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Life rather than climate influences diversity at scales greater than 40 million years

Abstract

The diversity of life on Earth is controlled by hierarchical processes that interact over wide ranges of timescales1. Here, we consider the megaclimate regime2 at scales ≥1 million years (Myr). We focus on determining the domains of ‘wandering’ stochastic Earth system processes (‘Court Jester’3) and stabilizing biotic interactions that induce diversity dependence of fluctuations in macroevolutionary rates (‘Red Queen’4). Using state-of-the-art multiscale Haar and cross-Haar fluctuation analyses, we analysed the global genus-level Phanerozoic marine animal Paleobiology Database record of extinction rates (E), origination rates (O) and diversity (D) as well as sea water palaeotemperatures (T). Over the entire observed range from several million years to several hundred million years, we found that the fluctuations of T, E and O showed time-scaling behaviour. The megaclimate was characterized by positive scaling exponents—it is therefore apparently unstable. E and O are also scaling but with negative exponents—stable behaviour that is biotically mediated. For D, there were two regimes with a crossover at critical timescale \(\Delta {t}_{{\rm{trans}}}\) ≈ 40 Myr. For shorter timescales, D exhibited nearly the same positive scaling as the megaclimate palaeotemperatures, whereas for longer timescales it tracks the scaling of macroevolutionary rates. At scales of at least \(\Delta {t}_{{\rm{trans}}}\) there is onset of diversity dependence of E and O, probably enabled by mixing and synchronization (globalization) of the biota by geodispersal (‘Geo-Red Queen’).

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Fig. 1: Scaling of macroevolutionary metrics and sea water palaeotemperatures.
Fig. 2: Scale-dependant correlations of macroevolutionary and palaeoclimate variables.
Fig. 3: Scale-dependant correlations of macroevolutionary and palaeoclimate variables.
Fig. 4: Space–time scaling of dominance in macroevolutionary modes.

Data availability

The palaeobiological genus occurrence data are freely available for download in the Paleobiology Database https://paleobiodb.org/data1.2/occs/list.csv?datainfo&rowcount&base_name=Animalia&taxon_reso=genus&pres=regular&interval=cambrian,quaternary&envtype=marine. Other data—palaeotemperatures, tectonic rates and sea levels are available as supplementary data in the original cited articles.

Code availability

Macroevolutionary metrics were calculated in R v.3.6.0 using functions available in divDyn package. The scripts needed for the Phanerozoic-scale analysis of marine diversity with divDyn can be found at https://github.com/divDyn/ddPhanero/. Haar fluctuation, scaling and cross-Haar analyses were done using Mathematica custom-made code and can be accessed at http://www.physics.mcgill.ca/~gang/software/index.html.

References

  1. Gould, S. J. The Structure of Evolutionary Theory (Harvard Univ. Press, 2002).

  2. Lovejoy, S. A voyage through scales, a missing quadrillion and why the climate is not what you expect. Clim. Dynam. 44, 3187–3210 (2015).

    Article  Google Scholar 

  3. Barnosky, A. D. Distinguishing the effects of the Red Queen and Court Jester on Miocene mammal evolution in the northern Rocky Mountains. J. Vertebr. Paleontol. 21, 172–185 (2001).

    Article  Google Scholar 

  4. Van Valen, L. A new evolutionary law. Evol. Theory 1, 1–30 (1973).

    Google Scholar 

  5. Sepkoski, J. J. J. in Evolutionary Paleobiology (eds Jablonski, D. et al.) 211–255 (Univ. of Chicago Press, 1996).

  6. Cornette, J. L. & Lieberman, B. S. Random walks in the history of life. Proc. Natl Acad. Sci. USA 101, 187–191 (2004).

    ADS  CAS  PubMed  Article  Google Scholar 

  7. Hoffman, A. in Neutral Models in Biology (eds Nitecki, M. H. & Hoffman, A.)133–146 (Oxford Univ. Press, 1987).

  8. Benton, M. J. The Red Queen and the Court Jester: species diversity and the role of biotic and abiotic factors through time. Science 323, 728–732 (2009).

    ADS  CAS  PubMed  Article  Google Scholar 

  9. Alroy, J. The shifting balance of diversity among major marine animal groups. Science 329, 1191–1194 (2010).

    ADS  CAS  PubMed  Article  Google Scholar 

  10. Alroy, J. Geographical, environmental and intrinsic biotic controls on Phanerozoic marine diversification. Palaeontology 53, 1211–1235 (2010).

