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Optimal Predator Risk Assessment by the Sonar-Jamming Arctiine Moth Bertholdia trigona

Overview of attention for article published in PLOS ONE, May 2013
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Title
Optimal Predator Risk Assessment by the Sonar-Jamming Arctiine Moth Bertholdia trigona
Published in
PLOS ONE, May 2013
DOI 10.1371/journal.pone.0063609
Pubmed ID
Authors

Aaron J. Corcoran, Ryan D. Wagner, William E. Conner

Abstract

Nearly all animals face a tradeoff between seeking food and mates and avoiding predation. Optimal escape theory holds that an animal confronted with a predator should only flee when benefits of flight (increased survival) outweigh the costs (energetic costs, lost foraging time, etc.). We propose a model for prey risk assessment based on the predator's stage of attack. Risk level should increase rapidly from when the predator detects the prey to when it commits to the attack. We tested this hypothesis using a predator--the echolocating bat--whose active biosonar reveals its stage of attack. We used a prey defense--clicking used for sonar jamming by the tiger moth Bertholdia trigona--that can be readily studied in the field and laboratory and is enacted simultaneously with evasive flight. We predicted that prey employ defenses soon after being detected and targeted, and that prey defensive thresholds discriminate between legitimate predatory threats and false threats where a nearby prey is attacked. Laboratory and field experiments using playbacks of ultrasound signals and naturally behaving bats, respectively, confirmed our predictions. Moths clicked soon after bats detected and targeted them. Also, B. trigona clicking thresholds closely matched predicted optimal thresholds for discriminating legitimate and false predator threats for bats using search and approach phase echolocation--the period when bats are searching for and assessing prey. To our knowledge, this is the first quantitative study to correlate the sensory stimuli that trigger defensive behaviors with measurements of signals provided by predators during natural attacks in the field. We propose theoretical models for explaining prey risk assessment depending on the availability of cues that reveal a predator's stage of attack.

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Geographical breakdown

Country Count As %
United Kingdom 1 1%
Netherlands 1 1%
United States 1 1%
Italy 1 1%
Unknown 66 94%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 21 30%
Researcher 12 17%
Student > Ph. D. Student 11 16%
Student > Master 10 14%
Other 4 6%
Other 7 10%
Unknown 5 7%
Readers by discipline Count As %
Agricultural and Biological Sciences 45 64%
Environmental Science 7 10%
Biochemistry, Genetics and Molecular Biology 2 3%
Engineering 2 3%
Computer Science 1 1%
Other 4 6%
Unknown 9 13%