Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

Insights into the assembly rules of a continent-wide multilayer network

Nature Ecology & Evolution volume 3, pages 1525–1532 (2019)Cite this article

Subjects

Abstract

How are ecological systems assembled? Identifying common structural patterns within complex networks of interacting species has been a major challenge in ecology, but researchers have focused primarily on single interaction types aggregating in space or time. Here, we shed light on the assembly rules of a multilayer network formed by frugivory and nectarivory interactions between bats and plants in the Neotropics. By harnessing a conceptual framework known as the integrative hypothesis of specialization, our results suggest that phylogenetic constraints separate species into different layers and shape the network’s modules. Then, the network shifts to a nested structure within its modules where interactions are mainly structured by geographic co-occurrence. Finally, organismal traits related to consuming fruits or nectar determine which bat species are central or peripheral to the network. Our results provide insights into how different processes contribute to the assemblage of ecological systems at different levels of organization, resulting in a compound network topology.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: The bat–plant multilayer network.
Fig. 2: Matrices evidencing compound topology.
Fig. 3: Centrality of bat species across layers.
Fig. 4: Influence of organismal traits on centrality.

Similar content being viewed by others

Data availability

Raw network data are freely available on GitHub via Zenodo: https://doi.org/10.5281/zenodo.1487572.

Code availability

Visualization codes are freely available on GitHub via Zenodo: https://doi.org/10.5281/zenodo.1487572.

References

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

    Article  Google Scholar 

  2. Latombe, G., Hui, C. & McGeoch, M. A. Beyond the continuum: a multi-dimensional phase space for neutral–niche community assembly. Proc. R. Soc. B 282, 20152417 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  3. Guimarães, P. R. & Deyn, G. B. De Ecological networks: assembly and consequences. Oikos 125, 443–445 (2016).

    Article  Google Scholar 

  4. Estes, J. A. et al. Trophic downgrading of planet Earth. Science 333, 301–306 (2011).

    Article  CAS  PubMed  Google Scholar 

  5. Peters, V. E. et al. Using plant–animal interactions to inform tree selection in tree-based agroecosystems for enhanced biodiversity. Bioscience 66, 1046–1056 (2016).

    Article  Google Scholar 

  6. Luis, A. D. et al. Network analysis of host-virus communities in bats and rodents reveals determinants of cross-species transmission. Ecol. Lett. 18, 1153–1162 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  7. Sutherland, W. J. et al. Identification of 100 fundamental ecological questions. J. Ecol. 101, 58–67 (2013).

    Article  Google Scholar 

  8. Guimarães, P. R., Pires, M. M., Jordano, P., Bascompte, J. & Thompson, J. N. Indirect effects drive coevolution in mutualistic networks. Nature 550, 511–514 (2017).

    Article  PubMed  CAS  Google Scholar 

  9. Dormann, C. F., Fründ, J. & Schaefer, H. M. Identifying causes of patterns in ecological networks: opportunities and limitations. Annu. Rev. Ecol. Evol. Syst. 48, 559–584 (2017).

    Article  Google Scholar 

  10. Delmas, E. et al. Analysing ecological networks of species interactions. Biol. Rev. 94, 16–36 (2018).

    Article  Google Scholar 

  11. 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  PubMed  PubMed Central  Google Scholar 

  12. Thebault, E. & Fontaine, C. Stability of ecological communities and the architecture of mutualistic and trophic networks. Science 329, 853–856 (2010).

    Article  CAS  PubMed  Google Scholar 

  13. Fortuna, M. A. et al. Nestedness versus modularity in ecological networks: two sides of the same coin? J. Anim. Ecol. 79, 811–817 (2010).

    PubMed  Google Scholar 

  14. Lewinsohn, T. M., Inácio Prado, P., Jordano, P., Bascompte, J. & Olesen, M.J. Structure in plant-animal interaction assemblages. Oikos 113, 174–184 (2006).

    Article  Google Scholar 

  15. Flores, C. O., Valverde, S. & Weitz, J. S. Multi-scale structure and geographic drivers of cross-infection within marine bacteria and phages. ISME J. 7, 520–532 (2013).

    Article  PubMed  Google Scholar 

  16. Pinheiro, R. B. P. et al. Trade-offs and resource breadth processes as drivers of performance and specificity in a host–parasite system: a new integrative hypothesis. Int. J. Parasitol. 46, 115–121 (2016).

