Listening forward: approaching marine biodiversity assessments using acoustic methods

Abstract

Ecosystems and the communities they support are changing at alarmingly rapid rates. Tracking species diversity is vital to managing these stressed habitats. Yet, quantifying and monitoring biodiversity is often challenging, especially in ocean habitats. Given that many animals make sounds, these cues travel efficiently under water, and emerging technologies are increasingly cost-effective, passive acoustics (a long-standing ocean observation method) is now a potential means of quantifying and monitoring marine biodiversity. Properly applying acoustics for biodiversity assessments is vital. Our goal here is to provide a timely consideration of emerging methods using passive acoustics to measure marine biodiversity. We provide a summary of the brief history of using passive acoustics to assess marine biodiversity and community structure, a critical assessment of the challenges faced, and outline recommended practices and considerations for acoustic biodiversity measurements. We focused on temperate and tropical seas, where much of the acoustic biodiversity work has been conducted. Overall, we suggest a cautious approach to applying current acoustic indices to assess marine biodiversity. Key needs are preliminary data and sampling sufficiently to capture the patterns and variability of a habitat. Yet with new analytical tools including source separation and supervised machine learning, there is substantial promise in marine acoustic diversity assessment methods.

Keywords: bioacoustics; ecosystem health; richness; soundscape.

Figure 1.

Molokini reef, Maui, Hawaii, USA, in October 2016 during a prolonged warming event with extended coral bleaching evident, potentially stressing the local community (Photo: M. Kaplan) [7].

Figure 2.

(a) Underwater soundscape of Tektite coral reef at the US Virgin Islands showing a diversity of sounds found on that reef (fish, snapping shrimp and marine mammals). (b) Underwater soundscape at the IMOS Perth Canyon site, WA. Middle panel shows a three-week spectrogram. The sounds of fish (individual fish sounds and regular night-time fish chorus), Antarctic blue whales, fin whales, humpback whales, an unidentified baleen whale, wind as well as passing ships are labelled. The five panels around the middle panel display short-term spectrograms of a few example sounds. Modified with permission from [42].

Figure 3.

Assessing biodiversity from the ocean soundscape. Diversity of bioacoustic signals in the soundscape is one way to estimate biodiversity. Complications to bioacoustic diversity measurements include the variability of the soundscape including its bioacoustic cues, presence of geophysical and anthropogenic ‘noise’, propagation and transmission loss in shallow water habitats, and a bias towards species that produce sounds.

Figure 4.

Eight-hour spectrograms of the lower-frequency component of a Mediterranean soundscape. (a) The classical overall spectrogram with combined background ambient noise and transient sounds, while (b) shows the spectrogram of the background ambient noise only, without individual transient sounds [131]. Bright green areas indicate fish choruses. (c) The spectrogram of the difference of (a) and (b), which results in the spectrogram of the transient sounds only. A high ANL can mask transient sounds, as highlighted by the areas surrounded in red. In part, this may also be that some biological signals that blend into mass choruses can also appear as low-amplitude ambient noise. ANL, ambient background noise level; RL, received level. Dark blue, 30 dB re 1 µPa; bright yellow, 90 dB re 1 µPa.

Figure 5.

Analysis results based on the biological sounds recorded at three observing locations in Taiwan. Within a location, the sounds are separated from the median and difference-based long-term spectrograms. The left panels show the diurnal and seasonal changes in biological sounds by using k-means clustering. Each colour represents a different biological sound with unique spectral features. The right panels show the seasonal change in bioacoustic diversity calculated by measuring the Shannon entropy of the probabilistic distribution of chorus and transient sounds measured via the clustering on the left panels. The solid lines represent the mean diversity, dashed lines represent the standard deviation and dots represent the diversity index measured on each day of recording. The three locations noted are Triangle Mountain (MLSY), Lienhuachih Research Center (LHC) and Taipingshan (hereafter YLTPS), Taiwan. Adapted from [209], see this paper for details.

Figure 6.

Three-dimensional localization of broadband transient sounds produced by invertebrates inhabiting an artificial reef (FAKIR). On the top panel, a schematic and a photographic representation of the artificial reef module. The lower panel represents the acoustic map of localized invertebrate sounds. In red, areas with a higher density (1000 sounds m⁻² min⁻¹), in blue, areas with low densities (10 sounds m⁻² min⁻¹). The upper ‘level’ of the FAKIR clearly shows biological hotspots. The black lines draw the contours of the artificial reef [243].