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Global determinants of zoogeographical boundaries

Abstract

The distribution of living organisms on Earth is spatially structured. Early biogeographers identified the existence of multiple zoogeographical regions, characterized by faunas with homogeneous composition that are separated by biogeographical boundaries. Yet, no study has deciphered the factors shaping the distributions of terrestrial biogeographical boundaries at the global scale. Here, using spatial regression analyses, we show that tectonic movements, sharp changes in climatic conditions and orographic barriers determine extant biogeographical boundaries. These factors lead to abrupt zoogeographical transitions when they act in concert, but their prominence varies across the globe. Clear differences exist among boundaries representing profound or shallow dissimilarities between faunas. Boundaries separating zoogeographical regions with limited divergence occur in areas with abrupt climatic transitions. In contrast, plate tectonics determine the separation between deeply divergent biogeographical realms, particularly in the Old World. Our study reveals the multiple drivers that have shaped the biogeographical regions of the world.

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Figure 1: The global zoogeographical regions of the world.
Figure 2: Relative importance of plate tectonics, altitude and climate on the boundary positions of the biogeographical regions worldwide.
Figure 3: Geographical variability of the importance of tectonics, altitude and climate on the position of biogeographical boundaries.
Figure 4: Factors most strongly related to the presence of biogeographical boundaries.

References

  1. 1

    Fabricius, J. C. Philosophia Entomologica (Impensis Carol. Ernest. Bohnii, 1778).

    Google Scholar 

  2. 2

    De Candolle, A. P. Essai Élémentaire de Géographie Botanique (F. Levrault, 1820).

    Google Scholar 

  3. 3

    Swainson, W. A Treatise on the Geography and Classification of Animals (Longman, Rees, Brown, Green, & Longman, 1835).

    Google Scholar 

  4. 4

    Wallace, A. R. The Geographical Distribution of Animals (Harper, 1876).

    Google Scholar 

  5. 5

    Sclater, P. L. On the general geographical distribution of the members of the class Aves. J. Proc. Linn. Soc. Lond. Zool. 2, 130–145 (1858).

    Article  Google Scholar 

  6. 6

    Cox, B. The biogeographic regions reconsidered. J. Biogeogr. 28, 511–523 (2001).

    Article  Google Scholar 

  7. 7

    Morrone, J. J. Biogeographical regionalisation of the world: a reappraisal. Aust. Syst. Bot. 28, 81–90 (2015).

    Article  Google Scholar 

  8. 8

    Crisci, J. V., Cigliano, M. M., Morrone, J. J. & Roig-Junent, S. Historical biogeography of southern South America. Syst. Biol. 40, 152–171 (1991).

    Article  Google Scholar 

  9. 9

    Rueda, M., Rodriguez, M. A. & Hawkins, B. A. Towards a biogeographic regionalization of the European biota. J. Biogeogr. 37, 2067–2076 (2010).

    Article  Google Scholar 

  10. 10

    Proches, S. & Ramdhani, S. The world’s zoogeographical regions confirmed by cross-taxon analyses. Bioscience 62, 260–270 (2012).

    Article  Google Scholar 

  11. 11

    Holt, B. et al. An update of Wallace’s zoogeographic regions of the world. Science 339, 74–78 (2013).

    CAS  Article  PubMed  Google Scholar 

  12. 12

    Rueda, M., Rodriguez, M. A. & Hawkins, B. A. Identifying global zoogeographical regions: lessons from Wallace. J. Biogeogr. 40, 2215–2225 (2013).

    Article  Google Scholar 

  13. 13

    Vilhena, D. A. & Antonelli, A. A network approach for identifying and delimiting biogeographical regions. Nat. Commun. 6, 6848 (2015).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  14. 14

    Kreft, H. & Jetz, W. A framework for delineating biogeographical regions based on species distributions. J. Biogeogr. 37, 2029–2053 (2010).

    Article  Google Scholar 

  15. 15

    Edler, D., Guedes, T., Zizka, A., Rosvall, M. & Antonelli, A. Infomap bioregions: interactive mapping of biogeographical regions from species distributions. Syst. Biol. https://doi.org/10.1093/sysbio/syw087 (in the press).

