Social dynamics and individual hunting tactics of white sharks revealed by biologging

Social foraging, where animals forage in groups, takes many forms but is less studied in marine predators as measuring social associations in the wild is challenging. We used biologging (activity, cameras and telemetry receivers) sensors to measure social associations and simultaneous behaviour, in white sharks (Carcharodon carcharias) off Guadalupe Island, Mexico. Animal-borne telemetry receivers revealed that sharks varied in the number of associations they formed and occurred most often when sharks were swimming in straight paths or when they were turning frequently. While many associations were likely random, there was evidence of some stronger associations. Sharks varied in the depths they used and their activity, with some individuals more active in shallow water while others were more active 200-300 m deep. We propose that white sharks associate with other individuals so they can inadvertently share information on the location or remains of large prey. However, there may be a wide range of individual variability in both behaviour and sociality. Biologging now enables social associations of animals to be measured, concurrent with measures of their behaviour, so that social foraging of large marine predators can be quantified in the wild.

Analysing detection gaps in acoustic telemetry data to infer differential movement patterns in fish

A wide array of technologies are available for gaining insight into the movement of wild aquatic animals. Although acoustic telemetry can lack the fine-scale spatial resolution of some satellite tracking technologies, the substantially longer battery life can yield important long-term data on individual behavior and movement for low per-unit cost. Typically, however, receiver arrays are designed to maximize spatial coverage at the cost of positional accuracy leading to potentially longer detection gaps as individuals move out of range between monitored locations. This is particularly true when these technologies are deployed to monitor species in hard-to-access locations.Here, we develop a novel approach to analyzing acoustic telemetry data, using the timing and duration of gaps between animal detections to infer different behaviors. Using the durations between detections at the same and different receiver locations (i.e., detection gaps), we classify behaviors into "restricted" or potential wider "out-of-range" movements synonymous with longer distance dispersal. We apply this method to investigate spatial and temporal segregation of inferred movement patterns in two sympatric species of reef shark within a large, remote, marine protected area (MPA). Response variables were generated using network analysis, and drivers of these movements were identified using generalized linear mixed models and multimodel inference.Species, diel period, and season were significant predictors of "out-of-range" movements. Silvertip sharks were overall more likely to undertake "out-of-range" movements, compared with gray reef sharks, indicating spatial segregation, and corroborating previous stable isotope work between these two species. High individual variability in "out-of-range" movements in both species was also identified.We present a novel gap analysis of telemetry data to help infer differential movement and space use patterns where acoustic coverage is imperfect and other tracking methods are impractical at scale. In remote locations, inference may be the best available tool and this approach shows that acoustic telemetry gap analysis can be used for comparative studies in fish ecology, or combined with other research techniques to better understand functional mechanisms driving behavior.

Observing the unwatchable: Integrating automated sensing, naturalistic observations and animal social network analysis in the age of big data

In the 4.5 decades since Altmann (1974) published her seminal paper on the methods for the observational study of behaviour, automated detection and analysis of social interaction networks have fundamentally transformed the ways that ecologists study social behaviour. Methodological developments for collecting data remotely on social behaviour involve indirect inference of associations, direct recordings of interactions and machine vision. These recent technological advances are improving the scale and resolution with which we can dissect interactions among animals. They are also revealing new intricacies of animal social interactions at spatial and temporal resolutions as well as in ecological contexts that have been hidden from humans, making the unwatchable seeable. We first outline how these technological applications are permitting researchers to collect exquisitely detailed information with little observer bias. We further recognize new emerging challenges from these new reality-mining approaches. While technological advances in automating data collection and its analysis are moving at an unprecedented rate, we urge ecologists to thoughtfully combine these new tools with classic behavioural and ecological monitoring methods to place our understanding of animal social networks within fundamental biological contexts.

