Abstract
Plant–soil feedbacks (PSFs), soil-mediated plant effects on conspecific or heterospecific successors, are a major driver of vegetation development. It has been proposed that specialist plant antagonists drive differences in PSF responses between conspecific and heterospecific plants, whereas contributions of generalist plant antagonists to PSFs remain understudied. Here we examined PSFs among nine annual and nine perennial grassland species to test whether poorly defended annuals accumulate generalist-dominated plant antagonist communities, causing equally negative PSFs on conspecific and heterospecific annuals, whereas well-defended perennial species accumulate specialist-dominated antagonist communities, predominantly causing negative conspecific PSFs. Annuals exhibited more negative PSFs than perennials, corresponding to differences in root–tissue investments, but this was independent of conditioning plant group. Overall, conspecific and heterospecific PSFs did not differ. Instead, conspecific and heterospecific PSF responses in individual species’ soils were correlated. Soil fungal communities were generalist dominated but could not robustly explain PSF variation. Our study nevertheless suggests an important role for host generalists as drivers of PSFs.
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Data availability
Fungal ITS2 sequence data are uploaded to NCBI under project number PRJNA952944. Plant biomass data of the main experiment as well as root trait data are available on figshare under: https://doi.org/10.6084/m9.figshare.22740974 ref. 69. The FUNGUILD database46 (http://www.funguild.org) was used for fungal ASV annotation to ecological guilds. Source data are provided with this paper.
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Acknowledgements
We acknowledge Z. Zhang, E. Hannula, S. Geisen, R. Reuter and M. Stift for advice on statistical, molecular and root trait analyses, Q. Yang for the phylogenetic data and O. Ficht, M. Fuchs, H. Vahlenkamp, B. Speißer, B. Rüter, P. Kukofka, T. Voortman, N. Buchenau and student helpers from the University of Konstanz for practical assistance. Moreover, we acknowledge the University of Konstanz Sequencing Analysis Core Facility for assistance in analysing the fungal ITS2 sequencing data, and three reviewers for their valuable comments on the paper. R.A.W. acknowledges funding from the Wageningen Graduate Schools (WGS Postdoc Talent Grant to R.A.W.).
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R.A.W. and M.v.K. designed the study. R.A.W. and E.M. performed, respectively, the greenhouse experiments and molecular laboratory work. B.C.C.H. processed the raw sequencing data. Data analyses were done by R.A.W. with inputs from M.v.K. The paper was written by R.A.W. with considerable inputs from M.v.K. and was reviewed by all authors.
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Extended data
Extended Data Fig. 1 Plant biomass in the conditioning phase does not explain average plant-soil-feedback responses.
Both panels show the average plant-soil-feedback response (Ln(biomassconditioned/biomasscontrol) of 18 responding plant species in relation to the average plant biomass (Ln-transformed) in pooled conditioning phase soils (see Methods). (A) Average feedback responses to all conditioned soils (N = 90; 18 conditioning species × 5 independent biological replicates). (B) Average feedback responses to all plant species, except legumes (N = 70; 14 conditioning species × 5 independent biological replicates). Results of two-sided Pearson’s correlation tests between conditioning phase biomass and average feedback responses are shown.
Extended Data Fig. 2 Root-trait variation does not predict soil-conditioning effects.
Species-level soil conditioning effects ln(biomassconditioned/biomasscontrol), averaged across 18 responding plant species, were not correlated with specific root length (A; mm/g, log-transformed), marginally significantly correlated with relative root weight (B), and not significantly correlated with average root diameter (C; mm × 10). Average trait values were obtained from a separate root-trait experiment (see Methods). Results of two-sided Pearson’s correlation tests between trait average and average feedback responses in conditioned soils are shown. In panel B, trend line and shading represent the correlation coefficient (±95% CI) between relative root weight and average PSF effect.
Extended Data Fig. 3 Fungal communities become more dissimilar with increasing phylogenetic distance.
Average pairwise Bray-Curtis dissimilarities of complete fungal communities among all 18 conditioning plant species (A), among the nine annual species (B) and among the nine perennial species (C) correlate to pairwise phylogenetic distances (ln transformed; see Methods). Results of Mantel tests between pairwise phylogenetic distances and pairwise Bray-Curtis dissimilarities are shown in each panel, while trend lines and shading represent correlation coefficients (±95% CI’s).
Extended Data Fig. 4 Putative fungal pathogen-community composition and soil-conditioning effects.
(A) NMDS-ordination showing Bray-Curtis dissimilarity-based composition of putative fungal pathogen communities, based on fungal amplicon sequence variant (ASV) abundances. PERMANOVA analysis revealed significant variation in of putative fungal pathogen community composition among conditioning plant species (see methods; full species names are listed in Supplementary Table 1). (B) Average plant-soil-feedback responses to individual conditioned soils marginally significantly vary with putative fungal pathogen community composition (NMDS-axis 2), as indicated by a linear mixed effect model and log-likelihood tests (see methods and Supplementary Table 7). In panel B, trend line and shading represent the predicted linear relationship (±95% CI) between NMDS2 and average PSF response.
Extended Data Fig. 5 Arbuscular mycorrhizal fungal community composition.
NMDS-ordination showing Bray-Curtis dissimilarity-based composition of arbuscular mycorrhizal fungal communities, based on of fungal amplicon sequence variant (ASV) abundances. PERMANOVA analysis revealed significant variation in composition of arbuscular mycorrhizal fungal communities among conditioning plant species (see methods; full species names are listed in Supplementary Table 1).
Extended Data Fig. 6 Total pathogen abundances explain soil-conditioning effects.
(A) Species-level variation in logit-transformed total pathogen abundances (means ± SEM, N = 5 independent biological replicates per plant species; full species names are listed in Supplementary Table 1). Abundances are based on all ASVs assigned as putative pathogens. (B) Average plant-soil-feedback responses to individual conditioned soils significantly vary with total pathogen abundances. In both panels, Log-likelihood ratio test results are based on linear mixed effect model (see methods and Supplementary Tables 11 & 12). In panel B, trend line and shading represent the predicted linear relationship (±95% CI) between pathogen abundance and average PSF response.
Extended Data Fig. 7 Relative abundances of generalist and specialist putative pathogens and arbuscular mycorrhizal fungi in soils conditioned by 18 annual and perennial plant species.
Fungal ASVs were manually assigned as generalists and specialists based on their occurrence in at least 2/3 or maximally 1/3 of the plant species in this study (full species names are listed in Supplementary Table 1). Relative abundances were calculated based on untransformed read counts.
Extended Data Fig. 8 Specialist-pathogen accumulation in soils of annual and perennial plant species.
Dots and bars represent means ± SEM, calculated based on average logit-transformed relative putative specialist pathogen abundances in rhizosphere soil of single plant species (N = 9 plant species per plant group (annuals/perennials)).
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Wilschut, R.A., Hume, B.C.C., Mamonova, E. et al. Plant–soil feedback effects on conspecific and heterospecific successors of annual and perennial Central European grassland plants are correlated. Nat. Plants 9, 1057–1066 (2023). https://doi.org/10.1038/s41477-023-01433-w
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DOI: https://doi.org/10.1038/s41477-023-01433-w