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Vibration detection and discrimination in the masked birch caterpillar (Drepana arcuata)

Authors :
Myron L. Smith
Jayne E. Yack
S. M. Matheson
Raul Narciso C. Guedes
Barbara Frei
Source :
LOCUS Repositório Institucional da UFV, Universidade Federal de Viçosa (UFV), instacron:UFV
Publication Year :
2012
Publisher :
Vibration detection and discrimination in the masked birch caterpillar (Drepana arcuata), 2012.

Abstract

Leaf-borne vibrations are potentially important to caterpillars for communication and risk assessment. Yet, little is known about the vibratory environment of caterpillars, or how they detect and discriminate between vibrations from relevant and non-relevant sources. We measured the vibratory ‘landscape’ of the territorial masked birch caterpillar Drepana arcuata (Drepanidae), and assessed its ability to detect and respond to vibrations generated by conspecific and predatory intruders, wind and rain. Residents of leaf shelters were shown to respond to low amplitude vibrations generated by a crawling conspecific intruder, since removal of the vibrations through leaf incision prevented the resident’s response. Residents did not respond to large amplitude, low frequency disturbances caused by wind and rain alone, but did respond to approaching conspecifics under windy conditions, indicating an ability to discriminate between these sources. Residents also responded differently in the presence of vibrations generated by approaching predators (Podisus) and conspecifics. An analysis of vibration characteristics suggests that despite significant overlap between vibrations from different sources, there are differences in frequency and amplitude characteristics that caterpillars may use to discriminate between sources. Caterpillars live in a vibration-rich environment that we argue forms a prominent part of the sensory world of substrate bound holometabolous larvae.

Details

Language :
English
Database :
OpenAIRE
Journal :
LOCUS Repositório Institucional da UFV, Universidade Federal de Viçosa (UFV), instacron:UFV
Accession number :
edsair.doi.dedup.....17e0172e0c419c86b8201623ee1b9a1e