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The community composition variation of Russulaceae associated with the Quercus mongolica forest during the growing season at Wudalianchi City, China

BACKGROUND: Most species of the Russulaceae are ectomycorrhizal (ECM) fungi, which are widely distributed in different types of forest ecology and drive important ecological and economic functions. Little is known about the composition variation of the Russulaceae fungal community aboveground and in...

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Autores principales: Xing, Pengjie, Xu, Yang, Gao, Tingting, Li, Guanlin, Zhou, Jijiang, Xie, Mengle, Ji, Ruiqing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7023826/
https://www.ncbi.nlm.nih.gov/pubmed/32095355
http://dx.doi.org/10.7717/peerj.8527
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author Xing, Pengjie
Xu, Yang
Gao, Tingting
Li, Guanlin
Zhou, Jijiang
Xie, Mengle
Ji, Ruiqing
author_facet Xing, Pengjie
Xu, Yang
Gao, Tingting
Li, Guanlin
Zhou, Jijiang
Xie, Mengle
Ji, Ruiqing
author_sort Xing, Pengjie
collection PubMed
description BACKGROUND: Most species of the Russulaceae are ectomycorrhizal (ECM) fungi, which are widely distributed in different types of forest ecology and drive important ecological and economic functions. Little is known about the composition variation of the Russulaceae fungal community aboveground and in the root and soil during the growing season (June–October) from a Quercus mongolica forest. In this study, we investigated the changes in the composition of the Russulaceae during the growing season of this type of forest in Wudalianchi City, China. METHODS: To achieve this, the Sanger sequencing method was used to identify the Russulaceae aboveground, and the high-throughput sequencing method was used to analyze the species composition of the Russulaceae in the root and soil. Moreover, we used the Pearson correlation analysis, the redundancy analysis and the multivariate linear regression analysis to analyze which factors significantly affected the composition and distribution of the Russulaceae fungal community. RESULTS: A total of 56 species of Russulaceae were detected in the Q. mongolica forest, which included 48 species of Russula, seven species of Lactarius, and one species of Lactifluus. Russula was the dominant group. During the growing season, the sporocarps of Russula appeared earlier than those of Lactarius. The number of species aboveground exhibited a decrease after the increase and were significantly affected by the average monthly air temperature (r = −0.822, p = 0.045), average monthly relative humidity (r = −0.826, p = 0.043), monthly rainfall (r = 0.850, p = 0.032), soil moisture (r = 0.841, p = 0.036) and soil organic matter (r = 0.911, p = 0.012). In the roots and soils under the Q. mongolica forest, the number of species did not show an apparent trend. The number of species from the roots was the largest in September and the lowest in August, while those from the soils were the largest in October and the lowest in June. Both were significantly affected by the average monthly air temperature (r(2) = 0.6083, p = 0.040) and monthly rainfall (r(2) = 0.6354, p = 0.039). Moreover, the relative abundance of Russula and Lactarius in the roots and soils showed a linear correlation with the relative abundance of the other fungal genera.
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spelling pubmed-70238262020-02-24 The community composition variation of Russulaceae associated with the Quercus mongolica forest during the growing season at Wudalianchi City, China Xing, Pengjie Xu, Yang Gao, Tingting Li, Guanlin Zhou, Jijiang Xie, Mengle Ji, Ruiqing PeerJ Agricultural Science BACKGROUND: Most species of the Russulaceae are ectomycorrhizal (ECM) fungi, which are widely distributed in different types of forest ecology and drive important ecological and economic functions. Little is known about the composition variation of the Russulaceae fungal community aboveground and in the root and soil during the growing season (June–October) from a Quercus mongolica forest. In this study, we investigated the changes in the composition of the Russulaceae during the growing season of this type of forest in Wudalianchi City, China. METHODS: To achieve this, the Sanger sequencing method was used to identify the Russulaceae aboveground, and the high-throughput sequencing method was used to analyze the species composition of the Russulaceae in the root and soil. Moreover, we used the Pearson correlation analysis, the redundancy analysis and the multivariate linear regression analysis to analyze which factors significantly affected the composition and distribution of the Russulaceae fungal community. RESULTS: A total of 56 species of Russulaceae were detected in the Q. mongolica forest, which included 48 species of Russula, seven species of Lactarius, and one species of Lactifluus. Russula was the dominant group. During the growing season, the sporocarps of Russula appeared earlier than those of Lactarius. The number of species aboveground exhibited a decrease after the increase and were significantly affected by the average monthly air temperature (r = −0.822, p = 0.045), average monthly relative humidity (r = −0.826, p = 0.043), monthly rainfall (r = 0.850, p = 0.032), soil moisture (r = 0.841, p = 0.036) and soil organic matter (r = 0.911, p = 0.012). In the roots and soils under the Q. mongolica forest, the number of species did not show an apparent trend. The number of species from the roots was the largest in September and the lowest in August, while those from the soils were the largest in October and the lowest in June. Both were significantly affected by the average monthly air temperature (r(2) = 0.6083, p = 0.040) and monthly rainfall (r(2) = 0.6354, p = 0.039). Moreover, the relative abundance of Russula and Lactarius in the roots and soils showed a linear correlation with the relative abundance of the other fungal genera. PeerJ Inc. 2020-02-12 /pmc/articles/PMC7023826/ /pubmed/32095355 http://dx.doi.org/10.7717/peerj.8527 Text en © 2020 Xing et al. https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited.
spellingShingle Agricultural Science
Xing, Pengjie
Xu, Yang
Gao, Tingting
Li, Guanlin
Zhou, Jijiang
Xie, Mengle
Ji, Ruiqing
The community composition variation of Russulaceae associated with the Quercus mongolica forest during the growing season at Wudalianchi City, China
title The community composition variation of Russulaceae associated with the Quercus mongolica forest during the growing season at Wudalianchi City, China
title_full The community composition variation of Russulaceae associated with the Quercus mongolica forest during the growing season at Wudalianchi City, China
title_fullStr The community composition variation of Russulaceae associated with the Quercus mongolica forest during the growing season at Wudalianchi City, China
title_full_unstemmed The community composition variation of Russulaceae associated with the Quercus mongolica forest during the growing season at Wudalianchi City, China
title_short The community composition variation of Russulaceae associated with the Quercus mongolica forest during the growing season at Wudalianchi City, China
title_sort community composition variation of russulaceae associated with the quercus mongolica forest during the growing season at wudalianchi city, china
topic Agricultural Science
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7023826/
https://www.ncbi.nlm.nih.gov/pubmed/32095355
http://dx.doi.org/10.7717/peerj.8527
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