Abstract Detail


Carruthers, Tom [1].

Uncertain timescales in plant macroevolution.

Divergence time estimation plays a central role in plant macroevolutionary research. It enables the ages of major clades and rates of evolutionary diversification to be estimated, and often acts as the foundation for analyses of the historical geological and environmental processes that underpin the distribution of different clades. However, the main source of data for estimating divergence times (molecular sequence data) is not informative about time, meaning that divergence time estimates are highly sensitive to methodological assumptions. Often these assumptions are impossible to justify, meaning that divergence time estimates can be highly erroneous. Here, I discuss a new approach to divergence time estimation (exTREEmaTIME) that uses a minimum possible set of assumptions and aims to avoid assumptions that are impossible to justify. Although divergence time estimates with this method are far less precise compared to other widely used methods, the avoidance of unjustifiable assumptions means this method more accurately represents uncertainty. I discuss the implications of this method for addressing key questions in plant macroevolution including: the age of angiosperms; the role of continental break-up in explaining distribution patterns; and the role of humans in the origin of important crops. Although exTREEmaTIME highlights very high levels of uncertainty in the divergence time estimates that are relevant to these questions, carefully framed hypotheses can still be tested that enable critical insights into plant macroevolution. Importantly, methods that make more stringent assumptions can still contribute to this endeavour, but their contribution is fundamentally more meaningful when the true extent of uncertainty underlying divergence time estimates is accurately estimated.

1 - Royal Botanic Gardens Kew, Richmond, London, TW9 3AE, United Kingdom

divergence time estimation

Presentation Type: Oral Paper
Number: MACRO II004
Abstract ID:435
Candidate for Awards:None

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