Determining Stingray Movement Patterns in a Wave-Swept Coastal Zone Using a Blimp for Continuous Aerial Video Surveillance

Stingrays play a key role in the regulation of nearshore ecosystems. However, their movement ecology in high-energy surf areas remains largely unknown due to the notorious difficulties in conducting research in these environments. Using a blimp as an aerial platform for video surveillance, we overcame some of the limitations of other tracking methods, such as the use of tags and drones. This novel technology offered near-continuous coverage to characterise the fine-scale movements of stingrays in a surf area in Kiama, Australia, without any invasive procedures. A total of 98 stingray tracks were recorded, providing 6 h 27 min of movement paths. The tracking data suggest that stingrays may use a depth gradient located in the sandflat area of the bay for orientating their movements and transiting between locations within their home range. Our research also indicates that stingray behaviour was influenced by diel periods and tidal states. We observed a higher stingray occurrence during the afternoon, potentially related to foraging and anti-predatory strategies. We also saw a reduced route fidelity during low tide, when the bathymetric reference was less accessible due to stranding risk. Considering the increasing threat of anthropogenic development to nearshore coastal environments, the identification of these patterns can better inform the management and mitigation of threats.

An interaction mechanism for the maintenance of fission-fusion dynamics under different individual densities

Animals often show high consistency in their social organisation despite facing changing environmental conditions. Especially in shoaling fish, fission-fusion dynamics that describe for which periods individuals are solitary or social have been found to remain unaltered even when density changed. This compensatory ability is assumed to be an adaptation towards constant predation pressure, but the mechanism through which individuals can actively compensate for density changes is yet unknown. The aim of the current study is to identify behavioural patterns that enable this active compensation. We compared the fission-fusion dynamics of two populations of the live-bearing Atlantic molly (Poecilia mexicana) that live in adjacent habitats with very different predator regimes: cave mollies that inhabit a low-predation environment inside a sulfidic cave with a low density of predatory water bugs (Belostoma sp.), and mollies that live directly outside the cave (henceforth called "surface" mollies) in a high-predation environment. We analysed their fission-fusion dynamics under two different fish densities of 12 and 6 fish per 0.36 m2. As expected, surface mollies spent more time being social than cave mollies, and this difference in social time was a result of surface mollies being less likely to discontinue social contact (once they had a social partner) and being more likely to resume social contact (once alone) than cave mollies. Interestingly, surface mollies were also less likely to switch among social partners than cave mollies. A random walk simulation predicted each population to show reduced social encounters in the low density treatment. While cave mollies largely followed this prediction, surface mollies maintained their interaction probabilities even at low density. Surface mollies achieved this by a reduction in the size of a convex polygon formed by the group as density decreased. This may allow them to largely maintain their fission-fusion dynamics while still being able to visit large parts of the available area as a group. A slight reduction (21%) in the area visited at low densities was also observed but insufficient to explain how the fish maintained their fission-fusion dynamics. Finally, we discuss potential movement rules that could account for the reduction of polygon size and test their performance.

Exercise intensity while hooked is associated with physiological status of longline-captured sharks

Some shark populations face declines owing to targeted capture and by-catch in longline fisheries. Exercise intensity during longline capture and physiological status may be associated, which could inform management strategies aimed at reducing the impacts of longline capture on sharks. The purpose of this study was to characterize relationships between exercise intensity and physiological status of longline-captured nurse sharks (Ginglymostoma cirratum) and Caribbean reef sharks (Carcharhinus perezi). Exercise intensity of longline-captured sharks was quantified with digital cameras and accelerometers, which was paired with blood-based physiological metrics from samples obtained immediately post-capture. Exercise intensity was associated with physiological status following longline capture. For nurse sharks, blood pH increased with capture duration and the proportion of time exhibiting low-intensity exercise. Nurse sharks also had higher blood glucose and plasma potassium concentrations at higher sea surface temperatures. Associations between exercise intensity and physiological status for Caribbean reef sharks were equivocal; capture duration had a positive relation with blood lactate concentrations and a negative relationship with plasma chloride concentrations. Because Caribbean reef sharks did not appear able to influence blood pH through exercise intensity, this species was considered more vulnerable to physiological impairment. While both species appear quite resilient to longline capture, it remains to be determined if exercise intensity during capture is a useful tool for predicting mortality or tertiary sub-lethal consequences. Fisheries management should consider exercise during capture for sharks when developing techniques to avoid by-catch or reduce physiological stress associated with capture.

