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.
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.
Aim
Advances in ecological and environmental modelling offer new opportunities for estimating dynamic habitat suitability for highly mobile species and supporting management strategies at relevant ...spatiotemporal scales. We used an ensemble modelling approach to predict daily, year‐round habitat suitability for a migratory species, the blue whale (Balaenoptera musculus), and demonstrate an application for evaluating the spatiotemporal dynamics of their exposure to ship strike risk.
Location
The California Current Ecosystem (CCE) and the Southern California Bight (SCB), USA.
Methods
We integrated a long‐term (1994–2008) satellite tracking dataset on 104 blue whales with data‐assimilative ocean model output to assess year‐round habitat suitability. We evaluated the relative utility of ensembling multiple model types compared to using single models, and selected and validated candidate models using multiple cross‐validation metrics and independent observer data. We quantified the spatial and temporal distribution of exposure to ship strike risk within shipping lanes in the SCB.
Results
Multi‐model ensembles outperformed single‐model approaches. The final ensemble model had high predictive skill (AUC = 0.95), resulting in daily, year‐round predictions of blue whale habitat suitability in the CCE that accurately captured migratory behaviour. Risk exposure in shipping lanes was highly variable within and among years as a function of environmental conditions (e.g., marine heatwave).
Main conclusions
Daily information on three‐dimensional oceanic habitats was used to model the daily distribution of a highly migratory species with high predictive power and indicated that management strategies could benefit by incorporating dynamic environmental information. This approach is readily transferable to other species. Dynamic, high‐resolution species distribution models are valuable tools for assessing risk exposure and targeting management needs.
Animals make behavioural and reproductive decisions that maximise their lifetime reproductive success, and thus their fitness, in light of periodic and stochastic variability of the environment. ...Modelling the variation of an individual's energy levels formalises this tradeoff and helps to quantify the population‐level consequences of stressors (e.g. disturbance from human activities and environmental change) that can affect behaviour or physiology. In this study, we develop a dynamic state variable model for the spatially explicit behaviour, physiology and reproduction of a female, long‐lived, migratory marine vertebrate. The model can be used to investigate the spatio‐temporal patterns of behaviour and reproduction that allow an individual to maximise its overall reproductive output. We parametrised the model for eastern North Pacific blue whales Balaenoptera musculus, and used it to predict the effects of changing environmental conditions and increasing human disturbance on the population's vital rates. In baseline conditions, the model output had high fidelity to observed energy dynamics, movement patterns and reproductive strategies. Simulated scenarios suggested that environmental changes could have severe consequences on the population's vital rates, but that individuals could tolerate high levels of anthropogenic disturbance. However, this ability depended on where, when and how often disturbance occurred. In scenarios with both environmental change and anthropogenic disturbance, synergistic interactions caused stronger effects than in isolation. In general, larger body size offered a buffer against stochasticity and disturbance, and, consequently, we predicted juveniles to be more susceptible to disturbance. We also predicted that females prioritise their own survival at the expense of the current reproductive attempt, presumably the result of their long lifespan. Our approach provides a general framework to make predictions of the cumulative and synergistic effects of human disturbance and climate change on migratory populations, which can inform effective management and conservation efforts.
There is a lack of detailed information about the range and habitat use of gray whales (Eschrichtius robustus) during their seasonal occupation off the Pacific Northwest (PNW) coast from northern ...California to southeast Alaska, USA. These data are important for management because of anthropogenic pressures (e.g., indigenous harvesting, fishing gear entanglements, ship strikes, naval exercises, siting of marine renewable energy facilities). We applied satellite tags to 35 gray whales in the eastern north Pacific (ENP) off the coasts of Oregon and northern California from September to December 2009, 2012, and 2013. These whales are members of the Pacific Coast Feeding Group (PCFG), a subset of gray whales in the ENP that feed off the PNW, during summer and fall. Tracking periods for the satellite-tagged whales in this study ranged from 3 days to 383 days. We applied a Bayesian switching state-space model (SSSM) to locations for each whale track to provide a regularized track with 2 estimated locations per day and associated movement behavior (either transiting or area-restricted searching ARS). We isolated the portion of the SSSM track in the feeding area for each whale by removing all southward and northward migration locations. We calculated home ranges (90% isopleths) and core areas (50% isopleths) for these non-migrating, feeding-area tracks with >50 SSSM locations using local convex hull utilization distributions. Feeding-area home ranges for the resulting 23 whales covered most of the near-shore waters from northern California to Icy Bay, Alaska, and ranged in size from 81 km² to 13,634 km². Core areas varied widely in size (11–3,976 km²) and location between individuals, with the highest-use areas off Point St. George in northern California, the central coast of Oregon, and the southern coast of Washington, USA. Nearshore waters off Point St. George were a hot spot for whales in the PCFG in late fall, close to where most of the whales were tagged; 19 whales had overlapping home ranges and 15 whales had overlapping core areas there. One whale, a male tracked for 383 days, did not migrate, spending the entire winter off Point St. George and the California-Oregon border. Residence times (portions of the track with a minimum of 3 successive locations in ARS behavioral mode) ranged from 1 day to 142.5 days; 19 whales had residencies >30 days in some areas. Because most of the whales in this study were tagged in the fall in the southern portion of the feeding area, off northern California, results are weighted toward fall and winter movements. Although some whales were tracked into the spring and summer, additional tagging earlier in the year and in more northerly locations would provide an even clearer picture of gray whale use of feeding areas in the PNW. Nevertheless, these results constitute valuable information about high-use areas for gray whales in this region, providing baseline home range data for future comparisons with regard to year-to-year variability, potential responses to climate change, and exposure to anthropogenic activities in the marine environment.
