Document Type

Article

Journal/Book Title/Conference

Evolution

Volume

72

Issue

12

Publisher

Wiley

Publication Date

10-29-2018

First Page

1

Last Page

9

Abstract

In a recent publication (Pearse et al. 2018b), we explored the macroevolution and macroecology of passerine song using a large citizen science database of bird songs and powerful machine learning tools. Mikula et al. (2018) examine a small subset (<8%) of the data we used, and suggest that our metric of song complexity, the SD of frequency (SDF), does not correlate to other metrics of birdsong complexity, specifically syllable repertoire size and syllable diversity. We comment on the diversity of complexity metrics that exist in the field at present, and, while acknowledging that metrics may differ, outline how this variety allows us to ask more biologically nuanced questions. We see no reason or need for all complexity metrics to be correlated. Since different complexity metrics have been, and will continue to be, used, we outline how metrics could be fairly compared in the future.

Comments

This is the peer reviewed version of the following article: Pearse, W. D., Morales‐Castilla, I. , James, L. S., Farrell, M. , Boivin, F. and Davies, T. J. (2018), Complexity is complicated and so too is comparing complexity metrics‐A response to Mikula et al. (2018). Evolution. . doi:10.1111/evo.13636, which has been published in final form at https://doi.org/10.1111/evo.13636. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions.

Available for download on Tuesday, October 29, 2019

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