Assessing cetacean populations using integrated population models:an example with Cook Inlet beluga whales

• Published in: Ecological Applications
• Main Authors: Jacobson, Eiren K., Boyd, Charlotte, McGuire, Tamara L., Shelden, Kim E. W., Himes Boor, Gina K., Punt, André E.
• Format: Article in Journal/Newspaper
• Language: English
• Published: 2020
• Subjects: Bayesian statistics; beluga whales; cetaceans; integrated modeling; population dynamics; state-space models; Beluga; Beluga*; Delphinapterus leucas
• Online Access: https://research-portal.st-andrews.ac.uk/en/researchoutput/assessing-cetacean-populations-using-integrated-population-models(11f37213-e246-4062-bf6e-456dc3ef7eab).html; https://doi.org/10.1002/eap.2114

Abstract Effective conservation and management of animal populations requires knowledge of abundance and trends. For many species, these quantities are estimated using systematic visual surveys. Additional individual-level data are available for some species. Integrated population modeling (IPM) offers a mechanism for leveraging these data sets into a single estimation framework. IPMs that incorporate both population- and individual-level data have previously been developed for birds, but have rarely been applied to cetaceans. Here, we explore how IPMs can be used to improve the assessment of cetacean populations. We combined three types of data that are typically available for cetaceans of conservation concern: population-level visual survey data, individual-level capture?recapture data, and data on anthropogenic mortality. We used this IPM to estimate the population dynamics of the Cook Inlet population of beluga whales (CIBW; Delphinapterus leucas ) as a case study. Our state-space IPM included a population process model and three observational submodels: (1) a group detection model to describe group size estimates from aerial survey data; (2) a capture?recapture model to describe individual photographic capture?recapture data; and (3) a Poisson regression model to describe historical hunting data. The IPM produces biologically plausible estimates of population trajectories consistent with all three data sets. The estimated population growth rate since 2000 is less than expected for a recovering population. The estimated juvenile/adult survival rate is also low compared to other cetacean populations, indicating that low survival may be impeding recovery. This work demonstrates the value of integrating various data sources to assess cetacean populations and serves as an example of how multiple, imperfect data sets can be combined to improve our understanding of a population of interest. The model framework is applicable to other cetacean populations and to other taxa for which similar data types are available.