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Heterogeneous selectivity and morphological evolution of marine clades during the Permian–Triassic mass extinction

Nature Ecology & Evolution volume 8, pages 1248–1258 (2024)Cite this article

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Abstract

Morphological disparity and taxonomic diversity are distinct measures of biodiversity, typically expected to evolve synergistically. However, evidence from mass extinctions indicates that they can be decoupled, and while mass extinctions lead to a drastic loss of diversity, their impact on disparity remains unclear. Here we evaluate the dynamics of morphological disparity and extinction selectivity across the Permian–Triassic mass extinction. We developed an automated approach, termed DeepMorph, for the extraction of morphological features from fossil images using a deep learning model and applied it to a high-resolution temporal dataset encompassing 599 genera across six marine clades. Ammonoids, brachiopods and ostracods experienced a selective loss of complex and ornamented forms, while bivalves, gastropods and conodonts did not experience morphologically selective extinctions. The presence and intensity of morphological selectivity probably reflect the variations in environmental tolerance thresholds among different clades. In clades affected by selective extinctions, the intensity of diversity loss promoted the loss of morphological disparity. Conversely, under non-selective extinctions, the magnitude of diversity loss had a negligible impact on disparity. Our results highlight that the Permian–Triassic mass extinction had heterogeneous morphological selective impacts across clades, offering new insights into how mass extinctions can reshape biodiversity and ecosystem structure.

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Fig. 1: Schematic illustration of the DeepMorph method and simulations for testing morphological selectivity.
Fig. 2: Evolution of disparity (SOV) and diversity over three time bins and across subsets.
Fig. 3: Morphological evolution of six clades across three intervals.
Fig. 4: Simulation results of marginal selective intensity under varying magnitude losses of diversity and disparity (SOV).
Fig. 5: Bivariate plots illustrating the intensity of morphological extinction selectivity.
Fig. 6: Four distinct patterns of morphological evolution were identified during the PTME.

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Data availability

All data including the taxonomy list, fossil images, codes and trained deep learning model are provided and available via Zenodo at ref. 90. The taxonomy dataset was compiled from ref. 51 and the Paleobiology Database.

Code availability

The DeepMorph was implemented in Python (v. 3.6.5) and R (v. 4.2.0). Other libraries include Pytorch (v. 1.10.2), torchvision (v. 0.11.3+cu113), opencv-python (v. 4.5.2.54), geomorph (v. 4.0.5) and dispRity (v. 1.7.0) was also used for feature extraction and disparity quantifiation. Models and scripts are available at GitHub (https://github.com/XiaokangLiuCUG/DeepMorph).

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Acknowledgements

We acknowledge J. Wan, J. Yin, S. Jiang and X. Li for collecting the literature. We thank J. Sun and Y. Sun for helping to collect the fossil images. This study is supported by the National Natural Science Foundation of China (42325202, 92155201, 92255303), the State Key R&D Project of China (2023YFF0804000), the Natural Science Foundation of Hubei (2023AFA006) and the Fundamental Research Funds for the Central Universities, China University of Geosciences (Wuhan). X.L. thanks the financial support from the China Scholarship Council (202206410024). D.S. received funding from the Swiss National Science Foundation (PCEFP3_187012), the Swedish Research Council (VR: 2019-04739) and the Swedish Foundation for Strategic Environmental Research MISTRA within the framework of the research programme BIOPATH (F 2022/1448). We acknowledge the contributors to the Paleobiology Database. This is Paleobiology Database publication number 485.

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Authors and Affiliations

  1. State Key Laboratory of Biogeology and Environmental Geology, School of Earth Sciences, China University of Geosciences, Wuhan, China

    Xiaokang Liu, Haijun Song, Daoliang Chu, Xu Dai & Fengyu Wang

  2. Department of Biology, University of Fribourg, Fribourg, Switzerland

    Xiaokang Liu & Daniele Silvestro

  3. Swiss Institute of Bioinformatics, Fribourg, Switzerland

    Daniele Silvestro

  4. Gothenburg Global Biodiversity Centre, Department of Biological and Environmental Sciences, University of Gothenburg, Gothenburg, Sweden

    Daniele Silvestro

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  1. Xiaokang Liu
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Contributions

H.S. and X.L. conceived this study. X.L., X.D. and F.W. collected data. X.L., H.S. and D.S. contributed to the writing of the manuscript. X.L. and D.S. analysed the data. X.L. and H.S. designed the figures. All authors revised and edited the manuscript.

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Correspondence to Haijun Song.

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Extended data

Extended Data Fig. 1 Percentages of PCA variances of six clades that are explained by the first 10 axes.

a–f, Percentages of PCA variances of ammonoids (a), brachiopods (b), ostracods (c), bivalves (d), gastropods (e), and conodonts (f).

Extended Data Fig. 2 Evolution of disparity (SOR, blue squares) and diversity (orange diamonds) over time and across subsets.

Vertical bars represent 95% of the quantiles, which are calculated from 10,000 bootstrap replicates for each subset. a–f, Disparity and diversity of ammonoids (a), brachiopods (b), ostracods (c), bivalves (d), gastropods (e), and conodonts (f). Abbreviations: SOR = Sum of ranges. Fossil silhouettes adapted from ref. 18 under a Creative Commons licence CC BY 4.0.

