Killer whale respiration rates.

Measuring breathing rates is a means by which oxygen intake and metabolic rates can be estimated to determine food requirements and energy expenditure of killer whales (Orcinus orca) and other cetaceans. This relatively simple measure also allows the energetic consequences of environmental stressors to cetaceans to be understood but requires knowing respiration rates while they are engaged in different behaviours such as resting, travelling and foraging. We calculated respiration rates for different behavioural states of southern and northern resident killer whales using video from UAV drones and concurrent biologging data from animal-borne tags. Behavioural states of dive tracks were predicted using hierarchical hidden Markov models (HHMM) parameterized with time-depth data and with labeled tracks of drone-identified behavioural states (from drone footage that overlapped with the time-depth data). Dive tracks were sequences of dives and surface intervals lasting ≥ 10 minutes cumulative duration. We calculated respiration rates and estimated oxygen consumption rates for the predicted behavioural states of the tracks. We found that juvenile killer whales breathed at a higher rate when travelling (1.6 breaths min-1) compared to resting (1.2) and foraging (1.5)-and that adult males breathed at a higher rate when travelling (1.8) compared to both foraging (1.7) and resting (1.3). The juveniles in our study were estimated to consume 2.5-18.3 L O2 min-1 compared with 14.3-59.8 L O2 min-1 for adult males across all behaviours based on estimates of mass-specific tidal volume and oxygen extraction. Our findings confirm that killer whales take single breaths between dives and indicate that energy expenditure derived from respirations requires using sex, age, and behavioural-specific respiration rates. These findings can be applied to bioenergetics models on a behavioural-specific basis, and contribute towards obtaining better predictions of dive behaviours, energy expenditure and the food requirements of apex predators.

Migratory movements of fin whales from the Gulf of St. Lawrence challenge our understanding of the Northwest Atlantic stock structure.

Fin whales, Balenoptera physalus, are capital breeders, having the potential to separate breeding and feeding both spatially and temporally. Fin whales occur throughout the Northwest Atlantic, but stock structure and seasonal movements remain unclear. By deploying satellite transmitters on 28 individuals, we examine movement patterns within and beyond the Gulf of St. Lawrence (GSL), Canada, and challenge the current understanding of stock structure. Eight individuals left the GSL in autumn, with five tags persisting into January. Migration patterns of these whales showed considerable variation in timing and trajectory, with movements extending south to 24°N, and thus beyond the assumed distribution limit of the species in the Northwest Atlantic. A rapid return to the Scotian Shelf or Gulf of Maine was observed from several whales after incursions in southern waters, suggesting that fin whales in the Northwest Atlantic may not have a common winter destination that fits the definition of a breeding ground. Area-restricted search (ARS) behavior dominated fin whale activities during summer (92%) and fall (72%), with persistence into the winter (56%); ARS occurred at multiple locations in the GSL, Scotian Shelf and Shelf edge, and near seamounts of the North Atlantic, having characteristics consistent with foraging areas.

Divergent migration routes reveal contrasting energy-minimization strategies to deal with differing resource predictability.

BACKGROUND: Seasonal long-distance movements are a common feature in many taxa allowing animals to deal with seasonal habitats and life-history demands. Many species use different strategies to prioritize time- or energy-minimization, sometimes employing stop-over behaviours to offset the physiological burden of the directed movement associated with migratory behaviour. Migratory strategies are often limited by life-history and environmental constraints, but can also be modulated by the predictability of resources en route. While theory on population-wide strategies (e.g. energy-minimization) are well studied, there are increasing evidence for individual-level variation in movement patterns indicative of finer scale differences in migration strategies. METHODS: We aimed to explore sources of individual variation in migration strategies for long-distance migrators using satellite telemetry location data from 41 narwhal spanning a 21-year period. Specifically, we aimed to determine and define the long-distance movement strategies adopted and how environmental variables may modulate these movements. Fine-scale movement behaviours were characterized using move-persistence models, where changes in move-persistence, highlighting autocorrelation in a movement trajectory, were evaluated against potential modulating environmental covariates. Areas of low move-persistence, indicative of area-restricted search-type behaviours, were deemed to indicate evidence of stop-overs along the migratory route. RESULTS: Here, we demonstrate two divergent migratory tactics to maintain a similar overall energy-minimization strategy within a single population of narwhal. Narwhal migrating offshore exhibited more tortuous movement trajectories overall with no evidence of spatially-consistent stop-over locations across individuals. Nearshore migrating narwhal undertook more directed routes, contrasted by spatially-explicit stop-over behaviour in highly-productive fjord and canyon systems along the coast of Baffin Island for periods of several days to several weeks. CONCLUSIONS: Within a single population, divergent migratory tactics can achieve a similar overall energy-minimizing strategy within a species as a response to differing trade-offs between predictable and unpredictable resources. Our methodological approach, which revealed the modulators of fine-scale migratory movements and predicted regional stop-over sites, is widely applicable to a variety of other aquatic and terrestrial species. Quantifying marine migration strategies will be key for adaptive conservation in the face of climate change and ever increasing human pressures.