    Article  Google Scholar 

  11. Close, R. A. et al. The apparent exponential radiation of Phanerozoic land vertebrates is an artefact of spatial sampling biases. Proc. R. Soc. B 287, 20200372 (2020).

    PubMed  PubMed Central  Article  Google Scholar 

  12. Foote, M. in Evolution after Darwin: The first 150 years (eds Bell, M. A. et al.) 479–510 (Sinauer Associates, 2010).

  13. Foote, M., Cooper, R. A., Crampton, J. S. & Sadler, P. M. Diversity-dependent evolutionary rates in early Palaeozoic zooplankton. Proc. R. Soc. B 285, 20180122 (2018).

    PubMed  PubMed Central  Article  Google Scholar 

  14. Alroy, J. et al. Phanerozoic trends in the global diversity of marine invertebrates. Science 321, 97–100 (2008).

    ADS  CAS  PubMed  Article  Google Scholar 

  15. Lovejoy, S. Spectra, intermittency, and extremes of weather, macroweather and climate. Sci. Rep. 8, 12697 (2018).

  16. Eichenseer, K. et al. Jurassic shift from abiotic to biotic control on marine ecological success. Nat. Geosci. 12, 638–642 (2019).

    CAS  Article  Google Scholar 

  17. Patzkowsky, M. E. Origin and evolution of regional biotas: a deep-time perspective. Annu. Rev. Earth Planet. Sci. 45, 471–495 (2017).

    ADS  CAS  Article  Google Scholar 

  18. Jablonski, D. Approaches to macroevolution: 2. Sorting of variation, some overarching issues, and general conclusions. Evol. Biol. 44, 451–475 (2017).

    PubMed  PubMed Central  Article  Google Scholar 

  19. Rosenzweig, M. L. Species Diversity in Space and Time (Cambridge Univ Press, 1995).

  20. Gould, S. J. The paradox of the first tier: an agenda for paleobiology. Paleobiology 11, 2–12 (1985).

    Article  Google Scholar 

  21. Erwin, D. H. in Chance in Evolution (eds Ramsey, G. & and Pence, C. H.) 279–298 (Univ. Chicago Press, 2016).

  22. Jablonski, D. Scale and hierarchy in macroevolution. Palaeontology 50, 87–109 (2007).

    Article  Google Scholar 

  23. Jablonski, D. Approaches to macroevolution: 1. General concepts and origin of variation. Evol. Biol. 44, 427–450 (2017).

    PubMed  PubMed Central  Article  Google Scholar 

  24. Newman, M. & Palmer, R. Modeling Extinction (Oxford Univ. Press, 2003).

  25. Lovejoy, S. & Schertzer, D. Haar wavelets, fluctuations and structure functions: convenient choices for geophysics. Nonlin. Processes Geophys. 19, 513–527 (2012).

  26. Plotnick, R. E. & Sepkoski, J. J. J. A multiplicative multifractal model of originations and extinctions. Paleobiology 27, 126–139 (2001).

    Article  Google Scholar 

  27. Alroy, J. A more precise speciation and extinction rate estimator. Paleobiology 41, 633–639 (2015).

    Article  Google Scholar 

  28. Song, H., Wignall, P. B., Song, H., Dai, X. & Chu, D. Seawater temperature and dissolved oxygen over the past 500 million years. J. Earth Sci. 30, 236–243 (2019).

    Article  CAS  Google Scholar 

  29. Veizer, J. et al. 87Sr/86Sr, δ13C and δ18O evolution of Phanerozoic seawater. Chem. Geol. 161, 59–88 (1999).

    ADS  CAS  Article  Google Scholar 

  30. O’Brien, C. L. et al. Cretaceous sea-surface temperature evolution: constraints from TEX86 and planktonic foraminiferal oxygen isotopes. Earth Sci. Rev. 172, 224–247 (2017).

    ADS  Article  CAS  Google Scholar 

  31. Lovejoy, S. Weather, Macroweather, and the Climate: Our Random Yet Predictable Atmosphere (Oxford Univ. Press, 2019).

  32. Cuthill, J. F. H., Guttenberg, N. & Budd, G. E. Impacts of speciation and extinction measured by an evolutionary decay clock. Nature 588, 636–641 (2020).

    ADS  Article  CAS  Google Scholar 

  33. Crampton, J. S., Cooper, R. A., Sadler, P. M. & Foote, M. Greenhouse–icehouse transition in the Late Ordovician marks a step change in extinction regime in the marine plankton. Proc. Natl Acad. Sci. USA 113, 1498–1503 (2016).

