Biogeographical distribution of bacterial communities in Changbai Mountain, Northeast China

Abstract

The broad‐leaved and Korean pine mixed forest in Changbai Mountain, China is an important component of boreal forest; the area is sensitive to global climate change. To understand spatial distribution patterns of soil bacterial community along elevation, we analyzed the soil bacterial community diversity and composition along an elevational gradient of 699–1177 m in a primitive Korean pine forest in Changbai Mountain using the high‐throughput sequencing. In total, 149,519 optimized sequences were obtained. Bacterial Shannon index increased along elevation from 699 m to 937 m and started to decrease at the elevation of 1,044 m, showing a humpback curve along elevation. Evenness (ACE index) and richness (Chao index) of the soil bacterial community both decreased with elevation (the highest values of 770 and 762 at 699 m and the lowest values of 548 and 539 at 1,177 m, respectively), all the indices are significantly different between elevations. Bacterial composition at phylum and genus levels had some differences between elevations, but the dominant bacterial populations were generally consistent. Beta‐diversity analysis showed a distance‐decay pattern of bacterial community similarity at different samples. Soil physical and chemical properties explained 70.78% of the variation in bacterial community structure (soil pH explained 19.95%), and elevational distance only explained 8.42%. In conclusion, the contemporary environmental disturbances are the critical factors in maintaining the bacterial spatial distribution compared with historical contingencies.

Microbial community structure and the relationship with soil carbon and nitrogen in an original Korean pine forest of Changbai Mountain, China

“…Han et al [15] and Ping et al [3] concluded that bacterial and fungal communities showed a distance-decay relationship in Korean pine forest of Changbai Mountain. In fact, this conclusion did not quantify the relationship between community similarity and geographical distance.…”

“…We sampled in September 2015. The method of sampling refers to Han et al [15]. All collected soil samples were sealed and refrigerated and then taken back to the laboratory.…”

“…Changes in these factors, and their interaction, will directly, or indirectly, affect the spatial distribution patterns of soil microbial community along an elevational gradient. Our previous studies have found that soil bacterial and fungal community structures obviously varied along different elevation gradients, especially bacteria and fungi of soil showed different response by soil physicochemical properties [3, 15]. However, the distribution patterns of overall microbial taxa in this area still unknown.…”

Soil physicochemical properties drive the variation in soil microbial communities along a forest successional series in a degraded wetland in northeastern China

“…The observed predominance of Basidiomycota and Ascomycota was not out of expectation due to the descriptions for these groups as general inhabitants for wetland and forest soils (Han et al., 2018; Sui, 2017). In addition, Ascomycota was more frequently identified in aquatic group than dryland group, while the Basidiomycota was more frequently identified in dryland group than aquatic group.…”

Analysis of Soil Fungal and Bacterial Communities in Tianchi Volcano Crater, Northeast China

“…In this study, we provided a comprehensive characterization of fungal and bacterial communities along the crater margin of Tianchi Volcano, in Changbai Mountain Nature Reserve, by combing molecular and morphological analyses of culturable microbes, and metabarcoding analyses based on Illumina sequencing. A few previous studies have been conducted on microbial diversity in relatively lower altitudes of Changbai Mountain northern slope, mostly using high-throughput sequencing methods alone [ 14 , 33 , 55 ]. To the best of our knowledge, this study represents the first microbial community analysis in different sides of Tianchi Volcano crater margin, using integrated culture-dependent and metabarcoding approaches.…”