Navigating uncertain waters: a critical review of inferring foraging behaviour from location and dive data in pinnipeds

Electromechanical enhancement of live jellyfish for ocean exploration

The vast majority of the ocean's volume remains unexplored, in part because of limitations on the vertical range and measurement duration of existing robotic platforms. In light of the accelerating rate of climate change impacts on the physics and biogeochemistry of the ocean, the need for new tools that can measure more of the ocean on faster timescales is becoming pressing. Robotic platforms inspired or enabled by aquatic organisms have the potential to augment conventional technologies for ocean exploration. Recent work demonstrated the feasibility of directly stimulating the muscle tissue of live jellyfish via implanted microelectronics. We present a biohybrid robotic jellyfish that leverages this external electrical swimming control, while also using a 3D printed passive mechanical attachment to streamline the jellyfish shape, increase swimming performance, and significantly enhance payload capacity. A six-meter-tall, 13 600 l saltwater facility was constructed to enable testing of the vertical swimming capabilities of the biohybrid robotic jellyfish over distances exceeding 35 body diameters. We found that the combination of external swimming control and the addition of the mechanical forebody resulted in an increase in swimming speeds to 4.5 times natural jellyfish locomotion. Moreover, the biohybrid jellyfish were capable of carrying a payload volume up to 105% of the jellyfish body volume. The added payload decreased the intracycle acceleration of the biohybrid robots relative to natural jellyfish, which could also facilitate more precise measurements by onboard sensors that depend on consistent platform motion. While many robotic exploration tools are limited by cost, energy expenditure, and varying oceanic environmental conditions, this platform is inexpensive, highly efficient, and benefits from the widespread natural habitats of jellyfish. The demonstrated performance of these biohybrid robots suggests an opportunity to expand the set of robotic tools for comprehensive monitoring of the changing ocean.

A novel method for identifying fine-scale bottom-use in a benthic-foraging pinniped

BACKGROUND

For diving, marine predators, accelerometer and magnetometer data provides critical information on sub-surface foraging behaviours that cannot be identified from location or time-depth data. By measuring head movement and body orientation, accelerometers and magnetometers can help identify broad shifts in foraging movements, fine-scale habitat use and energy expenditure of terrestrial and marine species. Here, we use accelerometer and magnetometer data from tagged Australian sea lions and provide a new method to identify key benthic foraging areas. As Australian sea lions are listed as endangered by the IUCN and Australian legislation, identifying key areas for the species is vital to support targeted management of populations.

METHODS

Firstly, tri-axial magnetometer and accelerometer data from adult female Australian sea lions is used in conjunction with GPS and dive data to dead-reckon their three-dimensional foraging paths. We then isolate all benthic phases from their foraging trips and calculate a range of dive metrics to characterise their bottom usage. Finally, k-means cluster analysis is used to identify core benthic areas utilised by sea lions. Backwards stepwise regressions are then iteratively performed to identify the most parsimonious model for describing bottom usage and its included predictor variables.

RESULTS

Our results show distinct spatial partitioning in benthic habitat-use by Australian sea lions. This method has also identified individual differences in benthic habitat-use. Here, the application of high-resolution magnetometer/accelerometer data has helped reveal the tortuous foraging movements Australian sea lions use to exploit key benthic marine habitats and features.

CONCLUSIONS

This study has illustrated how magnetometer and accelerometer data can provide a fine-scale description of the underwater movement of diving species, beyond GPS and depth data alone, For endangered species like Australian sea lions, management of populations must be spatially targeted. Here, this method demonstrates a fine-scale analysis of benthic habitat-use which can help identify key areas for both marine and terrestrial species. Future integration of this method with concurrent habitat and prey data would further augment its power as a tool for understanding the foraging behaviours of species.

