Estimating Deep-Sea Fish Population Density From the Odour Extension Area: A Theoretical Basis and Comparison With the Conventional Methods

Accurately estimating the population density of deep-sea fish with a baited camera system has long been significant challenge. Although several theoretical models have developed using first arrival time an individual or time-varying abundance at bait, none allows for spatio-temporal variability odour plume area extending from bait. This study shows theoretically that can be formulated as inverse sample mean extended until it reaches under condition rest random dispersion. Each estimate is governed by homogeneous Poisson process and, hence, its probability follows exponential distribution. A large uncertainty occur each (sample), but decreases number samples used to derive increases law numbers. Numerical experiments conducted in indicate proposed method inferring also potentially applicable cases which uniform large-scale clumped The show conventional based on fails any dispersion cases. indicates reliability most popular inference time-profile bait site was found depend extension and pattern.