Author ORCID Identifier
https://orcid.org/0000-0002-3221-675X
https://orcid.org/0000-0001-7886-3867
N/A
https://orcid.org/0000-0003-3209-4710
N/A
Document Type
Article
Publication Date
2018
College/Unit
Davis College of Agriculture, Natural Resources and Design
Department/Program/Center
Division of Forestry and Natural Resources
Abstract
Reliable species identification is vital for survey and monitoring programs. Recently, the development of digital technology for recording and analyzing vocalizations has assisted in acoustic surveying for cryptic, rare, or elusive species. However, the quan- titative tools that exist for species differentiation are still being refined. Using vocali- zations recorded in the course of ecological studies of a King Rail (Rallus elegans) and a Clapper Rail (Rallus crepitans) population, we assessed the accuracy and effective- ness of three parametric (logistic regression, discriminant function analysis, quadratic discriminant function analysis) and six nonparametric (support vector machine, CART, Random Forest, k-nearest neighbor, weighted k-nearest neighbor, and neural net- works) statistical classification methods for differentiating these species by their kek mating call. We identified 480 kek notes of each species and quantitatively character- ized them with five standardized acoustic parameters. Overall, nonparametric clas- sification methods outperformed parametric classification methods for species differentiation (nonparametric tools were between 57% and 81% accurate, paramet- ric tools were between 57% and 60% accurate). Of the nine classification methods, Random Forest was the most accurate and precise, resulting in 81.1% correct classi- fication of kek notes to species. This suggests that the mating calls of these sister species are likely difficult for human observers to tell apart. However, it also implies that appropriate statistical tools may allow reasonable species-level classification ac- curacy of recorded calls and provide an alternative to species classification where other capture- or genotype-based survey techniques are not possible.
Digital Commons Citation
Stiffler, Lydia L.; Schroeder, Katie M.; Anderson, James T.; McRae, Susan B.; and Katzner, Todd E., "Quantitative acoustic differentiation of cryptic species illustrated with King and Clapper rails" (2018). Faculty & Staff Scholarship. 1283.
https://researchrepository.wvu.edu/faculty_publications/1283
Source Citation
Stiffler LL, Schroeder KM, Anderson JT, McRae SB, Katzner TE. Quantitative acoustic differentiation of cryptic species illustrated with King and Clapper rails. Ecol Evol. 2018;8:12821–12831. https://doi.org/10.1002/ece3.4711
Comments
This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. © 2018 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd.
This article received support from the WVU Libraries' Open Access Author Fund.