Dataset Information

Reforestation of Cunninghamia lanceolata changes the relative abundances of important prokaryotic families in soil.

ABSTRACT: Over the past decades, many forests have been converted to monoculture plantations, which might affect the soil microbial communities that are responsible for governing the soil biogeochemical processes. Understanding how reforestation efforts alter soil prokaryotic microbial communities will therefore inform forest management. In this study, the prokaryotic communities were comparatively investigated in a secondary Chinese fir forest (original) and a reforested Chinese fir plantation (reforested from a secondary Chinese fir forest) in Southern China. The results showed that reforestation changed the structure of the prokaryotic community: the relative abundances of important prokaryotic families in soil. This might be caused by the altered soil pH and organic matter content after reforestation. Soil profile layer depth was an important factor as the upper layers had a higher diversity of prokaryotes than the lower ones (p < 0.05). The composition of the prokaryotic community presented a seasonality characteristic. In addition, the results showed that the dominant phylum was Acidobacteria (58.86%) with Koribacteraceae (15.38%) as the dominant family in the secondary Chinese fir forest and the reforested plantation. Furthermore, soil organic matter, total N, hydrolyzable N, and NH4+-N were positively correlated with prokaryotic diversity (p < 0.05). Also, organic matter and NO3--N were positively correlated to prokaryotic abundance (p < 0.05). This study demonstrated that re-forest transformation altered soil properties, which lead to the changes in microbial composition. The changes in microbial community might in turn influence biogeochemical processes and the environmental variables. The study could contribute to forest management and policy-making.

SUBMITTER: Hou XY

PROVIDER: S-EPMC10896735 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature

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Reforestation of <i>Cunninghamia lanceolata</i> changes the relative abundances of important prokaryotic families in soil.

Hou Xue-Yan XY Qiao Wen-Tao WT Gu Ji-Dong JD Liu Chao-Ying CY Hussain Muhammad Mahroz MM Du Dao-Lin DL Zhou Yi Y Wang Yong-Feng YF Li Qian Q

Frontiers in microbiology 20240213

Over the past decades, many forests have been converted to monoculture plantations, which might affect the soil microbial communities that are responsible for governing the soil biogeochemical processes. Understanding how reforestation efforts alter soil prokaryotic microbial communities will therefore inform forest management. In this study, the prokaryotic communities were comparatively investigated in a secondary Chinese fir forest (original) and a reforested Chinese fir plantation (reforeste ...[more]

PMID: 38414777

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Project description:Chinese fir (Cunninghamia lanceolata) is one of southern China's most important native tree species, which has experienced noticeable climate-induced changes. Published papers (1978-2020) on tree growth of Chinese fir forests in China were collected and critically reviewed. After that, a comprehensive growth data set was developed from 482 sites, which are distributed between 102.19° and 130.07°E in longitude, between 21.87° and 37.24°N in latitude and between 5 and 2260 m in altitude. The dataset consists of 2265 entries, including mean DBH (cm), mean H (m), volume (m3), biomass (dry weight) (kg) (stem (over bark) biomass, branches biomass, leaves biomass, bark biomass, aboveground biomass, roots biomass, total trees biomass) and related information, i.e. geographical location (Country, province, study site, longitude, latitude, altitude, slope, and aspect), climate (mean annual precipitation-MAP and mean annual temperature-MAT), stand description (origin, age, canopy density and stand density), and sample regime (plot size, number and investigation year). Our results showed that (1) the best prediction of height was obtained using nonlinear composite model Height = [Formula: see text], (R2 = 0.8715, p < 0.05), (2) the equation Volume = DBH2/(387.8 + 19,190/Height) (R2 = 0.9833, p < 0.05) was observed to be the most suitable model for volume estimation. Meanwhile, when the measurements of the variables are difficult to carry out, the volume model Volume = 0.03957 - 0.01215*DBH + 0.00118*DBH2 (R2 = 0.9573, p < 0.05) is determined from DBH only has a practical advantage, (3) the regression equations of component biomass against DBH explained more significant than 86% variability in almost all biomass data of woody tissues, which were ranked as total trees (97.25%) > aboveground (96.55%) > stems (with bark) (96.17%) > barks (88.95%) > roots (86.71%), and explained greater than 64% variability in branch biomass. The foliage biomass equation was the poorest among biomass components (R2 = 0.6122). The estimation equations derived in this study are particularly suitable for the Chinese fir forests in China. This dataset can provide a theoretical basis for predicting and assessing the potential of carbon sequestration and afforestation activities of Chinese fir forests on a national scale.

Dataset Information

Reforestation of Cunninghamia lanceolata changes the relative abundances of important prokaryotic families in soil.

Publications

Reforestation of <i>Cunninghamia lanceolata</i> changes the relative abundances of important prokaryotic families in soil.

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