Variation in foraging activity influences area-restricted search behaviour by bottlenose dolphins

Area-restricted search (ARS) behaviour is commonly used to characterize spatio-temporal variation in foraging activity of predators, but evidence of the drivers underlying this behaviour in marine systems is sparse. Advances in underwater sound recording techniques and automated processing of acoustic data now provide opportunities to investigate these questions where species use different vocalizations when encountering prey. Here, we used passive acoustics to investigate drivers of ARS behaviour in a population of dolphins and determined if residency in key foraging areas increased following encounters with prey. Analyses were based on two independent proxies of foraging: echolocation buzzes (widely used as foraging proxies) and bray calls (vocalizations linked to salmon predation attempts). Echolocation buzzes were extracted from echolocation data loggers and bray calls from broadband recordings by a convolutional neural network. We found a strong positive relationship between the duration of encounters and the frequency of both foraging proxies, supporting the theory that bottlenose dolphins engage in ARS behaviour in response to higher prey encounter rates. This study provides empirical evidence for one driver of ARS behaviour and demonstrates the potential for applying passive acoustic monitoring in combination with deep learning-based techniques to investigate the behaviour of vocal animals.

Track and dive-based movement metrics do not predict the number of prey encountered by a marine predator

BACKGROUND

Studying animal movement in the context of the optimal foraging theory has led to the development of simple movement metrics for inferring feeding activity. Yet, the predictive capacity of these metrics in natural environments has been given little attention, raising serious questions of the validity of these metrics. The aim of this study is to test whether simple continuous movement metrics predict feeding intensity in a marine predator, the southern elephant seal (SES; Mirounga leonine), and investigate potential factors influencing the predictive capacity of these metrics.

METHODS

We equipped 21 female SES from the Kerguelen Archipelago with loggers and recorded their movements during post-breeding foraging trips at sea. From accelerometry, we estimated the number of prey encounter events (nPEE) and used it as a reference for feeding intensity. We also extracted several track- and dive-based movement metrics and evaluated how well they explain and predict the variance in nPEE. We conducted our analysis at two temporal scales (dive and day), with two dive profile resolutions (high at 1 Hz and low with five dive segments), and two types of models (linear models and regression trees).

RESULTS

We found that none of the movement metrics predict nPEE with satisfactory power. The vertical transit rates (primarily the ascent rate) during dives had the best predictive performance among all metrics. Dive metrics performed better than track metrics and all metrics performed on average better at the scale of days than the scale of dives. However, the performance of the models at the scale of days showed higher variability among individuals suggesting distinct foraging tactics. Dive-based metrics performed better when computed from high-resolution dive profiles than low-resolution dive profiles. Finally, regression trees produced more accurate predictions than linear models.

CONCLUSIONS

Our study reveals that simple movement metrics do not predict feeding activity in free-ranging marine predators. This could emerge from differences between individuals, temporal scales, and the data resolution used, among many other factors. We conclude that these simple metrics should be avoided or carefully tested a priori with the studied species and the ecological context to account for significant influencing factors.

Biologging of emperor penguins-Attachment techniques and associated deployment performance

An increasing number of marine animals are equipped with biologgers, to study their physiology, behaviour and ecology, often for conservation purposes. To minimise the impacts of biologgers on the animals’ welfare, the Refinement principle from the Three Rs framework (Replacement, Reduction, Refinement) urges to continuously test and evaluate new and updated biologging protocols. Here, we propose alternative and promising techniques for emperor penguin (Aptenodytes forsteri) capture and on-site logger deployment that aim to mitigate the potential negative impacts of logger deployment on these birds. We equipped adult emperor penguins for short-term (GPS, Time-Depth Recorder (TDR)) and long-term (i.e. planned for one year) deployments (ARGOS platforms, TDR), as well as juvenile emperor penguins for long-term deployments (ARGOS platforms) in the Weddell Sea area where they had not yet been studied. We describe and qualitatively evaluate our protocols for the attachment of biologgers on-site at the colony, the capture of the animals and the recovery of the devices after deployment. We report unprecedented recaptures of long-term equipped adult emperor penguins (50% of equipped individuals recaptured after 290 days). Our data demonstrate that the traditional technique of long-term attachment by gluing the biologgers directly to the back feathers causes excessive feather breakage and the loss of the devices after a few months. We therefore propose an alternative method of attachment for back-mounted devices. This technique led to successful year-round deployments on 37.5% of the equipped juveniles. Finally, we also disclose the first deployments of leg-bracelet mounted TDRs on emperor penguins. Our findings highlight the importance of monitoring potential impacts of biologger deployments on the animals and the need to continue to improve methods to minimize disturbance and enhance performance and results.

