Acoustic classification of zooplankton

Abstract

Accurate acoustic characterization of zooplankton species is essential if reliable estimates of zooplankton biomass are to be made from acoustic backscatter measurements of the water column. Much work has recently been done on the forward problem, where scattering predictions have been made based on animal morphology. Three categories of scatterers, represented by theoretical scattering models, have been identified by Stanton et al. (1994): gas-bearing (e.g. siphonophores), fluid-like (e.g. euphausiids) and hard elastic-shelled (e.g. pteropods). If there are consistent differences in the characteristic acoustic signatures of each of these classes of zooplankton, it should be possible to solve the inverse problem by using acoustic backscatter data to infer mathematically the class of scatterer. In this investigation of the feasibility of inverting acoustic data for scatterer-type, two different inversion techniques are applied to hundreds of pings of data collected from broadband ensonifications (∼350 kHz–750 kHz) of individual, live zooplankton tethered and suspended in a large tank filled with filtered sea water. In the Model Parameterization Classifier (MPC), the theoretical models for each scatterer-type are represented as either straight lines with slope and intercept parameters or rectified sinusoids with frequency and phase parameters. Individual pings are classified by comparison with these model parameterizations. The Empirical Orthogonal Function-based Classifier (EOFC) exploits the basic structure of the frequency response (e.g. presence of a resonance structure) through decomposition of the response into empirical orthogonal functions. Small groups of pings are classified by comparing their dominant modes with the dominant modes representative of the three scatterer-types. Preliminary results indicate that the acoustic classification of zooplankton ensonifications into categories representing distinct scatterer-types is feasible. Ultimately, it may be possible to develop in situ acoustic systems that are capable of inverting for the types of organisms sampled, thereby bridging the gap between acoustic backscatter measurements and estimates of zooplankton biomass.