    Article  PubMed  Google Scholar 

  17. Futuyma, D. J. & Moreno, G. The evolution of ecological specialization. Annu. Rev. Ecol. Syst. 19, 207–233 (1988).

    Article  Google Scholar 

  18. Brown, J. H. On the relationship between abundance and distribution of species. Am. Nat. 124, 255–279 (1984).

    Article  Google Scholar 

  19. Pinheiro, R. B. P., Felix, G. M. F., Dormann, C. F. & Mello, M. A. R. A new model explaining the origin of different topologies in interaction networks. Ecology 100, e02796 (2019).

    Article  PubMed  Google Scholar 

  20. Boccaletti, S. et al. The structure and dynamics of multilayer networks. Phys. Rep. 544, 1–122 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  21. Fleming, T. H. & Kress, W. J. The Ornaments of Life: Coevolution and Conservation in the Tropics (Univ. Chicago Press, 2013).

  22. Dumont, E. R. et al. Morphological innovation, diversification and invasion of a new adaptive zone. Proc. R. Soc. B 279, 1797–1805 (2012).

    Article  PubMed  Google Scholar 

  23. Dumont, E. R. et al. Built to bite: cranial design and function in the wrinkle-faced bat. J. Zool. 279, 329–337 (2009).

    Article  Google Scholar 

  24. Kivela, M. et al. Multilayer networks. J. Complex Netw. 2, 203–271 (2014).

    Article  Google Scholar 

  25. Felix, G. M., Pinheiro, R. B. P., Poulin, R., Krasnov, B. R. & Mello, M. A. R. The compound topology of a continent-wide interaction network explained by an integrative hypothesis of specialization. Preprint at bioRxiv https://doi.org/10.1101/236687 (2017).

  26. Miranda, P. N. et al. The dilemma of binary or weighted data in interaction networks. Ecol. Complex. 38, 1–10 (2019).

    Article  Google Scholar 

  27. Fründ, J., McCann, K. S. & Williams, N. M. Sampling bias is a challenge for quantifying specialization and network structure: lessons from a quantitative niche model. Oikos 125, 502–513 (2016).

    Article  Google Scholar 

  28. Coelho, M. T. P., Rodrigues, J. F. M. & Rangel, T. F. Neutral biogeography of phylogenetically structured interaction networks. Ecography 40, 1467–1474 (2017).

    Article  Google Scholar 

  29. Barabasi, A.-L. & Albert, R. Emergence of scaling in random networks. Science 286, 509–512 (1999).

    Article  CAS  PubMed  Google Scholar 

  30. Chase, J. M. et al. Embracing scale-dependence to achieve a deeper understanding of biodiversity and its change across communities. Ecol. Lett. https://doi.org/10.1111/ele.13151 (2018).

  31. Stevan, J.A. Morphology, performance and fitness. Am. Zool. 23, 347–361 (1983).

    Article  Google Scholar 

  32. Anderson, R. A., Mcbrayer, L. D. & Herrel, A. Bite force in vertebrates: opportunities and caveats for use of a nonpareil whole-animal performance measure. Biol. J. Linn. Soc. 93, 709–720 (2008).

    Article  Google Scholar 

  33. Santana, S. E., Dumont, E. R. & Davis, J. L. Mechanics of bite force production and its relationship to diet in bats. Funct. Ecol. 24, 776–784 (2010).

    Article  Google Scholar 

  34. Villalobos-Chaves, D., Padilla-Alvárez, S. & Rodríguez-Herrera, B. Seed predation by the wrinkle-faced bat Centurio senex: a new case of this unusual feeding strategy in Chiroptera. J. Mammal. 97, 726–733 (2016).

    Article  Google Scholar 

  35. Gonzalez-Terrazas, T. P., Medellin, R. A., Knornschild, M. & Tschapka, M. Morphological specialization influences nectar extraction efficiency of sympatric nectar-feeding bats. J. Exp. Biol. 215, 3989–3996 (2012).

    Article  PubMed  Google Scholar 

  36. Bezerra, E. L. S., Machado, I. C. & Mello, M. A. R. Pollination networks of oil-flowers: a tiny world within the smallest of all worlds. J. Anim. Ecol. 78, 1096–1101 (2009).

    Article  PubMed  Google Scholar 

  37. Vellend, M. The Theory of Ecological Communities (Princeton Univ. Press, 2016).

  38. Mello, M. A. R. et al. Keystone species in seed dispersal networks are mainly determined by dietary specialization. Oikos 124, 1031–1039 (2015).

    Article  Google Scholar 

  39. Minoarivelo, H. O. & Hui, C. Trait-mediated interaction leads to structural emergence in mutualistic networks. Evol. Ecol. 30, 105–121 (2016).