Drone-Based High-Resolution Tracking of Aquatic Vertebrates

Determining the small-scale movement patterns of marine vertebrates usually requires invasive active acoustic tagging or in-water monitoring, with the inherent behavioural impacts of those techniques. In addition, these techniques rarely allow direct continuous behavioural assessments or the recording of environmental interactions, especially for highly mobile species. Here, we trial a novel method of assessing small-scale movement patterns of marine vertebrates using an unmanned aerial vehicle that could complement longer-term tracking approaches. This approach is unlikely to have behavioural impacts and provides high accuracy and high frequency location data (10 Hz), while subsequently allowing quantitative trajectory analysis. Unmanned aerial vehicle tracking is also relatively low cost compared to single-use acoustic and GPS tags. We tracked 14 sharks for up to 10 min in a shallow lagoon of Heron Island, Australia. Trajectory analysis revealed that Epaulette sharks (Hemiscyllium ocellatum) displayed sinusoidal movement patterns, while Blacktip Reef Sharks (Carcharhinus melanopterus) had more linear trajectories that were similar to those of a Lemon shark (Negaprion acutidens). Individual shark trajectory patterns and movement speeds were highly variable. Results indicate that Epaulette sharks may be more mobile during diurnal low tides than previously thought. The approach presented here allows the movements and behaviours of marine vertebrates to be analysed at resolutions not previously possible without complex and expensive acoustic arrays. This method would be useful to assess the habitat use and behaviours of sharks and rays in shallow water environments, where they are most likely to interact with humans.

Activity seascapes highlight central place foraging strategies in marine predators that never stop swimming

BACKGROUND

Central place foragers (CPF) rest within a central place, and theory predicts that distance of patches from this central place sets the outer limits of the foraging arena. Many marine ectothermic predators behave like CPF animals, but never stop swimming, suggesting that predators will incur 'travelling' costs while resting. Currently, it is unknown how these CPF predators behave or how modulation of behavior contributes to daily energy budgets. We combine acoustic telemetry, multi-sensor loggers, and hidden Markov models (HMMs) to generate 'activity seascapes', which combine space use with patterns of activity, for reef sharks (blacktip reef and grey reef sharks) at an unfished Pacific atoll.

RESULTS

Sharks of both species occupied a central place during the day within deeper, cooler water where they were less active, and became more active over a larger area at night in shallower water. However, video cameras on two grey reef sharks revealed foraging attempts/success occurring throughout the day, and that multiple sharks were refuging in common areas. A simple bioenergetics model for grey reef sharks predicted that diel changes in energy expenditure are primarily driven by changes in swim speed and not body temperature.

CONCLUSIONS

We provide a new method for simultaneously visualizing diel space use and behavior in marine predators, which does not require the simultaneous measure of both from each animal. We show that blacktip and grey reef sharks behave as CPFs, with diel changes in activity, horizontal and vertical space use. However, aspects of their foraging behavior may differ from other predictions of traditional CPF models. In particular, for species that never stop swimming, patch foraging times may be unrelated to patch travel distance.

Effect of weight and frontal area of external telemetry packages on the kinematics, activity levels and swimming performance of small-bodied sharks

This study sought to observe the effects of submerged weight and frontal cross-sectional area of external telemetry packages on the kinematics, activity levels and swimming performance of small-bodied juvenile sharks, using lemon sharks Negaprion brevirostris (60-80 cm total length, L_T ) as a model species. Juveniles were observed free-swimming in a mesocosm untagged and with small and large external accelerometer packages that increased frontal cross-sectional area of the animals and their submerged weight. Despite adhering to widely used standards for tag mass, the presence of an external telemetry package altered swimming kinematics, activity levels and swimming performance of juvenile N. brevirostris relative to untagged individuals, suggesting that tag mass is not a suitable standalone metric of device suitability. Changes in swimming performance could not be detected from tail-beat frequency, which suggests that tail-beat frequency is an unsuitable standalone metric of swimming performance for small N. brevirostris. Lastly, sharks experienced treatment-specific changes in activity level and swimming kinematics from morning to afternoon observation. Therefore, the presence of external telemetry packages altered the kinematics, activity levels and swimming performance of small young-of-the-year N. brevirostris and these data may therefore be relevant to other similar-sized juveniles of other shark species.