Extended Data Fig. 3 Marginal selective intensity simulations under different magnitude losses of diversity and disparity (SOR).

a–d, Selectivity intensities among morphologies. Strong selectivity (a) indicates the highest extinction risk is ten times higher than the lowest extinction possibility. Moderate selectivity (b) indicates the highest extinction risk is five times higher than the lowest extinction risk. Weak selectivity (c) represents the highest extinction risk for a taxon that is two times higher than the one with the lowest extinction risk. Random extinction (d) represents a non-selective extinction. The rest of the extinction rates are distributed linearly. e, Disparity loss under different magnitude of diversity loss and selectivity. f, Diversity loss under different magnitude of disparity loss and selectivity.

Extended Data Fig. 4 Frequency distribution of the centroid distance shifts under 10,000 replicates from pre-extinction ammonoids.

Gray histograms indicate the 95% quantile. The red arrows represent the empirical results.

Extended Data Fig. 5 Marginal selective intensity simulations based on empirical morphological occupations under different magnitude losses of diversity.

extinction probabilities were based on the linear distributed model. a–f, Disparity loss rates of ammonoids (a), brachiopods (b), ostracods (c), bivalves (d), gastropods (e), and conodonts (f).

Extended Data Fig. 6 Morphological variations of victims, survivors, and newcomers for six clades during the PTME.

a–f, Morphological variations of ammonoids (a), brachiopods (b), ostracods (c), bivalves (d), gastropods (e), and conodonts (f). All the specimens are not to scale. Taxonomy list for ammonoids, a1–a11: Urartoceras abichianum, Araxoceras latissimum, Changhsingoceras sichuangense, Schizoloboceras vediensis, Araxoceltites sanestapanus, Metotoceras woodwardi, Episageceras dalailamae, Dunedinites pinguis, Anotoceras kama, Tellerites sp., and Pseudovishnuites guidingensis. For brachiopods, b1–b12: Fusispirifer sp., Glyptorhynchia lens, Janiceps peracuta, Paramarginifera japonica, Cathaysia chonetoides, Marginifera ornata, Permianella typica, Paryphella orbicularis, Piarorhynchella selongensis, Lichuanorelloides lichuanensis, and Orbicoelia speciosa. For ostracods, c1–c11: Cooperuna tenuis, Baschkirina ballei, Triplacera sp., Polycope baudi, Coronakirkbya hamori, Acanthoscapha blessi, Fabalicypris parva, Basslerella superarella, Samarella meishanella, Permoyoungiella bogschi, and Hollinella martensiformis. For bivalves, d1–d10: Pteronites pinnaeformis, Parallelodon laochangensis, Dyasmya elegans, Unionites canalensis, Solemya togata, Ensipteria guizhouensis, Entolioides subdemissus, Nucinella taylori, Isognomon ephippium, and Permophorus bregeri. For gastropods, e1–e11: Palaeostylus pupoides, Streptacis whitfieldi, Retispira sinensis, Porcellia paucituberculata, Stachella micra, Tropidodiscus curvilineatus, Anomphalus fusuiensis, Worthenia humilis, Meekospira solenisciforma, Microlampra heshanensis, and Wannerispira shangganensis. For conodonts, f1–f9: Hadrodontina aequabilis, Gondolella constricta, Sweetocristatus arcticus, Cypridodella spengleri, Iranognathus sosioensis, Pachycladina rendona, Isarcicella isarcica, Clarkina meishanensis, and Furnishius triserratus.

Extended Data Fig. 7 Ammonoid morphological occupation across three intervals based on multiple species and specimens.

a, Multiple species from one genus and multiple specimens for the same species. b, The result of interspecific variations of some representatives. Plots based on the raw data, including 191 species and 219 specimens. Notably, genera dating from the Changhsingian and characterized by stronger shell ornamentations exhibited higher levels of interspecific variation, as exemplified by Paratirolites and Alibashites. Conversely, genera from the Induan fauna displayed fewer variations, as observed in Ambites and Mullericeras.

Extended Data Fig. 8 Disparity comparison between genus-based and species rarefied results and selectivity test based on the rarefied results.

a, The square dots represent results based on genus-level, and diamond dots indicate rarefied disparity changes. Vertical bars represent 95% quantiles, calculated from 10,000 bootstrap replicates for each subset (that is, one-side test). b, Frequency distribution of the SOV by subsampling six species (Nsurvivors = 6) from Changhsingian, and the Pquantile < 0.08. c, Frequency distribution of the SOV by subsampling 52 species (NInduan = 52) from Changhsingian, Pquantile < 0.05. d, Frequency distribution of the centroid distance shifts under random replicates from pre-extinction taxa, Pquantile « 0.01 (NInduan = 52).

Extended Data Fig. 9 SOV comparison between the results using two PCA axes and ten PCA axes from ammonoids and conodonts.

a, Sum of variance of ammonoids, first two and ten PCA axes include 89.4% and 98.0% of total variations, respectively. b, Sum of variance of conodonts, first two and ten PCA axes include 66.6% and 7.6% of total variations, respectively. Vertical bars represent 95% quantiles, calculated from 10,000 bootstrap replicates for each subset.

Extended Data Table 1 Generic diversity distribution of clades and its coverage compared to the Paleobiology Database (PBDB)
Full size table

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Liu, X., Song, H., Chu, D. et al. Heterogeneous selectivity and morphological evolution of marine clades during the Permian–Triassic mass extinction. Nat Ecol Evol 8, 1248–1258 (2024). https://doi.org/10.1038/s41559-024-02438-0

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