The development of sophisticated multi-sensor tags incorporating high-resolution movement sensors and hydrophones has enabled unprecedented views of the 3D fine-scale movement behaviour of cetaceans, especially for those species that use sound to forage. However, these tags are expensive, making them inaccessible to most researchers. Time-Depth Recorders (TDRs), which have been widely used to study diving and foraging behaviour of marine mammals, offer a more affordable alternative. Unfortunately, data collected by TDRs are bi-dimensional (time and depth only), so quantifying foraging effort from those data is challenging.Pérez-Jorge et al. (2023) developed a predictive model of prey capture attempts (PCAs) for sperm whales from low-resolution time-depth data. To develop this model, high-resolution movement and acoustic data from 12 sperm whales instrumented with digital acoustic recording tags (Dtags; Johnson et al., 2003; Oliveira et al., 2022) between 2017 and 2019 in the Azores archipelago, Portugal. This data was used to extract time-depth values at a sampling frequency of 1 second (typical sampling rate of low-resolution time-depth data) and detect buzzes, considered to represent PCAs. Based on the extracted time-depth values, a suite of dive metrics (ie., average depth, variance of depth) were obtained for different segment durations (30 seconds, 60 s, 180 s and 300 s). The present dataset includes the extracted dive metrics for the four segment durations selected on the final model of the study (Pérez-Jorge et al., 2023).Data provided for each record include the event number, individual identification, dive identification, date of sampling, latitude, longitude, dive phase, segment duration, number of buzzes, average of water depth per segment, variance of water depth per segment and variance of velocity.

Additional funding: Marine mammal and Ecosystem: anthropogenic Threat Assessment (META), FA_06_2017_017, Portuguese Republic through Fundo Azul