Selective logging enhances ecosystem multifunctionality via increase of functional diversity in a Pinus yunnanensis forest in Southwest China

Abstract Background The impacts of selective logging on ecosystem multifunctionality (EMF) remain largely unexplored. In this study, we analyzed the response of nine variables related to four ecosystem functions (i.e. nutrient cycling, soil carbon stocks, decomposition, and wood production) to five...

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Published in:Forest Ecosystems
Main Authors: Xiaobo Huang, Shuaifeng Li, Jianrong Su
Format: Article
Language:English
Published: KeAi Communications Co., Ltd. 2020-09-01
Subjects:
Online Access:http://link.springer.com/article/10.1186/s40663-020-00267-8
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author Xiaobo Huang
Shuaifeng Li
Jianrong Su
author_facet Xiaobo Huang
Shuaifeng Li
Jianrong Su
author_sort Xiaobo Huang
collection DOAJ
container_title Forest Ecosystems
description Abstract Background The impacts of selective logging on ecosystem multifunctionality (EMF) remain largely unexplored. In this study, we analyzed the response of nine variables related to four ecosystem functions (i.e. nutrient cycling, soil carbon stocks, decomposition, and wood production) to five selective logging intensities in a Pinus yunnanensis-dominated forest. We included a control group with no harvest to evaluate the potential shifts in EMF of the P. yunnanensis forests. We also assessed the relationship between above- and belowground biodiversity and EMF under these different selective logging intensities. Additionally, we evaluated the effects of biotic and abiotic factors on EMF using a structural equation modeling (SEM) approach. Results Individual ecosystem functions (EFs) all had a significant positive correlation with selective logging intensity. Different EFs showed different patterns with the increase of selective logging intensity. We found that EMF tended to increase with logging intensity, and that EMF significantly improved when the stand was harvested at least twice. Both functional diversity and soil moisture had a significant positive correlation with EMF, but soil fungal operational taxonomic units (OTUs) had a significant negative correlation with EMF. Based on SEM, we found that selective logging improved EMF mainly by increasing functional diversity. Conclusion Our study demonstrates that selective logging is a good management technique from an EMF perspective, and thus provide us with potential guidelines to improve forest management in P. yunnanensis forests in this region. The functional diversity is maximized through reasonable selective logging measures, so as to enhance EMF.
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spelling doaj-art-df7cd3da60a245ef8a633db7459bde4a2025-08-19T19:23:53ZengKeAi Communications Co., Ltd.Forest Ecosystems2197-56202020-09-017111310.1186/s40663-020-00267-8Selective logging enhances ecosystem multifunctionality via increase of functional diversity in a Pinus yunnanensis forest in Southwest ChinaXiaobo Huang0Shuaifeng Li1Jianrong Su2Research Institute of Resources Insects, Chinese Academy of ForestryResearch Institute of Resources Insects, Chinese Academy of ForestryResearch Institute of Resources Insects, Chinese Academy of ForestryAbstract Background The impacts of selective logging on ecosystem multifunctionality (EMF) remain largely unexplored. In this study, we analyzed the response of nine variables related to four ecosystem functions (i.e. nutrient cycling, soil carbon stocks, decomposition, and wood production) to five selective logging intensities in a Pinus yunnanensis-dominated forest. We included a control group with no harvest to evaluate the potential shifts in EMF of the P. yunnanensis forests. We also assessed the relationship between above- and belowground biodiversity and EMF under these different selective logging intensities. Additionally, we evaluated the effects of biotic and abiotic factors on EMF using a structural equation modeling (SEM) approach. Results Individual ecosystem functions (EFs) all had a significant positive correlation with selective logging intensity. Different EFs showed different patterns with the increase of selective logging intensity. We found that EMF tended to increase with logging intensity, and that EMF significantly improved when the stand was harvested at least twice. Both functional diversity and soil moisture had a significant positive correlation with EMF, but soil fungal operational taxonomic units (OTUs) had a significant negative correlation with EMF. Based on SEM, we found that selective logging improved EMF mainly by increasing functional diversity. Conclusion Our study demonstrates that selective logging is a good management technique from an EMF perspective, and thus provide us with potential guidelines to improve forest management in P. yunnanensis forests in this region. The functional diversity is maximized through reasonable selective logging measures, so as to enhance EMF.http://link.springer.com/article/10.1186/s40663-020-00267-8BiodiversityEcosystem multifunctionalityFunctional traitsPinus yunnanensisSoil enzymatic activityStructural equation modeling
spellingShingle Xiaobo Huang
Shuaifeng Li
Jianrong Su
Selective logging enhances ecosystem multifunctionality via increase of functional diversity in a Pinus yunnanensis forest in Southwest China
Biodiversity
Ecosystem multifunctionality
Functional traits
Pinus yunnanensis
Soil enzymatic activity
Structural equation modeling
title Selective logging enhances ecosystem multifunctionality via increase of functional diversity in a Pinus yunnanensis forest in Southwest China
title_full Selective logging enhances ecosystem multifunctionality via increase of functional diversity in a Pinus yunnanensis forest in Southwest China
title_fullStr Selective logging enhances ecosystem multifunctionality via increase of functional diversity in a Pinus yunnanensis forest in Southwest China
title_full_unstemmed Selective logging enhances ecosystem multifunctionality via increase of functional diversity in a Pinus yunnanensis forest in Southwest China
title_short Selective logging enhances ecosystem multifunctionality via increase of functional diversity in a Pinus yunnanensis forest in Southwest China
title_sort selective logging enhances ecosystem multifunctionality via increase of functional diversity in a pinus yunnanensis forest in southwest china
topic Biodiversity
Ecosystem multifunctionality
Functional traits
Pinus yunnanensis
Soil enzymatic activity
Structural equation modeling
url http://link.springer.com/article/10.1186/s40663-020-00267-8
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AT shuaifengli selectiveloggingenhancesecosystemmultifunctionalityviaincreaseoffunctionaldiversityinapinusyunnanensisforestinsouthwestchina
AT jianrongsu selectiveloggingenhancesecosystemmultifunctionalityviaincreaseoffunctionaldiversityinapinusyunnanensisforestinsouthwestchina