    ADS  CAS  PubMed  PubMed Central  Article  Google Scholar 

  34. Van Dam, J. A. et al. Long-period astronomical forcing of mammal turnover. Nature 443, 687–691 (2006).

    ADS  PubMed  Article  CAS  Google Scholar 

  35. Erwin, D. H. Seeds of diversity. Science 308, 1752–1753 (2005).

    CAS  PubMed  Article  Google Scholar 

  36. Roopnarine, P. D. Extinction cascades and catastrophe in ancient food webs. Paleobiology 32, 1–19 (2006).

    Article  Google Scholar 

  37. Close, R. A., Benson, R. B. J., Saupe, E. E., Clapham, M. E. & Butler, R. J. The spatial structure of Phanerozoic marine animal diversity. Science 368, 420–424 (2020).

    ADS  CAS  PubMed  Article  Google Scholar 

  38. Eldredge, N. Unfinished Synthesis: Biological Hierarchies and Modern Evolutionary Thought (Oxford Univ. Press, 1985).

  39. Lieberman, B. S., MillerIII, W. & Eldredge, N. Paleontological patterns, macroecological dynamics and the evolutionary process. Evol. Biol. 34, 28–48 (2007).

    Article  Google Scholar 

  40. Stigall, A. L. Invasive species and biodiversity crises: testing the link in the Late Devonian. PLoS ONE 5, e15584 (2010).

    ADS  CAS  PubMed  PubMed Central  Article  Google Scholar 

  41. Lam, A. R., Stigall, A. L. & Matzke, N. J. Dispersal in the Ordovician: speciation patterns and paleobiogeographic analyses of brachiopods and trilobites. Palaeogeogr. Palaeoclimatol. Palaeoecol. 489, 147–165 (2018).

    Article  Google Scholar 

  42. DeMets, C., Gordon, R. G., Argus, D. F. & Stein, S. Current plate motions. Geophys. J. Int. 101, 425–478 (1990).

    ADS  Article  Google Scholar 

  43. Valentine, J. W., Foin, T. C. & Peart, D. A provincial model of Phanerozoic marine diversity. Paleobiology 4, 55–66 (1978).

    Article  Google Scholar 

  44. Button, D. J., Lloyd, G. T., Ezcurra, M. D. & Butler, R. J. Mass extinctions drove increased global faunal cosmopolitanism on the supercontinent Pangaea. Nat. Commun. 8, 733 (2017).

  45. Spiridonov, A. et al. Integrated record of Ludlow (Upper Silurian) oceanic geobioevents—coordination of changes in conodont, and brachiopod faunas, and stable isotopes. Gondwana Res. 51, 272–288 (2017).

    ADS  CAS  Article  Google Scholar 

  46. Sheehan, P. & Coorough, P. Brachiopod zoogeography across the Ordovician–Silurian extinction event. Geol. Soc. Lond. Mem. 12, 181–187 (1990).

    Article  Google Scholar 

  47. Borrelli, J. J. et al. Selection on stability across ecological scales. Trends Ecol. Evol. 30, 417–425 (2015).

    PubMed  Article  Google Scholar 

  48. Stanley, S. M. Predation defeats competition on the seafloor. Paleobiology 34, 1–21 (2008).

    Article  Google Scholar 

  49. Spiridonov, A., Brazauskas, A. & Radzevičius, S. Dynamics of abundance of the mid- to late Pridoli conodonts from the eastern part of the Silurian Baltic Basin: multifractals, state shifts, and oscillations. Am. J. Sci. 316, 363–400 (2016).

    ADS  Article  Google Scholar 

  50. Lovejoy, S. & Schertzer, D. The Weather and Climate: Emergent Laws and Multifractal Cascades (Cambridge Univ. Press, 2013).

  51. Cornette, J. L., Lieberman, B. S. & Goldstein, R. H. Documenting a significant relationship between macroevolutionary origination rates and Phanerozoic pCO2 levels. Proc. Natl Acad. Sci. USA 99, 7832–7835 (2002).

    ADS  CAS  PubMed  PubMed Central  Article  Google Scholar 

  52. Hannisdal, B. & Peters, S. E. Phanerozoic Earth system evolution and marine biodiversity. Science 334, 1121–1124 (2011).

    ADS  CAS  PubMed  Article  Google Scholar 

  53. Mayhew, P. J., Bell, M. A., Benton, T. G. & McGowan, A. J. Biodiversity tracks temperature over time. Proc. Natl Acad. Sci. USA 109, 15141–15145 (2012).

    ADS  CAS  PubMed  PubMed Central  Article  Google Scholar 

  54. Mathes, G. H., van Dijk, J., Kiessling, W. & Steinbauer, M. J. Extinction risk controlled by interaction of long-term and short-term climate change. Nat. Ecol. Evol. 5, 304–310 (2021).

