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The true tempo of evolutionary radiation and decline revealed on the Hawaiian archipelago

Abstract

Establishing the relationship between rates of change in species richness and biotic and abiotic environmental change is a major goal of evolutionary biology. Although exquisite fossil and geological records provide insight in rare cases1, most groups lack high-quality fossil records. Consequently, biologists typically rely on molecular phylogenies to study the diversity dynamics of clades, usually by correlating changes in diversification rate with environmental or trait shifts2,3,4,5,6. However, inferences drawn from molecular phylogenies can be limited owing to the challenge of accounting for extinct species, making it difficult7,8,9 to accurately determine the underlying diversity dynamics that produce them. Here, using a geologically informed model of the relationship between changing island area and species richness for the Hawaiian archipelago, we infer the rates of species richness change for 14 endemic groups over their entire evolutionary histories without the need for fossil data, or molecular phylogenies. We find that these endemic clades underwent evolutionary radiations characterized by initially increasing rates of species accumulation, followed by slow-downs. In fact, for most groups on most islands, their time of evolutionary expansion has long past, and they are now undergoing previously unrecognized long-term evolutionary decline. Our results show how landscape dynamism can drive evolutionary dynamics over broad timescales10, including driving species loss that is not readily detected using molecular phylogenies, or without a rich fossil record11. We anticipate that examination of other clades where the relationship between environmental change and species richness change can be quantified will reveal that many other living groups have also experienced similarly complex evolutionary trajectories, including long-term and ongoing evolutionary decline.

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Figure 1: Generalized growth and decay of the Hawaiian islands used in the island ontogeny model.
Figure 2: Species numbers and inferred diversity trajectories of Hawaiian clades for the major islands of the Hawaiian archipelago.
Figure 3: Species accumulation rates inferred for the 14 clades analysed under the island ontogeny model.
Figure 4: Representative inferred diversity trajectories (grey) and carrying capacities (orange) on the oldest island, Kauai, under the island ontogeny model.

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Acknowledgements

We thank R. Gillespie, B. Baldwin, D. Clague, and M. Manga, K. Magnacca, I. Cooper, D. Polhemus, and the Berkeley Dimensions in Biodiversity research group for help with the primary biological and geological data and their interpretation. We also thank L. Chang, J. Ly, A. Jordon, M. Pires, K. Roy, R. Bowie, and S. P. Quek.

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Authors and Affiliations

Authors

Contributions

C.R.M. developed the analytic approach, augmented by ideas from J.Y.L. J.Y.L. developed the model comparison and statistical approaches. J.Y.L. coded the analytic approach into R, and ran all the analyses. J.Y.L. compiled the species richness data. C.R.M. compiled the island ontogeny data. C.R.M. and J.Y.L. co-wrote the manuscript.

Corresponding authors

Correspondence to Jun Y. Lim or Charles R. Marshall.

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The authors declare no competing financial interests.

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Reviewer Information Nature thanks P. Weigelt and the other anonymous reviewer(s) for their contribution to the peer review of this work.

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Extended data figures and tables

Extended Data Figure 1 Schematic description of the island ontogeny model.

Extended Data Figure 2 Sensitivity of the model comparison results in uncertainties in the ontogenies of the islands.

See Fig. 1 and Extended Data Table 1. For the columns labelled ‘Mean’, the mean values of the durations of growth (tgrowth), and decay (tdecay) were used; ‘Old Island’ means oldest of time of growth first habitability was used; ‘Young Island’ means youngest estimate of time of first habitability was used; ‘Longer Growth’ means youngest estimate of time of maximum area was used; ‘Shorter Growth’ means oldest estimate of time of maximum area was used. The corresponding values of r0,max and Kmax can be found in Extended Data Tables 3, 4, 5, 6, 7.

Extended Data Figure 3 Sensitivity of island ontogeny model to uncertainties in area estimates of older islands.

a, AIC weights for the island ontogeny model (x axis) plotted against the weights when the maximum areas of the two older islands (Kauai and Oahu) were increased by 60% (y axis). b, AIC weights for the island ontogeny model (x axis) plotted against the weights when the maximum areas of the two older islands were decreased by 40% (y axis). If there were no changes in the AIC weight for a clade, its data point would lie on the diagonal line.

Extended Data Table 1 Estimated time of growth (tgrowth), time of decay (tdecay), current area (Acurr), estimated area at the last glacial maximum22 (ALGM), and estimated maximum area (Amax) for the major Hawaiian islands
Extended Data Table 2 The species richness values for each of the 14 clades for each of the four major islands
Extended Data Table 3 Model parameter estimates and Akaike weights (ω) using mean times of first habitability and maximum area
Extended Data Table 4 Model parameter estimates and Akaike weights (ω) using oldest times of first habitability and youngest times of maximum area
Extended Data Table 5 Model parameter estimates and Akaike weights (ω) using oldest times of first habitability and oldest times of maximum area
Extended Data Table 6 Model parameter estimates and Akaike weights (ω) using youngest times of first habitability and youngest times of maximum area
Extended Data Table 7 Model parameter estimates and Akaike weights (ω) using youngest times of first habitability and oldest times of maximum area

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Lim, J., Marshall, C. The true tempo of evolutionary radiation and decline revealed on the Hawaiian archipelago. Nature 543, 710–713 (2017). https://doi.org/10.1038/nature21675

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