Linking movement and dive data to prey distribution models: new insights in foraging behaviour and potential pitfalls of movement analyses.

BACKGROUND: Animal movement data are regularly used to infer foraging behaviour and relationships to environmental characteristics, often to help identify critical habitat. To characterize foraging, movement models make a set of assumptions rooted in theory, for example, time spent foraging in an area increases with higher prey density. METHODS: We assessed the validity of these assumptions by associating horizontal movement and diving of satellite-telemetered ringed seals (Pusa hispida)-an opportunistic predator-in Hudson Bay, Canada, to modelled prey data and environmental proxies. RESULTS: Modelled prey biomass data performed better than their environmental proxies (e.g., sea surface temperature) for explaining seal movement; however movement was not related to foraging effort. Counter to theory, seals appeared to forage more in areas with relatively lower prey diversity and biomass, potentially due to reduced foraging efficiency in those areas. CONCLUSIONS: Our study highlights the need to validate movement analyses with prey data to effectively estimate the relationship between prey availability and foraging behaviour.

Drivers of polar bear behavior and the possible effects of prey availability on foraging strategy.

BACKGROUND: Change in behavior is one of the earliest responses to variation in habitat suitability. It is therefore important to understand the conditions that promote different behaviors, particularly in areas undergoing environmental change. Animal movement is tightly linked to behavior and remote tracking can be used to study ethology when direct observation is not possible. METHODS: We used movement data from 14 polar bears (Ursus maritimus) in Hudson Bay, Canada, during the foraging season (January-June), when bears inhabit the sea ice. We developed an error-tolerant method to correct for sea ice drift in tracking data. Next, we used hidden Markov models with movement and orientation relative to wind to study three behaviors (stationary, area-restricted search, and olfactory search) and examine effects of 11 covariates on behavior. RESULTS: Polar bears spent approximately 47% of their time in the stationary drift state, 29% in olfactory search, and 24% in area-restricted search. High energy behaviors occurred later in the day (around 20:00) compared to other populations. Second, olfactory search increased as the season progressed, which may reflect a shift in foraging strategy from still-hunting to active search linked to a shift in seal availability (i.e., increase in haul-outs from winter to the spring pupping and molting seasons). Last, we found spatial patterns of distribution linked to season, ice concentration, and bear age that may be tied to habitat quality and competitive exclusion. CONCLUSIONS: Our observations were generally consistent with predictions of the marginal value theorem, and differences between our findings and other populations could be explained by regional or temporal variation in resource availability. Our novel movement analyses and finding can help identify periods, regions, and conditions of critical habitat.

Decadal migration phenology of a long-lived Arctic icon keeps pace with climate change.

Animals migrate in response to seasonal environments, to reproduce, to benefit from resource pulses, or to avoid fluctuating hazards. Although climate change is predicted to modify migration, only a few studies to date have demonstrated phenological shifts in marine mammals. In the Arctic, marine mammals are considered among the most sensitive to ongoing climate change due to their narrow habitat preferences and long life spans. Longevity may prove an obstacle for species to evolutionarily respond. For species that exhibit high site fidelity and strong associations with migration routes, adjusting the timing of migration is one of the few recourses available to respond to a changing climate. Here, we demonstrate evidence of significant delays in the timing of narwhal autumn migrations with satellite tracking data spanning 21 y from the Canadian Arctic. Measures of migration phenology varied annually and were explained by sex and climate drivers associated with ice conditions, suggesting that narwhals are adopting strategic migration tactics. Male narwhals were found to lead the migration out of the summering areas, while females, potentially with dependent young, departed later. Narwhals are remaining longer in their summer areas at a rate of 10 d per decade, a similar rate to that observed for climate-driven sea ice loss across the region. The consequences of altered space use and timing have yet to be evaluated but will expose individuals to increasing natural changes and anthropogenic activities on the summering areas.

Predicting how climate change threatens the prey base of Arctic marine predators.