    PubMed  Article  Google Scholar 

  55. Mathes, G. H., Kiessling, W. & Steinbauer, M. J. Deep-time climate legacies affect origination rates of marine genera. Proc. Natl Acad. Sci. USA 118, e2105769118 (2021).

  56. Roberts, G. G. & Mannion, P. D. Timing and periodicity of Phanerozoic marine biodiversity and environmental change. Sci. Rep. 9, 6116 (2019).

  57. Žliobaitė, I. & Fortelius, M. On calibrating the completometer for the mammalian fossil record. Paleobiology 48, 1–11 (2021).

  58. Valentine, J. W. & Walker, T. D. Diversity trends within a model taxonomic hierarchy. Physica D 22, 31–42 (1986).

    ADS  MathSciNet  Article  Google Scholar 

  59. Sepkoski, J. J. & Kendrick, D. C. Numerical experiments with model monophyletic and paraphyletic taxa. Paleobiology 19, 168–184 (1993).

    PubMed  Article  Google Scholar 

  60. Crampton, J. S., Cooper, R. A., Foote, M. & Sadler, P. M. Ephemeral species in the fossil record? Synchronous coupling of macroevolutionary dynamics in mid-Paleozoic zooplankton. Paleobiology 46, 123–135 (2020).

    Article  Google Scholar 

  61. Sepkoski, J. J. Ten years in the library: new data confirm paleontological patterns. Paleobiology 19, 43–51 (1993).

    PubMed  Article  Google Scholar 

  62. Alroy, J. Successive approximations of diversity curves: ten more years in the library. Geology 28, 1023–1026 (2000).

    ADS  Article  Google Scholar 

  63. R Core Team. R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, 2015).

  64. Kocsis, A. T., Reddin, C. J., Alroy, J. & Kiessling, W. The R package divDyn for quantifying diversity dynamics using fossil sampling data. Methods Ecol. Evol. 10, 735–743 (2019).

    Article  Google Scholar 

  65. Kocsis, A. T., Alroy, J., Reddin, C. J. & Kiessling, W. Phanerozoic-scale global marine biodiversity analysis with the R package divDyn v0.7. divDyn vignette (2019).

  66. Na, L. & Kiessling, W. Diversity partitioning during the Cambrian radiation. Proc. Natl Acad. Sci. USA 112, 4702–4706 (2015).

    ADS  CAS  PubMed  PubMed Central  Article  Google Scholar 

  67. Fan, J.-x et al. A high-resolution summary of Cambrian to Early Triassic marine invertebrate biodiversity. Science 367, 272–277 (2020).

    ADS  CAS  PubMed  Article  Google Scholar 

  68. Raup, D. M. Cohort analysis of generic survivorship. Paleobiology 4, 1–15 (1978).

    Article  Google Scholar 

  69. Raup, D. M. Mathematical models of cladogenesis. Paleobiology 11, 42–52 (1985).

    Article  Google Scholar 

  70. Foote, M. Pulsed origination and extinction in the marine realm. Paleobiology 40, 6–20 (2005).

    Article  Google Scholar 

  71. Payne, J. L. & Heim, N. A. Body size, sampling completeness, and extinction risk in the marine fossil record. Paleobiology 46, 23–40 (2020).

    Article  Google Scholar 

  72. Hearing, T. W. et al. An early Cambrian greenhouse climate. Sci. Adv. 4, eaar5690 (2018).

    ADS  PubMed  PubMed Central  Article  CAS  Google Scholar 

  73. Goldberg, S. L., Present, T. M., Finnegan, S. & Bergmann, K. D. A high-resolution record of early Paleozoic climate. Proc. Natl Acad. Sci. USA 118, e2013083118 (2021).

  74. Schrag, D. P., DePaolo, D. J. & Richter, F. M. Reconstructing past sea surface temperatures: correcting for diagenesis of bulk marine carbonate. Geochim. Cosmochim. Acta 59, 2265–2278 (1995).

    ADS  CAS  Article  Google Scholar 

  75. Miller, K. G. et al. The Phanerozoic record of global sea-level change. Science 310, 1293–1298 (2005).

    ADS  CAS  PubMed  Article  Google Scholar 

  76. Van der Meer, D. et al. Reconstructing first-order changes in sea level during the Phanerozoic and Neoproterozoic using strontium isotopes. Gondwana Res. 44, 22–34 (2017).

