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Climate drives global functional trait variation in lizards

Abstract

A major challenge in ecology and evolution is to disentangle the mechanisms driving broad-scale variation in biological traits such as body size, colour, thermal physiology traits and behaviour. Climate has long been thought to drive trait evolution and abiotic filtering of trait variation in ectotherms because their thermal performance and fitness are closely related to environmental conditions. However, previous studies investigating climatic variables associated with trait variation have lacked a mechanistic description of the underpinning processes. Here, we use a mechanistic model to predict how climate affects thermal performance of ectotherms and thereby the direction and strength of the effect of selection on different functional traits. We show that climate drives macro-evolutionary patterns in body size, cold tolerance and preferred body temperatures among lizards, and that trait variation is more constrained in regions where selection is predicted to be stronger. These findings provide a mechanistic explanation for observations on how climate drives trait variation in ectotherms through its effect on thermal performance. By connecting physical, physiological and macro-evolutionary principles, the model and results provide an integrative, mechanistic framework for predicting organismal responses to present climates and climate change.

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Fig. 1: Model description.
Fig. 2: Sensitivity of thermal performance to each functional trait.
Fig. 3: Relationship between mean species traits and predicted sensitivity.
Fig. 4: Trait variances of species assemblages in relation to the absolute value of sensitivity.

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Data availability

The data that support the findings of this study62 are openly available in Figshare under https://doi.org/10.6084/m9.figshare.19949315.

Code availability

The R code used to compute the sensitivity analysis is available in the GitHub repository: github.com/JRubalcaba/Tb_sensitivity_analysis.

References

  1. Higham, T. E. et al. Linking ecomechanical models and functional traits to understand phenotypic diversity. Trends Ecol. Evol. 36, 860–873 (2021).

    Article  PubMed  Google Scholar 

  2. Kearney, M. R., Jusup, M., McGeoch, M. A., Kooijman, S. A. & Chown, S. L. Where do functional traits come from? The role of theory and models. Funct. Ecol. 35, 1385–1396 (2021).

    Article  CAS  Google Scholar 

  3. Mayr, E. Geographical character gradients and climatic adaptation. Evolution 10, 105–108 (1956).

    Article  Google Scholar 

  4. Gaston, K. J., Chown, S. L. & Evans, K. L. Ecogeographical rules: elements of a synthesis. J. Biogeogr. 35, 483–500 (2008).

    Article  Google Scholar 

  5. Chown, S. L. & Gaston, K. J. Macrophysiology for a changing world. Proc. R. Soc. B 275, 1469–1478 (2008).

    Article  PubMed  PubMed Central  Google Scholar 

  6. Rubalcaba, J. G. & Jimeno, B. Biophysical models unravel associations between glucocorticoids and thermoregulatory costs across avian species. Funct. Ecol. 36, 64–72 (2022).

    Article  CAS  Google Scholar 

  7. Anderson, R. O., White, C. R., Chapple, D. G. & Kearney, M. R. A hierarchical approach to understanding physiological associations with climate. Glob. Ecol. Biogeogr. 31, 332–346 (2022).

    Article  Google Scholar 

  8. Angilletta, M. J. Jr, Niewiarowski, P. H. & Navas, C. A. The evolution of thermal physiology in ectotherms. J. Therm. Biol. 27, 249–268 (2002).

    Article  Google Scholar 

  9. Olalla‐Tárraga, M. Á., Rodríguez, M. Á. & Hawkins, B. A. Broad‐scale patterns of body size in squamate reptiles of Europe and North America. J. Biogeogr. 33, 781–793 (2006).

    Article  Google Scholar 

  10. Amado, T., Moreno Pinto, M. G. & Olalla‐Tárraga, M. Á. Anuran 3D models reveal the relationship between surface area‐to‐volume ratio and climate. J. Biogeogr. 46, 1429–1437 (2019).

    Google Scholar 

  11. Castro, K. M. S. A. et al. Water constraints drive allometric patterns in the body shape of tree frogs. Sci. Rep. 11, 1218 (2021).

