How predictable are mass extinction events?. Issue 3 (15th March 2023)
- Record Type:
- Journal Article
- Title:
- How predictable are mass extinction events?. Issue 3 (15th March 2023)
- Main Title:
- How predictable are mass extinction events?
- Authors:
- Foster, William J.
Allen, Bethany J.
Kitzmann, Niklas H.
Münchmeyer, Jannes
Rettelbach, Tabea
Witts, James D.
Whittle, Rowan J.
Larina, Ekaterina
Clapham, Matthew E.
Dunhill, Alexander M. - Abstract:
- Abstract : Many modern extinction drivers are shared with past mass extinction events, such as rapid climate warming, habitat loss, pollution and invasive species. This commonality presents a key question: can the extinction risk of species during past mass extinction events inform our predictions for a modern biodiversity crisis? To investigate if it is possible to establish which species were more likely to go extinct during mass extinctions, we applied a functional trait-based model of extinction risk using a machine learning algorithm to datasets of marine fossils for the end-Permian, end-Triassic and end-Cretaceous mass extinctions. Extinction selectivity was inferred across each individual mass extinction event, before testing whether the selectivity patterns obtained could be used to 'predict' the extinction selectivity exhibited during the other mass extinctions. Our analyses show that, despite some similarities in extinction selectivity patterns between ancient crises, the selectivity of mass extinction events is inconsistent, which leads to a poor predictive performance. This lack of predictability is attributed to evolution in marine ecosystems, particularly during the Mesozoic Marine Revolution, associated with shifts in community structure alongside coincident Earth system changes. Our results suggest that past extinctions are unlikely to be informative for predicting extinction risk during a projected mass extinction.
- Is Part Of:
- Royal Society open science. Volume 10:Issue 3(2023)
- Journal:
- Royal Society open science
- Issue:
- Volume 10:Issue 3(2023)
- Issue Display:
- Volume 10, Issue 3 (2023)
- Year:
- 2023
- Volume:
- 10
- Issue:
- 3
- Issue Sort Value:
- 2023-0010-0003-0000
- Page Start:
- Page End:
- Publication Date:
- 2023-03-15
- Subjects:
- mass extinction -- machine learning -- fossil -- end-Permian -- end-Triassic -- end-Cretaceous
Science -- Periodicals
500 - Journal URLs:
- https://royalsocietypublishing.org/journal/rsos ↗
- DOI:
- 10.1098/rsos.221507 ↗
- Languages:
- English
- ISSNs:
- 2054-5703
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library STI - ELD Digital store
- Ingest File:
- 26172.xml