pH is the major predictor of soil microbial network complexity in Chinese forests along a latitudinal gradient

横断面 土壤水分 生态学 生态系统 环境科学 利基 群落结构 生态位 土壤pH值 生态位分化 微生物种群生物学 物种丰富度 生物 栖息地 遗传学 细菌
作者
Dorsaf Kerfahi,Yaping Guo,Ke Dong,Qingkui Wang,Jonathan M. Adams
出处
期刊:Catena [Elsevier]
卷期号:234: 107595-107595 被引量:27
标识
DOI:10.1016/j.catena.2023.107595
摘要

Patterns in the network structure of microbial communities may give indications of their degree of interaction and interdependence, and their resilience to environmental disturbance. Geographical differences in network patterns of forest communities may reflect broad-scale differences in ecosystem structure and responses to environmental change. We analyzed a large dataset of 144 samples of soil bacterial and fungal communities characterized by 16S and ITS amplicon sequencing from forests in eastern China, along a 4,100 km latitudinal transect. This showed that fungal-bacterial network complexity was most closely related to soil pH. Results showed that pH was the strongest predictor of variation in community network structure across the forest soils of eastern China. Lower network complexity and stability were found around neutral pH, which was the strongest environmental predictor. This may be due to the optimal conditions that neutral soils provide for microorganism survival, reducing the necessity for physiological interdependence, consequently leading to fewer positive connections. Additionally, neutral soils provide more generalized niches, resulting in less specific niche exclusion, showing up as fewer negative connections. Unlike the trend for overall connectivity, the richness and relative abundances of keystone taxa were significantly and negatively correlated with pH. Overall, both connectivity and numbers of keystones were consistent in suggesting that network complexity was greatest overall at acidic pH. It appears that at the broad scale studied here, pH plays a more significant role in shaping microbial community integration than such factors as ecosystem productivity or climate.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
PDF的下载单位、IP信息已删除 (2025-6-4)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
ommmw完成签到,获得积分10
刚刚
jmjm发布了新的文献求助10
刚刚
周冯雪完成签到 ,获得积分10
1秒前
愿好完成签到,获得积分10
1秒前
5秒前
CC完成签到,获得积分10
5秒前
天涯明月刀完成签到,获得积分10
5秒前
研友_LMpo68完成签到 ,获得积分0
7秒前
包容若风完成签到,获得积分10
7秒前
SciGPT应助chenzhi采纳,获得10
7秒前
KingYugene完成签到,获得积分10
8秒前
大葡萄发布了新的文献求助10
8秒前
浮浮世世发布了新的文献求助10
8秒前
guohuameike完成签到,获得积分10
8秒前
叶燕完成签到 ,获得积分10
8秒前
9秒前
Lucas应助科研通管家采纳,获得10
11秒前
cdercder应助科研通管家采纳,获得10
11秒前
彭于晏应助科研通管家采纳,获得10
11秒前
cdercder应助科研通管家采纳,获得10
11秒前
华仔应助科研通管家采纳,获得10
11秒前
量子星尘发布了新的文献求助10
11秒前
11秒前
强砸完成签到,获得积分10
12秒前
13秒前
yyds应助大葡萄采纳,获得200
16秒前
17秒前
gaowei完成签到,获得积分10
18秒前
18秒前
18秒前
20秒前
Buster完成签到,获得积分10
20秒前
领导范儿应助且歌且行采纳,获得10
21秒前
21秒前
xiao发布了新的文献求助10
22秒前
jmjm完成签到,获得积分10
23秒前
Buster发布了新的文献求助10
23秒前
李若诗完成签到,获得积分10
23秒前
胡萝卜完成签到 ,获得积分10
23秒前
Eureka发布了新的文献求助10
23秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
The Social Work Ethics Casebook: Cases and Commentary (revised 2nd ed.).. Frederic G. Reamer 1070
Introduction to Early Childhood Education 1000
2025-2031年中国兽用抗生素行业发展深度调研与未来趋势报告 1000
List of 1,091 Public Pension Profiles by Region 871
Alloy Phase Diagrams 500
A Guide to Genetic Counseling, 3rd Edition 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 生物化学 物理 纳米技术 计算机科学 内科学 化学工程 复合材料 物理化学 基因 遗传学 催化作用 冶金 量子力学 光电子学
热门帖子
关注 科研通微信公众号,转发送积分 5419479
求助须知:如何正确求助?哪些是违规求助? 4534726
关于积分的说明 14146477
捐赠科研通 4451326
什么是DOI,文献DOI怎么找? 2441717
邀请新用户注册赠送积分活动 1433274
关于科研通互助平台的介绍 1410587