First insights Into the fine-scale movements of the Sandbar Shark, Carcharhinus plumbeus

The expanding use of biologging tags in studies of shark movement provides an opportunity to elucidate the context and drivers of fine-scale movement patterns of these predators. In May 2017, we deployed high-resolution biologging tags on four mature female sandbar sharks Carcharhinus plumbeus at Ningaloo Reef for durations ranging between 13 and 25.5 h. Pressure and tri-axial motion sensors within these tags enabled the calculation of dive geometry, swimming kinematics and path tortuosity at fine spatial scales (m-km) and concurrent validation of these behaviors from video recordings. Sandbar sharks oscillated through the water column at shallow dive angles, with gliding behavior observed in the descent phase for all sharks. Continual V-shaped oscillatory movements were occasionally interspersed by U-shaped dives that predominately occurred around dusk. The bottom phase of these U-shaped dives likely occurred on the seabed, with dead-reckoning revealing a highly tortuous, circling track. By combining these fine-scale behavioral observations with existing ecological knowledge of sandbar habitat and diet, we argue that these U-shaped dives are likely to be a strategy for bentho-pelagic foraging. Comparing the diving geometry of sandbar sharks with those of other shark species reveals common patterns in oscillatory swimming. Collectively, the fine-scale movement patterns of sandbar sharks reported here are consistent with results of previous biologging studies that emphasize the role of cost-efficient foraging in sharks

Direct measurement of swimming and diving kinematics of giant Atlantic bluefin tuna (Thunnus thynnus)

Tunas possess a range of physiological and mechanical adaptations geared towards high-performance swimming that are of considerable interest to physiologists, ecologists and engineers. Advances in biologging have provided significant improvements in understanding tuna migrations and vertical movement patterns, yet our understanding of the locomotion and swimming mechanics of these fish under natural conditions is limited. We equipped Atlantic bluefin tuna (Thunnus thynnus) with motion-sensitive tags and video cameras to quantify the gaits and kinematics used by wild fish. Our data reveal significant variety in the locomotory kinematics of Atlantic bluefin tuna, ranging from continuous locomotion to two types of intermittent locomotion. The tuna sustained swimming speeds in excess of 1.5 m s−1 (0.6 body lengths s−1), while beating their tail at a frequency of approximately 1 Hz. While diving, some descents were entirely composed of passive glides, with slower descent rates featuring more gliding, while ascents were primarily composed of active swimming. The observed swimming behaviour of Atlantic bluefin tuna is consistent with theoretical models predicting such intermittent locomotion to result in mechanical and physiological advantages. Our results confirm that Atlantic bluefin tuna possess behavioural specializations to increase their locomotory performance, which together with their unique physiology improve their capacity to use pelagic and mesopelagic habitats

A new approach to identifying behaviour in animals using tiger sharks, Galeocerdo cuvier, as a test species

There are many advantages in determining animal behaviour for conservation initiatives seeking to protect species impacted by the changing planet. However, for many years, direct observation of elusive or dangerous animals in challenging habitats precluded the acquisition of representative, non-biased behavioural data. Recently though, animal-attached tag technology incorporating accelerometers, magnetometers and pressure sensors, has greatly advanced our abilities to document the behaviour of a numerous vertebrate species (e.g. birds, reptiles, fish, mammals), even when they cannot be observed. For this, supervised and unsupervised machine learning are often used to categorise behaviours by identifying patterns within the biotelemetry data. However, supervised machine learning requires training data, which is not always available, and both methods are driven by machine-based software with no explicitly defined parameters associated with behaviours which can be cross-checked. This work aimed to use a proper physics-based understanding of triaxial accelerometer-, magnetometer- and pressure data taken from electronic tags deployed on tiger sharks, Galeocerdo cuvier, to interpret patterns and group them into behaviours. As part of this, multi-modality in frequency distributions of parameters was investigated, on the premise that different behaviours can result in different frequency distributions in particular metrics. Following examination, algorithms using defined numerical limits were created to isolate distinct behaviours and these used to detect the extent of identified patterns within entire data sets and across individuals. A total of 12,338 minutes of tag data was processed, from which 10 behaviours were identified. Seven of these were successfully described using numerical metric limits from recorded and/or derived data including; ‘descent’, ‘ascent’, ‘burst power’, etc. However, frequency distributions showed a continuum rather than multiple distinct modes, indicating that this approach is likely to be more complex than thought. The use of physical principles seems a promising method for interpreting accelerometer, magnetometer and pressure data to identify behaviours that occur in study animals that cannot be directly observed. Although these algorithms are specific to tiger sharks in this work, this method is likely to be applicable to other species in aerial, aquatic or terrestrial habitats and could inform a broad range of conservations initiatives in the future

Biologging Tags Reveal Links Between Fine-Scale Horizontal and Vertical Movement Behaviors in Tiger Sharks (Galeocerdo cuvier)