    Article  Google Scholar 

  40. Borge-Holthoefer, J., Baños, R. A., Gracia-Lázaro, C. & Moreno, Y. Emergence of consensus as a modular-to-nested transition in communication dynamics. Sci. Rep. 7, 41673 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Geiselman, C. K., Mori, S. A. & Blanchard, F. Database of Neotropical Bat/Plant Interactions (batplant.org, 2002); http://www.batplant.org

  42. Lobova, T. A., Geiselman, C. K. & Mori, S. A. Seed Dispersal by Bats in the Neotropics (New York Botanical Garden Press, 2009).

  43. Jordano, P. Sampling networks of ecological interactions. Funct. Ecol. 30, 1883–1893 (2016).

    Article  Google Scholar 

  44. Petit, S. The diet and reproductive schedules of Leptonycteris curasoae curasoae and Glossophaga longirostris elongata (Chiroptera: Glossophaginae) on Curacao. Biotropica 29, 214–223 (1997).

    Article  Google Scholar 

  45. Sazima, M., Buzato, S. & Sazima, I. Dyssochroma viridiflorum (Solanaceae): a reproductively bat-dependent epiphyte from the Atlantic rainforest in Brazil. Ann. Bot. 92, 725–730 (2003).

    Article  PubMed  PubMed Central  Google Scholar 

  46. Pilosof, S., Porter, M. A., Pascual, M. & Kéfi, S. The multilayer nature of ecological networks. Nat. Ecol. Evol. 1, 0101 (2017).

    Article  Google Scholar 

  47. Dormann, C. F., Gruber, B. & Fründ, J. Introducing the bipartite package: analysing ecological networks. R. News 8, 8–11 (2008).

    Google Scholar 

  48. R Core Team R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, 2019).

  49. Beckett, S. J. Improved community detection in weighted bipartite networks. R. Soc. Open Sci. 3, 140536 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  50. Gotelli, N. J. & Graves, G. R. Null Models in Ecology (Smithsonian Institution Press, 1996).

  51. Ulrich, W., Almeida-Neto, M. & Gotelli, N. J. A consumer’s guide to nestedness analysis. Oikos 118, 3–17 (2009).

    Article  Google Scholar 

  52. Vázquez, D. P. et al. Species abundance and asymmetric interaction strength in ecological networks. Oikos 116, 1120–1127 (2007).

    Article  Google Scholar 

  53. Dávalos, L. M., Cirranello, A. L., Geisler, J. H. & Simmons, N. B. Understanding phylogenetic incongruence: lessons from phyllostomid bats. Biol. Rev. 87, 991–1024 (2012).

    Article  PubMed  Google Scholar 

  54. Cirtwill, A. R. et al. A review of species role concepts in food webs. Food Webs 16, e00093 (2018).

    Article  Google Scholar 

  55. Martín González, A. M., Dalsgaard, B. & Olesen, J. M. Centrality measures and the importance of generalist species in pollination networks. Ecol. Complex. 7, 36–43 (2010).

    Article  Google Scholar 

  56. Bates, D., Mächler, M., Bolker, B. & Walker, S. Fitting linear mixed-effects models using lme4. Drug Inf. J. 35, 1215–1225 (2014).

    Google Scholar 

  57. Santana, S. E. Quantifying the effect of gape and morphology on bite force: biomechanical modelling and in vivo measurements in bats. Funct. Ecol. 30, 557–565 (2016).

    Article  Google Scholar 

  58. Brown, J. H., Stevens, G. C. & Kaufman, D. M. The geographic range: size, shape, boundaries, and internal structure. Annu. Rev. Ecol. Syst. 27, 597–623 (1996).