Multivariate analysis of biologging data reveals the environmental determinants of diving behaviour in a marine reptile

Diving behaviour of 'surfacers' such as sea snakes, cetaceans and turtles is complex and multi-dimensional, thus may be better captured by multi-sensor biologging data. However, analysing these large multi-faceted datasets remains challenging, though a high priority. We used high-resolution multi-sensor biologging data to provide the first detailed description of the environmental influences on flatback turtle (Natator depressus) diving behaviour, during its foraging life-history stage. We developed an analytical method to investigate seasonal, diel and tidal effects on diving behaviour for 24 adult flatback turtles tagged with biologgers. We extracted 16 dive variables associated with three-dimensional and kinematic characteristics for 4128 dives. K-means and hierarchical cluster analyses failed to identify distinct dive types. Instead, principal component analysis objectively condensed the dive variables, removing collinearity and highlighting the main features of diving behaviour. Generalized additive mixed models of the main principal components identified significant seasonal, diel and tidal effects on flatback turtle diving behaviour. Flatback turtles altered their diving behaviour in response to extreme tidal and water temperature ranges, displaying thermoregulation and predator avoidance strategies while likely optimizing foraging in this challenging environment. This study demonstrates an alternative statistical technique for objectively interpreting diving behaviour from multivariate collinear data derived from biologgers.

Equivalence classification, learning by exclusion, and long-term memory in pinnipeds: cognitive mechanisms demonstrated through research with subjects under human care and in the field

Comparative cognition, as an interdisciplinary field, should utilize a holistic approach for studying cognitive mechanisms. We suggest that research with species of interest should employ both work with animals under human care and in the field. This complimentary approach allows for a better understanding of functional cognitive mechanisms themselves (i.e., comparative cognition regarding processes), and how these skill sets can relate to a particular species' ecological niche. We suggest that research evidence for equivalence classification, learning by exclusion, and long-term memory in pinnipeds can provide a foundation for discussion and implementation of a two-pronged methodological approach utilizing 'lab' and field' work. First, we describe evidence from research with pinnipeds under human care supporting each of these cognitive abilities, then follow this with evidence for implications of these mechanisms from complimentary field research. Lastly, we provide a brief discussion of implementation of a purposeful and two-pronged research approach as an understanding of pinnipeds' high levels of cognitive flexibility may underlie their success for navigating the ever-changing, and often human-altered, natural environment.

Deep inference of seabird dives from GPS-only records: Performance and generalization properties

At-sea behaviour of seabirds have received significant attention in ecology over the last decades as it is a key process in the ecology and fate of these populations. It is also, through the position of top predator that these species often occupy, a relevant and integrative indicator of the dynamics of the marine ecosystems they rely on. Seabird trajectories are recorded through the deployment of GPS, and a variety of statistical approaches have been tested to infer probable behaviours from these location data. Recently, deep learning tools have shown promising results for the segmentation and classification of animal behaviour from trajectory data. Yet, these approaches have not been widely used and investigation is still needed to identify optimal network architecture and to demonstrate their generalization properties. From a database of about 300 foraging trajectories derived from GPS data deployed simultaneously with pressure sensors for the identification of dives, this work has benchmarked deep neural network architectures trained in a supervised manner for the prediction of dives from trajectory data. It first confirms that deep learning allows better dive prediction than usual methods such as Hidden Markov Models. It also demonstrates the generalization properties of the trained networks for inferring dives distribution for seabirds from other colonies and ecosystems. In particular, convolutional networks trained on Peruvian boobies from a specific colony show great ability to predict dives of boobies from other colonies and from distinct ecosystems. We further investigate accross-species generalization using a transfer learning strategy known as ‘fine-tuning’. Starting from a convolutional network pre-trained on Guanay cormorant data reduced by two the size of the dataset needed to accurately predict dives in a tropical booby from Brazil. We believe that the networks trained in this study will provide relevant starting point for future fine-tuning works for seabird trajectory segmentation.