  12. Clusella-Trullas, S., Terblanche, J. S., Blackburn, T. M. & Chown, S. L. Testing the thermal melanism hypothesis: a macrophysiological approach. Funct. Ecol. 22, 232–238 (2008).

  13. Ghalambor, C. K., Huey, R. B., Martin, P. R., Tewksbury, J. J. & Wang, G. Are mountain passes higher in the tropics? Janzen’s hypothesis revisited. Integr. Comp. Biol. 46, 5–17 (2006).

    Article  PubMed  Google Scholar 

  14. Bennett, J. M. et al. The evolution of critical thermal limits of life on Earth. Nat. Commun. 12, 1198 (2021).

  15. Sunday, J. M. et al. Thermal-safety margins and the necessity of thermoregulatory behavior across latitude and elevation. Proc. Natl Acad. Sci. USA 111, 5610–5615 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Muñoz, M. M. The Bogert effect, a factor in evolution. Evolution 76, 49–66 (2021).

    Article  PubMed  Google Scholar 

  17. Bogert, C. M. Thermoregulation in reptiles, a factor in evolution. Evolution 3, 195–211 (1949).

    Article  CAS  PubMed  Google Scholar 

  18. Huey, R. B., Hertz, P. E. & Sinervo, B. Behavioral drive versus behavioral inertia in evolution: a null model approach. Am. Nat. 161, 357–366 (2003).

    Article  PubMed  Google Scholar 

  19. Kearney, M. R. & Porter, W. P. NicheMapR—an R package for biophysical modelling: the microclimate model. Ecography 40, 664–674 (2017).

    Article  Google Scholar 

  20. Messier, J., McGill, B. J., Enquist, B. J. & Lechowicz, M. J. Trait variation and integration across scales: is the leaf economic spectrum present at local scales? Ecography 40, 685–697 (2017).

    Article  Google Scholar 

  21. Ricklefs, R. E. & Schluter, D. (eds) Species Diversity in Ecological Communities: Historical and Geographical Perspectives (Univ. Chicago Press, 1993).

  22. Angilletta, M. J. Jr, Steury, T. D. & Sears, M. W. Temperature, growth rate, and body size in ectotherms: fitting pieces of a life-history puzzle. Integr. Comp. Biol. 44, 498–509 (2004).

    Article  PubMed  Google Scholar 

  23. Pincheira-Donoso, D. The balance between predictions and evidence and the search for universal macroecological patterns: taking Bergmann’s rule back to its endothermic origin. Theory Biosci. 129, 247–253 (2010).

    Article  PubMed  Google Scholar 

  24. Slavenko, A. et al. Global patterns of body size evolution in squamate reptiles are not driven by climate. Glob. Ecol. Biogeogr. 28, 471–483 (2019).

    Article  Google Scholar 

  25. Stevenson, R. D. Body size and limits to the daily range of body temperature in terrestrial ectotherms. Am. Nat. 125, 102–117 (1985).

    Article  Google Scholar 

  26. Rubalcaba, J. G., Gouveia, S. F. & Olalla‐Tárraga, M. A. A mechanistic model to scale up biophysical processes into geographical size gradients in ectotherms. Glob. Ecol. Biogeogr. 28, 793–803 (2019).

    Article  Google Scholar 

  27. Rubalcaba, J. G. & Olalla‐Tárraga, M. Á. The biogeography of thermal risk for terrestrial ectotherms: scaling of thermal tolerance with body size and latitude. J. Anim. Ecol. 89, 1277–1285 (2020).

    Article  PubMed  Google Scholar 

  28. Pincheira-Donoso, D., Hodgson, D. J. & Tregenza, T. The evolution of body size under environmental gradients in ectotherms: why should Bergmann’s rule apply to lizards? BMC Evol. Biol. 8, 68 (2008).

  29. Jablonski, D. Biotic interactions and macroevolution: extensions and mismatches across scales and levels. Evolution 62, 715–739 (2008).

