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Ecosystem restoration strengthens pollination network resilience and function

Nature volume 542, pages 223–227 (2017)Cite this article

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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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References

  1. Butchart, S. H. M. et al. Global biodiversity: indicators of recent declines. Science 328, 1164–1168 (2010)

    Article  CAS  ADS  Google Scholar 

  2. McCann, K. Protecting biostructure. Nature 446, 29 (2007)

    Article  CAS  ADS  Google Scholar 

  3. Devoto, M., Bailey, S., Craze, P. & Memmott, J. Understanding and planning ecological restoration of plant–pollinator networks. Ecol. Lett. 15, 319–328 (2012)

    Article  Google Scholar 

  4. Potts, S. G. et al. Global pollinator declines: trends, impacts and drivers. Trends Ecol. Evol. 25, 345–353 (2010)

    Article  Google Scholar 

  5. Bengtsson, J. et al. Reserves, resilience and dynamic landscapes. Ambio 32, 389–396 (2003)

    Article  Google Scholar 

  6. Oliver, T. H. et al. Biodiversity and resilience of ecosystem functions. Trends Ecol. Evol. 30, 673–684 (2015)

    Article  Google Scholar 

  7. Menz, M. H. M. et al. Reconnecting plants and pollinators: challenges in the restoration of pollination mutualisms. Trends Plant Sci. 16, 4–12 (2011)

    Article  CAS  Google Scholar 

  8. Forup, M. L., Henson, K. S. E., Craze, P. G. & Memmott, J. The restoration of ecological interactions: plant–pollinator networks on ancient and restored heathlands. J. Appl. Ecol. 45, 742–752 (2008)

    Article  Google Scholar 

  9. Kaiser-Bunbury, C. N. & Blüthgen, N. Integrating network ecology with applied conservation: a synthesis and guide to implementation. AoB Plants 7, plv076 (2015)

    Article  Google Scholar 

  10. Clewell, A. F. & Aronson, J. Ecological Restoration: Principles, Values, and Structure of an Emerging Profession 2nd edn (Island Press, 2013)

  11. Ollerton, J., Winfree, R. & Tarrant, S. How many flowering plants are pollinated by animals? Oikos 120, 321–326 (2011)

    Article  Google Scholar 

  12. Traveset, A. & Richardson, D. M. Biological invasions as disruptors of plant reproductive mutualisms. Trends Ecol. Evol. 21, 208–216 (2006)

    Article  Google Scholar 

  13. Aguilar, R., Ashworth, L., Galetto, L. & Aizen, M. A. Plant reproductive susceptibility to habitat fragmentation: review and synthesis through a meta-analysis. Ecol. Lett. 9, 968–980 (2006)

    Article  Google Scholar 

  14. Schleuning, M., Fründ, J. & García, D. Predicting ecosystem functions from biodiversity and mutualistic networks: an extension of trait-based concepts to plant–animal interactions. Ecography 38, 380–392 (2015)

    Article  Google Scholar 

  15. Blüthgen, N., Menzel, F. & Blüthgen, N. Measuring specialization in species interaction networks. BMC Ecol. 6, 9 (2006)

    Article  Google Scholar 

  16. Kaiser-Bunbury, C. N., Valentin, T., Mougal, J., Matatiken, D. & Ghazoul, J. The tolerance of island plant–pollinator networks to alien plants. J. Ecol. 99, 202–213 (2011)

    Article  Google Scholar 

  17. Tur, C., Castro-Urgal, R. & Traveset, A. Linking plant specialization to dependence in interactions for seed set in pollination networks. PLoS One 8, e78294 (2013)

    Article  CAS  ADS  Google Scholar 

  18. Blüthgen, N. & Klein, A.-M. Functional complementarity and specialisation: The role of biodiversity in plant–pollinator interactions. Basic Appl. Ecol. 12, 282–291 (2011)

    Article  Google Scholar 

  19. Walker, B. Conserving biological diversity through ecosystem resilience. Conserv. Biol. 9, 747–752 (1995)

    Article  Google Scholar 

  20. Memmott, J., Waser, N. M. & Price, M. V. Tolerance of pollination networks to species extinctions. Proc. R. Soc. Lond. B 271, 2605–2611 (2004)

    Article  Google Scholar 

  21. Olesen, J. M., Eskildsen, L. I. & Venkatasamy, S. Invasion of pollination networks on oceanic islands: importance of invader complexes and endemic super generalists. Divers. Distrib. 8, 181–192 (2002)

    Article  Google Scholar 

  22. Morris, W. F., Vázquez, D. P. & Chacoff, N. P. Benefit and cost curves for typical pollination mutualisms. Ecology 91, 1276–1285 (2010)

    Article  Google Scholar 

  23. Larsson, M. Higher pollinator effectiveness by specialist than generalist flower-visitors of unspecialized Knautia arvensis (Dipsacaceae). Oecologia 146, 394–403 (2005)

    Article  ADS  Google Scholar 

  24. Araújo, M. S., Bolnick, D. I. & Layman, C. A. The ecological causes of individual specialisation. Ecol. Lett. 14, 948–958 (2011)

    Article  Google Scholar 

  25. Hagen, M. et al. Biodiversity, species interactions and ecological networks in a fragmented world. Adv. Ecol. Res 46, 89–210 (2012)