An understanding of the role that large marine predators play in structuring trophic flow and nutrient cycling in marine ecosystems requires knowledge of their fine-scale (m-km) movement behaviors. In this study, biologging tags were used to reveal new insights into the three-dimensional fine-scale movement ecology of tiger sharks (Galeocerdo cuvier) at Ningaloo Reef, Western Australia. Tags deployed on 21 sharks in April-May 2017 for durations of 5–48 h recorded both physical parameters such as depth and temperature, and, through the use of accelerometers, gyroscopes and compasses, in-situ measurements of animal trajectory and locomotion. Animal-borne-video enabled the validation of behavioral signatures, mapping of habitat, and recording of interactions with prey. Collectively, these data were used to examine the link between vertical (oscillations) and horizontal (tortuosity) movements, and link sensor data to prey interactions recorded by the video. This biologging approach revealed complex movements that would otherwise be invisible within the time-depth records provided by traditional tagging techniques. The rate of horizontal turning was not related to vertical oscillations, suggesting that vertical movements occur independently of searching behaviors in tiger sharks. These animals displayed tortuous movements possibly associated with prey searching for 27% of their tracks, and interactions with prey elicited varied responses including highly tortuous paths and burst movements. Accurate speed measurements and GPS anchor points will considerably enhance the value of magnetometer data in future studies by facilitating more accurate dead-reckoning and geo-referencing of area-restricted search behaviors

Direct measurement of cruising and burst swimming speeds of the shortfin mako shark (Isurus oxyrinchus) with estimates of field metabolic rate

The shortfin mako shark is a large-bodied pursuit predator thought to be capable of the highest swimming speeds of any elasmobranch and potentially one of the highest energetic demands of any marine fish. Nonetheless, few direct speed measurements have been reported for this species. Here, animal-borne bio-loggers attached to two mako sharks were used to provide direct measurements of swimming speeds, kinematics and thermal physiology. Mean sustained (cruising) speed was 0.90 m s−1 (±0.07 s.d.) with a mean tail-beat frequency (TBF) of 0.51 Hz (±0.16 s.d.). The maximum burst speed recorded was 5.02 m s−1 (TBFmax = 3.65 Hz) from a 2 m long female. Burst swimming was sustained for 14 s (mean speed = 2.38 m s−1), leading to a 0.24°C increase in white muscle temperature in the 12.5 min after the burst. Routine field metabolic rate was estimated at 185.2 mg O2 kg−1 h−1 (at 18°C ambient temperature). Gliding behaviour (zero TBF) was more frequently observed after periods of high activity, especially after capture when internal (white muscle) temperature approached 21°C (ambient temperature: 18.3°C), indicating gliding probably functions as an energy recovery mechanism and limits further metabolic heat production. The results show shortfin mako sharks generally cruise at speeds similar to other endothermic fish – but faster than ectothermic sharks – with the maximum recorded burst speed being among the highest so far directly measured among sharks, tunas and billfishes. This newly recorded high-oxygen-demand performance of mako sharks suggests it may be particularly vulnerable to habitat loss due to climate-driven ocean deoxygenatio

日本における外来魚チャネルキャットフィッシュの分布様式および流れに関連した行動特性

学位の種別: 課程博士審査委員会委員 : （主査）東京大学教授 佐藤 克文, 東京大学教授 木村 伸吾, 東京大学教授 青山 潤, 東京大学准教授 山川 卓, 東京大学准教授 北川 貴士University of Tokyo(東京大学

High definition video loggers provide new insights into behaviour, physiology, and the oceanic habitat of a marine predator, the yellow-eyed penguin

Camera loggers are increasingly used to examine behavioural aspects of free-ranging animals. However, often video loggers are deployed with a focus on specific behavioural traits utilizing small cameras with a limited field of view, poor light performance and video quality. Yet rapid developments in consumer electronics provide new devices with much improved visual data allowing a wider scope for studies employing this novel methodology. We developed a camera logger that records full HD video through a wide-angle lens, providing high resolution footage with a greater field of view than other camera loggers. The main goal was to assess the suitability of this type of camera for the analysis of various aspects of the foraging ecology of a marine predator, the yellow-eyed penguin in New Zealand. Frame-by-frame analysis allowed accurate timing of prey pursuits and time spent over certain seafloor types. The recorded video footage showed that prey species were associated with certain seafloor types, revealed different predator evasion strategies by benthic fishes, and highlighted varying energetic consequences for penguins pursuing certain types of prey. Other aspects that could be analysed were the timing of breathing intervals between dives and observe exhalation events during prey pursuits, a previously undescribed behaviour. Screen overlays facilitated analysis of flipper angles and beat frequencies throughout various stages of the dive cycle. Flipper movement analysis confirmed decreasing effort during descent phases as the bird gained depth, and that ascent was principally passive. Breathing episodes between dives were short (<1 s) while the majority of the time was devoted to subsurface scanning with a submerged head. Video data recorded on free-ranging animals not only provide a wealth of information recorded from a single deployment but also necessitate new approaches with regards to analysis of visual data. Here, we demonstrate the diversity of information that can be gleaned from video logger data, if devices with high video resolution and wide field of view are utilized