Abstract:

Soil microbial diversity has not been extensively observed due to technique limitations. With the development of the high-throughput sequencing technique and bioinformatics, much progress has been made in observations of microbial diversity. Currently, international microbiome initiatives have been founded (including the Earth Microbial Project). However, problems in these projects include a lack of dynamic observations, differences in observational methods, and data integration. The soil microbial observation network (SMON) is an important part of the Chinese Biodiversity Monitoring and Research Network (Sino BON). The observational network initially selected field observation sites in forest ecosystems along a temperature and precipitation gradient from south to north, in grassland ecosystems along a precipitation transect from east to west, and in typical wetland and agricultural ecosystems in China. Field ecological observation stations have been established in these selected ecosystems. Key tasks for the SMON are to observe spatial and temporal dynamics of soil microbial communities and functional genes in various ecosystems, including bacteria, archaea, fungi, and lichens. Observational data will be published periodically in the format of database, annals, and illustrated handbooks. Key methods used in the SMON are high- throughput sequencing, metagenomics, and bioinformatics. A soil biota database is currently being constructed to store observational data for public inquiry and analysis. Through the efforts of SMON, we plan to explore the driving mechanisms of spatial and temporal variations of soil microbial communities and their functional genes, and understand the relationships between microbial diversity and ecosystem function, in order to predict microbial dynamics under global environmental change scenarios, and to design strategies to protect soil microbial diversity and properly utilize microbial resources.

Key words: soil microbial community, diversity, monitoring network, metagenomics, ecosystem function