    Article  Google Scholar 

  26. Tylianakis, J. M., Tscharntke, T. & Lewis, O. T. Habitat modification alters the structure of tropical host-parasitoid food webs. Nature 445, 202–205 (2007)

    Article  CAS  ADS  Google Scholar 

  27. Morales, C. L. & Traveset, A. A meta-analysis of impacts of alien vs. native plants on pollinator visitation and reproductive success of co-flowering native plants. Ecol. Lett. 12, 716–728 (2009)

    Article  Google Scholar 

  28. van Hengstum, T., Hooftman, D. A. P., Oostermeijer, J. G. B. & van Tienderen, P. H. Impact of plant invasions on local arthropod communities: a meta-analysis. J. Ecol. 102, 4–11 (2013)

    Article  Google Scholar 

  29. Heleno, R., Lacerda, I., Ramos, J. A. & Memmott, J. Evaluation of restoration effectiveness: community response to the removal of alien plants. Ecol. Appl. 20, 1191–1203 (2010)

    Article  Google Scholar 

  30. Thompson, J. N. et al. Frontiers of ecology. Bioscience 51, 15–24 (2001)

    Article  Google Scholar 

  31. Fleischmann, K., Porembski, S., Biedinger, N. & Barthlott, W. Inselbergs in the sea: vegetation of granite outcrops on the islands of Mahé, Praslin and Silhouette (Seychelles). Bull. Geobot. Inst. ETH 62, 61–74 (1996)

    Google Scholar 

  32. Kaiser-Bunbury, C. N., Vázquez, D. P., Stang, M. & Ghazoul, J. Determinants of the microstructure of plant–pollinator networks. Ecology 95, 3314–3324 (2014)

    Article  Google Scholar 

  33. Kaiser-Bunbury, C. N., Mougal, J., Valentin, T., Gabriel, R. & Blüthgen, N. Herbicide application as a habitat restoration tool: impact on native island plant communities. Appl. Veg. Sci. 18, 650–660 (2015)

    Article  Google Scholar 

  34. Ghazoul, J. Pollen and seed dispersal among dispersed plants. Biol. Rev. Camb. Philos. Soc. 80, 413–443 (2005)

    Article  Google Scholar 

  35. Kaiser-Bunbury, C. N., Memmott, J. & Müller, C. B. Community structure of pollination webs of Mauritian heathland habitats. Perspect. Plant Ecol. Evol. Syst. 11, 241–254 (2009)

    Article  Google Scholar 

  36. Kaiser-Bunbury, C. N., Muff, S., Memmott, J., Müller, C. B. & Caflisch, A. The robustness of pollination networks to the loss of species and interactions: a quantitative approach incorporating pollinator behaviour. Ecol. Lett. 13, 442–452 (2010)

    Article  Google Scholar 

  37. Gibson, R. H., Knott, B., Eberlein, T. & Memmott, J. Sampling method influences the structure of plant–pollinator networks. Oikos 120, 822–831 (2011)

    Article  Google Scholar 

  38. Vázquez, D. P., Blüthgen, N., Cagnolo, L. & Chacoff, N. P. Uniting pattern and process in plant-animal mutualistic networks: a review. Ann. Bot. 103, 1445–1457 (2009)

    Article  Google Scholar 

  39. Legendre, P. & Legendre, L. Numerical Ecology 2nd edn, Vol. 20 (Elsevier Science, 1998)

  40. Proctor, M., Yeo, P. & Lack, A. The Natural History of Pollination 1st edn, (Timber Press, 1996)

  41. Zuur, A. F., Ieno, E. N., Walker, N. J., Saveliev, A. A. & Smith, G. M. Mixed Effects Models and Extensions in Ecology with R (Springer, 2009)

  42. Burnham, K. P. & Anderson, D. R. Model Selection and Multimodel Inference: A Practical Information-Theoretic Approach 2nd edn (Springer, 2002)

  43. Guisan, A. & Zimmermann, N. E. Predictive habitat distribution models in ecology. Ecol. Modell. 135, 147–186 (2000)

    Article  Google Scholar 

  44. Nakagawa, S. & Schielzeth, H. A general and simple method for obtaining R2 from generalized linear mixed-effects models. Methods Ecol. Evol. 4, 133–142 (2013)

    Article  Google Scholar 

Download references

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).

Author information

Authors and Affiliations

  1. Department of Biology, Ecological Networks, TU Darmstadt, Darmstadt, 64287, Germany

    Christopher N. Kaiser-Bunbury & Nico Blüthgen

  2. Seychelles National Parks Authority, PO Box 1240, Mahé, Seychelles

    James Mougal, Terence Valentin & Ronny Gabriel

  3. Department of Archaeology, Anthropology & Forensic Science, Bournemouth University, Poole, BH12 5BB, UK

    Andrew E. Whittington

  4. Department of Bioscience, Ecology and Genetics, Aarhus University, Aarhus C, 8000, Denmark

    Jens M. Olesen

Authors
  1. Christopher N. Kaiser-Bunbury
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  4. Terence Valentin
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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
Full size table
Extended Data Table 2 Results of full-factorial linear mixed model
Full size table
Extended Data Table 3 List of plant species included in the study
Full size table
Extended Data Table 4 Spatial auto-correlation coefficients of community and network parameters across the study sites
Full size table

Supplementary information

Supplementary Information

This file contains Supplementary Methods 1-3, Supplementary References and Supplementary Tables 1-4. (PDF 343 kb)

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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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