Links between chemical composition of soil organic matter and soil enzyme activity in alpine grassland ecosystems of the Tibetan Plateau

土壤有机质 化学 营养循环 自行车 有机质 转化酶 草原 生态系统 土壤碳 作文(语言) 纤维素酶 环境化学 土壤水分 营养物 农学 生态学 生物化学 有机化学 生物 林业 哲学 地理 语言学
作者
Ziwei Wang,Shuqin Ma,Yang Hu,Youchao Chen,Hongmao Jiang,Baoli Duan,Xuyang Lu
出处
期刊:Catena [Elsevier]
卷期号:218: 106565-106565 被引量:39
标识
DOI:10.1016/j.catena.2022.106565
摘要

• N-compounds, polysaccharides and fatty acids dominated Tibetan SOM. • SOM significantly influence the activity of invertase and cellulase. • Gram positive and negative bacteria contribute the most to the SOM-enzyme-env system in env factors. • Chemical composition of SOM was evident using Py-GC/MS. Soil enzymes play a key role in soil organic matter dynamics in terrestrial ecosystems; however, the relationship between soil enzyme activity and the chemical composition of soil organic matter remains unclear. We analysed the soil organic matter (SOM) of five types of alpine grassland ecosystems in the Tibetan Plateau at the molecular level using pyrolysis gas chromatography/mass spectrometry (Py-GC/MS), which allowed us to examine the relationship between the patterns of enzyme activities and SOM composition. We found that the level of activity of carbon (C)-cycling enzymes (invertase, β-1,4-glucosidase, polyphenol oxidase, and peroxidase), nitrogen (N)-cycling enzymes (arylamidase), and phosphorus (P)-cycling enzyme (alkaline phosphatase) was significantly different among the five grassland ecosystems. In addition, we found significant variation among the different grassland ecosystems in terms of the activity of enzymes involved in C-cycling less so with those enzymes involved in N-cycling. In general, SOM was dominated by N-compounds (∼32.47–51.76%), polysaccharides (∼10.67–20.42%), and fatty acids (∼7.03–20.33%) in the different alpine grasslands. The most abundant compounds in SOM were D-alanine (10.06–20.77%), 9-octadecenamide, (Z) (4.43–9.68%), and 13-docosenamide (1.52–14.76%). Correlation analysis showed that the N-compound abundance was negatively correlated with nitrate reductase. Polysaccharides were positively correlated with activity levels of invertase and cellulase. Fatty acids were positively correlated with polyphenol oxidase activity and negatively correlated with alkaline phosphatase activity. Some abundant compounds consistently showed strong correlations with activity levels of invertase and cellulase, including toluene, styrene, benzene, phenol, furfural, pyrrole, p-cresol, 2-methylphenylacetylene and indole (positive correlation), 13-docosenamide, dodecanamide and o-hydroxybiphenyl (negative correlation). Furthermore, Gram-positive and Gram-negative bacteria also play a significant role in regulating SOM-enzyme interactions. These findings confirmed the strong effects of SOM composition on the activity of invertase and cellulase, indicating that invertase and cellulase play an important role in regulating SOM to some extent, resulting in complex interactions among organic-enzyme-microbes.
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
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
科研通AI6.2应助zw0907采纳,获得10
1秒前
hyyy关注了科研通微信公众号
1秒前
1秒前
1秒前
2秒前
2秒前
2秒前
2秒前
2秒前
ardejiang发布了新的文献求助10
2秒前
fupaiyunyan发布了新的文献求助50
2秒前
3秒前
科研通AI6.1应助勇敢小羊采纳,获得10
3秒前
3秒前
4秒前
4秒前
4秒前
4秒前
李爱国应助坚强血茗采纳,获得10
4秒前
1733完成签到,获得积分20
4秒前
lfzw完成签到,获得积分10
5秒前
FashionBoy应助兰兰不懒采纳,获得10
5秒前
面包战士发布了新的文献求助10
5秒前
友好广缘完成签到,获得积分10
6秒前
6秒前
李萍发布了新的文献求助10
6秒前
6秒前
nqq发布了新的文献求助10
6秒前
火星访冬完成签到,获得积分10
6秒前
绝迹天明发布了新的文献求助10
7秒前
jiaminghao完成签到,获得积分10
7秒前
背后访风完成签到 ,获得积分10
7秒前
7秒前
Maroon5发布了新的文献求助10
7秒前
7秒前
yy关闭了yy文献求助
8秒前
lihuahui发布了新的文献求助50
8秒前
cc发布了新的文献求助10
8秒前
9秒前
amanda应助沉静的梦玉采纳,获得20
9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
Kinesiophobia : a new view of chronic pain behavior 3000
Les Mantodea de guyane 2500
Molecular Biology of Cancer: Mechanisms, Targets, and Therapeutics 2000
What is the Future of Psychotherapy in a Digital Age? 700
The Psychological Quest for Meaning 600
Zeolites: From Fundamentals to Emerging Applications 600
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 计算机科学 有机化学 物理 生物化学 纳米技术 复合材料 内科学 化学工程 人工智能 催化作用 遗传学 数学 基因 量子力学 物理化学
热门帖子
关注 科研通微信公众号,转发送积分 5955172
求助须知:如何正确求助?哪些是违规求助? 7165292
关于积分的说明 15937270
捐赠科研通 5090001
什么是DOI,文献DOI怎么找? 2735504
邀请新用户注册赠送积分活动 1696337
关于科研通互助平台的介绍 1617268