Similarities in the behavior of diverse animal species that form large groups have motivated attempts to establish general principles governing animal group behavior. It has been difficult, however, to make quantitative measurements of the temporal and spatial behavior of extensive animal groups in the wild, such as bird flocks, fish shoals, and locust swarms. By quantifying the formation processes of vast oceanic fish shoals during spawning, we show that (i) a rapid transition from disordered to highly synchronized behavior occurs as population density reaches a critical value; (ii) organized group migration occurs after this transition; and (iii) small sets of leaders significantly influence the actions of much larger groups. Each of these findings confirms general theoretical predictions believed to apply in nature irrespective of animal species.

Ocean Acoustic Waveguide Remote Sensing (OAWRS) has recently been shown to be capable of instantaneously imaging and continuously monitoring fish populations over continental shelf-scale areas, covering thousands of km 2 . We show how OAWRS can be used in a variety of oceanic ecosystems to remotely assess populations and study the behavior of fish and other marine organisms, such as Antarctic krill, to help the study of marine ecology and the ecosystem-based approach to fisheries management.

Photoclinometry is the most common method used to obtain high-resolution topographic maps of planetary terrain. We derive the likelihood function of photoclinometric surface slope from (1) the probability distribution of the measured photon count of natural sunlight through a Charge-Coupled Device (CCD) including uncertainty due to camera shot noise, camera read noise, small scale albedo fluctuation and atmospheric haze, and (2) a photometric model relating photocount to surface orientation. We then use classical estimation theory to determine the theoretically exact biases and errors inherent in photoclinometric surface slope and show when they may be approximated by asymptotic expressions for sufficiently high sample size. We show how small-scale albedo variability often dominates biases and errors, which may become an order of magnitude larger than surface slopes when surface reflectance has a weak dependence on surface tilt. We provide bounds on the * Corresponding author * * Principal corresponding author

The mean low-frequency target strength (TS) of spawning Atlantic herring populations in the Gulf of Maine is estimated from the experimental data acquired during September–October 2006 near the northern flank of Georges Bank. A low-frequency OAWRS system with an instantaneous imaging diameter of 100 km was deployed to provide spatially unaliased imaging of fish populations over wide areas. The OAWRS system’s scattering strength measurements are calibrated with areal fish population density estimates obtained from concurrent localized line-transect measurements with several conventional fish finding sonars (CFFSs). Trawl sampling at selected locations enables the identification of the imaged species. The mean TS estimates of herring individuals exhibits significant variation over OAWRS operating frequency range, in accordance with the results from a resonant scattering model for swimbladder-bearing fish. The neutral buoyancy depth of herring and the species composition in the imaged population is inferred by comparing the measured TS with those derived from the model. Our analysis indicates that the herring population has a neutral buoyancy depth of between 70 and 90 m and is therefore negatively buoyant between 120 and 180 m water depth at which it is commonly found. The herring populations instantaneously imaged with OAWRS often exceeds 200×106, of which over 150×106 individuals can be organized into a large shoal.

Doppler analysis has been extensively used in active radar and sonar sensing to estimate the speed and direction of a single target within an imaging system resolution cell following deterministic theory. For target swarms, such as fish and plankton in the ocean, and raindrops, birds and bats in the atmosphere, multiple randomly moving targets typically occupy a single resolution cell, making single-target theory inadequate. Here, a method is developed for simultaneously estimating the instantaneous mean velocity and position of a group of randomly moving targets within a resolution cell, as well as the respective standard deviations across the group by Doppler analysis in free-space and in a stratified ocean waveguide. While the variance of the field scattered from the swarm is shown to typically dominate over the mean in the range-velocity ambiguity function, cross-spectral coherence remains and maintains high Doppler velocity and position resolution even for coherent signal processing algorithms such as the matched filter. For pseudo-random signals, the mean and variance of the swarms' velocity and position can be expressed in terms of the first two moments of the measured range-velocity ambiguity function. This is shown analytically for free-space and with Monte-Carlo simulations for an ocean waveguide.