Capturing shell-crushing by large mobile predators using passive acoustics technology

Durophagy (shell-crushing) is a predatory mode that has evolved across numerous marine taxa from relatively sessile crustaceans to large and highly mobile fishes and mammals. Despite its preponderance in the marine environment, the ecology of durophagy (i.e., dynamics and spatiotemporal distribution) remains poorly understood especially for highly mobile species, limiting our ability to quantify their predatory effects on benthic communities. Here, we used passive acoustics (i.e., remote monitoring of underwater sounds with acoustic recorders) to characterize consumption of hard-shelled mollusk prey by a model predator, the whitespotted eagle ray (Aetobatus narinari). Acoustic recordings were made in captivity for 434 total prey items, spanning eight species of hard-shelled mollusks (1 bivalve, 7 gastropods). For all prey types, consumption sequences were generally characterized by an initial high-energy signal (Sound Pressure Level > 160 dB re 1μPa), presumably associated with shell failure, followed by numerous additional signals of lesser energy as prey was further fractured and winnowed by the predator. Fracture events were short-lived (<0.1 s) with peak frequencies ranging from 3.1 to 5.0 kHz, depending on prey type. Statistical analyses showed capacity to distinguish between the two dominant prey types offered (hard clam, Mercenaria mercenaria and banded tulip, Cinctura lilium) based on processing time, the number of fractures, as well as using a suite of energy and spectral features associated with these acoustic signals. Importantly, we noted that the directionality of these relationships (i.e., relative differences in signals between prey types) can change depending on the chronological location within a consumption sequence and the amount of data analyzed (e.g., first fracture event vs. all fracture event), which may present analytical challenges. Additionally, in situ simulation of fracture events in the target environment suggested events could be detected above ambient noise out to 100 s of m. To our knowledge, this is the first attempt to both quantify and classify durophagy using passive acoustics. We recommend that future studies conduct extensive testing in controlled and target environments to build robust data sets capable of supporting feature extraction as well as detection-classification schemes via machine-learning. Lastly, collaborations with biomechanical scientists are suggested to facilitate a better understanding of the mechanisms driving acoustic variation of shell fracture across prey taxa.