Aim
Ship strikes are one of the largest sources of human‐caused mortality for baleen whales on the West Coast of the United States. Reducing ship‐strike risk in this region is complicated by changes ...in ship traffic that resulted from air pollution regulations and economic factors. A diverse group of stakeholders was convened to develop strategies to reduce ship‐strike risk in the Southern California Bight. Strategies proposed by some stakeholders included: (a) adding a shipping route; (b) expanding the existing area to be avoided (ATBA); and (c) reducing ship speeds.
Location
Southern California Bight, off the coast of California, United States.
Methods
We developed methods to estimate ship traffic in the stakeholder‐derived strategies using 8 years of ship traffic data. To assess ship‐strike risk for fin, humpback, and blue whales, we used habitat models developed from 7 years of survey data and home ranges derived from 53 blue whale tags. We defined collision risk as the co‐occurrence between whales and ships. The risk of a lethal collision was calculated by multiplying collision risk by the probability that a collision is lethal, which is estimated using ship speed.
Results
Speed reductions resulted in a large decrease in the risk of a lethal ship strike. Creating a shipping route or expanding the ATBA reduced the risk of a strike by removing traffic from a whale feeding area. Creating a shipping route was opposed by the United States Navy and the shipping industry, but expanding the ATBA was broadly supported.
Main conclusions
Our analyses suggest that speed reductions and expanding the ATBA may provide an optimal solution for addressing stakeholder needs and reducing ship strikes in the Southern California Bight. The methods we developed can be used to address the global issue of balancing human use of the marine environment with the protection of whale populations.
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.
Despite spending most time underwater, the technology in use to track whales over large geographic ranges via satellite has been largely limited to locational data, with most applications focusing on ...characterizing their horizontal movements. We describe the development of the RDW tag, a new Argos-based satellite telemetry device that incorporates sensors for monitoring the movements and dive behavior of large whales over several months without requiring recovery. Based on an implantable design, the tag features a saltwater conductivity switch, a tri-axial accelerometer, and an optional pressure transducer, along with onboard software for data processing and detection of behavioral events or activities of interest for transmission. We configured the software to detect dives and create per-dive summaries describing behavioral events associated with feeding activities in rorqual whales. We conducted a validation by proxy of the dive summary and event detection algorithms using field data from a medium-duration archival tag. We also conducted a simulation exercise to examine how the expected data recovery would vary under different dive behavior scenarios and compared those results to empirical values from field deployments of the RDW tag on blue (Balaenoptera musculus) and humpback (Megaptera novaeangliae) whales. The dive summary algorithm accurately reported dive depth and duration, while the accuracy of the lunge-feeding event detection algorithm was dependent on the precision of the accelerometer data that was used, with a predicted accuracy of 0.74 for correctly classifying feeding dives from 1/64-G precision data and 0.95 from 1-mG precision data. Simulated data recovery was lower with sparser transmission schedules, shorter mean dive durations, and lower rates of successfully received transmissions. Empirical data recovery was lower than expected from the simulation, suggesting the effect of additional factors, such as data gaps. By measuring key aspects of the per-dive behavior of large whales over multi-month timescales of movement, the RDW tags provide the ability to monitor previously unobservable behaviors across entire geographic ranges, extending the applications of satellite telemetry devices to new areas of whale physiology, behavior, ecology, and conservation.
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.
We present a multiweek data logger developed to record large whale behavior at high resolution (1‐Hz) while collecting GPS‐quality locations. The tag has been deployed on blue, fin, and sperm whales, and it has recorded diving and feeding behaviors during dives down to 1,600 m deep. Capable of staying attached to an animal for periods of up to 7 weeks, this tag fills a critical technology gap and represents a dramatic improvement in our ability to study the behavior of large whales and the ecological mechanisms that drive it.
Species distribution models have shown that blue whales (
) 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.
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.
The best model contained four predictors: chlorophyll-
, sea surface temperature, and seafloor aspect and depth. This model estimated highest ARS likelihood (> 0.8) in areas with high chlorophyll-
levels (> 0.65 mg/m
), 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.
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.
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