气候变化领域集成服务门户(CCPortal): Soil bacterial and fungal communities and the associated nutrient cycling responses to forest conversion after selective logging in a subtropical forest of China

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DOI	10.1016/j.foreco.2019.04.032
	Soil bacterial and fungal communities and the associated nutrient cycling responses to forest conversion after selective logging in a subtropical forest of China
	Jin X.; Liu Y.; Hu W.; Wang G.; Kong Z.; Wu L.; Ge G.
发表日期	2019
ISSN	0378-1127
起始页码	308
结束页码	317
卷号	444
英文摘要	Forest conversion can affect the diversity and community structure of soil bacteria and fungi. However, little is known about the impact of forest conversion on aboveground-belowground linkages and associated nutrient cycling. To address this research gap, we investigated the aboveground and belowground recovery, the specific responses of bacterial and fungal communities and the associated nutrient cycling in the conversion from artificial Chinese fir forests to broad-leaved conifer-mixed forests at 5-yr-, 10-yr- and 25-yr-old stands after selective logging. Bacterial and fungal community structures were analyzed using high-throughput sequencing of the 16S rRNA and ITS genes. Six microbial enzyme activities involved in the cycling of C, N and P were studied. Our results showed that the aboveground forest structure was recovering towards native evergreen broad-leaved forest after selective logging. The alpha-diversity of fungal community was significantly increased across the chronosequence of logging, but the alpha-diversity of bacterial community was not. Fungal community composition and structure changed during forest conversion, whereas the bacterial community showed slight changes in unique taxa. Neither bacterial nor fungal community structures changed towards the similar pattern as native evergreen broad-leaved forest across 25 years. These results indicated that fungi were more susceptible to forest conversion than bacteria. Furthermore, compared with bacteria, fungi were more strongly affected by soil properties, such as NH4 +-N, pH, AK and TOC. Structural equation modeling indicated that fungi had strong impacts on C-, N- and P-cycling but that bacteria only affected C-cycling. Overall, the fungal community may play a more important role in the aboveground-belowground linkages and C-, N-, and P-cycling compared with the bacterial community during forest conversion. © 2019 Elsevier B.V.
英文关键词	Aboveground vegetation; Bacteria and fungi; Forest conversion; Nutrient cycling; Selective logging
语种	英语
scopus关键词	Bacteria; Enzymes; Forestry; Nutrients; RNA; Soils; Tropics; Community structures; Evergreen broad-leaved forests; Forest conversion; Fungal community compositions; High-throughput sequencing; Nutrient cycling; Selective logging; Structural equation modeling; Fungi; aboveground biomass; bacterium; community structure; forest soil; fungus; nutrient cycling; selective logging; soil microorganism; subtropical region; tropical forest; Bacteria; Conversion; Forests; Fungi; Selective Cutting; Soil; Structures; China; Bacteria (microorganisms); Coniferophyta; Cunninghamia lanceolata; Fungi
来源期刊	Forest Ecology and Management
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/155979
作者单位	School of Life Science, Key Laboratory of Poyang Lake Environment and Resource Utilization, Ministry of Education, Nanchang University, Nanchang, 330022, China; Jiangxi Guanshan National Nature Reserve, Yichun, 336000, China
推荐引用方式 GB/T 7714	Jin X.,Liu Y.,Hu W.,et al. Soil bacterial and fungal communities and the associated nutrient cycling responses to forest conversion after selective logging in a subtropical forest of China[J],2019,444.
APA	Jin X..,Liu Y..,Hu W..,Wang G..,Kong Z..,...&Ge G..(2019).Soil bacterial and fungal communities and the associated nutrient cycling responses to forest conversion after selective logging in a subtropical forest of China.Forest Ecology and Management,444.
MLA	Jin X.,et al."Soil bacterial and fungal communities and the associated nutrient cycling responses to forest conversion after selective logging in a subtropical forest of China".Forest Ecology and Management 444(2019).