  16. 16

    Lomolino, M. V., Riddle, B. R., Whittaker, R. J. & Brown, J. H. Biogeography 4th edn (Sinauer Associates, 2010).

    Google Scholar 

  17. 17

    Riddle, B. R. & Hafner, D. J. Integrating pattern with process at biogeographic boundaries: the legacy of Wallace. Ecography 33, 321–325 (2010).

    Article  Google Scholar 

  18. 18

    Glor, R. E. & Warren, D. Testing ecological explanations for biogeographic boundaries. Evolution 65, 673–683 (2011).

    Article  PubMed  Google Scholar 

  19. 19

    Kreft, H. & Jetz, W. Comment on ‘An update of Wallace’s zoogeographic regions of the world’. Science 341, 343 (2013).

    CAS  Article  PubMed  Google Scholar 

  20. 20

    Sexton, J. P., McIntyre, P. J., Angert, A. L. & Rice, K. J. Evolution and ecology of species range limits. Annu. Rev. Ecol. Evol. Syst. 40, 415–436 (2009).

    Google Scholar 

  21. 21

    Buckley, L. B. & Jetz, W. Linking global turnover of species and environments. Proc. Natl Acad. Sci. USA 105, 17836–17841 (2008).

    CAS  Article  PubMed  Google Scholar 

  22. 22

    Melo, A. S., Rangel, T. F. L. V. B. & Diniz-Filho, J. A. F. Environmental drivers of beta-diversity patterns in New-World birds and mammals. Ecography 32, 226–236 (2009).

    Article  Google Scholar 

  23. 23

    Graham, R. W. et al. Spatial response of mammals to Late Quaternary environmental fluctuations. Science 272, 1601–1606 (1996).

    CAS  Article  PubMed  Google Scholar 

  24. 24

    Davis, M. B. & Shaw, R. G. Range shifts and adaptive responses to Quaternary climate change. Science 292, 673–679 (2001).

    CAS  Article  PubMed  Google Scholar 

  25. 25

    Taberlet, P., Fumagalli, L., Wust-Saucy, A. G. & Cosson, J. F. Comparative phylogeography and postglacial colonization routes in Europe. Mol. Ecol. 7, 453–464 (1998).

    CAS  Article  PubMed  Google Scholar 

  26. 26

    Sandel, B. et al. The influence of Late Quaternary climate-change velocity on species endemism. Science 334, 660–664 (2011).

    CAS  Article  PubMed  Google Scholar 

  27. 27

    Mao, K. S. et al. Distribution of living Cupressaceae reflects the breakup of Pangea. Proc. Natl Acad. Sci. USA 109, 7793–7798 (2012).

    CAS  Article  PubMed  Google Scholar 

  28. 28

    Chan, W.-P. et al. Seasonal and daily climate variation have opposite effects on species elevational range size. Science 351, 1437–1439 (2016).

    CAS  Article  PubMed  Google Scholar 

  29. 29

    Bivand, R., Pebesma, E. J. & Gómez-Rubio, V. Applied Spatial Data Analysis with R (Springer, 2008).

    Google Scholar 

  30. 30

    Vermeij, G. J. When biotas meet: understanding biotic interchange. Science 253, 1099–1104 (1991).

    CAS  Article  PubMed  Google Scholar 

  31. 31

    Simpson, G. G. S. Splendid Isolation: The Curious History of South American Mammals (Yale Univ. Press, 1980).

    Google Scholar 

  32. 32

    Bacon, C. D. et al. Biological evidence supports an early and complex emergence of the Isthmus of Panama. Proc. Natl Acad. Sci. USA 112, 6110–6115 (2015).

    CAS  Article  PubMed  Google Scholar 

  33. 33

    Daza, J. M., Castoe, T. A. & Parkinson, C. L. Using regional comparative phylogeographic data from snake lineages to infer historical processes in middle America. Ecography 33, 343–354 (2010).

