Ecological correlates of blue whale movement behavior and its predictability in the California Current Ecosystem during the summer-fall feeding season.

BACKGROUND: Species distribution models have shown that blue whales (Balaenoptera musculus) occur seasonally in high densities in the most biologically productive regions of the California Current Ecosystem (CCE). Satellite telemetry studies have additionally shown that blue whales in the CCE regularly switch between behavioral states consistent with area-restricted searching (ARS) and transiting, indicative of foraging in and moving among prey patches, respectively. However, the relationship between the environmental correlates that serve as a proxy of prey relative to blue whale movement behavior has not been quantitatively assessed. METHODS: We investigated the association between blue whale behavioral state and environmental predictors in the coastal environments of the CCE using a long-term satellite tracking data set (72 tagged whales; summer-fall months 1998-2008), and predicted the likelihood of ARS behavior at tracked locations using nonparametric multiplicative regression models. The models were built using data from years of cool, productive conditions and validated against years of warm, low-productivity conditions. RESULTS: The best model contained four predictors: chlorophyll-a, sea surface temperature, and seafloor aspect and depth. This model estimated highest ARS likelihood (> 0.8) in areas with high chlorophyll-a levels (> 0.65 mg/m3), intermediate sea surface temperatures (11.6-17.5 °C), and shallow depths (< 850 m). Overall, the model correctly predicted behavioral state throughout the coastal environments of the CCE, while the validation indicated an ecosystem-wide reduction in ARS likelihood during warm years, especially in the southern portion. For comparison, a spatial coordinates model (longitude × latitude) performed slightly better than the environmental model during warm years, providing further evidence that blue whales exhibit strong foraging site fidelity, even when conditions are not conducive to successful foraging. CONCLUSIONS: We showed that blue whale behavioral state in the CCE was predictable from environmental correlates and that ARS behavior was most prevalent in regions of known high whale density, likely reflecting where large prey aggregations consistently develop in summer-fall. Our models of whale movement behavior enhanced our understanding of species distribution by further indicating where foraging was more likely, which could be of value in the identification of key regions of importance for endangered species in management considerations. The models also provided evidence that decadal-scale environmental fluctuations can drive shifts in the distribution and foraging success of this blue whale population.

Memory and resource tracking drive blue whale migrations.

In terrestrial systems, the green wave hypothesis posits that migrating animals can enhance foraging opportunities by tracking phenological variation in high-quality forage across space (i.e., "resource waves"). To track resource waves, animals may rely on proximate cues and/or memory of long-term average phenologies. Although there is growing evidence of resource tracking in terrestrial migrants, such drivers remain unevaluated in migratory marine megafauna. Here we present a test of the green wave hypothesis in a marine system. We compare 10 years of blue whale movement data with the timing of the spring phytoplankton bloom resulting in increased prey availability in the California Current Ecosystem, allowing us to investigate resource tracking both contemporaneously (response to proximate cues) and based on climatological conditions (memory) during migrations. Blue whales closely tracked the long-term average phenology of the spring bloom, but did not track contemporaneous green-up. In addition, blue whale foraging locations were characterized by low long-term habitat variability and high long-term productivity compared with contemporaneous measurements. Results indicate that memory of long-term average conditions may have a previously underappreciated role in driving migratory movements of long-lived species in marine systems, and suggest that these animals may struggle to respond to rapid deviations from historical mean environmental conditions. Results further highlight that an ecological theory of migration is conserved across marine and terrestrial systems. Understanding the drivers of animal migration is critical for assessing how environmental changes will affect highly mobile fauna at a global scale.

Capturing foraging and resting behavior using nested multivariate Markov models in an air-breathing marine vertebrate.

BACKGROUND: Matching animal movement with the behaviors that shape life history requires a rigorous connection between the observed patterns of space use and inferred behavioral states. As animal-borne dataloggers capture a greater diversity and frequency of three dimensional movements, we can increase the complexity of movement models describing animal behavior. One challenge in combining data streams is the different spatial and temporal frequency of observations. Nested movement models provide a flexible framework for gleaning data from long-duration, but temporally sparse, data sources. RESULTS: Using a two-layer nested model, we combined geographic and vertical movement to infer traveling, foraging and resting behaviors of Humpback whales off the West Antarctic Peninsula. This approach refined previous work using only geographic data to delineate coarser behavioral states. Our results showed increased intensity in foraging activity in late season animals as the whales prepared to migrate north to tropical calving grounds. Our model also suggests strong diel variation in movement states, likely linked to daily changes in prey distribution. CONCLUSIONS: Using a combination of two-dimensional and three-dimensional movement data, we highlight the connection between whale movement and krill availability, as well as the complex spatial pattern of whale foraging in productive polar waters.

Sperm whale dive behavior characteristics derived from intermediate-duration archival tag data.

Here, we describe the diving behavior of sperm whales (Physeter macrocephalus) using the Advanced Dive Behavior (ADB) tag, which records depth data at 1-Hz resolution and GPS-quality locations for over 1 month, before releasing from the whale for recovery. A total of 27 ADB tags were deployed on sperm whales in the central Gulf of California, Mexico, during spring 2007 and 2008, of which 10 were recovered for data download. Tracking durations of all tags ranged from 0 to 34.5 days (median = 2.3 days), and 0.6 to 26.6 days (median = 5.0 days) for recovered tags. Recovered tags recorded a median of 50.8 GPS-quality locations and 42.6 dives per day. Dive summary metrics were generated for archived dives and were subsequently classified into six categories using hierarchical cluster analysis. A mean of 77% of archived dives per individual were one of four dive categories with median Maximum Dive Depth >290 m (V-shaped, Mid-water, Benthic, or Variable), likely associated with foraging. Median Maximum Dive Depth was <30 m for the other two categories (Short- and Long-duration shallow dives), likely representing socializing or resting behavior. Most tagged whales remained near the tagging area during the tracking period, but one moved north of Isla Tiburón, where it appeared to regularly dive to, and travel along the seafloor. Three whales were tagged on the same day in 2007 and subsequently traveled in close proximity (<1 km) for 2 days. During this period, the depth and timing of their dives were not coordinated, suggesting they were foraging on a vertically heterogeneous prey field. The multiweek dive records produced by ADB tags enabled us to generate a robust characterization of the diving behavior, activity budget, and individual variation for an important predator of the mesopelagos over temporal and spatial scales not previously possible.

