Transformation of <i>n</i>-alkanes from plant to soil: a review

烷烃 植被(病理学) 土壤碳 土壤有机质 环境化学 环境科学 化学 土壤水分 土壤科学 有机化学 医学 病理 碳氢化合物
作者
Carrie L. Thomas,Boris Jansen,E. Emiel van Loon,Guido L. B. Wiesenberg
出处
期刊:Soil [Copernicus Publications]
卷期号:7 (2): 785-809 被引量:29
标识
DOI:10.5194/soil-7-785-2021
摘要

Abstract. Despite the importance of soil organic matter (SOM) in the global carbon cycle, there remain many open questions regarding its formation and preservation. The study of individual organic compound classes that make up SOM, such as lipid biomarkers including n-alkanes, can provide insight into the cycling of bulk SOM. While studies of lipid biomarkers, particularly n-alkanes, have increased in number in the past few decades, only a limited number have focused on the transformation of these compounds following deposition in soil archives. We performed a systematic review to consolidate the available information on plant-derived n-alkanes and their transformation from plant to soil. Our major findings were (1) a nearly ubiquitous trend of decreased total concentration of n-alkanes either with time in litterbag experiments or with depth in open plant–soil systems and (2) preferential degradation of odd-chain length and shorter chain length n-alkanes represented by a decrease in either carbon preference index (CPI) or odd-over-even predominance (OEP) with depth, indicating degradation of the n-alkane signal or a shift in vegetation composition over time. The review also highlighted a lack of data transparency and standardization across studies of lipid biomarkers, making analysis and synthesis of published data time-consuming and difficult. We recommend that the community move towards more uniform and systematic reporting of biomarker data. Furthermore, as the number of studies examining the complete leaf–litter–soil continuum is very limited as well as unevenly distributed over geographical regions, climate zones, and soil types, future data collection should focus on underrepresented areas as well as quantifying the transformation of n-alkanes through the complete continuum from plant to soil.

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
longjie发布了新的文献求助10
刚刚
山泽发布了新的文献求助10
2秒前
万能图书馆应助生动早晨采纳,获得10
3秒前
cdercder应助kk采纳,获得10
3秒前
小宇发布了新的文献求助10
4秒前
7秒前
cdercder应助王莹莹采纳,获得10
10秒前
Narionananana完成签到,获得积分10
12秒前
养猪人完成签到,获得积分10
12秒前
12秒前
Jiuqing发布了新的文献求助10
12秒前
12秒前
ruui应助小宇采纳,获得20
14秒前
14秒前
深情安青应助大栗子采纳,获得10
16秒前
大模型应助xuan采纳,获得10
17秒前
18秒前
molihuakai应助LDX采纳,获得10
21秒前
22秒前
卡卡完成签到,获得积分10
23秒前
酱酱C完成签到,获得积分10
24秒前
24秒前
nekoneko发布了新的文献求助10
24秒前
张欢馨应助cindy采纳,获得10
27秒前
27秒前
27秒前
大栗子发布了新的文献求助10
28秒前
拾三发布了新的文献求助10
30秒前
张欢馨应助呆呆的猕猴桃采纳,获得10
30秒前
31秒前
搜集达人应助VVV采纳,获得10
31秒前
Sakura完成签到,获得积分10
32秒前
隆咚锵发布了新的文献求助10
32秒前
33秒前
卡卡完成签到,获得积分10
34秒前
35秒前
37秒前
37秒前
Feng应助科研通管家采纳,获得10
37秒前
NCEPUHIT应助科研通管家采纳,获得10
37秒前
高分求助中
Markov Chain Monte Carlo 10000
(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
Common Foundations of American and East Asian Modernisation: From Alexander Hamilton to Junichero Koizumi 5000
How to Use Machine Learning in Chemistry: An Introduction 1000
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
Discerning Saints: Moralization of Intrinsic Motivation and Selective Prosociality at Work 500
Handbuch Trainingswissenschaft – Trainingslehre 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7583651
求助须知:如何正确求助?哪些是违规求助? 9162345
关于积分的说明 19606805
捐赠科研通 7165660
什么是DOI,文献DOI怎么找? 3266302
关于科研通互助平台的介绍 2431200
邀请新用户注册赠送积分活动 2257779