IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0151090.html
   My bibliography  Save this article

Where to Dig for Fossils: Combining Climate-Envelope, Taphonomy and Discovery Models

Author

Listed:
  • Sebastián Block
  • Frédérik Saltré
  • Marta Rodríguez-Rey
  • Damien A Fordham
  • Ingmar Unkel
  • Corey J A Bradshaw

Abstract

Fossils represent invaluable data to reconstruct the past history of life, yet fossil-rich sites are often rare and difficult to find. The traditional fossil-hunting approach focuses on small areas and has not yet taken advantage of modelling techniques commonly used in ecology to account for an organism’s past distributions. We propose a new method to assist finding fossils at continental scales based on modelling the past distribution of species, the geological suitability of fossil preservation and the likelihood of fossil discovery in the field, and apply it to several genera of Australian megafauna that went extinct in the Late Quaternary. Our models predicted higher fossil potentials for independent sites than for randomly selected locations (mean Kolmogorov-Smirnov statistic = 0.66). We demonstrate the utility of accounting for the distribution history of fossil taxa when trying to find the most suitable areas to look for fossils. For some genera, the probability of finding fossils based on simple climate-envelope models was higher than the probability based on models incorporating current conditions associated with fossil preservation and discovery as predictors. However, combining the outputs from climate-envelope, preservation, and discovery models resulted in the most accurate predictions of potential fossil sites at a continental scale. We proposed potential areas to discover new fossils of Diprotodon, Zygomaturus, Protemnodon, Thylacoleo, and Genyornis, and provide guidelines on how to apply our approach to assist fossil hunting in other continents and geological settings.

Suggested Citation

  • Sebastián Block & Frédérik Saltré & Marta Rodríguez-Rey & Damien A Fordham & Ingmar Unkel & Corey J A Bradshaw, 2016. "Where to Dig for Fossils: Combining Climate-Envelope, Taphonomy and Discovery Models," PLOS ONE, Public Library of Science, vol. 11(3), pages 1-16, March.
  • Handle: RePEc:plo:pone00:0151090
    DOI: 10.1371/journal.pone.0151090
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0151090
    Download Restriction: no

    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0151090&type=printable
    Download Restriction: no

