摘要
土壤微生物生物地理学是研究土壤中微生物空间分布格局及其随时间变化的一门科学,是土壤微生物学和微生物生态学等领域的研究前沿。近年来,尽管土壤微生物生物地理学研究取得了巨大进展,目前仍面临诸多难题与挑战。本文简要回顾了土壤微生物生物地理学的发展历程,重点介绍近年来我国在森林、草地和农田生态系统中土壤微生物生物地理学研究的主要进展。同时进一步阐述了目前土壤微生物生物地理学研究的国际前沿方向,包括微生物群落空间分布及其驱动机制、群落构建过程与共存网络、微生物地理分布与生态系统功能的关联以及预测微生物群落对全球变化的响应。最后,对土壤微生物生物地理学未来的研究方向进行了展望,强调了清晰的微生物物种定义、微生物群落的时间动态、多组学与合成生物学技术以及高精度的预测模型在土壤微生物生物地理学研究中的重要性。
Soil microbial biogeography is a discipline that aims to study the spatial distribution pattern of soil microbial community and their changes across time,and is research frontiers in the fields of soil biology and microbial ecology.In recent years,despite the tremendous progress in the study of soil microbial biogeography,there are still many difficulties and challenges.This mini-review will briefly review the development of soil microbial biogeography and emphatically introduce the recent progresses of soil microbial biogeography in forest,grassland and farmland ecosystems in China.This mini-review further elaborates the current international frontiers of soil microbial biogeography,including the spatial distribution of microbial communities and their driving mechanisms,community assembly processes and co-occurrence network,the relationship between microbial geographic distribution and ecosystem functions,and the prediction of microbial community under global change scenarios.Finally,this mini-review outlooks the future developments in the study of soil microbial biogeography,and emphasizes the importance of clear microbial species definitions,temporal dynamics of microbial communities,multiomics approaches and synthetic biology,and the prediction modelling with high accuracy in the study of soil microbial biogeography.
作者
褚海燕
冯毛毛
柳旭
时玉
杨腾
高贵锋
CHU Haiyan;FENG Maomao;LIU Xu;SHI Yu;YANG Teng;GAO Guifeng(Institute of Soil Science,Chinese Academy of Sciences,Nanjing 210008,China)
出处
《土壤学报》
CAS
CSCD
北大核心
2020年第3期515-529,共15页
Acta Pedologica Sinica
基金
中国科学院战略性先导科技专项(B类)(XDB15010101)资助。
关键词
土壤微生物分布
驱动机制
群落构建过程
共存网络
微生物预测
Soil microbial distribution
Driving mechanisms
Community assembly processes
Co-Occurrence network
Microbial prediction