    Article  Google Scholar 

  59. MacArthur, R. H. Geographical Ecology: Patterns in the Distribution of Species (Princeton Univ. Press, 1972).

  60. Woodward, G. et al. Body size in ecological networks. Trends Ecol. Evol. 20, 402–409 (2005).

    Article  PubMed  Google Scholar 

  61. Rosseel, Y. lavaan: an R package for structural equation modeling. J. Stat. Softw. 48, 1–36 (2012).

    Article  Google Scholar 

Download references

Acknowledgements

We are deeply grateful to all naturalists who carried out fieldwork in the Neotropics over several decades and collected the information used to build our dataset. J. Bronstein gave invaluable suggestions for an early draft of this study. P. Guimarães Jr, T. Quental and T. Lewinsohn discussed with us the assembly rules of interaction networks. P. Jordano, C. Dormann and K. Ognyanova gave us invaluable tips on how to analyse and draw networks in R. M. White and the StackOverflow community helped us build the model used in the latent variable analysis. M.A.R.M. was funded by the São Paulo Research Foundation (FAPESP, no. 2018/20695-7), Research Dean of the University of São Paulo (PRP-USP, no. 18.1.660.41.7), the Brazilian Council for Scientific and Technological Development (CNPq, no. 302700/2016-1), Minas Gerais Research Foundation (FAPEMIG, no. PPM-00324-15), and the Alexander von Humboldt Foundation (AvH, no. 3.4-8151/15037). G.M.F. and R.B.P.P. received scholarships from the Brazilian Coordination for the Improvement of Higher Education Personnel (CAPES) and CNPq through the Graduate School in Ecology of the Federal University of Minas Gerais. R.L.M. received scholarships from FAPESP (nos. 2015/17739-4 and 2017/01816-0). S.E.S. was supported by the National Science Foundation (no. NSF-1456375). N.L. received a scholarship from CNPq and The World Academy of Sciences (no. 312518/2015-3) and grants from CAPES (no. 88887.308754/2018-00) and Pernambuco Research Foundation (FACEPE, no. BCT-0426-1.05/18). F.A.R. acknowledges CNPq (no. 307974/2013-8) and FAPESP (nos. 17/50144-0 and 16/25682-5) for the financial support given for his research, and the Leverhulme Trust for the Visiting Professorship provided.

Author information

Authors and Affiliations

  1. Department of Ecology, Institute of Biosciences, University of São Paulo, São Paulo, Brazil

    Marco A. R. Mello

  2. Graduate School in Ecology, State University of Campinas, Campinas, Brazil

    Gabriel M. Felix

  3. Graduate School in Ecology, Conservation, and Wildlife Management, Federal University of Minas Gerais, Belo Horizonte, Brazil

    Rafael B. P. Pinheiro

  4. Graduate School in Ecology and Biodiversity, São Paulo State University, Rio Claro, Brazil

    Renata L. Muylaert

  5. Bat Conservation International, Austin, TX, USA

    Cullen Geiselman

  6. Department of Biology and Burke Museum of Natural History and Culture, University of Washington, Seattle, WA, USA

    Sharlene E. Santana

  7. Institute of Evolutionary Ecology and Conservation Genomics, Ulm University, Ulm, Germany

    Marco Tschapka

  8. Smithsonian Tropical Research Institute, Balboa Ancon, Panama

    Marco Tschapka

  9. Department of Applied Mathematics and Statistics, University of São Paulo, São Carlos, Brazil

    Nastaran Lotfi & Francisco A. Rodrigues

  10. Physics Department, Federal University of Pernambuco, Recife, Brazil

    Nastaran Lotfi

  11. Mathematics Institute, University of Warwick, Coventry, UK

    Francisco A. Rodrigues

  12. Centre for Complexity Science, University of Warwick, Coventry, UK

    Francisco A. Rodrigues

  13. Department of Natural Resources Management and Museum of Texas Tech University, Lubbock, TX, USA

    Richard D. Stevens

Authors
  1. Marco A. R. Mello
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Gabriel M. Felix
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Rafael B. P. Pinheiro
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Renata L. Muylaert
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Cullen Geiselman
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Sharlene E. Santana
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Marco Tschapka
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Nastaran Lotfi
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Francisco A. Rodrigues
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Richard D. Stevens
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

M.A.R.M. conceived the project. The first version of the working question, hypothesis and predictions was created by M.A.R.M. together with R.B.P.P. and G.M.F., and all authors contributed to improving the logical argument of the study. C.G. and M.T. acquired the literature data and field data used to build the dataset of bat–plant interactions, and M.A.R.M. updated the dataset. S.E.S. reconstructed the bat phylogeny. S.E.S. and R.D.S. built the dataset on bat morphology and performance. F.A.R. and N.L. developed the new multilayer version of the centrality metrics. M.A.R.M., R.L.M., R.B.P.P., G.M.F., F.A.R. and N.L. performed tasks related to data analysis and coding in R and Python. The first draft of the manuscript was written by M.A.R.M., R.B.P.P., G.M.F. and R.L.M., and all authors contributed to editing the text.

Corresponding author

Correspondence to Marco A. R. Mello.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Supplementary Information

Supplementary data, methods, results and glossary.

Reporting Summary

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Mello, M.A.R., Felix, G.M., Pinheiro, R.B.P. et al. Insights into the assembly rules of a continent-wide multilayer network. Nat Ecol Evol 3, 1525–1532 (2019). https://doi.org/10.1038/s41559-019-1002-3

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41559-019-1002-3

This article is cited by

Search

Advanced search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing