Detection method for diel vertical migration pattern using 2D cross‐correlation with ADCP backscatter time‐series data
Abstract
Abstract Diel vertical migration (DVM), which refers to the global daily migration of zooplankton and micronekton (hereafter ‘zooplankton’), serves an important function in oceanic ecosystems. DVM can be recognized as a variation in the sound scattering layer (SSL), but no standard exists for identifying SSLs, and no definition has been proposed to describe the basic features of DVM. Hence, a standardized DVM detection method is needed to report consistent results and efficiently compare the parameters over broad ocean areas and long time‐scales. We developed an automated, quantitative method for detecting DVM and identifying the characteristic parameters using 2D cross‐correlation. We established the DVM trajectory model with linear and sinusoidal parts featuring a specific height and width. The 2D cross‐correlation method was applied to acoustic echogram images of the volume backscattering strength (Sv, dB re 1 m −1 ) with a synthetic image made from the DVM trajectory model. From the cross‐correlation coefficients, we found the candidate lines exhibiting the strongest possibility of being DVM trajectories. We tested the DVM detection method on the acoustic echograms for 273 days, of which Sv was gathered by a bottom‐moored, upward‐looking acoustic Doppler current profiler (ADCP). For each identified DVM trajectory, four quantitative parameters describing their spatial and temporal structures (the maximum and minimum depths and ascent and descent times) were determined,…
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