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Organic fertilization drives shifts in microbiome complexity and keystone taxa increase the resistance of microbial mediated functions to biodiversity loss

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Abstract

Long-term intensive fertilization profoundly alters soil properties including microbial diversity and co-occurrence associations, but little is known about the relative and combined importance of biotic and abiotic factors for the stability of soil microbial mediated functions (MMF) to biodiversity loss. Here, we experimentally manipulated microbial α-diversity by inoculating diluted soil suspensions into sterilized soil to tease apart the biotic and abiotic effects on the microbiomes and temporal shifts in MMF in soils subjected to different fertilization treatments during a 3-month re-colonization. We showed that bacterial and fungal biomass remained similar between different diversity levels at each sampling date (0, 7, 15, 30, and 90 days). Organic fertilization accelerated the resilience of copiotrophic bacterial assemblages to biodiversity loss compared with non-fertilization and mineral fertilization and increased the strength of positive relationships between soil MMF and diversity and network complexity of bacterial rather than fungal community. A suite of biotic and abiotic factors were found to account for up to 73% of the variation in MMF, with the combined effects of diversity and microbiome complexity accounting for 43% of the variation in MMF. Moreover, the overall diversity of keystone taxa, primarily driven by soil organic carbon, was particularly important for promoting soil MMF (P < 0.001), with the abundances of oligotrophic- (Blastocatellaceae) and copiotrophic-selected (Comamonadaceae) keystone taxa positively and negatively relating to soil MMF, respectively. Collectively, our study indicates the importance of fertilization-induced shifts in network complexity and microbial life strategies for maintaining the stability of MMF following biodiversity decline and calls for organically based microbiome complexity conservation strategies to mitigate negative impacts of biodiversity loss on multiple agroecosystem functions.

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Funding

This research is financially supported by the National Natural Science Foundation of China (42107009, 41977107, and 42177008), the fellowship of China Postdoctoral Science Foundation (2022M712770), and the Key Research and Development Projects of Zhejiang Province, China (2022C02018, 2022C02022).

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Authors and Affiliations

  1. Ministry of Education Key Laboratory of Environmental Remediation and Ecological Health, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou, 310058, China

    Jipeng Luo, Qingxu Ma, Guangcheng Liao, Bifeng Hu, Heping Zhao & Tingqiang Li

  2. Department of Microbiological Sciences, North Dakota State University, Fargo, ND, USA

    Samiran Banerjee

  3. Department of Land Resource Management, School of Tourism and Urban Management, Jiangxi University of Finance and Economics, Nanchang, 330013, China

    Bifeng Hu

  4. Zhejiang Provincial Key Laboratory of Agricultural Resources and Environment, Hangzhou, 310058, China

    Tingqiang Li

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  1. Jipeng Luo
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Supplementary information

ESM 1:

