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Acoustically eavesdropping bat predators take longer to capture katydid prey signalling in aggregation

Citation

Prakash, Harish; Greif, Stefan; Yovel, Yossi; Balakrishnan, Rohini (2021), Acoustically eavesdropping bat predators take longer to capture katydid prey signalling in aggregation, Dryad, Dataset, https://doi.org/10.5061/dryad.pk0p2ngng

Abstract

Prey signalling in aggregation become more conspicuous with increasing numbers and tend to attract more predators. Such grouping may, however, benefit prey by lowering the risk of being captured due to the predator's difficulty in targeting individuals. Previous studies have investigated anti-predatory benefits of prey aggregation using visual predators, but it is unclear whether such benefits are gained in an auditory context. We investigated whether katydids of the genus Mecopoda gain protection from their acoustically eavesdropping bat predator, Megaderma spasma, when calling in aggregation. In a choice experiment, bats approached calls of prey aggregates more often than those of prey calling alone, indicating that prey calling in aggregation were at higher risk. In prey capture tasks, however, the average time taken, and the number of flight passes made by bats before capturing a katydid, were significantly higher for prey calling in aggregates as compared to calling alone-, indicating that prey face lower predation risk when calling in aggregation. We also tested the effectiveness of another common anti-predatory strategy: calling from within vegetation clutter. Vegetation increased the time taken by bats to capture katydids calling alone but did not increase the time taken to capture prey calling from aggregations. The increased time taken to capture a prey calling in aggregation as compared to solitary calling prey offers an escape opportunity for the prey, thus providing prey signalling acoustically in aggregation with anti-predatory benefits.

Methods

The dataset has been created by observing videos of bats performing experiments with different treatments. The statistical analysis of this data has been carried out in the software R. See R codes for how the data has been processed. 

Usage Notes

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