    File URL: https://libkey.io/10.1371/journal.pone.0151090?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Chefaoui, Rosa M. & Lobo, Jorge M., 2008. "Assessing the effects of pseudo-absences on predictive distribution model performance," Ecological Modelling, Elsevier, vol. 210(4), pages 478-486.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Lewis A. Jones & Philip D. Mannion & Alexander Farnsworth & Fran Bragg & Daniel J. Lunt, 2022. "Climatic and tectonic drivers shaped the tropical distribution of coral reefs," Nature Communications, Nature, vol. 13(1), pages 1-10, December.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Václavík, Tomáš & Meentemeyer, Ross K., 2009. "Invasive species distribution modeling (iSDM): Are absence data and dispersal constraints needed to predict actual distributions?," Ecological Modelling, Elsevier, vol. 220(23), pages 3248-3258.
    2. Iturbide, Maialen & Bedia, Joaquín & Herrera, Sixto & del Hierro, Oscar & Pinto, Miriam & Gutiérrez, Jose Manuel, 2015. "A framework for species distribution modelling with improved pseudo-absence generation," Ecological Modelling, Elsevier, vol. 312(C), pages 166-174.
    3. Doko, Tomoko & Fukui, Hiromichi & Kooiman, Andre & Toxopeus, A.G. & Ichinose, Tomohiro & Chen, Wenbo & Skidmore, A.K., 2011. "Identifying habitat patches and potential ecological corridors for remnant Asiatic black bear (Ursus thibetanus japonicus) populations in Japan," Ecological Modelling, Elsevier, vol. 222(3), pages 748-761.
    4. Jiang, Dong & Wang, Qian & Ding, Fangyu & Fu, Jingying & Hao, Mengmeng, 2019. "Potential marginal land resources of cassava worldwide: A data-driven analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 104(C), pages 167-173.
    5. Mouton, Ans M. & De Baets, Bernard & Goethals, Peter L.M., 2010. "Ecological relevance of performance criteria for species distribution models," Ecological Modelling, Elsevier, vol. 221(16), pages 1995-2002.
    6. Schartel, Tyler E. & Cao, Yong, 2024. "Background selection complexity influences Maxent predictive performance in freshwater systems," Ecological Modelling, Elsevier, vol. 488(C).
    7. Coro, Gianpaolo & Pagano, Pasquale & Ellenbroek, Anton, 2013. "Combining simulated expert knowledge with Neural Networks to produce Ecological Niche Models for Latimeria chalumnae," Ecological Modelling, Elsevier, vol. 268(C), pages 55-63.
    8. Haider, Saira M. & Benscoter, Allison M. & Pearlstine, Leonard & D'Acunto, Laura E. & Romañach, Stephanie S., 2021. "Landscape-scale drivers of endangered Cape Sable Seaside Sparrow (Ammospiza maritima mirabilis) presence using an ensemble modeling approach," Ecological Modelling, Elsevier, vol. 461(C).
    9. Sillero, Neftalí & Arenas-Castro, Salvador & Enriquez‐Urzelai, Urtzi & Vale, Cândida Gomes & Sousa-Guedes, Diana & Martínez-Freiría, Fernando & Real, Raimundo & Barbosa, A.Márcia, 2021. "Want to model a species niche? A step-by-step guideline on correlative ecological niche modelling," Ecological Modelling, Elsevier, vol. 456(C).
    10. Chefaoui, Rosa M. & Serrão, Ester A., 2017. "Accounting for uncertainty in predictions of a marine species: Integrating population genetics to verify past distributions," Ecological Modelling, Elsevier, vol. 359(C), pages 229-239.
    11. Stokland, Jogeir N. & Halvorsen, Rune & Støa, Bente, 2011. "Species distribution modelling—Effect of design and sample size of pseudo-absence observations," Ecological Modelling, Elsevier, vol. 222(11), pages 1800-1809.
    12. Watling, James I. & Romañach, Stephanie S. & Bucklin, David N. & Speroterra, Carolina & Brandt, Laura A. & Pearlstine, Leonard G. & Mazzotti, Frank J., 2012. "Do bioclimate variables improve performance of climate envelope models?," Ecological Modelling, Elsevier, vol. 246(C), pages 79-85.
    13. Brice B Hanberry & Hong S He & Brian J Palik, 2012. "Pseudoabsence Generation Strategies for Species Distribution Models," PLOS ONE, Public Library of Science, vol. 7(8), pages 1-12, August.
    14. VanDerWal, Jeremy & Shoo, Luke P. & Graham, Catherine & Williams, Stephen E., 2009. "Selecting pseudo-absence data for presence-only distribution modeling: How far should you stray from what you know?," Ecological Modelling, Elsevier, vol. 220(4), pages 589-594.
    15. Senait D Senay & Susan P Worner & Takayoshi Ikeda, 2013. "Novel Three-Step Pseudo-Absence Selection Technique for Improved Species Distribution Modelling," PLOS ONE, Public Library of Science, vol. 8(8), pages 1-16, August.
    16. Whitford, Anna M. & Shipley, Benjamin R. & McGuire, Jenny L., 2024. "The influence of the number and distribution of background points in presence-background species distribution models," Ecological Modelling, Elsevier, vol. 488(C).
    17. Hengl, Tomislav & Sierdsema, Henk & Radović, Andreja & Dilo, Arta, 2009. "Spatial prediction of species’ distributions from occurrence-only records: combining point pattern analysis, ENFA and regression-kriging," Ecological Modelling, Elsevier, vol. 220(24), pages 3499-3511.
    18. Laze, Kuenda & Gordon, Ascelin, 2016. "Incorporating natural and human factors in habitat modelling and spatial prioritisation for the Lynx lynx martinoi," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 16(1), pages 17-31.
    19. Peiwei Fan & Mengmeng Hao & Fangyu Ding & Dong Jiang & Donglin Dong, 2020. "Quantifying Global Potential Marginal Land Resources for Switchgrass," Energies, MDPI, vol. 13(23), pages 1-13, November.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:plo:pone00:0151090. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.