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Abstract Detail

Modeling the processes that mediate speciation and extinction rates across plants

Vasconcelos, Thais [1], O'Meara, Brian [2], Beaulieu, Jeremy [1].

Hidden-state-only models provide accurate tip-estimates of diversification rates.

State-dependent speciation and extinction (SSE) models allow examining correlation between an observed trait and variations in speciation and extinction rates of a lineage. BiSSE allowed joint estimation of trait evolution and diversification and HiSSE extended that to allow hidden and observed states. In reality, however, multiple traits and circumstances play a role in changing diversification dynamics of a lineage over time, which may restrict the use of SSE models that require trait information to be assigned at the tips a priori in more integrative questions. Here we introduce MiSSE, an approach using hidden states only. It can be used similarly to BAMM or the DR statistic to estimate rates at the tips of a tree, but it can estimate varying speciation, extinction, net diversification, and turnover rates as well as extinction fraction. MiSSE is based on hidden states only and does not require any trait data to be informed a priori, which greatly improves its flexibility in testing more complex diversification hypotheses. We compare the accuracy of tip rates inferred by MiSSE against other popular state-free models of diversification and demonstrate that the error associated with tip estimates is generally lower for most to all of the estimated parameters. Finally, we apply MiSSE and a renewed focus on these comparative methods to understand processes happening near the present, rather than deep in the tree, to investigate how the evolution of the tree habit impacts turnover rates in a lineage of flowering plants.

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1 - University of Arkansas, Fayetteville, AR, USA
2 - University of Tennessee, Knoxville, TN, USA

state-dependent speciation and extinction

Presentation Type: Colloquium Presentations
Session: C01, Modeling the processes that mediate speciation and extinction rates across plants
Location: /
Date: Monday, July 19th, 2021
Time: 11:30 AM(EDT)
Number: C01006
Abstract ID:521
Candidate for Awards:None

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