Responses of soil multifunctionality, microbial diversity, and network complexity to tree species mixing in Eucalyptus plantations

Mixed afforestation has the potential to enhance soil biodiversity and sustain multiple ecosystem functions (i.e., multifunctionality). Microbial diversity is essential in supporting soil multifunctionality (SMF) in forest ecosystems. However, the patterns and drivers of SMF and the role of microbial communities in regulating SMF among different stand types remain virtually unknown. Here, an 11-year field experiment was conducted to evaluate the effects of mixtures consisting of either one N 2 -fixing or one non-N 2 -fixing tree species on SMF and microbial community across Eucalyptus stands. Mixtures with either N 2 -fixing (0.54) or non-N 2 -fixing species (0.21) presented higher SMF values than did the pure stand (−0.75). Bacterial alpha diversity and network complexity significantly increased with tree species mixing. Compared with other stand types, mixing of N 2 -fixing species presented greater fungal alpha diversity. Microbial alpha and beta diversity, Proteobacteria, and network complexity were strongly and positively linked with SMF, whereas Chloroflexi was highly negatively related to SMF. Random forest modeling indicated that Chloroflexi, network complexity, and bacterial beta diversity were the primary predictors of SMF. Variance partitioning analysis verified that microbial diversity was a major contributor to SMF, accounting for 31 % of the variance. Piecewise structural equation modeling further revealed that linkages between soil properties, microbiome, and SMF were strongly affected by forest type. Additionally, microbial diversity indirectly and positively impacted SMF by promoting network complexity. Altogether, these findings indicated that mixed afforestation positively affected SMF by facilitating microbial diversity and network complexity. Hence, this research highlights the positive ecological implications of tree species mixing as well as the importance of microbial network complexity and diversity in maintaining SMF, helping to elucidate the mechanism of microbially driven SMF to maximize the potential of SMF in plantation ecosystems and providing mixed species candidates for optimizing afforestation strategies. • Soil multifunctionality is greater in mixed forests than in pure forests. • Shifts in soil and microbiome induced by forest type impact soil multifunctionality. • Microbial diversity predicts soil multifunctionality better than network complexity. • Microbial diversity–soil multifunctionality links are governed by network complexity.

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Publication Details

Journal
Industrial Crops and Products
Published
2025-01-22
DOI
https://doi.org/10.1016/j.indcrop.2025.120575
Citations
8
Primary Topic
Ecology and Vegetation Dynamics Studies
Type
article
Field-Weighted Citation Impact
18.51

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article

Responses of soil multifunctionality, microbial diversity, and network complexity to tree species mixing in Eucalyptus plantations

Shaoming Ye, Kaixiang Li, Han Zhang, Yaqin He et al.
8 citations
Industrial Crops and Products
Ecology and Vegetation Dynamics Studies
18.51
article

Responses of soil multifunctionality, microbial diversity, and network complexity to tree species mixing in Eucalyptus plantations

Shaoming Ye, Kaixiang Li, Han Zhang, Yaqin He, Yuanguang Wen, Hao Wu, Fei He, Rongyuan Fan
article en
8 citations

Abstract

Mixed afforestation has the potential to enhance soil biodiversity and sustain multiple ecosystem functions (i.e., multifunctionality). Microbial diversity is essential in supporting soil multifunctionality (SMF) in forest ecosystems. However, the patterns and drivers of SMF and the role of microbial communities in regulating SMF among different stand types remain virtually unknown. Here, an 11-year field experiment was conducted to evaluate the effects of mixtures consisting of either one N 2 -fixing or one non-N 2 -fixing tree species on SMF and microbial community across Eucalyptus stands. Mixtures with either N 2 -fixing (0.54) or non-N 2 -fixing species (0.21) presented higher SMF values than did the pure stand (−0.75). Bacterial alpha diversity and network complexity significantly increased with tree species mixing. Compared with other stand types, mixing of N 2 -fixing species presented greater fungal alpha diversity. Microbial alpha and beta diversity, Proteobacteria, and network complexity were strongly and positively linked with SMF, whereas Chloroflexi was highly negatively related to SMF. Random forest modeling indicated that Chloroflexi, network complexity, and bacterial beta diversity were the primary predictors of SMF. Variance partitioning analysis verified that microbial diversity was a major contributor to SMF, accounting for 31 % of the variance. Piecewise structural equation modeling further revealed that linkages between soil properties, microbiome, and SMF were strongly affected by forest type. Additionally, microbial diversity indirectly and positively impacted SMF by promoting network complexity. Altogether, these findings indicated that mixed afforestation positively affected SMF by facilitating microbial diversity and network complexity. Hence, this research highlights the positive ecological implications of tree species mixing as well as the importance of microbial network complexity and diversity in maintaining SMF, helping to elucidate the mechanism of microbially driven SMF to maximize the potential of SMF in plantation ecosystems and providing mixed species candidates for optimizing afforestation strategies. • Soil multifunctionality is greater in mixed forests than in pure forests. • Shifts in soil and microbiome induced by forest type impact soil multifunctionality. • Microbial diversity predicts soil multifunctionality better than network complexity. • Microbial diversity–soil multifunctionality links are governed by network complexity.

Industrial Crops and ProductsVol. 225
Guangxi University (CN), Forestry Research Institute (UZ), Guangxi Academy of Sciences (CN)
National Natural Science Foundation of China
Life in Land
Openalex Percentile: Top 1%
Ecology and Vegetation Dynamics Studies
18.51
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