Over the last decades, the use of miniaturized electronic devices enabled the tracking of many wide-ranging animal species. The deployment of GPS has notably informed on migratory, habitat and foraging strategies of numerous seabird species. A key challenge in movement ecology is to identify specific behavioural patterns (e.g. travelling, resting, foraging) through the observed movement data. In this work, we address the inference of seabird diving behaviour from GPS data using deep learning methods. We demonstrate the performance of deep networks to accurately identify movement patterns from GPS data over state-of-the-art tools, and we illustrate their great accross-species generalization properties (i.e. the ability to generalize prediction from one seabird species to aother). Our results further supports the relevance of deep learning schemes as ‘ready-to-use’ tools which could be used by ecologists to segmentate animal trajectories on new (small) datasets, including when these datasets do not include groundtruthed labelled data for a supervised training.

Horizontal-vertical movement relationships: Adélie penguins forage continuously throughout provisioning trips

BACKGROUND

Diving marine predators forage in a three-dimensional environment, adjusting their horizontal and vertical movement behaviour in response to environmental conditions and the spatial distribution of prey. Expectations regarding horizontal-vertical movements are derived from optimal foraging theories, however, inconsistent empirical findings across a range of taxa suggests these behavioural assumptions are not universally applicable.

METHODS

Here, we examined how changes in horizontal movement trajectories corresponded with diving behaviour and marine environmental conditions for a ubiquitous Southern Ocean predator, the Adélie penguin. Integrating extensive telemetry-based movement and environmental datasets for chick-rearing Adélie penguins at Béchervaise Island, we tested the relationships between horizontal move persistence (continuous scale indicating low ['resident'] to high ['directed'] movement autocorrelation), vertical dive effort and environmental variables.

RESULTS

Penguins dived continuously over the course of their foraging trips and lower horizontal move persistence corresponded with less intense foraging activity, likely indicative of resting behaviour. This challenges the traditional interpretation of horizontal-vertical movement relationships based on optimal foraging models, which assumes increased residency within an area translates to increased foraging activity. Movement was also influenced by different environmental conditions during the two stages of chick-rearing: guard and crèche. These differences highlight the strong seasonality of foraging habitat for chick-rearing Adélie penguins at Béchervaise Island.

CONCLUSIONS

Our findings advance our understanding of the foraging behaviour for this marine predator and demonstrates the importance of integrating spatial location and behavioural data before inferring habitat use.

Drivers and constraints on offshore foraging in harbour seals

Central place foragers are expected to offset travel costs between a central place and foraging areas by targeting productive feeding zones. Harbour seals (Phoca vitulina) make multi-day foraging trips away from coastal haul-out sites presumably to target rich food resources, but periodic track points from telemetry tags may be insufficient to infer reliably where, and how often, foraging takes place. To study foraging behaviour during offshore trips, and assess what factors limit trip duration, we equipped harbour seals in the German Wadden Sea with high-resolution multi-sensor bio-logging tags, recording 12 offshore trips from 8 seals. Using acceleration transients as a proxy for prey capture attempts, we found that foraging rates during travel to and from offshore sites were comparable to offshore rates. Offshore foraging trips may, therefore, reflect avoidance of intra-specific competition rather than presence of offshore foraging hotspots. Time spent resting increased by approx. 37 min/day during trips suggesting that a resting deficit rather than patch depletion may influence trip length. Foraging rates were only weakly correlated with surface movement patterns highlighting the value of integrating multi-sensor data from on-animal bio-logging tags (GPS, depth, accelerometers and magnetometers) to infer behaviour and habitat use.