    Article  PubMed  Google Scholar 

  30. Kearney, M. R., Porter, W. P. & Huey, R. B. Modelling the joint effects of body size and microclimate on heat budgets and foraging opportunities of ectotherms. Methods Ecol. Evol. 12, 458–467 (2021).

    Article  Google Scholar 

  31. Campbell-Staton, S. C., Bare, A., Losos, J. B., Edwards, S. V. & Cheviron, Z. A. Physiological and regulatory underpinnings of geographic variation in reptilian cold tolerance across a latitudinal cline. Mol. Ecol. 27, 2243–2255 (2018).

    Article  CAS  PubMed  Google Scholar 

  32. Boretto, J. M., Fernández, J. B., Cabezas-Cartes, F., Medina, M. S. & Ibargüengoytía, N. R. in Lizards of Patagonia (eds Morando, M. & Avila, L. J.) 335–371 (Springer, 2020).

  33. Deutsch, C. A. et al. Impacts of climate warming on terrestrial ectotherms across latitude. Proc. Natl Acad. Sci. USA 105, 6668–6672 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Araújo, M. B. et al. Heat freezes niche evolution. Ecol. Lett. 16, 1206–1219 (2013).

    Article  PubMed  Google Scholar 

  35. Sunday, J. M., Bates, A. E. & Dulvy, N. K. Global analysis of thermal tolerance and latitude in ectotherms. Proc. R. Soc. B 278, 1823–1830 (2011).

    Article  PubMed  Google Scholar 

  36. Hoffmann, A. A., Chown, S. L. & Clusella‐Trullas, S. Upper thermal limits in terrestrial ectotherms: how constrained are they? Funct. Ecol. 27, 934–949 (2013).

    Article  Google Scholar 

  37. Sunday, J. et al. Thermal tolerance patterns across latitude and elevation. Philos. Trans. R. Soc. B 374, 20190036 (2019).

    Article  Google Scholar 

  38. Huey, R. B. & Slatkin, M. Cost and benefits of lizard thermoregulation. Q. Rev. Biol. 51, 363–384 (1976).

    Article  CAS  PubMed  Google Scholar 

  39. Vasseur, D. A. et al. Increased temperature variation poses a greater risk to species than climate warming. Proc. R. Soc. B 281, 20132612 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  40. Porter, W. P., Mitchell, J. W., Beckman, W. A. & DeWitt, C. B. Behavioral implications of mechanistic ecology. Oecologia 13, 1–54 (1973).

    Article  CAS  PubMed  Google Scholar 

  41. Hertz, P. E., Huey, R. B. & Stevenson, R. D. Evaluating temperature regulation by field-active ectotherms: the fallacy of the inappropriate question. Am. Nat. 142, 796–818 (1993).

    Article  CAS  PubMed  Google Scholar 

  42. Fey, S. B. et al. Opportunities for behavioral rescue under rapid environmental change. Glob. Change Biol. 25, 3110–3120 (2019).

    Article  Google Scholar 

  43. Martin, T. L. & Huey, R. B. Why ‘suboptimal’ is optimal: Jensen’s inequality and ectotherm thermal preferences. Am. Nat. 171, E102–E118 (2008).

    Article  PubMed  Google Scholar 

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

  45. Campbell, G. S. & Norman, J. M. An Introduction to Environmental Biophysics 2nd edn (Springer-Verlag, 1998).

  46. Mao, J. & Yan, B. Global Monthly Mean Leaf Area Index Climatology, 1981–2015 (ORNL DAAC, 2019).

  47. Meiri, S. et al. Are lizards feeling the heat? A tale of ecology and evolution under two temperatures. Glob. Ecol. Biogeogr. 22, 834–845 (2013).

    Article  Google Scholar 

  48. Marino, S., Hogue, I. B., Ray, C. J. & Kirschner, D. E. A methodology for performing global uncertainty and sensitivity analysis in systems biology. J. Theor. Biol. 254, 178–196 (2008).

