Hierarchical modelling approach to estimate the abundance of data-limited cetacean species and its application to fishery-targeted and rarely seen delphinid species off Japan

An assessment of the abundances and their trends is urgently needed for the conservation and management of fishery-targeted and rarely seen cetacean species (FTCS and RSCS, respectively); however, such assessment is often challenging because of the paucity of available data. In particular, the number of sightings is smaller than the general requirement for the reliable estimation of a detection function, and the spatial coverage of many cetacean surveys is insufficient. To address these issues, we propose a Bayesian approach that uses the previous abundance estimation of the same species or a species with similar biological traits as prior information. Therefore, we obtained the latest abundance estimates for six FTCS and two RSCS. For FTCS, we also estimated abundance trends by fitting an exponential population dynamics model with random effects accounting for interannual changes in animal distributions to the posterior samples of the Bayesian abundance estimates. Our approach enables us to (1) facilitate stakeholders' consensus by maintaining previously agreed abundances while updating the conservation information; (2) identify the species of greater concern and prioritize conservation efforts towards those species; and (3) monitor the abundance and trends of data-limited cetacean species.

Automated summary

An assessment of the abundances and trends of fishery-targeted and rarely seen cetacean species is urgently needed, but there is a lack of data. To address this, a Bayesian approach is proposed using prior information from previous abundance estimations. This approach allows for maintaining previous consensus, prioritizing conservation efforts, and monitoring data-limited cetacean species.