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Changes in precipitation patterns can destabilize plant species coexistence via changes in plant–soil feedback

Nature Ecology & Evolution volume 6, pages 546–554 (2022)Cite this article

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Abstract

Climate change can alter species coexistence through changes in biotic interactions. By describing reciprocal interactions between plants and soil microbes, plant–soil feedback (PSF) has emerged as a powerful framework for predicting plant species coexistence and community dynamics, but little is known about how PSF will respond to changing climate conditions. Hence, the context dependency of PSF has recently gained attention. Water availability is a major driver of all biotic interactions, and it is expected that precipitation patterns will change with ongoing climate change. We tested how soil water content affects PSF by conducting a full factorial pairwise PSF experiment using eight plant species common to southeastern United States coastal prairies under three watering treatments. We found coexistence-stabilizing negative PSF at drier-than-average conditions shifted to coexistence-destabilizing positive PSF under wetter-than-average conditions. A simulation model parameterized with the experimental results supports the prediction that more positive PSF accelerates the erosion of diversity within communities while decreasing the predictability in plant community composition. Our results underline the importance of considering environmental context dependency of PSF in light of a rapidly changing climate.

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Fig. 1: Net pairwise PSFs for all plant species combinations under different watering treatments.
Fig. 2: Standardized plant performance in conditioned soils under different watering treatments.
Fig. 3: Non-metric multi-dimensional scaling (NMDS) of the fungal communities at the end of the conditioning phase and dissimilarities between the plant species.
Fig. 4: Dynamics of alpha and beta diversity of simulated plant communities under different watering treatments.

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Data availability

Data associated with this study is available in the Open Science Framework repository: https://doi.org/10.17605/osf.io/x2wds. The sequences generated for this study can be found in GenBank BioProject PRJNA804565.

Code availability

The code for the simulation model is available in the Open Science Framework repository: https://doi.org/10.17605/osf.io/x2wds.

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Acknowledgements

We thank S. Aziz, K. Boakye, S. Durand-Luecke, J. Nicholas, O. Oladapo and A. Sölter for helping with planting and the biomass harvest. We further thank M. Afkhami and R. Callaway for helpful comments on the manuscript. This study was funded by the grant NSF DEB no. 1754287.

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Authors and Affiliations

  1. Department of Biology and Biochemistry, University of Houston, Houston, TX, USA

    Jan-Hendrik Dudenhöffer, Noah C. Luecke & Kerri M. Crawford

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Contributions

K.M.C. acquired funding and initiated the study. J.-H.D., N.C.L. and K.M.C. participated in the study design. J.-H.D. and N.C.L. performed the greenhouse experiment and data collection. N.C.L. and K.M.C. performed the bioinformatics for fungal community sequencing. N.C.L. performed the nutrient analysis. J.-H.D. performed the data analyses and wrote the simulation model. J.-H.D. wrote the initial manuscript with significant edits from K.M.C. and N.C.L. All authors contributed to revisions.

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Correspondence to Jan-Hendrik Dudenhöffer.

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Extended data

Extended Data Fig. 1 Pairwise plant–soil feedbacks by growth form and naturalization status.

Pairings of growth form (grass vs. forb) and naturalization status (native vs. exotic) are indicated in the panel headers (n forb/forb = 6, n grass/forb = 16, n grass/grass = 6, n exotic/exotic = 3, n native/exotic = 15, n native/native = 10). Box-whisker plots indicate the median, 25th/75th percentile and 1.5 x IQR.

Extended Data Fig. 2 Plant biomass of the response phase.

Bars above and below the zero intercept represent aboveground biomass and belowground biomass of the surviving plants respectively (Mean ± SE). Focal species and watering treatment are indicated in the panel headers and soil conditioning species at the x-axes. Species codes: AT = Asclepias tuberosa, BI = Bothriochloa ischaemum, RC = Ratibida columnifera, RH = Rudbeckia hirta, SH = Sorghum halepense, SN = Sorghastrum nutans, SS = Schizachyrium scoparium, VB = Verbena brasiliensis, ST = sterilized inocculum. n = initially 9 plants per conditioned soil in each watering treatment; note that only surviving plants are represented here.

Extended Data Fig. 3 Plant mortality of the response phase.

Bars represent plant mortality rates. Focal species and watering treatment are indicated in the panel headers and soil conditioning species at the x-axes. Species codes: AT = Asclepias tuberosa, BI = Bothriochloa ischaemum, RC = Ratibida columnifera, RH = Rudbeckia hirta, SH = Sorghum halepense, SN = Sorghastrum nutans, SS = Schizachyrium scoparium, VB = Verbena brasiliensis, ST = sterilized inocculum. n = 9 plants per conditioned soil in each water treatment.

Extended Data Fig. 4 Alpha diversity and relative pathogen abundance of fungal communities at the end of the conditioning phase.

(a) Simpson’s diversity of fungal ASVs, and (b) richness of fungal ASVs. Significance of the watering treatment (Pwater) was evaluated using linear models (Methods and Supplementary Table 4). (c) Relative abundance of probable pathogens, and (d) relative abundance of putative pathogens. Box-whisker plots indicate the median, 25th/75th percentile and 1.5 x IQR. Species codes: AT = Asclepias tuberosa, BI = Bothriochloa ischaemum, RC = Ratibida columnifera, RH = Rudbeckia hirta, SH = Sorghum halepense, SN = Sorghastrum nutans, SS = Schizachyrium scoparium, VB = Verbena brasiliensis. n = 71 soil samples; note that for Asclepias tuberosa in the medium watering treatment only two samples were available.

Extended Data Fig. 5 Simulation results under alternative parameterizations of plant mortality and the spatial extent of recruitment under different watering treatments of simulated plant communities.

(a) Alpha diversity (median species richness and average Simpson’s diversity). (b) Average relative abundance of the single species. Species codes: AT = Asclepias tuberosa, BI = Bothriochloa ischaemum, RC = Ratibida columnifera, RH = Rudbeckia hirta, SH = Sorghum halepense, SN = Sorghastrum nutans, SS = Schizachyrium scoparium, VB = Verbena brasiliensis. n = 200 simulated plant communities per watering treatment and parameterization.

Extended Data Fig. 6 Plant biomass of the conditioning phase.

Bars above and below the zero intercept represent aboveground biomass and belowground biomass of the surviving plants respectively (Mean ± SE). The focal plant species is indicated in the panel headers; note the different y-axis scaling. Species codes: AT = Asclepias tuberosa, BI = Bothriochloa ischaemum, RC = Ratibida columnifera, RH = Rudbeckia hirta, SH = Sorghum halepense, SN = Sorghastrum nutans, SS = Schizachyrium scoparium, VB = Verbena brasiliensis. n = 9 plants per species in each watering treatment.

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Dudenhöffer, JH., Luecke, N.C. & Crawford, K.M. Changes in precipitation patterns can destabilize plant species coexistence via changes in plant–soil feedback. Nat Ecol Evol 6, 546–554 (2022). https://doi.org/10.1038/s41559-022-01700-7

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