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Uncertainties in dating constrain model choice for inferring extinction time from fossil records


Saltre, F and Brook, BW and Rodriguez-Rey, M and Cooper, A and Johnson, CN and Turney, CSM and Bradshaw, CJA, Uncertainties in dating constrain model choice for inferring extinction time from fossil records, Quaternary Science Reviews, 112 pp. 128-137. ISSN 0277-3791 (2015) [Refereed Article]

Copyright Statement

© 2015 Elsevier

DOI: doi:10.1016/j.quascirev.2015.01.022


Accurate estimates of the timing of extinctions (θ  ) are critical for understanding the causes of major die-off events and for identifying evolutionary or environmental transitions. Yet many studies have demonstrated that sampling biases and underlying statistical assumptions affect the accuracy of model-based estimates of extinction times (View the MathML source), and the added uncertainty contributed by inherent (laboratory) dating errors has largely been neglected. Here we provide a general guide (model-selection key) for choosing from among eight alternative ‘frequentist sampling’ (i.e., non-Bayesian) methods, differentiated by their treatment of both the probability of record occurrence and uncertainties in record dates, the most appropriate for a given record. We first provide a methodological framework to characterize time series of dated records as a function of the number of records, the size of the interval between successive records, and laboratory dating errors. Using both simulated data and dated Australian megafauna remains, we then assess how the characteristic of a dataset's time series dictates model performance and the probability of misclassification (false extant vs. false extinct). Among the four classic frequentist methods providing highest model performance, Marshall's (1997) and McCarthy's (1998) methods have the highest model precision. However, high model performance did not prevent misclassification errors, such that the Gaussian-resampled inverse-weighted McInerny (GRIWM) approach is the only method providing both high model accuracy and no misclassification issues, because of its unique down-weighting interval procedure and its ability to account for uncertainties in record dates. Applying the guideline to three time series of extinct Australian species, we recommend using Marshall's, McCarthy's and/or GRIWM methods to infer θ of both Thylacinus sp. and Genyornis sp., because each dataset is characterized by many sightings and a low variance of the interval between records, whereas McInerny's method better suits Diprotodon sp. due to an even lower interval variance.

Item Details

Item Type:Refereed Article
Keywords:megafauna, paleobiology
Research Division:Biological Sciences
Research Group:Ecology
Research Field:Palaeoecology
Objective Division:Environmental Management
Objective Group:Other environmental management
Objective Field:Other environmental management not elsewhere classified
UTAS Author:Brook, BW (Professor Barry Brook)
UTAS Author:Johnson, CN (Professor Christopher Johnson)
ID Code:102548
Year Published:2015
Web of Science® Times Cited:33
Deposited By:Zoology
Deposited On:2015-08-27
Last Modified:2017-11-01

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