Ecosystem restoration strengthens pollination network resilience and function

Abstract

Land degradation results in declining biodiversity and the disruption of ecosystem functioning worldwide, particularly in the tropics1. Vegetation restoration is a common tool used to mitigate these impacts and increasingly aims to restore ecosystem functions rather than species diversity2. However, evidence from community experiments on the effect of restoration practices on ecosystem functions is scarce3. Pollination is an important ecosystem function and the global decline in pollinators attenuates the resistance of natural areas and agro-environments to disturbances4. Thus, the ability of pollination functions to resist or recover from disturbance (that is, the functional resilience)5,6 may be critical for ensuring a successful restoration process7. Here we report the use of a community field experiment to investigate the effects of vegetation restoration, specifically the removal of exotic shrubs, on pollination. We analyse 64 plant–pollinator networks and the reproductive performance of the ten most abundant plant species across four restored and four unrestored, disturbed mountaintop communities. Ecosystem restoration resulted in a marked increase in pollinator species, visits to flowers and interaction diversity. Interactions in restored networks were more generalized than in unrestored networks, indicating a higher functional redundancy in restored communities. Shifts in interaction patterns had direct and positive effects on pollination, especially on the relative and total fruit production of native plants. Pollinator limitation was prevalent at unrestored sites only, where the proportion of flowers producing fruit increased with pollinator visitation, approaching the higher levels seen in restored plant communities. Our results show that vegetation restoration can improve pollination, suggesting that the degradation of ecosystem functions is at least partially reversible. The degree of recovery may depend on the state of degradation before restoration intervention and the proximity to pollinator source populations in the surrounding landscape5,8. We demonstrate that network structure is a suitable indicator for pollination quality, highlighting the usefulness of interaction networks in environmental management6,9.

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Figure 1: The island of Mahé with study sites and pollination networks.
Figure 2: Treatment effects on pollinator communities and network structure.
Figure 3: Fruit set increased with visitation rate at unrestored sites.

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Acknowledgements

We thank the Seychelles National Parks Authority, the Ministry of Environment, Energy and Climate Change and the Seychelles Bureau of Standards for permission to conduct the work and administrative assistance. S. van de Velde and P. Acuña helped with data collection. J. Ghazoul, N. Bunbury, L. Turnbull, and D. Vázquez provided comments on earlier versions and C. Dormann, A. Hector, and M. Schleuning advised on statistics. C.N.K.-B. was funded by the German Research Foundation (KA 3349/2-1).

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Authors

Contributions

C.N.K.-B. conceived the study, led the experiments, collected and analysed the data and wrote the manuscript. J.M. contributed to project implementation and restoration. T.V. and R.G. conducted the restoration and collected data. A.E.W. identified pollinators. J.M.O. and N.B. contributed conceptually during the planning and implementation phases. N.B. assisted with data analysis. J.M., A.E.W., J.M.O. and N.B. commented on the manuscript.

Corresponding author

Correspondence to Christopher N. Kaiser-Bunbury.

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Competing interests

The authors declare no competing financial interests.

Additional information

Reviewer Information Nature thanks L. Carvalheiro, J. Memmott, J. Ollerton and I. Parker for their contribution to the peer review of this work.

Extended data figures and tables

Extended Data Figure 1 Level of specialization (d′pl) of the ten most common flowering plant species across all networks.

Asterisks indicate a significantly higher level of specialization (mean ± s.e.m.) in the unrestored compared to the restored networks. For full species names see Extended Data Table 3. Linear mixed model: P. bibracteata t = 2.836, P = 0.036; P. lancifolia t = 2.644, P = 0.038; E. sechellarum (variance structure weighted by treatment) t = 3.141, P = 0.020. Site was entered as random effect in all models. All other species P > 0.05. Source data

Extended Data Figure 2 Fruit set of the ten most abundant plant species at restored and unrestored sites.

The species occurred at ≥ 2 sites per treatment (Nepenthes, Mimusops), seven sites (Roscheria, Timonius), and eight sites (all others). The reproductive systems included dioecy (Pyrostria, Nepenthes, Timonius), monoecy with temporally separated male and female flowers (Roscheria, Phoenicophorium, Nephrosperma) and protandrous hermaphrodite flowers (Erythroxylum, Memecylon, Mimusops, Paragenipa). The three palm species Roscheria, Phoenicophorium and Nephrosperma had higher fruit set at the restored sites (GLMM: Nephrosperma n = 120, z = 2.54, P = 0.011, Phoenicophorium n = 120, z = 2.66, P = 0.008, Roscheria n = 108, z = 2.29, P = 0.022), the other species showed no clear species-specific pattern. The boxes depict the median and 25th and 75th percentiles, whiskers show 1.5 × interquartile range of the data, white circles indicate outliers. Source data

Extended Data Figure 3 Fruit set increased with visitation frequency at unrestored sites.

Square-root-transformed visitation frequency (n = 810, displayed seven most common species across all sites) of > 1.6 (see Methods) were only observed at restored sites. Mean fruit set was higher at restored sites than unrestored sites (see Table 1 for statistics of all ten species included in reproductive performance analysis). Shown are lines of best fit (solid) and 95% confidence interval (dotted). Source data

Extended Data Figure 4 Partial residual plots of network metrics.

Box plots of partial residuals show the effect of treatment after removing the effect of month and site. Partial residuals were calculated from linear mixed models with month and treatment as fixed main and interaction effects and site as random effect. Shown are partial residuals plus intercept. Metrics include number of visits (visits, log-transformed), number of interactions, interaction evenness, interaction diversity and network specialization (H2′). Boxplots depict the median ± 5th, 10th and 25th percentiles.

Extended Data Table 1 Study site details and summary of plant and pollinator communities
Extended Data Table 2 Results of full-factorial linear mixed model
Extended Data Table 3 List of plant species included in the study
Extended Data Table 4 Spatial auto-correlation coefficients of community and network parameters across the study sites

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Kaiser-Bunbury, C., Mougal, J., Whittington, A. et al. Ecosystem restoration strengthens pollination network resilience and function. Nature 542, 223–227 (2017). https://doi.org/10.1038/nature21071

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