    ADS  Article  CAS  Google Scholar 

  77. Müller, R. D. & Dutkiewicz, A. Oceanic crustal carbon cycle drives 26-million-year atmospheric carbon dioxide periodicities. Sci. Adv. 4, eaaq0500 (2018).

    ADS  PubMed  PubMed Central  Article  CAS  Google Scholar 

  78. Kiessling, W. Long-term relationships between ecological stability and biodiversity in Phanerozoic reefs. Nature 433, 410–413 (2005).

    ADS  CAS  PubMed  Article  Google Scholar 

  79. McKinney, M. L. & Oyen, C. W. Causation and nonrandomness in biological and geological time series: temperature as a proximal control of extinction and diversity. Palaios 4, 3–15 (1989).

    ADS  Article  Google Scholar 

  80. Haar, A. Zur theorie der orthogonalen funktionensysteme. Math. Ann. 69, 331–371 (1910).

    MathSciNet  MATH  Article  Google Scholar 

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Acknowledgements

We thank A. Kocsis for help with divDyn package functions. We also thank many contributors to the Paleobiology Database and the authors of descriptive taxonomic papers and geochemical analyses that generated the primary data used in this study. This research was supported by project S-MIP-21-9 ‘The role of spatial structuring in major transitions in macroevolution’. S.L. acknowledges the National Science and Engineering Council for some support. This paper is Paleobiology Database official publication 426.

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A.S. and S.L. developed the design of the study, analysed the data and wrote the text.

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Correspondence to Andrej Spiridonov or Shaun Lovejoy.

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Nature thanks Jurgen Kurths, Gene Hunt, Appy Sluijs and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Peer reviewer reports are available.

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Extended data figures and tables

Extended Data Fig. 1 Macroevolutionary and paleoclimate time series.

A. Average global surface water temperatures (T) Song and others (2019) data28, B marine animal genus diversity (D), C second-for-third genus extinction rates per bin (E), D second-for-third origination rates per bin (O). Paleobiological patterns are per bin averages with \(\pm \sigma \) confidence intervals based on 100 bootstrap replications.

Extended Data Fig. 2 Paleoclimate time series and time scaling.

A. Song et al., 2019 (blue) and Veizer et al., 1999 (red) global sea water paleotemperature stacks32,33 expressed in \(\delta {}^{18}O\) ‰ units as a function of age (time flows from right to left). The Song et al., 2019 data was standardized by setting mean to zero and standard deviations were made equal. B Cretaceous sea surface water temperatures based on TEX86 and \(\delta {}^{18}O_{pl}\) data73 for low latitudes (black) [n = 2856 temperature estimates] and high latitudes (red)[n = 638 temperature estimates] in °C. C. Haar fluctuation scaling curves for high latitude (pink), and low latitude (brown) Cretaceous sea surface temperatures (in °C); timescales shown in \({\log }_{10}\) Myr; dashed line shows scaling pattern with H = +0.25.

Extended Data Fig. 3 Scaling of macroevolutionary time series with confidence bands.

Haar fluctuation scaling curves with standard errors based on the analysis of 100 subsamplings: A origination (red) and extinction (brown) rates (x10)[as in the Fig. 1]; B genus diversity (x0.01))[as in the Fig. 1]. Timescales shown in \({\log }_{10}\) Myr.

Extended Data Fig. 4 Time-dependant correlations.

scale-dependant correlations of fluctuations in A extinction rates with temperatures, time in Myr. Same for B origination rates with temperatures; C global diversity levels with extinction rates; D global diversity levels with origination rates. Mean (black) and one standard deviation confidence limits dashed red. Mean (black) and one standard deviation confidence limits dashed red (16–84%).

Extended Data Fig. 5 Time scaling of the global sea level and sea floor spreading.

Haar fluctuation scaling of the sea level75 (in m from the present level) during the Phanerozoic and Neoproterozoic (brown), and of the sea floor production rates76 through the Meso-Cenozoic (m2/year /3 x 104) (pink). Timescales shown in \({\log }_{10}\) Myr. Both geophyscal variables scale positively at least to the timescale of 100 Myr. \(\varDelta {t}_{trans}\) signifies critical transition time from the positive to the negative diversity scaling, and the start of synchronization of macroevolutionary rates. Sea level and tectonic activity scales positively well beyound this critical threshold.

Supplementary information

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Discussion of uncertainties in the estimation of scaling relations and correlation of scaling time series and Supplementary Figs. 1–5 and references.

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Spiridonov, A., Lovejoy, S. Life rather than climate influences diversity at scales greater than 40 million years. Nature (2022). https://doi.org/10.1038/s41586-022-04867-y

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