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. 2023 Apr 3;5(4):1614-1621.
doi: 10.1016/j.fmre.2023.03.002. eCollection 2025 Jul.

Fauna-microbe diversity coupling lost in agricultural soils: Implications from the bacteria hidden in earthworm gut

Affiliations

Fauna-microbe diversity coupling lost in agricultural soils: Implications from the bacteria hidden in earthworm gut

Xin Gong et al. Fundam Res. .

Abstract

Earthworms are critical for supporting soil health and microbial diversity and simultaneously maintaining a highly diverse gut microbiome. The earthworm is predominantly vulnerable to physical disturbance, yet how changes in earthworm diversity influence the richness and ecological network of soil-gut microbiomes in response to anthropogenic disturbance is virtually unknown. Here, we investigated the richness of earthworms, and their connection with the diversity of the soil-gut microbiome using a large-scale survey covering paired agricultural and natural sites. Our results showed that earthworm diversity was positively correlated with soil and gut bacterial diversity across sites. However, the connection between soil bacterial and earthworm diversity is lost in agricultural ecosystems. We further show that earthworm richness supported greater modularity in microbial networks, being both positively correlated with the richness of earthworm gut bacteria in both land-use types. Together, we provided the first empirical evidence that agricultural practices can break the fundamental links between soil bacterial and earthworm diversity, and further identify an unreported consistent connection between the diversity of earthworms and the modularity of microbial networks in natural and managed ecosystems. These findings emphasize the primary roles of earthworms in supporting soil biodiversity and point to the wider contributions of the soil animal-microbe interactions in preserving the whole soil biodiversity in anthropogenically disturbed ecosystems.

Keywords: Biodiversity; Earthworm; Land-use change; Large scale; Network stability.

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Conflict of interest statement

The authors declare that they have no conflicts of interest in this work.

Figures

Image, graphical abstract
Graphical abstract
Fig 1
Fig. 1
Agricultural activities alter the α- and β-diversity of soil earthworms, soil bacteria, and earthworm gut bacteria. Richness of earthworms (a), soil bacteria (b), and earthworm gut bacteria (c) and community composition of earthworms (d), soil bacteria (e), and earthworm gut bacteria (f). Data in the barplot are shown as mean ± standard deviations. In d–f, ns, not significant; *, P < 0.05;**, P < 0.01; ***, P < 0.001, which were derived from the results of permutational multivariate analysis of variance using distance matrices; The ellipse corresponds to the 95% confidence interval.
Fig 2
Fig. 2
Relationships between bacterial richness and earthworm richness in agricultural and natural land-use types. The relationships between earthworm richness and the richness of soil (a) and gut (b) bacteria. The richness of bacteria shared by gut and soil (c) refers to the bacteria that are occurred simultaneously in the gut and soil. The R2 and P values from linear regressions are shown. Dashed and solid regression lines represent non-significant (P > 0.05) and significant (P < 0.05) relationships.
Fig 3
Fig. 3
Modular networks and the relationships between network modularity and bacteria richness. Cross-domain co-occurrence networks (a) of soil bacteria, gut bacteria, and earthworms in agricultural and natural land-use types. Relationships between bacterial richness and network modularity for earthworm gut (b) and soil (c) in agricultural and natural land-use types.
Fig 4
Fig. 4
Network stability in agricultural and natural land-use types. (a) Robustness measured as the proportion of taxa remained with 50% of the taxa randomly removed from each of the networks. (b) Robustness is measured as the proportion of earthworm taxa removed from each of the networks. In (a) and (b), error bars correspond to the standard deviations of 100 times of simulations. Significant comparisons (two-sided t-test) between agricultural and natural habitats are indicated by ***P <  0.001. (c) Network vulnerability measured by maximum node vulnerability in each network. (d) Compositional stability of the networks. The adjusted R2 and P values from linear regressions are shown.

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