FiSSE: A simple nonparametric test for the effects of a binary character on lineage diversification rates

Daniel L. Rabosky, Emma E. Goldberg

Research output: Contribution to journalArticlepeer-review

40 Scopus citations


It is widely assumed that phenotypic traits can influence rates of speciation and extinction, and several statistical approaches have been used to test for correlations between character states and lineage diversification. Recent work suggests that model-based tests of state-dependent speciation and extinction are sensitive to model inadequacy and phylogenetic pseudoreplication. We describe a simple nonparametric statistical test (“FiSSE”) to assess the effects of a binary character on lineage diversification rates. The method involves computing a test statistic that compares the distributions of branch lengths for lineages with and without a character state of interest. The value of the test statistic is compared to a null distribution generated by simulating character histories on the observed phylogeny. Our tests show that FiSSE can reliably infer trait-dependent speciation on phylogenies of several hundred tips. The method has low power to detect trait-dependent extinction but can infer state-dependent differences in speciation even when net diversification rates are constant. We assemble a range of macroevolutionary scenarios that are problematic for likelihood-based methods, and we find that FiSSE does not show similarly elevated false positive rates. We suggest that nonparametric statistical approaches, such as FiSSE, provide an important complement to formal process-based models for trait-dependent diversification.

Original languageEnglish (US)
Pages (from-to)1432-1442
Number of pages11
Issue number6
StatePublished - Jun 2017

Bibliographical note

Funding Information:
DLR developed the FiSSE test and performed the model fits. EEG created the testing datasets. DLR and EEG interpreted analyses and wrote the manuscript. This research was supported in part by the David and Lucile Packard Foundation and the US National Science Foundation [DEB- 1256330]. We thank H. Blackmon for discussions about the diverse testing scenarios and A. Mooers, B. O'Meara, A. Phillimore, G. Thomas, and members of the Rabosky lab for comments on the manuscript. The authors declare no conflicts of interest. The doi for our data is 10.5061/dryad.b277d.

Publisher Copyright:
© 2017 The Author(s). Evolution © 2017 The Society for the Study of Evolution.


  • BiSSE
  • extinction
  • key innovation
  • macroevolution
  • speciation
  • species selection


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