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

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.

Using paired visual and passive acoustic surveys to estimate passive acoustic detection parameters for harbor porpoise abundance estimates.

Passive acoustic monitoring is a promising approach for monitoring long-term trends in harbor porpoise (Phocoena phocoena) abundance. Before passive acoustic monitoring can be implemented to estimate harbor porpoise abundance, information about the detectability of harbor porpoise is needed to convert recorded numbers of echolocation clicks to harbor porpoise densities. In the present study, paired data from a grid of nine passive acoustic click detectors (C-PODs, Chelonia Ltd., United Kingdom) and three days of simultaneous aerial line-transect visual surveys were collected over a 370 km2 study area. The focus of the study was estimating the effective detection area of the passive acoustic sensors, which was defined as the product of the sound production rate of individual animals and the area within which those sounds are detected by the passive acoustic sensors. Visually estimated porpoise densities were used as informative priors in a Bayesian model to solve for the effective detection area for individual harbor porpoises. This model-based approach resulted in a posterior distribution of the effective detection area of individual harbor porpoises consistent with previously published values. This technique is a viable alternative for estimating the effective detection area of passive acoustic sensors when other experimental approaches are not feasible.

Using individual-based bioenergetic models to predict the aggregate effects of disturbance on populations: A case study with beaked whales and Navy sonar.

Anthropogenic activities can lead to changes in animal behavior. Predicting population consequences of these behavioral changes requires integrating short-term individual responses into models that forecast population dynamics across multiple generations. This is especially challenging for long-lived animals, because of the different time scales involved. Beaked whales are a group of deep-diving odontocete whales that respond behaviorally when exposed to military mid-frequency active sonar (MFAS), but the effect of these nonlethal responses on beaked whale populations is unknown. Population consequences of aggregate exposure to MFAS was assessed for two beaked whale populations that are regularly present on U.S. Navy training ranges where MFAS is frequently used. Our approach integrates a wide range of data sources, including telemetry data, information on spatial variation in habitat quality, passive acoustic data on the temporal pattern of sonar use and its relationship to beaked whale foraging activity, into an individual-based model with a dynamic bioenergetic module that governs individual life history. The predicted effect of disturbance from MFAS on population abundance ranged between population extinction to a slight increase in population abundance. These effects were driven by the interaction between the temporal pattern of MFAS use, baseline movement patterns, the spatial distribution of prey, the nature of beaked whale behavioral response to MFAS and the top-down impact of whale foraging on prey abundance. Based on these findings, we provide recommendations for monitoring of marine mammal populations and highlight key uncertainties to help guide future directions for assessing population impacts of nonlethal disturbance for these and other long-lived animals.