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Estimating spatio-temporal reproductive dynamics of fish populations with passive acoustic monitoring: A state-space model approach

Ota, Keisuke1; Akamatsu, Tomonari2; Osada, Yutaka1; Kondoh, Michio1

Published Dec 10, 2025 on Dryad. https://doi.org/10.5061/dryad.zkh1893qn

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Abstract

Passive acoustic monitoring (PAM) has been used to estimate the presence and spatial distribution of target organisms using biological sounds received by microphones. Due to its cost-effectiveness and non-invasiveness, PAM is becoming a promising approach for studying the spatiotemporal dynamics of large groups in response to environmental changes. However, conventional PAM can face significant constraints in dealing with the collective vocalisations of organisms. Here, we extend the traditional sound propagation equation for targeting a collectively vocalising group and propose a state-space model that estimates the acoustic group’s location and size with a limited number of microphones. These developments overcome traditional limitations, such as financial, operational, and methodological costs and problems associated with the use of numerous microphones. Simulation studies confirmed that the model produced systematically unbiased estimates of acoustic group size and location across varying group parameters. Furthermore, the estimations of the acoustic group locations were robust to a violation of the model assumption that the spatial extent of the acoustic group is temporally constant. As an empirical demonstration, applying the proposed approach to white croaker (Pennahia argentata) tracked the daily movement of the acoustic group centre in relation to tidal conditions. Moreover, the approach not only revealed temporal variations in acoustic group size with a 10-minute resolution but also revealed temporal shifts in the peak timing of choruses. These findings demonstrate the potential for novel biological insights. The proposed approach enables long-term and comprehensive assessment of biological status and supports effective resource management through spatiotemporally fine-scale predictions of future distribution and abundance. Moreover, this approach can be applied to collectively vocalising groups across a wide range of taxonomic groups, including birds, insects and amphibians, even when using a limited number of microphones.