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acousticTS

DOI Documentation Build status Coverage License: GPL-3

Overview

acousticTS is an R package for estimating the acoustic target strength (TS) of aquatic organisms and objects using physics-based scattering models. It supports a range of scatterer types: fluid-like bodies (e.g., fish, zooplankton), gas-filled bodies (e.g. swimbladders), elastic shells (e.g. pteropods, euphausiids), and calibration spheres. It further provides a unified interface for parameterizing, running, and comparing models across frequencies, orientations, and morphologies. Acoustic backscatter from a single target is expressed as the backscattering cross-section (\sigma_\text{bs}, m²). Target strength (TS, dB re. 1 m²) is its logarithmic form:

TS = 10 \log_{10}(\sigma_\text{bs})

TS is used to:

  • Convert integrated backscatter (e.g. S_\text{A}), NASC) or volumetric backscatter (S_\text{V}) into number density or biomass
  • Classify backscatter by species or taxon based on multi-frequency response
  • Parameterize and evaluate physics-based scattering models over statistical distributions of organism size and orientation

Installation

Install the latest release from GitHub:

# install.packages("devtools")
devtools::install_github("brandynlucca/acousticTS")

Scatterer classes

acousticTS organizes targets into five S4 classes:

Class Description Example taxa
FLS Fluid-like scatterer Euphausiids, myctophids, decapod shrimp
SBF Swimbladder-bearing fish Herring, cod, sardine
GAS Gas-filled body Siphonophore pneumatophores
ESS Elastic-shelled scatterer Pteropods, juvenile bivalves
CAL Calibration sphere Tungsten carbide, copper spheres

Each class stores a shape (position matrix + morphometrics), body material properties (density and sound speed contrasts), and model results in a structured S4 object.

Models

Model Abbreviation Scatterer type Boundary
Distorted-wave Born approximation DWBA FLS Fluid
Stochastic DWBA SDWBA FLS Fluid
Kirchhoff-ray mode KRM FLS, SBF Fluid + gas
High-pass approximation HPA FLS, GAS Fluid / gas
Two-ray cylinder model TRCM FLS Fluid
Modal series solution (sphere) SPHMS CAL, ESS Multiple
Modal series solution (prolate spheroid) PSMS FLS Fluid
Modal series solution (elastic shell) ESSMS ESS Elastic
Finite-cylinder modal series FCMS CAL Rigid / fluid
Resonance model (gas sphere) SOEMS GAS, CAL Gas

Quick start 

library(acousticTS)

# Build a fluid-like scatterer (e.g. krill) with a cylinder shape
krill_shape <- cylinder(
  length_body = 0.03,          # 30 mm body length
  radius_body = 0.003          # 3 mm max radius
)
# ---- Create the actual Scatterer-class object (FLS)
krill <- fls_generate(
  shape = krill_shape,
  g = 1.0357,             # density contrast
  h = 1.0279,             # sound speed contrast
  theta = pi / 2          # broadside incidence
)

# Run the DWBA model from 1 kHz to 300 kHz
krill <- target_strength(krill,
  frequency = seq(1e3, 300e3, by = 1e3),
  model = "DWBA"
)

# Plot TS vs frequency
plot(krill, type = "model")

Shapes and reforging

Scatterer shapes are created via dedicated constructors:

# Cylinder (used by FLS / CAL)
fish_shape <- cylinder(length_body = 0.25, radius_body = 0.02)

# Prolate spheroid (used by FLS / PSMS)
ps_shape <- prolate_spheroid(length_body = 0.02, radius_body = 0.002)

# Arbitrary shape from digitized position matrix
arb_shape <- arbitrary(rpos = my_matrix)

# Dorsal/ventral style inputs
arbitrary(
  x_body = c(0, 0.015),
  w_body = c(0.005, 0.0075),
  zU_body = c(0.001, 0.002),
  zL_body = c(-0.001, -0.002)
)

Existing scatterer objects can be resized or re-discretized without reconstructing them from scratch using reforge():

# Rescale a krill to 40 mm
krill_40mm <- reforge(krill, body_target = c(length = 0.04))

# Change segment count
krill_fine <- reforge(krill, n_segments_body = 200)

Configuring simulations

simulate_ts() runs repeated model evaluations across distributions of input parameters, supporting both vectorized and batch modes:

results <- simulate_ts(
  krill,
  model = "DWBA",
  frequency = 120e3,
  n_realizations = 1000,
  parameters = list(
    theta_body = function() rnorm(1, pi / 2, pi / 18),
    length_body = function() rnorm(1, 0.03, 0.003)
  )
)

Built-in datasets

Dataset Description
krill Antarctic krill (Euphausia superba) shape and material properties
cod Atlantic cod (Gadus morhua) shape and swimbladder
sardine Pacific sardine (Sardinops sagax) shape and swimbladder
benchmark_ts Benchmark TS values for model validation 
data(krill)
data(cod)
data(sardine)
data(benchmark_ts)

Citation

If you use acousticTS in published work, please cite:

citation("acousticTS")

The Zenodo concept DOI for acousticTS, which resolves to the latest archived release record, is:

https://doi.org/10.5281/zenodo.7600659

Contributing and bug reports

Bug reports and feature requests are welcome via the GitHub Issues page. Please include a minimal reproducible example when reporting bugs.

License

GPL-3. See LICENSE for details.