    Google Scholar 

  34. 34

    Montes, C. et al. Middle Miocene closure of the Central American Seaway. Science 348, 226 (2015).

    CAS  Article  PubMed  Google Scholar 

  35. 35

    Müller, P. Aspects of Biogeography (Springer, 1974).

    Book  Google Scholar 

  36. 36

    Holt, B. G. et al. Response to comment on ‘An update of Wallace’s zoogeographic regions of the world’. Science 341, 343 (2013).

    CAS  Article  PubMed  Google Scholar 

  37. 37

    Seton, M. et al. Global continental and ocean basin reconstructions since 200 Ma. Earth-Sci. Rev. 113, 212–270 (2012).

    Article  Google Scholar 

  38. 38

    Briggs, J. C. Biogeography and Plate Tectonics (Elsevier, 1987).

    Google Scholar 

  39. 39

    He, J., Kreft, H., Gao, E., Wang, Z. & Jiang, H. Patterns and drivers of zoogeographical regions of terrestrial vertebrates in China. J. Biogeogr. https://doi.org/10.1111/jbi.12892 (2016).

    Article  Google Scholar 

  40. 40

    Smith, B. T. & Klicka, J. The profound influence of the Late Pliocene Panamanian uplift on the exchange, diversification, and distribution of New World birds. Ecography 33, 333–342 (2010).

    Article  Google Scholar 

  41. 41

    Pomara, L. Y., Ruokolainen, K. & Young, K. R. Avian species composition across the Amazon River: the roles of dispersal limitation and environmental heterogeneity. J. Biogeogr. 41, 784–796 (2014).

    Article  Google Scholar 

  42. 42

    Hurlbert, A. H. & Jetz, W. Species richness, hotspots, and the scale dependence of range maps in ecology and conservation. Proc. Natl Acad. Sci. USA 104, 13384–13389 (2007).

    CAS  Article  PubMed  Google Scholar 

  43. 43

    Ficetola, G. F. et al. An evaluation of the robustness of global amphibian range maps. J. Biogeogr. 41, 211–221 (2014).

    Article  Google Scholar 

  44. 44

    Hijmans, R. J., Cameron, S. E., Parra, J. L., Jones, P. G. & Jarvis, A. High resolution interpolated climate surfaces for global land areas. Int. J. Climatol. 25, 1965–1978 (2005).

    Article  Google Scholar 

  45. 45

    Boucher-Lalonde, V., Morin, A. & Currie, D. J. A consistent occupancy–climate relationship across birds and mammals of the Americas. Oikos 123, 1029–1036 (2014).

    Article  Google Scholar 

  46. 46

    Harrison, S. P., Bartlein, P. J. & Prentice, I. C. What have we learnt from palaeoclimate simulations? J. Quaternary Sci. 31, 363–385 (2016).

    Article  Google Scholar 

  47. 47

    Harrison, S. P. et al. Evaluation of CMIP5 palaeo-simulations to improve climate projections. Nat. Clim. Change 5, 735–743 (2015).

    Article  Google Scholar 

  48. 48

    Mauri, A., Davis, B. A. S., Collins, P. M. & Kaplan, J. O. The influence of atmospheric circulation on the mid-Holocene climate of Europe: a data-model comparison. Clim. Past 10, 1925–1938 (2014).

    Article  Google Scholar 

  49. 49

    Williams, S., Müller, R., Landgrebe, T. & Whittaker, J. An open-source software environment for visualizing and refining plate tectonic reconstructions using high-resolution geological and geophysical data sets. GSA Today 22, 4–9 (2012).

    Article  Google Scholar 

  50. 50

    Boyden, J. A. et al. in Geoinformatics: Cyberinfrastructure for the Solid Earth Sciences (eds Keller G. R. & Baru C. ) 99–113 (Cambridge Univ. Press, 2011).

    Google Scholar 

  51. 51

    Beale, C. M., Lennon, J. J., Yearsley, J. M., Brewer, M. J. & Elston, D. A. Regression analysis of spatial data. Ecol. Lett. 13, 246–264 (2010).