    Article  PubMed  PubMed Central  Google Scholar 

  49. Renardy, M., Hult, C., Evans, S., Linderman, J. J. & Kirschner, D. E. Global sensitivity analysis of biological multiscale models. Curr. Opin. Biomed. Eng. 11, 109–116 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  50. Carnell, R. lhs: Latin hypercube samples. R package version 1.1.1 (2020).

  51. Meiri, S. Traits of lizards of the world: variation around a successful evolutionary design. Glob. Ecol. Biogeogr. 27, 1168–1172 (2018).

    Article  Google Scholar 

  52. Clusella-Trullas, S., Blackburn, T. M. & Chown, S. L. Climatic predictors of temperature performance curve parameters in ectotherms imply complex responses to climate change. Am. Nat. 177, 738–751 (2011).

    Article  PubMed  Google Scholar 

  53. Bennett, J. M. et al. GlobTherm, a global database on thermal tolerances for aquatic and terrestrial organisms. Sci. Data 5, 180022 (2018).

  54. Roll, U. et al. The global distribution of tetrapods reveals a need for targeted reptile conservation. Nat. Ecol. Evol. 1, 1677–1682 (2017).

    Article  PubMed  Google Scholar 

  55. Tonini, J. F. R., Beard, K. H., Ferreira, R. B., Jetz, W. & Pyron, R. A. Fully-sampled phylogenies of squamates reveal evolutionary patterns in threat status. Biol. Conserv. 204, 23–31 (2016).

    Article  Google Scholar 

  56. Ives, A. R. R2s for correlated data: phylogenetic models, LMMs, and GLLMs. Syst. Biol. 68, 234–251 (2019).

    Article  PubMed  Google Scholar 

  57. Johnson, T. F., Isaac, N. J. B., Paviolo, A. & González-Suárez, M. Handling missing values in trait data. Glob. Ecol. Biogeogr. 30, 51–62 (2020).

    Article  Google Scholar 

  58. Goolsby, E. W., Bruggeman, J. & Ané, C. Rphylopars: fast multivariate phylogenetic comparative methods for missing data and within‐species variation. Methods Ecol. Evol. 8, 22–27 (2017).

    Article  Google Scholar 

  59. Koenker, R. et al. Package ‘quantreg’ (R-CRAN, 2018); https://cran.r-project.org/web/packages/quantreg/quantreg.pdf

  60. Griffith, D. A. & Peres-Neto, P. R. Spatial modeling in ecology: the flexibility of eigenfunction spatial analyses. Ecology 87, 2603–2613 (2006).

    Article  PubMed  Google Scholar 

  61. Bivand, R. R packages for analyzing spatial data: a comparative case study with areal data. Geogr. Anal. 54, 488–518 (2022).

    Article  Google Scholar 

  62. Rubalcaba, J. G. et al. Data: ‘Climate drives global functional trait variation in lizards’. figshare https://doi.org/10.6084/m9.figshare.19949315 (2022).

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Acknowledgements

This project has received funding from the European Union Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement no. 843094 to J.G.R. The authors S.F.G., F.V., and M.Á.O-T. are members of the INCT-EECBio (CNPq-FAPEG, grant 380733/2017-0). The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript.

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Conceptualization and design of this study was by J.G.R., S.F.G., F.V., M.Á.O-T. and J.S. The model and sensitivity analysis were developed by J.G.R. Data analyses were performed by J.G.R., S.F.G. and F.V. Funding was obtained by J.G.R. with supervision by J.S. and M.Á.O-T. All co-authors wrote the first draft and contributed to subsequent revisions of the manuscript.

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Correspondence to Juan G. Rubalcaba.

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Rubalcaba, J.G., Gouveia, S.F., Villalobos, F. et al. Climate drives global functional trait variation in lizards. Nat Ecol Evol 7, 524–534 (2023). https://doi.org/10.1038/s41559-023-02007-x

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