Predicting the exposure of diving grey seals to shipping noise

There is high spatial overlap between grey seals and shipping traffic, and the functional hearing range of grey seals indicates sensitivity to underwater noise emitted by ships. However, there is still very little data regarding the exposure of grey seals to shipping noise, constraining effective policy decisions. Particularly, there are few predictions that consider the at-sea movement of seals. Consequently, this study aimed to predict the exposure of adult grey seals and pups to shipping noise along a three-dimensional movement track, and assess the influence of shipping characteristics on sound exposure levels. Using ship location data, a ship source model, and the acoustic propagation model, RAMSurf, this study estimated weighted 24-h sound exposure levels (10-1000 Hz) (SEL_w). Median predicted 24-h SEL_w was 128 and 142 dB re 1 μPa²s for the pups and adults, respectively. The predicted exposure of seals to shipping noise did not exceed best evidence thresholds for temporary threshold shift. Exposure was mediated by the number of ships, ship source level, the distance between seals and ships, and the at-sea behaviour of the seals. The results can inform regulatory planning related to anthropogenic pressures on seal populations.

Sex-differences in fine-scale home-range use in an upper-trophic level marine predator

BACKGROUND

The distribution of prey in the ocean is spatially and temporally patchy. How predators respond to this prey patchiness may have consequences on their foraging success, and thus physical condition. The recent ability to record fine-scale movements of marine animals combined with novel home-range analyses that incorporate the dimension of time should permit a better understanding of how individuals utilise different regions of space and the consequences on their foraging success.

METHODS

Over a six-year study, we used T-LoCoH (Time-Local Convex Hull) home-range software to model archival GPS (Global Positioning System) data from 81 grey seals to investigate the fine-scale spatio-temporal use of space and the distribution of apparent foraging effort. Regions of home-ranges were classified according to the frequency of return visits (site fidelity) and duration of visits (intensity of use). Generalized linear mixed -effects models were used to test hypotheses on seasonal changes in foraging distribution and behaviour and the role of space-use and state on determining foraging success.

RESULTS

Male grey seals had larger home-ranges and core areas than females, and both sexes showed a contraction in home-range and core area in fall leading up to the breeding season compared with summer. Heavier individuals had smaller core areas than lighter ones, suggesting access to higher quality habitat might be limited to those individuals with greater foraging experience and competitive ability. The size of the home-range or core area was not an important predictor of the rate of mass gain. A fine-scale spatio-temporal analysis of habitat use within the home-range provided evidence of intra-annual site fidelity at presumed foraging locations, suggesting predictably in prey distribution. Neither sex nor season were useful predictors for classifying behaviour. Rather, individual identity explained much of the variation in fine-scale behaviour.

CONCLUSIONS

Understanding how upper-trophic level marine predators use space provides opportunities to explore the consequences of variation in foraging tactics and their success on fitness. Having knowledge of the drivers that shape this intraspecific variation can contribute toward predicting how these predators may respond to both natural and man-made environmental forcing.

Foraging behaviour of a continental shelf marine predator, the grey seal (Halichoerus grypus), is associated with in situ, subsurface oceanographic conditions

BACKGROUND

The heterogeneous oceanographic conditions of continental shelf ecosystems result in a three-dimensionally patchy distribution of prey available to upper-trophic level predators. The association of bio-physical conditions with movement patterns of large marine predators has been demonstrated in diverse taxa. However, obtaining subsurface data that are spatio-temporally relevant to the decisions made by benthically-foraging species can be challenging.

METHODS

Between 2009 and 2015, grey seals were captured on Sable Island, Nova Scotia, Canada during summer and fall and instrumented with high-resolution archival GPS tags. These tags recorded location data as well as depth (m), temperature (°C), and light level measurements during dives, until animals returned to the haulout site to breed. Hidden Markov models were used to predict apparent foraging along movement tracks for 79 individuals (59 females, 20 males) every 3 h. In situ measurements were used to estimate chlorophyll-a concentration (mg m^- 3) and temperature within the upper-water column (50 m) and temperature and depth at the bottom of dives. As chlorophyll-a could only be estimated from 10:00 to 14:00 AST for dive depths ≥50 m, we formulated two generalized linear mixed-effects models to test the association of predicted grey seal behavioural states with oceanographic conditions and phytoplankton biomass: the first representing conditions of the upper-water column likely to influence primary productivity, and a second model including environmental conditions encountered by grey seals at the bottom of dives, when seals were more likely to be foraging.

