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The rise and fall of proboscidean ecological diversity

Nature Ecology & Evolution volume 5, pages 1266–1272 (2021)Cite this article

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Abstract

Proboscideans were keystone Cenozoic megaherbivores and present a highly relevant case study to frame the timing and magnitude of recent megafauna extinctions against long-term macroevolutionary patterns. By surveying the entire proboscidean fossil history using model-based approaches, we show that the dramatic Miocene explosion of proboscidean functional diversity was triggered by their biogeographical expansion beyond Africa. Ecomorphological innovations drove niche differentiation; communities that accommodated several disparate proboscidean species in sympatry became commonplace. The first burst of extinctions took place in the late Miocene, approximately 7 million years ago (Ma). Importantly, this and subsequent extinction trends showed high ecomorphological selectivity and went hand in hand with palaeoclimate dynamics. The global extirpation of proboscideans began escalating from 3 Ma with further extinctions in Eurasia and then a dramatic increase in African extinctions at 2.4 Ma. Overhunting by humans may have served as a final double jeopardy in the late Pleistocene after climate-triggered extinction trends that began long before hominins evolved suitable hunting capabilities.

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Fig. 1: Ecological diversity and diversification in proboscideans.
Fig. 2: Effect of ecomorphology on diversification.
Fig. 3: Extinction trends in the last 10 Myr.

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Data availability

Datasets are available in Supplementary Data 1 and from figshare (https://doi.org/10.6084/m9.figshare.14035109).

Code availability

PyRate v.3.0 is a Python-based (v.3.) program available at https://github.com/dsilvestro/PyRate. Computation in R used functions in the packages mvMORPH v.1.1.3, phytools v.0.7-70, ape v.5.5 and lme4 v.1.1-23. Input files can be obtained from Supplementary Data 1 and figshare (https://doi.org/10.6084/m9.figshare.14035109).

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Acknowledgements

We thank D. Silvestro, J. Calatayud and J. Clavel for technical assistance and F. Bibi, M. J. Benton and W. J. Sanders for helpful comments. S. Wang and G. van den Bergh provided important constructive comments on the informal supertree. We also thank E. M. Dunne, D. Mothé and F. Rivals, whose comments and recommendations improved the presentation of this paper. This work was supported by the Talent Attraction Program of the Madrid Government (no. 2017-T1/AMB5298), the German Research Foundation (AOBJ no. 637491) and the Academy of Finland (post-doctoral research fund no. 315691).

Author information

Authors and Affiliations

  1. Universidad de Alcalá, GloCEE - Global Change Ecology and Evolution Research Group, Departamento de Ciencias de la Vida, Madrid, Spain

    Juan L. Cantalapiedra & Óscar Sanisidro

  2. School of Earth Sciences, University of Bristol, Wills Memorial Building, Bristol, UK

    Hanwen Zhang

  3. Department of Earth Sciences, Natural History Museum, London, UK

    Hanwen Zhang

  4. Departamento de Paleobiología, Museo Nacional de Ciencias Naturales, Madrid, Spain

    María T. Alberdi

  5. Instituto de Investigaciones Arqueológicas y Paleontológicas del Cuaternario Pampeano, Consejo Nacional de InvestigacionesCientíficas y Técnicas-Universidad Nacional del Centro de la Provincia de Buenos Aires, Olavarría, Argentina

    José L. Prado

  6. Museum für Naturkunde, Leibniz-Institut für Evolutions- und Biodiversitätsforschung, Berlin, Germany

    Fernando Blanco

  7. Department of Geosciences and Geography, University of Helsinki, Helsinki, Finland

    Juha Saarinen

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Contributions

J.L.C., O.S. and J.S. conceptualized the research. J.L.C., O.S., J.S., H.Z., M.T.A. and J.L.P. gathered the data. J.L.C., O.S. and F.B. designed and performed the analysis. J.S. wrote the description and relevance of functional traits. J.L.C. and O.S. wrote the first version of the paper. H.Z. and J.S. contributed to the final version (main text and supplement).

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Correspondence to Juan L. Cantalapiedra.

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The authors declare no competing interests.

Additional information

Peer review information Nature Ecology & Evolution thanks Emma Dunne, Pasquale Raia, Dimila Mothé, Florent Rivals and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Peer reviewer reports are available.

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

Extended data

Extended Data Fig. 1 Description of the 17 ecomorphological traits.

Further details regarding traits scoring can be found in the Supplementary Methods.

Extended Data Fig. 2 Phylo-functional space of proboscideans.

Species coloured according to taxonomic affinities (a) and proboscidean functional type (b). Correlations of the different ecomorphological features with the functional space (c). Correlations of ordered variables (for example body size) are shown in one plot, whereas unordered variables have been broken down into binary traits prior to each correlation analysis.

Extended Data Fig. 3 Phenograms of NMDS axes 1 and 2.

PFTs reconstructed on the tree using a stochastic mapping as implemented in the make.simmap function in the R library phytools52.

Extended Data Fig. 4 Global and continental proboscidean diversity through time as estimated using PyRate.

Shaded areas represent 95% credible intervals. Diversity axis is log-scaled.

Extended Data Fig. 5 Results from macroevolutionary phylogenetic models.

Support is indicated by AICc scores (smaller is better) and AICc Weights (higher is better). Average parameter estimates were obtained from 100 trees. Evolutionary rates are colour-coded for comparison (reddish being faster rates).

Extended Data Fig. 6 Parameter estimates of the community-level general linear mixed-effects models.

Mean, upper and lower confidence limits are provided for intercepts and slopes.

Extended Data Fig. 7 Representation of the mixed-effects models.

Relationship of local species richness with age (a), and averaged DMD (b) across different phases. Density plots show the distribution of average DMD scores in each phase. A schematic comparison of slopes and intercepts is included, showing whether parameters estimates are significantly larger (>), significantly smaller (<), or not significantly different (≈).

Extended Data Fig. 8 Effect of ecology (NMDS scores in axis 1 and 2) on speciation (𝛼λ, blue) and extinction (𝛼𝜇, red).

Posterior estimates of the correlation parameters. Horizontal lines beneath the histograms represent 95% credible intervals, which in all cases are significantly different from 0. NMDS-1 is associated with differential speciation potencial, whereas NMDS-2 is associated with differential extinction.

Extended Data Fig. 9 Aggregated effect of ecology on speciation (blue), and extinction (red).

The effect of specific species ecology as the departure from baseline rates plotted over time (a,b) and on the tree (c,d). Phylogenetic reconstructions were conducted with the contMap function in the R library phytools52.

Extended Data Fig. 10 Extinction selectivity through time.

Differences in mean pairwise disparity between random extinctions and observed extinctions across the entire proboscidean history (a), and the last 10 Myr (b). Positive values represent ecologically-restricted extinction; negative values result when extinction hits on broad regions of the functional space; the grey points show values consistent with a random signal (non-significant P-values).

Supplementary information

Supplementary Information

Supplementary Methods

Reporting Summary

Peer Review Information

Supplementary Data 1

Proboscidean occurrences, traits and PFTs.

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Cantalapiedra, J.L., Sanisidro, Ó., Zhang, H. et al. The rise and fall of proboscidean ecological diversity. Nat Ecol Evol 5, 1266–1272 (2021). https://doi.org/10.1038/s41559-021-01498-w

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