Underwater and surface behavior of homing juvenile northern elephant seals

Development of a multisensor biologging collar and analytical techniques to describe high-resolution spatial behavior in free-ranging terrestrial mammals

Biologging has proven to be a powerful approach to investigate diverse questions related to movement ecology across a range of spatiotemporal scales and increasingly relies on multidisciplinary expertise. However, the variety of animal-borne equipment, coupled with little consensus regarding analytical approaches to interpret large, complex data sets presents challenges and makes comparison between studies and study species difficult. Here, we present a combined hardware and analytical approach for standardizing the collection, analysis, and interpretation of multisensor biologging data. Here, we present (i) a custom-designed integrated multisensor collar (IMSC), which was field tested on 71 free-ranging wild boar (Sus scrofa) over 2 years; (ii) a machine learning behavioral classifier capable of identifying six behaviors in free-roaming boar, validated across individuals equipped with differing collar designs; and (iii) laboratory and field-based calibration and accuracy assessments of animal magnetic heading measurements derived from raw magnetometer data. The IMSC capacity and durability exceeded expectations, with a 94% collar recovery rate and a 75% cumulative data recording success rate, with a maximum logging duration of 421 days. The behavioral classifier had an overall accuracy of 85% in identifying the six behavioral classes when tested on multiple collar designs and improved to 90% when tested on data exclusively from the IMSC. Both laboratory and field tests of magnetic compass headings were in precise agreement with expectations, with overall median magnetic headings deviating from ground truth observations by 1.7° and 0°, respectively. Although multisensor equipment and sophisticated analyses are now commonplace in biologging studies, the IMSC hardware and analytical framework presented here provide a valuable tool for biologging researchers and will facilitate standardization of biologging data across studies. In addition, we highlight the potential of additional analyses available using this framework that can be adapted for use in future studies on terrestrial mammals.

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.

A harbour seal (Phoca vitulina) can learn geometrical relationships between landmarks

Marine mammals travel the world's oceans. Some species regularly return to specific places to breathe, haul-out or breed. However, the mechanisms they use to return are unknown. Theoretically, landmarks could mediate the localisation of these places. Occasionally, it might be beneficial or even required to localise places using geometrical information provided by landmarks such as to apply a 'middle rule'. Here, we trained a harbour seal to find its goal in the middle of numerous vertically and horizontally orientated two-landmark arrays. During testing, the seal was confronted with unfamiliar two-landmark arrays. After having successfully learnt to respond to the midpoint of multiple two-landmark arrays, the seal directly and consistently followed a 'middle rule' during testing. It chose the midpoint of the two-landmark arrays with high precision. Harbour seals with the ability to localise goals based on geometrical information would be able to home in on places even from unknown positions relative to goal-defining features. Altogether, the results obtained with our harbour seal individual in the present and a previous study, examining the basis of landmark orientation, provide evidence that this seal can use landmark information very flexibly. Depending on context, this flexibility is adaptive to an environment in which the information content can vary over time.

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.

How harbour seals (Phoca vitulina) encode goals relative to landmarks

Visual landmarks are defined as object with prominent shape or size that distinguish themselves from the background. With the help of landmarks, animals can orient themselves in their natural environment. Yet, the way in which landmarks are perceived and encoded has previously only been described in insects, fish, birds, reptilians and terrestrial mammals. The present study aimed to provide insight into how a marine mammal, the harbour seal, is encoding goals relative to landmarks. In our expansion test, three harbour seals were trained to find a goal inside an array of landmarks. After diagonal, horizontal or vertical expansion of the landmark array, the search behaviour displayed by the animals was documented and analyzed regarding the underlying encoding strategy. The harbour seals mainly encoded directional vector information from landmarks and did neither search arbitrarily around a landmark nor used a rule-based approach. Depending on the number of landmarks available within the array, the search behaviour of some harbor seals changed, indicating flexibility in landmark-based search. Our results present first insight in how a semi-aquatic predator could encode landmark information when swimming along the coastline in search for a goal-location.

