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Pollinators contribute to the maintenance of flowering plant diversity

Abstract

Mechanisms that favour rare species are key to the maintenance of diverse communities1,2,3. One of the most critical tasks for conservation of flowering plant biodiversity is to understand how plant–pollinator interactions contribute to the maintenance of rare species4,5,6,7. Here we show that niche partitioning in pollinator use and asymmetric facilitation confer fitness advantage of rarer species in a biodiversity hotspot using phylogenetic structural equation modelling that integrates plant–pollinator and interspecific pollen transfer networks with floral functional traits. Co-flowering species filtered pollinators via floral traits, and rarer species showed greater pollinator specialization leading to higher pollination-mediated male and female fitness than more abundant species. When plants shared pollinator resources, asymmetric facilitation via pollen transport dynamics benefitted the rarer species at the cost of more abundant species, serving as an alternative diversity-promoting mechanism. Our results emphasize the importance of community-wide plant–pollinator interactions that affect reproduction for biodiversity maintenance.

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Fig. 1: Schematic framework of how pollinator niche partitioning, asymmetric facilitation and automatic assurances confer rare species advantage.
Fig. 2: Plant–pollinator interactions favour rare species through pollinator niche partitioning and asymmetric facilitation, which are mediated by floral traits.

Data availability

All data that support the findings of this study are included in this published article and its Supplementary Information files and source data files. Source data are provided with this paper.

Code availability

All software used in this study are provided in the Methods, Supplementary Information and the accompanying Reporting Summary.

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Acknowledgements

We thank J. Baker, D. Chang, A. M. Arters, U. Meenakshinathan, K. Doleski, S. Barratt-Boyes, R. A. Ashman and M. Holden for assistance with stigma pollen identification, floral trait measurements and insect specimen processing; J. Rawlins, J. Pawelek, R. Androw and B. Coulter for insect identification; J. Hyland and V. Verdecia for logistic support at the Carnegie Museum of Natural History; McLaughlin field station staff for logistical support of field work; and the members of the Ashman, Wood and Turcotte laboratories for discussion. This work was supported by the National Science Foundation (DEB 1452386) to T.-L.A.

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Authors and Affiliations

Authors

Contributions

T.-L.A. conceived the study. N.W. and T.-L.A. led the conceptual development. N.W. analysed the data. N.W., T.-L.A. and R.L.K. wrote the manuscript. N.W., T.-L.A., R.L.K. and G.A.-G. contributed to manuscript revisions. R.L.K., E.M.O., R.A.H., G.A.-G. and T.-L.A. collected the data.

Corresponding authors

Correspondence to Na Wei or Tia-Lynn Ashman.

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The authors declare no competing interests.

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Peer review information Nature thanks Marcelo Aizen, Christopher Kaiser-Bunbury and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Extended data figures and tables

Extended Data Fig. 1 Community-wide plant–pollinator network.

a, Plant species (n = 79) coloured by families are arranged on the left according to phylogeny. The numbers of pollinator species that plants interacted with are shown as black bars and numbers within parentheses. b, Pollinator species (n = 416) are arranged along the top according to the size and similarity of plant assemblages that they interacted with. c, The observed numbers of interactions are denoted as frequency (‘Freq’) by the colour scale

Source data.

Extended Data Fig. 2 Rarefaction shows that the majority of pollinator diversity was captured with our sampling intensity.

Rarefaction curves of each of the 79 plant species (a, b) that were observed for plant–pollinator interactions (Supplementary Table 1) and the 64 plant species (c, d) that were included in the phylogenetic structural equation models (Fig. 2). The observed number of pollinators is represented by the solid portion of each coloured line, whereas the dashed portion indicates extrapolation in the rarefaction analysis using the R package iNEXT42. Lines colours are randomly assigned. Pollinator diversity, especially Chao’s Shannon diversity (b, d), started to level off at the observed number of pollinators for most plant species, reflecting sufficient sampling to capture pollinator diversity

Source data.

Extended Data Fig. 3 Floral trait variation and abundance.

a, Multivariate analysis (factor analysis of mixed data, FAMD) of 20 floral traits (Supplementary Table 3). Plant species (n = 73, abbreviated as the first two letters of genus and species names and coloured by plant family) are segregated along the first two dimensions, representing mainly size-related and other (shape/colour/inflorescence) floral traits, respectively. These traits vary independently from species floral abundance (symbol size). b, Species rarity based on floral abundance (log-transformed) was correlated with rarity based on occurrence in the number of surveyed plots (see Methods, two-sided Pearson’s correlation test, r = 0.64, t = 6.9, d.f. = 70, P = 1.8 × 10−9). The 95% confidence intervals of the mean are shown

Source data.

