moisture content, organic matter, and total organic carbon (<i>p</i> < 0.05), while total potassium and pH increased significantly (<i>p</i> < 0.05). With increasing depth, total nitrogen significantly decreased across all degradation types (<i>p</i> < 0.05). Bacterial diversity, as measured by the Shannon and Simpson indices, showed a significant correlation with several soil properties (moisture, organic matter, total nitrogen, total potassium, cation exchange capacity, and total organic carbon; <i>p</i> < 0.05). Furthermore, pH emerged as a primary environmental driver shaping microbial community structure across different soil depths. These findings offer technical guidance and a theoretical framework for comprehending the degradation and restoration dynamics of alpine marsh wetland ecosystems in the Qilian Mountains.

BiologyVol. 14(6)
Qinghai Normal University (CN)
National Natural Science Foundation of China, Natural Science Foundation of Qinghai
Life in Land
Openalex Percentile: Top 5%
Coastal wetland ecosystem dynamics
5.15
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.