The energetic, physiological, and behavioral response of lemon sharks (Negaprion brevirostris) to simulated longline capture

Commercial fisheries bycatch is a considerable threat to elasmobranch population recovery, and techniques to mitigate sub-lethal consequences can be improved with data on the energetic, physiological, and behavioral response of individuals to capture. This study sought to estimate the effects of simulated longline capture on the behavior, energy use, and physiological stress of juvenile lemon sharks (Negaprion brevirostris). Captive sharks equipped with acceleration biologgers were subjected to 1h of simulated longline capture. Swimming behaviors were identified from acceleration data using a machine-learning algorithm, energetic costs were estimated using accelerometer-calibrated relationships and respirometry, and physiological stress was quantified with point-of-care blood analyzers. During capture, sharks exhibited nine-fold increases in the frequency of burst swimming, 98% reductions in resting, and swam as often as unrestrained sharks. Aerobic metabolic rates during capture were 8% higher than for unrestrained sharks, and accounted for a 57.7% increase in activity costs when excess post-exercise oxygen consumption was included. Lastly, sharks exhibited significant increases in blood lactate and glucose, but no change in blood pH after 1h of capture. Therefore, these results provide preliminary insight into the behavioral and energetic responses of sharks to capture, and have implications for mitigating sub-lethal consequences of capture for sharks as commercial longline bycatch.

Demystifying animal 'personality' (or not): why individual variation matters to experimental biologists

Animal 'personality', defined as repeatable inter-individual differences in behaviour, is a concept in biology that faces intense controversy. Critics argue that the field is riddled with terminological and methodological inconsistencies and lacks a sound theoretical framework. Nevertheless, experimental biologists are increasingly studying individual differences in physiology and relating these to differences in behaviour, which can lead to fascinating insights. We encourage this trend, and in this Commentary we highlight some of the benefits of estimating variation in (and covariation among) phenotypic traits at the inter- and intra-individual levels. We focus on behaviour while drawing parallels with physiological and performance-related traits. First, we outline some of the confusion surrounding the terminology used to describe repeatable inter-individual differences in behaviour. Second, we argue that acknowledging individual behavioural differences can help researchers avoid sampling and experimental bias, increase explanatory power and, ultimately, understand how selection acts on physiological traits. Third, we summarize the latest methods to collect, analyse and present data on individual trait variation. We note that, while measuring the repeatability of phenotypic traits is informative in its own right, it is only the first step towards understanding how natural selection and genetic architecture shape intra-specific variation in complex, labile traits. Thus, understanding how and why behavioural traits evolve requires linking repeatable inter-individual behavioural differences with core aspects of physiology (e.g. neurophysiology, endocrinology, energy metabolism) and evolutionary biology (e.g. selection gradients, heritability).

Emerging Network-Based Tools in Movement Ecology

New technologies have vastly increased the available data on animal movement and behaviour. Consequently, new methods deciphering the spatial and temporal interactions between individuals and their environments are vital. Network analyses offer a powerful suite of tools to disentangle the complexity within these dynamic systems, and we review these tools, their application, and how they have generated new ecological and behavioural insights. We suggest that network theory can be used to model and predict the influence of ecological and environmental parameters on animal movement, focusing on spatial and social connectivity, with fundamental implications for conservation. Refining how we construct and randomise spatial networks at different temporal scales will help to establish network theory as a prominent, hypothesis-generating tool in movement ecology.