Extended Data Fig. 4 Multivariate analysis of floral traits associated with pollinator attraction.

a, b, In the first four dimensions of the factor analysis of mixed data (FAMD), the centroid of each category within a qualitative trait is indicated, with symbol shape representing different qualitative traits. Quantitative traits are represented by arrows. Individual plant species (n = 73) are shown in the background with colours indicating plant families and symbol sizes indicating floral abundances (Extended Data Fig. 3). c, The traits that contributed to ≥15% of variation of the first three dimensions are highlighted in colour

Source data.

Extended Data Fig. 5 Multivariate analysis of floral traits associated with male organ.

a, b, In the first four dimensions of the factor analysis of mixed data (FAMD), the centroid of each category within a qualitative trait is indicated, with symbol shape representing different qualitative traits. Quantitative traits are represented by arrows. Individual plant species (n = 73) are shown in the background with colours indicating plant families and symbol sizes indicating floral abundances (Extended Data Fig. 3). c, The traits that contributed to ≥15% of variation of the first three dimensions are highlighted in colour

Source data.

Extended Data Fig. 6 Multivariate analysis of floral traits associated with female organ.

a, b, In the first four dimensions of the factor analysis of mixed data (FAMD), the centroid of each category within a qualitative trait is indicated, with symbol shape representing different qualitative traits. Quantitative traits are represented by arrows. Individual plant species (n = 73) are shown in the background with colours indicating plant families and symbol sizes indicating floral abundances (Extended Data Fig. 3). c, The traits that contributed to ≥15% of variation of the first four dimensions are highlighted in colour

Source data.

Extended Data Fig. 7 Pollen transfer network.

The network was constructed based on pollen deposited on 54 stigmas of 66 individual plant species (Supplementary Table 5). Plant species (nodes) are abbreviated as the first two letters of genus and species names (Supplementary Table 3), with unidentified species denoted with ‘U’. Node size indicates the number of flowering plant species that pollen is received from, and node colour darkness indicates the number of flowering plant species that pollen is donated to. That is, larger nodes represent better recipients and darker nodes better donors. Arrows and their sizes indicate the direction and amount (counts) of pollen transfer, respectively

Source data.

Extended Data Fig. 8 Validation of fractional identity approach and rarefaction of pollen received by stigmas.

a, There was a strong relationship between heterospecific pollen (HP) richness when fractionally identified pollen grains were excluded (y-axis, ‘no ambiguity’) and included (x-axis, ‘fractional’): n = 66 plant species, general linear model, slope = 0.73, t = 17.1, P < 2 × 10−9. The dotted 95% confidence intervals of the mean are shown. b, c, Rarefaction analysis using the R package iNEXT42 showed that the majority of pollen species richness (b) and Chao’s Shannon diversity (c) were captured by the sampled styles (n = 54 on average) for each plant species (n = 66, coloured lines). The observed (solid) and extrapolated (dashed) portion of each rarefaction line are indicated

Source data.

Extended Data Fig. 9 Phylogenetic structural equation models (PSEMs).

ah, The PSEMs considered pollinator niche partitioning, asymmetric facilitation, pollination assurance and numeric assurance (orange arrows). Pollination assurance and numeric assurance are collectively referred to as automatic assurances. i, Model fitting and nested model selection used the R packages piecewiseSEM70 and phylopath74. Sample size was 64 plant species. df and P, degree of freedom and P value of the two-sided Fisher’s C statistic; AIC, the Akaike’s information criterion; CICc, the C statistic information criterion corrected for small sample sizes; w, CICc weights. Standardized regression coefficients of paths and model averaging are in Supplementary Table 6.

Extended Data Table 1 Serpentine seep system within the McLaughlin Natural Reserve study area

Supplementary information

Supplementary Information

This file contains Supplementary Methods, Supplementary Notes and Supplementary References.

Reporting Summary

Supplementary Table 1

Plant–pollinator interactions observed across sites and years.

Supplementary Table 2

Plant–pollinator network metrics and comparisons to null models.

Supplementary Table 3

Species-level floral traits.

Supplementary Table 4

Phylogenetic signals of plant–pollinator interactions, interspecific pollen transfer network metrics and floral traits.

Supplementary Table 5

Stigma pollen data.

Supplementary Table 6

Standardized regression coefficients and model averaging of phylogenetic structural equation models.

Source data

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Wei, N., Kaczorowski, R.L., Arceo-Gómez, G. et al. Pollinators contribute to the maintenance of flowering plant diversity. Nature 597, 688–692 (2021). https://doi.org/10.1038/s41586-021-03890-9

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