Figure S1 The priori structural equation model including fertilization regime, dilution, soil properties and bacterial community diversity as a predictor of microbial mediated functions (MMF) is shown (a). The priori structural equation model including fertilization regime, dilution, soil properties, bacterial community diversity and complexity of bacterial network as a predictor of soil MMF is shown (a). Figure S2 Microbial biomass in the three levels of diversity D0, D1 and D2 across different fertilization regimes after 6 weeks pre-incubation (Day 0). Data are the form of mean ± s.d.. Different letters above the bars indicate significant difference at P < 0.05 (Tukey’s HSD). Figure S3 Quantification of the bacterial (a-c) and fungal (d-f) communities in the three levels of diversity D0, D1 and D2 at each sampling time throughout the 90 days of incubation. Data are the form of mean ± s.d.. For each treatment, the same letters above the bars indicate microcosms without significant differences (P < 0.05; Tukey’s HSD). Figure S4 Shifts of fungal community composition and diversity across treatments. (a) Principal coordinates analysis (PCoA) of all incubated soil samples based on the Bray-Curtis dissimilarity. (b) Variance in bacterial community explained by dilution, fertilization regimes and their interactions. (c) Bray-Curtis distance of pairwise bacterial communities from different soils between the soils receiving diluted and undiluted suspensions. (d) Relative abundances of the ten most abundant fungal phyla/classes across treatments. Abbreviation: Ori, original soil. (e) The index of fungal richness, Shannon index, pielou evenness of the original and diluted soils under different fertilization regimes. Richness represents the number of ASV. Data are present in the form of mean ± s.e. Different letters above the bars indicate significant differences according to Tukey’s HSD test. Figure S5 The index of bacterial richness (a), shannon (b), faith’s pd (c) and pielou evenness (d) of the original and diluted soils under different fertilization regimes. Richness denotes the observed number of ASVs, Faith’s pd denotes faith’s phylogenetic diversity. Data are present in the form of mean ± s.e. Different letters above the bars indicate significant differences according to Tukey’s HSD test (p-value < 0.05). Abbreviation: Ori, original soil. Figure S6 Temporal shifts of average microbial mediated functions (MMF) index between different treatments. (a) Temporal shifts of MMF between different fertilized soils across different dilution levels, and asterisks (*) indicate significant differences between fertilized soils at the level of P < 0.05. (b) Temporal shifts of soil MMF between dilution gradients across different soils, and asterisks (*) indicate significant differences between dilution levels at the level of P < 0.05. Figure S7 Shifts of the individual functions related to DNA concentration (a), nitrification (b), net N mineralization (Nm; c), acid phosphatase activity (d), β-glucosidase activity (e), β-1,4-N-acetylglucosaminidase activity (NAG, f), P availability (g), N2O emission (h), glucose mineralization (i) and available N (i) with increasing dilution levels across fertilized soils. Figure S8 Relationships between the indexes of bacterial richness (a), Shannon (b), Faith’s pd (c), Pielou evenness (d) and average microbial mediated functions (AMF), and between the bacterial richness (e), Shannon (f), Faith’s pd (g), Pielou evenness (h) and the principal coordinate microbial mediated functions (PCoA MMF). The solid lines represent the fitted significant ordinary least squares (OLS) linear regressions at P < 0.05. The fitted linear relationships between AMF and PCoA MMF and Shannon index (i), Faith’s pd (j) and Pielou evenness (k) across fertilization treatments. Figure S9 Relationships between the index of fungal richness (a), Shannon (b), Pielou evenness (c) and average microbial mediated functions (AMF), and between the fungal richness (d), shannon (e), pielou evenness (f) and the principal coordinate microbial mediated functions (PCoA MMF). The dashed lines represent the fitted ordinary least squares (OLS) linear regressions at P > 0.05. Figure S10 The relationships between average microbial mediated functions (AMF) and number of node (a) and edge (b) and average degree (c) and assortativity (d) across the fertilized soils. Only significant fitted lines are shown on the graphs. Figure S11 Co-occurrence patterns of fungal community did no differ significantly according to dilution and fertilization regime and the relationships of average microbial mediated functions (AMF) to co-occurrence networks characteristics. Co-occurrence networks of fungal community from CK (a), NPK (b) and NPKM (c) soils. The sizes of the nodes (ASVs) are proportional to the number of connections (that is, degree). Line width is proportional to the strength of the correlation between nodes. Only nodes (ASVs) with spearman’s ρ > 0.76 (after Benjamini and Hochberg FDR adjust, P < 0.05) were connected. The numbers of node (d) and edge (e) and the average degree (f) and assortativity (g) of soil bacterial co-occurrence networks in different fertilized soils inoculated with different dilution levels of suspension. Data are in the form of mean ± s.d., and different letters above bars indicate significant differences at P < 0.05. The relationships of average microbial mediated functions (AMF) with number of node (h) and edge (i) and the average degree (j) and assortativity (k). Figure S12 The topological properties of average degree, closeness centrality and betweenness centrality for the family taxon present in the co-occurrence networks constructed from bacterial community in CK soil (a-c), NPK soil (e-g) and NPKM soil (h-j). The taxon name shown in red color indicates the keystone taxa, which were identified as the nodes with high degree (> 100) and closeness centrality, and low betweenness centrality (< 5000). Figure S13 Relationships between the principal coordinate microbial mediated functions (PCoA MMF) and the relative abundance (log2 transformed) of the keystone taxa identified in different fertilized soils. Solid lines represent the significant ordinary least squares (OLS) linear regressions, R2 denotes the proportion of variance explained and shade area shows 95% confidence interval of the fit. * P < 0.05, ** P < 0.01, *** P < 0.001. Only significant fitted lines are displayed on the graphs. Figure S14 Relationships between the relative abundance (log2 transformed) of the keystone taxa and the principal coordinate microbial mediated functions (PCoA MMF) in each soil (a-f). Only the significant (P < 0.05) relationship was displayed. Solid lines represent the significant ordinary least squares (OLS) linear regressions, R2 denotes the proportion of variance explained and shade area shows 95% confidence interval of the fit. * P < 0.05, ** P < 0.01, *** P < 0.001. Only significant fitted lines are displayed on the graphs. (g) Distribution of the relative abundance of 438 bacterial ASVs taxonomically affiliated with the keystone taxa. The horizontal red line corresponds to 0.01% relative abundance. Figure S15 Relationships between soil abiotic factors and average microbial mediated functions (AMF). a) soil pH, b) electrical conductivity (EC), c) soil NH4+, d) soil total N, e) soil total nitrogen carbon (TOC), f) C/N ratio, g) bacterial Shannon index, h) bacterial richness, i) bacterial evenness, j) bacterial Faith’s pd. * P < 0.05, ** P < 0.01, *** P < 0.001. Figure S16 Biplot derived from principal component analysis (PCA) including the principal components of PC2 and PC5 as well as the observations. The biotic and abiotic factors correlated with PC1 and PC2 are shown. Ellipses represent the confidence interval at 95% probability, only statistically significant correlations at P < 0.05 level are displayed. Figure S17 The relative abundance of the top 30 most abundant bacterial families across different soils at different dilution levels. Keystone taxa are shown in bold. Table S1 Basic physicochemical parameters of different fertilized soils used in this study. Table S2 Correlations and topological properties of microbial community co-occurrence networks of soils under different fertilization regimes. Table S3 Spearman correlations between multiple diversity metrics of bacterial keystone taxa and soil TOC. Bolded values are significant at P < 0.05. Table S4 Summary of the general linear models (GLMs) and ANOVA for the effects of microbial diversity and network complexity (network edges) on soil multifunctionality. Table S5 Summary of the general linear models (GLMs) for the effects of PCA components on soil multifunctionality. We derived nine components from the abiotic factors (soil pH, electrical conductivity, NH4+, total nitrogen, total organic carbon and C/N ratio) and biotic factors (bacterial diversity, edge number and node number) that mostly influenced multifunctionality. Table S6 Spearman rank correlations between the relative abundance of the ten most abundant bacterial and fungal phyla/classes and soil pH, TN and TOC. Significant P-values less than 0.05 are shown in bold.

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Luo, J., Banerjee, S., Ma, Q. et al. Organic fertilization drives shifts in microbiome complexity and keystone taxa increase the resistance of microbial mediated functions to biodiversity loss. Biol Fertil Soils 59, 441–458 (2023). https://doi.org/10.1007/s00374-023-01719-3

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