How often should dead-reckoned animal movement paths be corrected for drift?

BACKGROUND

Understanding what animals do in time and space is important for a range of ecological questions, however accurate estimates of how animals use space is challenging. Within the use of animal-attached tags, radio telemetry (including the Global Positioning System, 'GPS') is typically used to verify an animal's location periodically. Straight lines are typically drawn between these 'Verified Positions' ('VPs') so the interpolation of space-use is limited by the temporal and spatial resolution of the system's measurement. As such, parameters such as route-taken and distance travelled can be poorly represented when using VP systems alone. Dead-reckoning has been suggested as a technique to improve the accuracy and resolution of reconstructed movement paths, whilst maximising battery life of VP systems. This typically involves deriving travel vectors from motion sensor systems and periodically correcting path dimensions for drift with simultaneously deployed VP systems. How often paths should be corrected for drift, however, has remained unclear.

METHODS AND RESULTS

Here, we review the utility of dead-reckoning across four contrasting model species using different forms of locomotion (the African lion Panthera leo, the red-tailed tropicbird Phaethon rubricauda, the Magellanic penguin Spheniscus magellanicus, and the imperial cormorant Leucocarbo atriceps). Simulations were performed to examine the extent of dead-reckoning error, relative to VPs, as a function of Verified Position correction (VP correction) rate and the effect of this on estimates of distance moved. Dead-reckoning error was greatest for animals travelling within air and water. We demonstrate how sources of measurement error can arise within VP-corrected dead-reckoned tracks and propose advancements to this procedure to maximise dead-reckoning accuracy.

CONCLUSIONS

We review the utility of VP-corrected dead-reckoning according to movement type and consider a range of ecological questions that would benefit from dead-reckoning, primarily concerning animal-barrier interactions and foraging strategies.

Similar circling movements observed across marine megafauna taxa

Advances in biologging technology have enabled 3D dead-reckoning reconstruction of marine animal movements at spatiotemporal scales of meters and seconds. Examining high-resolution 3D movements of sharks (Galeocerdo cuvier, N = 4; Rhincodon typus, N = 1), sea turtles (Chelonia mydas, N = 3), penguins (Aptenodytes patagonicus, N = 6), and marine mammals (Arctocephalus gazella, N = 4; Ziphius cavirostris, N = 1), we report the discovery of circling events where animals consecutively circled more than twice at relatively constant angular speeds. Similar circling behaviors were observed across a wide variety of marine megafauna, suggesting these behaviors might serve several similar purposes across taxa including foraging, social interactions, and navigation.

•

Biologging 3D movement data revealed circling behaviors in marine animals

•

Circling behaviors were observed in sharks, turtles, penguins, and marine mammals

•

Circlings might serve several purposes including foraging, navigation, etc.

Behavioural compass: animal behaviour recognition using magnetometers

BACKGROUND

Animal-borne data loggers today often house several sensors recording simultaneously at high frequency. This offers opportunities to gain fine-scale insights into behaviour from individual-sensor as well as integrated multi-sensor data. In the context of behaviour recognition, even though accelerometers have been used extensively, magnetometers have recently been shown to detect specific behaviours that accelerometers miss. The prevalent constraint of limited training data necessitates the importance of identifying behaviours with high robustness to data from new individuals, and may require fusing data from both these sensors. However, no study yet has developed an end-to-end approach to recognise common animal behaviours such as foraging, locomotion, and resting from magnetometer data in a common classification framework capable of accommodating and comparing data from both sensors.

METHODS

We address this by first leveraging magnetometers' similarity to accelerometers to develop biomechanical descriptors of movement: we use the static component given by sensor tilt with respect to Earth's local magnetic field to estimate posture, and the dynamic component given by change in sensor tilt with time to characterise movement intensity and periodicity. We use these descriptors within an existing hybrid scheme that combines biomechanics and machine learning to recognise behaviour. We showcase the utility of our method on triaxial magnetometer data collected on ten wild Kalahari meerkats (Suricata suricatta), with annotated video recordings of each individual serving as groundtruth. Finally, we compare our results with accelerometer-based behaviour recognition.