RESULTS

Predicted grey seal behavioural states were associated with fine-scale chlorophyll-a concentrations and other environmental conditions they encountered across the continental shelf. In the Water Column Model, season had no influence on the probability of observing apparent foraging, but chlorophyll-a, upper-water column temperature, and sex did, with females having a greater probability of foraging than males. In the Bottom Conditions Model, again season had no influence on the probability of apparent foraging, but females were over twice as likely as males to be foraging.

CONCLUSIONS

The results of this study highlight the value of in situ measurements of oceanographic properties that can be collected at high temporal resolution by animal-borne data loggers. These data provide insight into how inferred behavioural decisions made by large marine predators, such as the grey seal, may be influenced by fine-scale oceanographic conditions.

Factors affecting energy expenditure in a declining fur seal population

Quantifying metabolic rates and the factors that influence them is key to wildlife conservation efforts because anthropogenic activities and habitat alteration can disrupt energy balance, which is critical for reproduction and survival. We investigated the effect of diving behaviour, diet and season on field metabolic rates (FMR) and foraging success of lactating northern fur seals (Callorhinus ursinus) from the Pribilof Islands during a period of population decline. Variation in at-sea FMR was in part explained by season and trip duration, with values that ranged from 5.18 to 9.68 W kg^-1 (n = 48). Fur seals experienced a 7.2% increase in at-sea FMR from summer to fall and a 1.9% decrease in at-sea FMR for each additional day spent at sea. There was no effect of foraging effort, dive depth or diet on at-sea FMR. Mass gains increased with trip duration and were greater in the fall compared with summer, but were unrelated to at-sea FMR, diving behaviour and diet. Seasonal increases in at-sea FMR may have been due to costs associated with the annual molt but did not appear to adversely impact the ability of females to gain mass on foraging trips. The overall high metabolic rates in conjunction with the lack of any diet-related effects on at-sea FMR suggests that northern fur seals may have reached a metabolic ceiling early in the population decline. This provides indirect evidence that food limitation may be contributing to the low pup growth rates observed in the Pribilof Islands, as a high metabolic overhead likely results in less available energy for lactation. The limited ability of female fur seals to cope with changes in prey availability through physiological mechanisms is particularly concerning given the recent and unprecedented environmental changes in the Bering Sea that are predicted to have ecosystem-level impacts.

Predicting acoustic dose associated with marine mammal behavioural responses to sound as detected with fixed acoustic recorders and satellite tags

To understand the consequences of underwater noise exposure for cetaceans, there is a need for assessments of behavioural responses over increased spatial and temporal scales. Bottom-moored acoustic recorders and satellite tags provide such long-term and large spatial coverage of behaviour compared to short-duration acoustic-recording tags. However, these tools result in a decreased resolution of data from which an animal response can be inferred, and no direct recording of the sound received at the animal. This study discusses the consequence of the decreased resolution of data from satellite tags and fixed acoustic recorders on the acoustic dose estimated by propagation modelling and presents a method for estimating the range of sound levels that animals observed with these methods have received. This problem is illustrated using experimental results obtained during controlled exposures of northern bottlenose whales (Hyperoodon ampullatus) exposed to naval sonar, carried out near Jan Mayen, Norway. It is shown that variability and uncertainties in the sound field, resulting from limited sampling of the acoustic environment, as well as decreased resolution in animal locations, can lead to quantifiable uncertainties in the estimated acoustic dose associated with the behavioural response (in this case avoidance and cessation of foraging).

