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Article: Time for a rethink: time sub‐sampling methods in disparity‐through‐time analyses

Palaeontology Cover Image - Volume 61 Part 4
Publication: Palaeontology
Volume: 61
Part: 4
Publication Date: July 2018
Page(s): 481 493
Author(s): Thomas Guillerme, and Natalie Cooper
Addition Information

How to Cite

GUILLERME, T., COOPER, N. 2018. Time for a rethink: time sub‐sampling methods in disparity‐through‐time analyses. Palaeontology, 61, 4, 481-493. DOI: 10.1111/pala.12364

Author Information

  • Thomas Guillerme - School of Biological Sciences University of Queensland St Lucia Queensland Australia
  • Natalie Cooper - Department of Life Sciences Natural History Museum Cromwell Road London SW7 5BD UK

Publication History

  • Issue published online: 12 June 2018
  • Manuscript Accepted: 13 February 2018
  • Manuscript Received: 22 December 2017

Funded By

Australian Research Council. Grant Number: DP170103227

Online Version Hosted By

Wiley Online Library
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Abstract

Disparity‐through‐time analyses can be used to determine how morphological diversity changes in response to mass extinctions, or to investigate the drivers of morphological change. These analyses are routinely applied to palaeobiological datasets, yet, although there is much discussion about how to best calculate disparity, there has been little consideration of how taxa should be sub‐sampled through time. Standard practice is to group taxa into discrete time bins, often based on stratigraphic periods. However, this can introduce biases when bins are of unequal size, and implicitly assumes a punctuated model of evolution. In addition, many time bins may have few or no taxa, meaning that disparity cannot be calculated for the bin and making it harder to complete downstream analyses. Here we describe a different method to complement the disparity‐through‐time tool‐kit: time‐slicing. This method uses a time‐calibrated phylogenetic tree to sample disparity‐through‐time at any fixed point in time rather than binning taxa. It uses all available data (tips, nodes and branches) to increase the power of the analyses, specifies the implied model of evolution (punctuated or gradual), and is implemented in R. We test the time‐slicing method on four example datasets and compare its performance in common disparity‐through‐time analyses. We find that the way we time sub‐sample taxa can change our interpretations of the results of disparity‐through‐time analyses. We advise using multiple methods for time sub‐sampling taxa, rather than just time binning, to gain a better understanding disparity‐through‐time.

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