Arctic sea ice loss has direct consequences for predators. Climate-driven distribution shifts of native and invasive prey species may exacerbate these consequences. We assessed potential changes by modelling the prey base of a widely distributed Arctic predator (ringed seal; Pusa hispida) in a sentinel area for change (Hudson Bay) under high- and low-greenhouse gas emission scenarios from 1950 to 2100. All changes were relatively negligible under the low-emission scenario, but under the high-emission scenario, we projected a 50% decline in the abundance of the well-distributed, ice-adapted and energy-rich Arctic cod (Boreogadus saida) and an increase in the abundance of smaller temperate-associated fish in southern and coastal areas. Furthermore, our model predicted that all fish species declined in mean body size, but a 29% increase in total prey biomass. Declines in energy-rich prey and restrictions in their spatial range are likely to have cascading effects on Arctic predators.

Assessing the post-release effects of capture, handling and placement of satellite telemetry devices on narwhal (Monodon monoceros) movement behaviour.

Animal-borne telemetry devices have become a popular and valuable means for studying the cryptic lives of cetaceans. Evaluating the effect of capture, handling and tagging procedures remains largely unassessed across species. Here, we examine the effect of capture, handling and tagging activities on an iconic Arctic cetacean, the narwhal (Monodon monoceros), which has previously been shown to exhibit an extreme response to extended capture and handling. Using accelerometry-derived metrics of behaviour, including activity level, energy expenditure and swimming activity, we quantify the post-release responses and time to recovery of 19 individuals following capture and tagging activities considering the intrinsic covariates of sex and individual size and the extrinsic covariates of handling time and presence of a 'bolt-on' satellite telemetry device. From accelerometer-derived behaviour, most narwhals appeared to return to mean baseline behaviour (recovery) within 24 hours after release, which was supported by longer-term measures of diving data. None of the covariates measured, however, had an effect on the time individuals took to recover following release. Using generalized additive models to describe changes in behaviour over time, we found handling time to be a significant predictor of activity levels, energy expenditure and swimming behaviour following release. Individuals held for the longest period (>40 min) were found to display the largest effect in behaviour immediately following release with respect to swimming behaviour and activity levels. We also found some support for relationships between activity levels, energy expenditure and swimming activity and two other covariates: sex and the attachment of a bolt-on configuration satellite tags. Our results indicate that narwhals recover relatively quickly following capture, handling and tagging procedures, but we suggest that researchers should minimize handling time and further investigation is needed on how to mitigate potential effects of bolt-on satellite tags in these sensitive species.

A hidden Markov movement model for rapidly identifying behavioral states from animal tracks.

Electronic telemetry is frequently used to document animal movement through time. Methods that can identify underlying behaviors driving specific movement patterns can help us understand how and why animals use available space, thereby aiding conservation and management efforts. For aquatic animal tracking data with significant measurement error, a Bayesian state-space model called the first-Difference Correlated Random Walk with Switching (DCRWS) has often been used for this purpose. However, for aquatic animals, highly accurate tracking data are now becoming more common. We developed a new hidden Markov model (HMM) for identifying behavioral states from animal tracks with negligible error, called the hidden Markov movement model (HMMM). We implemented as the basis for the HMMM the process equation of the DCRWS, but we used the method of maximum likelihood and the R package TMB for rapid model fitting. The HMMM was compared to a modified version of the DCRWS for highly accurate tracks, the DCRWSNOME, and to a common HMM for animal tracks fitted with the R package moveHMM. We show that the HMMM is both accurate and suitable for multiple species by fitting it to real tracks from a grey seal, lake trout, and blue shark, as well as to simulated data. The HMMM is a fast and reliable tool for making meaningful inference from animal movement data that is ideally suited for ecologists who want to use the popular DCRWS implementation and have highly accurate tracking data. It additionally provides a groundwork for development of more complex modeling of animal movement with TMB. To facilitate its uptake, we make it available through the R package swim.

Evaluating random search strategies in three mammals from distinct feeding guilds.