Long-term sound and movement recording tags to study natural behavior and reaction to ship noise of seals

The impact of anthropogenic noise on marine fauna is of increasing conservation concern with vessel noise being one of the major contributors. Animals that rely on shallow coastal habitats may be especially vulnerable to this form of pollution.Very limited information is available on how much noise from ship traffic individual animals experience, and how they may react to it due to a lack of suitable methods. To address this, we developed long-duration audio and 3D-movement tags (DTAGs) and deployed them on three harbor seals and two gray seals in the North Sea during 2015-2016.These tags recorded sound, accelerometry, magnetometry, and pressure continuously for up to 21 days. GPS positions were also sampled for one seal continuously throughout the recording period. A separate tag, combining a camera and an accelerometer logger, was deployed on two harbor seals to visualize specific behaviors that helped interpret accelerometer signals in the DTAG data.Combining data from depth, accelerometer, and audio sensors, we found that animals spent 6.6%-42.3% of the time hauled out (either on land or partly submerged), and 5.3%-12.4% of their at-sea time resting at the sea bottom, while the remaining time was used for traveling, resting at surface, and foraging. Animals were exposed to audible vessel noise 2.2%-20.5% of their time when in water, and we demonstrate that interruption of functional behaviors (e.g., resting) in some cases coincides with high-level vessel noise. Two-thirds of the ship noise events were traceable by the AIS vessel tracking system, while one-third comprised vessels without AIS.This preliminary study demonstrates how concomitant long-term continuous broadband on-animal sound and movement recordings may be an important tool in future quantification of disturbance effects of anthropogenic activities at sea and assessment of long-term population impacts on pinnipeds.

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.

Spatial segregation of home ranges between neighbouring colonies in a diurnal raptor

Enhancement of information transfer has been proposed as a key driver of the evolution of coloniality. Transfer of information on location of food resources implies that individuals from the same colony share foraging areas and that each colony can be associated to a specific foraging area. In colonial breeding vertebrates, colony-specific foraging areas are often spatially segregated, mitigating intercolony intraspecific competition. By means of simultaneous GPS tracking of lesser kestrels (Falco naumanni) from neighbouring colonies, we showed a clear segregation of space use between individuals from different colonies. Foraging birds from different neighbouring colonies had home ranges that were significantly more segregated in space than expected by chance. This was the case both between large and between small neighbouring colonies. To our knowledge, the lesser kestrel is the only terrestrial species where evidence of spatial segregation of home ranges between conspecifics from neighbouring colonies has been demonstrated. The observed spatial segregation pattern is consistent with the occurrence of public information transfer about foraging areas and with the avoidance of overexploited areas located between neighbouring colonies. Our findings support the idea that spatial segregation of exploited areas may be widespread among colonial avian taxa, irrespective of colony size.

Scaling marine fish movement behavior from individuals to populations

Understanding how, where, and when animals move is a central problem in marine ecology and conservation. Key to improving our knowledge about what drives animal movement is the rising deployment of telemetry devices on a range of free-roaming species. An increasingly popular way of gaining meaningful inference from an animal's recorded movements is the application of hidden Markov models (HMMs), which allow for the identification of latent behavioral states in the movement paths of individuals. However, the use of HMMs to explore the population-level consequences of movement is often limited by model complexity and insufficient sample sizes. Here, we introduce an alternative approach to current practices and provide evidence of how the inclusion of prior information in model structure can simplify the application of HMMs to multiple animal movement paths with two clear benefits: (a) consistent state allocation and (b) increases in effective sample size. To demonstrate the utility of our approach, we apply HMMs and adapted HMMs to over 100 multivariate movement paths consisting of conditionally dependent daily horizontal and vertical movements in two species of demersal fish: Atlantic cod (Gadus morhua; n = 46) and European plaice (Pleuronectes platessa; n = 61). We identify latent states corresponding to two main underlying behaviors: resident and migrating. As our analysis considers a relatively large sample size and states are allocated consistently, we use collective model output to investigate state-dependent spatiotemporal trends at the individual and population levels. In particular, we show how both species shift their movement behaviors on a seasonal basis and demonstrate population space use patterns that are consistent with previous individual-level studies. Tagging studies are increasingly being used to inform stock assessment models, spatial management strategies, and monitoring of marine fish populations. Our approach provides a promising way of adding value to tagging studies because inferences about movement behavior can be gained from a larger proportion of datasets, making tagging studies more relevant to management and more cost-effective.