RESULTS

The overall recognition accuracy of > 94% obtained with magnetometer data was found to be comparable to that achieved using accelerometer data. Interestingly, higher robustness to inter-individual variability in dynamic behaviour was achieved with the magnetometer, while the accelerometer was better at estimating posture.

CONCLUSIONS

Magnetometers were found to accurately identify common behaviours, and were particularly robust to dynamic behaviour recognition. The use of biomechanical considerations to summarise magnetometer data makes the hybrid scheme capable of accommodating data from either or both sensors within the same framework according to each sensor's strengths. This provides future studies with a method to assess the added benefit of using magnetometers for behaviour recognition.

Three-dimensional space use during the bottom phase of southern elephant seal dives

BACKGROUND

In marine pelagic ecosystems, the spatial distribution of biomass is heterogeneous and dynamic. At large scales, physical processes are the main driving forces of biomass distribution. At fine scales, both biotic and abiotic parameters are likely to be key determinants in the horizontal and vertical distribution of biomass, with direct consequences on the foraging behaviour of diving predators. However, fine scale three-dimensional (3D) spatial interactions between diving predators and their prey are still poorly known.

RESULTS

We reconstructed and examined the patterns of southern elephant seals 3D path during the bottom phase of their dives, and related them to estimated prey encounter density. We found that southern elephant seal tracks at bottom are strongly dominated by a single horizontal direction. In high prey density areas, seals travelled shorter distances but their track remained strongly orientated according to a main linear direction. Horizontal, and more importantly, vertical deviations from this main direction, were related negatively to the estimated prey density. We found that prey encounter density decreased with diving depth but tended to be more predictable.

CONCLUSION

Southern elephant seal behaviour during the bottom phase of their dives suggest that the prey are dispersed and distributed into layers in which their density relates to the vertical spread of the layer. The linear trajectories performed by the elephant seals would allow to explore the largest volume of water, maximizing the opportunities of prey encounter, while travelling great horizontal distances.

A path reconstruction method integrating dead-reckoning and position fixes applied to humpback whales

BACKGROUND

Detailed information about animal location and movement is often crucial in studies of natural behaviour and how animals respond to anthropogenic activities. Dead-reckoning can be used to infer such detailed information, but without additional positional data this method results in uncertainty that grows with time. Combining dead-reckoning with new Fastloc-GPS technology should provide good opportunities for reconstructing georeferenced fine-scale tracks, and should be particularly useful for marine animals that spend most of their time under water. We developed a computationally efficient, Bayesian state-space modelling technique to estimate humpback whale locations through time, integrating dead-reckoning using on-animal sensors with measurements of whale locations using on-animal Fastloc-GPS and visual observations. Positional observation models were based upon error measurements made during calibrations.

RESULTS

High-resolution 3-dimensional movement tracks were produced for 13 whales using a simple process model in which errors caused by water current movements, non-location sensor errors, and other dead-reckoning errors were accumulated into a combined error term. Positional uncertainty quantified by the track reconstruction model was much greater for tracks with visual positions and few or no GPS positions, indicating a strong benefit to using Fastloc-GPS for track reconstruction. Compared to tracks derived only from position fixes, the inclusion of dead-reckoning data greatly improved the level of detail in the reconstructed tracks of humpback whales. Using cross-validation, a clear improvement in the predictability of out-of-set Fastloc-GPS data was observed compared to more conventional track reconstruction methods. Fastloc-GPS observation errors during calibrations were found to vary by number of GPS satellites received and by orthogonal dimension analysed; visual observation errors varied most by distance to the whale.

CONCLUSIONS

By systematically accounting for the observation errors in the position fixes, our model provides a quantitative estimate of location uncertainty that can be appropriately incorporated into analyses of animal movement. This generic method has potential application for a wide range of marine animal species and data recording systems.