Searching allows animals to find food, mates, shelter and other resources essential for survival and reproduction and is thus among the most important activities performed by animals. Theory predicts that animals will use random search strategies in highly variable and unpredictable environments. Two prominent models have been suggested for animals searching in sparse and heterogeneous environments: (i) the Lévy walk and (ii) the composite correlated random walk (CCRW) and its associated area-restricted search behaviour. Until recently, it was difficult to differentiate between the movement patterns of these two strategies. Using a new method that assesses whether movement patterns are consistent with these two strategies and two other common random search strategies, we investigated the movement behaviour of three species inhabiting sparse northern environments: woodland caribou (Rangifer tarandus caribou), barren-ground grizzly bear (Ursus arctos) and polar bear (Ursus maritimus). These three species vary widely in their diets and thus allow us to contrast the movement patterns of animals from different feeding guilds. Our results showed that although more traditional methods would have found evidence for the Lévy walk for some individuals, a comparison of the Lévy walk to CCRWs showed stronger support for the latter. While a CCRW was the best model for most individuals, there was a range of support for its absolute fit. A CCRW was sufficient to explain the movement of nearly half of herbivorous caribou and a quarter of omnivorous grizzly bears, but was insufficient to explain the movement of all carnivorous polar bears. Strong evidence for CCRW movement patterns suggests that many individuals may use a multiphasic movement strategy rather than one-behaviour strategies such as the Lévy walk. The fact that the best model was insufficient to describe the movement paths of many individuals suggests that some animals living in sparse environments may use strategies that are more complicated than those described by the standard random search models. Thus, our results indicate a need to develop movement models that incorporate factors such as the perceptual and cognitive capacities of animals.

State-space models' dirty little secrets: even simple linear Gaussian models can have estimation problems.

State-space models (SSMs) are increasingly used in ecology to model time-series such as animal movement paths and population dynamics. This type of hierarchical model is often structured to account for two levels of variability: biological stochasticity and measurement error. SSMs are flexible. They can model linear and nonlinear processes using a variety of statistical distributions. Recent ecological SSMs are often complex, with a large number of parameters to estimate. Through a simulation study, we show that even simple linear Gaussian SSMs can suffer from parameter- and state-estimation problems. We demonstrate that these problems occur primarily when measurement error is larger than biological stochasticity, the condition that often drives ecologists to use SSMs. Using an animal movement example, we show how these estimation problems can affect ecological inference. Biased parameter estimates of a SSM describing the movement of polar bears (Ursus maritimus) result in overestimating their energy expenditure. We suggest potential solutions, but show that it often remains difficult to estimate parameters. While SSMs are powerful tools, they can give misleading results and we urge ecologists to assess whether the parameters can be estimated accurately before drawing ecological conclusions from their results.

Inferring parturition and neonate survival from movement patterns of female ungulates: a case study using woodland caribou.

Analyses of animal movement data have primarily focused on understanding patterns of space use and the behavioural processes driving them. Here, we analyzed animal movement data to infer components of individual fitness, specifically parturition and neonate survival. We predicted that parturition and neonate loss events could be identified by sudden and marked changes in female movement patterns. Using GPS radio-telemetry data from female woodland caribou (Rangifer tarandus caribou), we developed and tested two novel movement-based methods for inferring parturition and neonate survival. The first method estimated movement thresholds indicative of parturition and neonate loss from population-level data then applied these thresholds in a moving-window analysis on individual time-series data. The second method used an individual-based approach that discriminated among three a priori models representing the movement patterns of non-parturient females, females with surviving offspring, and females losing offspring. The models assumed that step lengths (the distance between successive GPS locations) were exponentially distributed and that abrupt changes in the scale parameter of the exponential distribution were indicative of parturition and offspring loss. Both methods predicted parturition with near certainty (>97% accuracy) and produced appropriate predictions of parturition dates. Prediction of neonate survival was affected by data quality for both methods; however, when using high quality data (i.e., with few missing GPS locations), the individual-based method performed better, predicting neonate survival status with an accuracy rate of 87%. Understanding ungulate population dynamics often requires estimates of parturition and neonate survival rates. With GPS radio-collars increasingly being used in research and management of ungulates, our movement-based methods represent a viable approach for estimating rates of both parameters.

Spatial memory and animal movement.

Memory is critical to understanding animal movement but has proven challenging to study. Advances in animal tracking technology, theoretical movement models and cognitive sciences have facilitated research in each of these fields, but also created a need for synthetic examination of the linkages between memory and animal movement. Here, we draw together research from several disciplines to understand the relationship between animal memory and movement processes. First, we frame the problem in terms of the characteristics, costs and benefits of memory as outlined in psychology and neuroscience. Next, we provide an overview of the theories and conceptual frameworks that have emerged from behavioural ecology and animal cognition. Third, we turn to movement ecology and summarise recent, rapid developments in the types and quantities of available movement data, and in the statistical measures applicable to such data. Fourth, we discuss the advantages and interrelationships of diverse modelling approaches that have been used to explore the memory-movement interface. Finally, we outline key research challenges for the memory and movement communities, focusing on data needs and mathematical and computational challenges. We conclude with a roadmap for future work in this area, outlining axes along which focused research should yield rapid progress.