Large differences in the distribution of pelagic biomass as a result of sonar frequency choice

Recent efforts to understand the global distribution of pelagic fauna have primarily relied on 38 kHz sonar observations, using water-column backscatter as a proxy of biomass. However, backscatter gradients across ocean provinces are not always consistent with biomass observations from net sampling. This mismatch is particularly evident in temperate to polar transition zones due to changes in resonance of pelagic fauna, which depends on sonar frequency but also on the size of resonant organs, such as fish swimbladders or zooplankton gas inclusions. Here, we investigate how sonar frequency choice changes our vision of pelagic ecosystems across latitudes. We analyse sonar observations at 38 and 18 kHz along with size distributions of swimbladdered fish species across the Indian Ocean Subantarctic Front. Our results show a shift from 38 to 18 kHz dominance towards the poles. More interestingly, backscatter differences across the Subantarctic Front are four times larger at 38 kHz compared t..., , , # **Large differences in the distribution of pelagic biomass as a result of sonar frequency choice**

**Dataset DOI:** 10.5061/dryad.3n5tb2rs7

### Description of the Data and File Structure

This dataset supports the analyses presented in our paper and its supplementary material. The latter provides detailed information on the methodology and intermediate results used to describe and model the vertical distribution of acoustic backscatter across the Indian sector of the Southern Ocean. Data were collected as part of the *Toward Hydroacoustics and Ecology of Mid-trophic levels in Indian and Southern Ocean* (THEMISTO) observation programme (DOI: 10.18142/288).

We recommend consulting the supplementary material alongside this dataset and the provided scripts. Data were collected during austral summer cruises in January, February, and March of 2021, 2022, and 2023.

Firstly, we detail the analysis of *in situ* acoustic observations, focusing on the application of functional data analysis ...,