    Article  PubMed  Google Scholar 

  52. 52

    Dormann, C. F. et al. Methods to account for spatial autocorrelation in the analysis of species distributional data: a review. Ecography 30, 609–628 (2007).

    Article  Google Scholar 

  53. 53

    Kissling, W. D. & Carl, G. Spatial autocorrelation and the selection of simultaneous autoregressive models. Global Ecol. Biogeogr. 17, 59–71 (2008).

    Article  Google Scholar 

  54. 54

    Alam, M., Roennegard, L. & Shen, X. Fitting conditional and simultaneous autoregressive spatial models in hglm. R Journal 7, 5–18 (2015).

    Article  Google Scholar 

  55. 55

    Rousset, F. & Ferdy, J.-B. Testing environmental and genetic effects in the presence of spatial autocorrelation. Ecography 37, 781–790 (2014).

    Article  Google Scholar 

  56. 56

    Dormann, C. F. et al. Collinearity: a review of methods to deal with it and a simulation study evaluating their performance. Ecography 36, 27–46 (2013).

    Article  Google Scholar 

  57. 57

    Hijmans, R. J. raster: Geographic Data Analysis and Modeling. R package version 2.5-2 (2015); http://CRAN.R-project.org/package=raster

  58. 58

    Ronnegard, L., Shen, X. & Alam, M. hglm: a package for fitting hierarchical generalized linear models. R Journal 2, 20–28 (2010).

    Article  Google Scholar 

  59. 59

    Fox, J. & Weisberg, S. An R Companion to Applied Regression (Sage, 2011).

    Google Scholar 

  60. 60

    Bivand, R. & Lewin-Koh, N. maptools: Tools for Reading and Handling Spatial Objects (www.r-project.org, 2014).

  61. 61

    Allouche, O., Tsoar, A. & Kadmon, R. Assessing the accuracy of species distribution models: prevalence, kappa and the true skill statistic (TSS). J. Appl. Ecol. 43, 1223–1232 (2006).

    Article  Google Scholar 

  62. 65

    Rosenthal, R. in The Handbook of Research Synthesis (eds Cooper, H. & Hedges, L. V. ) 231–244 (Russel Sage Foundation, 1994).

    Google Scholar 

  63. 62

    Mellin, C., Mengersen, K., Bradshaw, C. J. A. & Caley, M. J. Generalizing the use of geographical weights in biodiversity modelling. Global Ecol. Biogeogr. 23, 1314–1323 (2014).

    Article  Google Scholar 

  64. 63

    Nakaya, T., Fotheringham, A. S., Brunsdon, C. & Charlton, M. Geographically weighted Poisson regression for disease association mapping. Stat. Med. 24, 2695–2717 (2005).

    CAS  Article  PubMed  Google Scholar 

  65. 64

    da Silva, A. R. & Fotheringham, A. S. The multiple testing issue in geographically weighted regression. Geogr. Anal. 48, 233–247 (2016).

    Article  Google Scholar 

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Acknowledgements

We thank S. Ramdhani for providing high-resolution maps of bioregions. The research leading to these results has received funding from the European Research Council under the European Community’s Seven Framework Programme FP7/2007–2013 Grant Agreement no. 281422 (TEEMBIO). All authors belong to the Laboratoire d’Écologie Alpine, which is part of Labex OSUG@2020 (ANR10 LABX56).

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G.F.F., F.M. and W.T. conceived the study. G.F.F. performed all analyses with the help of F.M. G.F.F. wrote the first version of the manuscript, with contributions from F.M. and W.T.

Corresponding author

Correspondence to Gentile Francesco Ficetola.

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The authors declare no competing financial interests.

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Supplementary Figures 1–5, Supplementary Tables 1–5, Supplementary Discussion, Supplementary References. (PDF 1576 kb)

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Ficetola, G., Mazel, F. & Thuiller, W. Global determinants of zoogeographical boundaries. Nat Ecol Evol 1, 0089 (2017). https://doi.org/10.1038/s41559-017-0089

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