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Data from: Sympatric wren-warblers partition acoustic signal space and song perch height

Cite this dataset

Chitnis, Shivam; Rajan, Samyuktha; Krishnan, Anand (2019). Data from: Sympatric wren-warblers partition acoustic signal space and song perch height [Dataset]. Dryad.


Animals employing acoustic signals, such as birds, must effectively communicate over both background noise and potentially attenuating objects in the environment. To surmount these obstacles, animals evolve species-specific acoustic signals that do not overlap with sources of interference (such as songs of close relatives), and issue these songs from locations that maximize transmission. In multispecies assemblages of birds, the acoustic resource may thus be interspecifically partitioned along multiple axes, including song perch height and signal space. However, very few such studies have focused on open habitats, where differences in sound transmission patterns and limited availability of song perches may drive competition across multiple axes within signal space. Here, we demonstrate acoustic signal space partitioning in four sympatric species of wren-warbler (Cisticolidae, Prinia), in an Indian dry deciduous scrub-grassland habitat. We found that the breeding songs of the four species partition acoustic signal space, resulting in interspecific community organization. Within each species’ signal space, we uncovered different intraspecific patterns in note diversity. Two species partitioned intraspecific signal space into multiple note types, whereas the other two varied note repetition rate to different extents. Finally, we found that the four species also partition song perch heights, thus exhibiting acoustic niche separation along multiple axes. We hypothesize that divergent song perch heights may be driven by competition for higher singing perches or other ecological factors rather than signal propagation. Acoustic signal partitioning along multiple axes may therefore arise from a combination of diverse ecological processes.

Usage notes

Data related to the manuscript are all within these files. song_data and call_data MAT files contain all the song and call data used here. In each, P contains the species classifications and vbls contains the parameter names. The randomisation and shuffling stats files contain the mean distances from the randomised distributions as well as the observed. In all cases, g is P.hodgsonii, j is P. sylvatica, a is P.socialis and p is P.inornata. The song PC space contains the results of PCA, whereas the NT clusters file contains NT variables representing note type classifications for each species. Codes are also attached as M files and MATLAb live scripts. Further information is in the manuscript supplementary.


DST- INSPIRE Faculty Award

SERB Early Career Research Award