Processing of acceleration and dive data on-board satellite relay tags to investigate diving and foraging behaviour in free-ranging marine predators

Biologging technologies are changing the way in which the marine environment is observed and monitored. However, because device retrieval is typically required to access the high-resolution data they collect, their use is generally restricted to those animals that predictably return to land. Data abstraction and transmission techniques aim to address this, although currently these are limited in scope and do not incorporate, for example, acceleration measurements which can quantify animal behaviours and movement patterns over fine-scales.In this study, we present a new method for the collection, abstraction and transmission of accelerometer data from free-ranging marine predators via the Argos satellite system. We test run the technique on 20 juvenile southern elephant seals Mirounga leonina from the Kerguelen Islands during their first months at sea following weaning. Using retrieved archival data from nine individuals that returned to the colony, we compare and validate abstracted transmissions against outputs from established accelerometer processing procedures.Abstracted transmissions included estimates, across five segments of a dive profile, of time spent in prey catch attempt (PrCA) behaviours, swimming effort and pitch. These were then summarised and compared to archival outputs across three dive phases: descent, bottom and ascent. Correlations between the two datasets were variable but generally good (dependent on dive phase, marginal R2 values of between .45 and .6 to >.9) and consistent between individuals. Transmitted estimates of PrCA behaviours and swimming effort were positively biased to those from archival processing.Data from this study represent some of the first remotely transmitted quantifications from accelerometers. The methods presented and analysed can be used to provide novel insight towards the behaviours and movements of free-ranging marine predators, such as juvenile southern elephant seals, from whom logger retrieval is challenging. Future applications could however benefit from some adaption, particularly to reduce positive bias in transmitted PrCA behaviours and swimming effort, for which this study provides useful insight.

Intrinsic and extrinsic factors drive ontogeny of early-life at-sea behaviour in a marine top predator

Young animals must learn to forage effectively to survive the transition from parental provisioning to independent feeding. Rapid development of successful foraging strategies is particularly important for capital breeders that do not receive parental guidance after weaning. The intrinsic and extrinsic drivers of variation in ontogeny of foraging are poorly understood for many species. Grey seals (Halichoerus grypus) are typical capital breeders; pups are abandoned on the natal site after a brief suckling phase, and must develop foraging skills without external input. We collected location and dive data from recently-weaned grey seal pups from two regions of the United Kingdom (the North Sea and the Celtic and Irish Seas) using animal-borne telemetry devices during their first months of independence at sea. Dive duration, depth, bottom time, and benthic diving increased over the first 40 days. The shape and magnitude of changes differed between regions. Females consistently had longer bottom times, and in the Celtic and Irish Seas they used shallower water than males. Regional sex differences suggest that extrinsic factors, such as water depth, contribute to behavioural sexual segregation. We recommend that conservation strategies consider movements of young naïve animals in addition to those of adults to account for developmental behavioural changes.

Satellite tagging of Mediterranean fin whales: working towards the identification of critical habitats and the focussing of mitigation measures

Mediterranean fin whales comprise a genetically distinct population, listed as Vulnerable (VU) in the IUCN Red List. Collisions with vessels are believed to represent the main cause of human-induced mortality. The identification of critical habitats (including migration routes) incorporating satellite telemetry data is therefore crucial to develop focussed conservation efforts. Between 2012 and 2015 thirteen fin whales were equipped with satellite transmitters, 8 in the Pelagos Sanctuary (although two ceased within two days) and 5 in the Strait of Sicily, to evaluate movements and habitat use. A hierarchical switching state-space model was used to identify transiting and area-restricted search (ARS) behaviours, believed to indicate foraging activities. All whales undertook mid- to long-distance migrations, crossing some of the world's busiest maritime routes. Areas where the animals predominantly engaged in ARS behaviour were identified in both study areas. The telemetry data were compared with results from ecosystem niche modelling, and showed that 80% of tagged whale positions was near (<7 km) the closest suitable habitat. The results contribute to the view that precautionary management should include establishment of a coordinated and dynamic basin-wide management scheme; if appropriate, this may include the establishment of protected areas by specific regional Conventions.