The development of an intermediate-duration tag to characterize the diving behavior of large whales.

The development of high-resolution archival tag technologies has revolutionized our understanding of diving behavior in marine taxa such as sharks, turtles, and seals during their wide-ranging movements. However, similar applications for large whales have lagged behind due to the difficulty of keeping tags on the animals for extended periods of time. Here, we present a novel configuration of a transdermally attached biologging device called the Advanced Dive Behavior (ADB) tag. The ADB tag contains sensors that record hydrostatic pressure, three-axis accelerometers, magnetometers, water temperature, and light level, all sampled at 1 Hz. The ADB tag also collects Fastloc GPS locations and can send dive summary data through Service Argos, while staying attached to a whale for typical periods of 3-7 weeks before releasing for recovery and subsequent data download. ADB tags were deployed on sperm whales (Physeter macrocephalus; N = 46), blue whales (Balaenoptera musculus; N = 8), and fin whales (B. physalus; N = 5) from 2007 to 2015, resulting in attachment durations from 0 to 49.6 days, and recording 31 to 2,539 GPS locations and 27 to 2,918 dives per deployment. Archived dive profiles matched well with published dive shapes of each species from short-term records. For blue and fin whales, feeding lunges were detected using peaks in accelerometer data and matched corresponding vertical excursions in the depth record. In sperm whales, rapid orientation changes in the accelerometer data, often during the bottom phase of dives, were likely related to prey pursuit, representing a relative measure of foraging effort. Sperm whales were documented repeatedly diving to, and likely foraging along, the seafloor. Data from the temperature sensor described the vertical structure of the water column in all three species, extending from the surface to depths >1,600 m. In addition to providing information needed to construct multiweek time budgets, the ADB tag is well suited to studying the effects of anthropogenic sound on whales by allowing for pre- and post-exposure monitoring of the whale's dive behavior. This tag begins to bridge the gap between existing long-duration but low-data throughput tags, and short-duration, high-resolution data loggers.

Critically endangered western gray whales migrate to the eastern North Pacific.

Western North Pacific gray whales (WGWs), once considered extinct, are critically endangered with unknown migratory routes and reproductive areas. We attached satellite-monitored tags to seven WGWs on their primary feeding ground off Sakhalin Island, Russia, three of which subsequently migrated to regions occupied by non-endangered eastern gray whales (EGWs). A female with the longest-lasting tag visited all three major EGW reproductive areas off Baja California, Mexico, before returning to Sakhalin Island the following spring. Her 22 511 km round-trip is the longest documented mammal migration and strongly suggests that some presumed WGWs are actually EGWs foraging in areas historically attributed to WGWs. The observed migration routes provide evidence of navigational skills across open water that break the near-shore north-south migratory paradigm of EGWs. Despite evidence of genetic differentiation, these tagging data indicate that the population identity of whales off Sakhalin Island needs further evaluation.

Spatial and temporal occurrence of blue whales off the U.S. West Coast, with implications for management.

Mortality and injuries caused by ship strikes in U.S. waters are a cause of concern for the endangered population of blue whales (Balaenoptera musculus) occupying the eastern North Pacific. We sought to determine which areas along the U.S. West Coast are most important to blue whales and whether those areas change inter-annually. Argos-monitored satellite tags were attached to 171 blue whales off California during summer/early fall from 1993 to 2008. We analyzed portions of the tracks that occurred within U.S. Exclusive Economic Zone waters and defined the 'home range' (HR) and 'core areas' (CAU) as the 90% and 50% fixed kernel density distributions, respectively, for each whale. We used the number of overlapping individual HRs and CAUs to identify areas of highest use. Individual HR and CAU sizes varied dramatically, but without significant inter-annual variation despite covering years with El Niño and La Niña conditions. Observed within-year differences in HR size may represent different foraging strategies for individuals. The main areas of HR and CAU overlap among whales were near highly productive, strong upwelling centers that were crossed by commercial shipping lanes. Tagged whales generally departed U.S. Exclusive Economic Zone waters from mid-October to mid-November, with high variability among individuals. One 504-d track allowed HR and CAU comparisons for the same individual across two years, showing similar seasonal timing, and strong site fidelity. Our analysis showed how satellite-tagged blue whales seasonally used waters off the U.S. West Coast, including high-risk areas. We suggest possible modifications to existing shipping lanes to reduce the likelihood of collisions with vessels.

Cumulative human impacts on marine predators.

Stressors associated with human activities interact in complex ways to affect marine ecosystems, yet we lack spatially explicit assessments of cumulative impacts on ecologically and economically key components such as marine predators. Here we develop a metric of cumulative utilization and impact (CUI) on marine predators by combining electronic tracking data of eight protected predator species (n=685 individuals) in the California Current Ecosystem with data on 24 anthropogenic stressors. We show significant variation in CUI with some of the highest impacts within US National Marine Sanctuaries. High variation in underlying species and cumulative impact distributions means that neither alone is sufficient for effective spatial management. Instead, comprehensive management approaches accounting for both cumulative human impacts and trade-offs among multiple stressors must be applied in planning the use of marine resources.