Uniform Manifold Approximation and Projection for Clustering Taxa through Vocalizations in a Neotropical Passerine (Rough-Legged Tyrannulet, Phyllomyias burmeisteri)

Abstract

Simple Summary

Recognizing the different species can help us better understand the nature. One way to differentiate bird species is the bird song. There are mathematical techniques that extract information from the bird songs, potentially allowing automatic differentiation of species. However, there is still a lack of techniques that use the extracted information and accurately differentiate individuals of different species. For the first time, we have used a technique called Uniform Manifold Approximation and Projection (UMAP) to identify the two taxonomic groups of a bird named Rough-legged Tyrannulet Phyllomyias burmeisteri, which is a species that can be found all the way from Costa Rica to Argentina. Although there is evidence of the existence of two taxonomic groups, previous studies have shown them to be difficult to distinguish. We collected Rough-legged Tyrannulet bird songs of 101 birds from 11 countries. UMAP allowed us to make a transformation of the multiple measures obtained from the bird song of each bird into just two values. Plotting the UMAP values of each bird in a two-dimensional graph, it turns out that UMAP was able to clearly identify the two taxonomic groups, which has been named as Rough-legged Tyrannulet Phyllomyias burmeisteri and White-fronted Tyrannulet Phyllomyias zeledoni. UMAP can potentially help the identification of other species difficult to classify.

Abstract

Vocalizations from birds are a fruitful source of information for the classification of species. However, currently used analyses are ineffective to determine the taxonomic status of some groups. To provide a clearer grouping of taxa for such bird species from the analysis of vocalizations, more sensitive techniques are required. In this study, we have evaluated the sensitivity of the Uniform Manifold Approximation and Projection (UMAP) technique for grouping the vocalizations of individuals of the Rough-legged Tyrannulet Phyllomyias burmeisteri complex. Although the existence of two taxonomic groups has been suggested by some studies, the species has presented taxonomic difficulties in classification in previous studies. UMAP exhibited a clearer separation of groups than previously used dimensionality-reduction techniques (i.e., principal component analysis), as it was able to effectively identify the two taxa groups. The results achieved with UMAP in this study suggest that the technique can be useful in the analysis of species with complex in taxonomy through vocalizations data as a complementary tool including behavioral traits such as acoustic communication.