Long-Term Monitoring of Swimming and Feeding Behaviors Related to Reproductive Cycles in Captive Loggerhead Turtles, Caretta caretta

Marine turtles spend their life at sea and can rest on the seafloor for hours. As air-breathers, the breath-hold capacity of marine turtles is a function of oxygen (O2) stores, O2 consumption during dives and hypoxia tolerance. However, some physiological adaptations to diving observed in mammals are absent in marine turtles. This study examined cardiovascular responses in loggerhead sea turtles, which have even fewer adaptations to diving than other marine turtles, but can dive for extended durations. Heart rates (fH) of eight undisturbed loggerhead turtles in shallow tanks were measured using self-contained ECG data loggers under five conditions: spontaneous dives, resting motionless on the tank bottom, resting in shallow water with their head out of water, feeding on squid, and swimming at the surface between dives. There was no significant difference between resting fH while resting on the bottom of the tank, diving or resting in shallow water with their head out of water. fH rose as soon as turtles began to move and was highest between dives when turtles were swimming at the surface. These results suggest cardiovascular responses in captive loggerhead turtles are driven by activity and apneic fH is not reduced by submergence under these conditions.

Estimation of sperm storage duration in captive loggerhead turtles (Caretta caretta)

ABSTRACTHeart rates of air-breathing diving animals can change on a short time scale due to the diving response during submergence. Heart rate is used frequently as a proxy for indirectly estimating metabolic rates on a fine time scale. However, most studies to date have been conducted on endothermic diving animals, and the relationships between metabolic rates and heart rates in ectothermic diving animals have not been well studied. Sea turtles are unique model organisms of diving ectotherms because they spend most of their life in the ocean and perform deep and/or long dives. In this study, we examined the relationship between heart rates and metabolic rates in captive loggerhead turtles, Caretta caretta, to estimate oxygen consumption rates during each dive based on heart rates. The oxygen consumption rates (V̇O2: mlO2 min−1 kg−1) and average heart rates (fH: beats min−1) were measured simultaneously in indoor tanks at water temperatures of 15–25°C. Our results showed that oxygen consumption rate was affected by heart rate and water temperature in loggerhead turtles. Based on the collected data, we formulated the model equation as V̇O2=0.0124fH+0.0047Tw - 0.0791. The equation can be used for estimating fine-scaled field metabolic rates in free-ranging loggerhead turtles. The results of this study will contribute to future comparative studies of the physiological states of ectothermic diving animals.

Sea turtles are known to detect chemical cues, but in contrast to most marine animals, turtles surface to breathe and thus potentially have access to olfactory cues both in air and in water. To determine whether sea turtles can detect airborne chemical cues, captive loggerhead turtles (Caretta caretta) were placed into a circular, water-filled arena in which odorants could be introduced to the air above the water surface. Air that had passed across the surface of a cup containing food elicited increased activity, diving and other behavior normally associated with feeding. By contrast, air that had passed across the surface of an identical cup containing distilled water elicited no response. Increases in activity during food odor trials occurred only after turtles surfaced to breathe and peaked in the first post-breath minute, implying that the chemical cues eliciting the responses were unlikely to have been detected while the turtles were under water. These results provide the first direct evidence that sea turtles can detect airborne odors. Under natural conditions, this sensory ability might function in foraging, navigation or both.

Gulps, wheezes, and sniffs: how measurement of beak movement in sea turtles can elucidate their behaviour and ecology

Sturgeon populations are imperiled worldwide. Declines are attributed to many factors including habitat degradation and alteration, overexploitation, and contamination. In North America, white sturgeon (Acipenser transmontanus) populations in the upper Columbia River (UCR) face many of the same factors. White sturgeon in this system have been declining for decades due to a lack of recruitment to the population, despite evidence of spawning and early larval survival in the wild. Early life stage white sturgeon are among the most sensitive of aquatic species to copper. The UCR has been contaminated with metal laden slag and liquid effluents from smelter and mining activities, resulting in UCR sediment metal concentrations, including copper, being elevated. The goal of my dissertation was to understand the potential role of metal contamination in the decline of white sturgeon in the UCR. This effort included toxicity tests with copper contaminated water as well as sediments collected from the URC, with a focus on the behavioral responses of exposed fish as a consequence of sublethal exposures. In chapter 1, I exposed early life stage white sturgeon to sublethal concentrations of copper, one of the contaminants of concern in the UCR, to characterize and quantify the effects of copper on swimming and feeding behavior. I found that changes in larval sturgeon swimming behavior were apparent up to seven days earlier than mortality and that copper exposure reduced food consumption in juvenile sturgeon. Critical swimming performance, however, was not affected by copper exposure. While not directly lethal, these alterations in behavior would impair a sturgeon's ability to locate, capture, and consume prey, thus impacting survival. In chapter 2, I evaluated the toxicity of metal contaminated sediments from the UCR to larval white sturgeon. Sediment was collected from six sites in the transboundary reach of the UCR. All six sites had elevated metal concentrations above equilibrium partitioning sediment benchmarks, which would suggest the metals could pose a risk to benthic invertebrates. The overlying water metal concentrations were also above water quality criteria levels in three of the six sites. I found sediment at one site reduced survival and affected swimming behavior of larval sturgeon.In chapter 3, I provide a synthesis evaluation of white sturgeon life history with what has been reported about metal contamination in the UCR, including documented concentrations from the river, and what we know about how metals affect larval sturgeon behavior and survival. Of particular concern are reported field observations of large numbers of sturgeon larvae with empty guts at a critical point in their life cycle. By putting all these pieces together, I found that metal contamination in the UCR could be reducing the prey base of larval sturgeon, altering swimming behavior to increase likelihood of starvation or predation, and evidence of an additional exposure route when larval sturgeon ingest sediment. Thus, the most important findings from my dissertation include 1) low, environmentally relevant concentrations of copper alter swimming behavior of larval sturgeon indicative of sublethal injury, 2) sediments collected from the UCR can affect larval sturgeon survival and swimming behavior, and 3) metal concentrations measured at some sites in the UCR are above effect concentrations from laboratory studies. These findings suggest that metal contamination could be a factor in the decline of the upper Columbia River white sturgeon, and should be considered in recovery efforts for the population.

To study habitat use by loggerhead sea turtles in the Algerian Basin (western Mediterranean), ten juveniles (straight carapace length range: 39.0–63.3 cm) were tracked by satellite from March 2004 to September 2005. Swimming behaviour (characterized by speed of travel, time spent at the surface, and the cosine of turning angles) varied individually, but these differences were unrelated to body size. Despite individual differences in swimming behaviour, the ten immature loggerhead sea turtles spent most of their time in the oceanic waters of the Algerian Basin, although simulations indicated that the average tracking time (235.7 ± 98.7 SD days) was sufficiently long for them to leave the Algerian Basin and disperse through most of the Mediterranean. Furthermore, none of the ten turtles swam in any preferred direction, and their bearings were all randomly distributed. Finally, all them consistently avoided the continental shelf and did not migrate seasonally, as the average latitude, the average longitude, and the average distance of the population to the release point did not change seasonally. Seasonality also had only a weak influence in swimming behaviour, as the time spent at the surface during light hours was the only parameter that changed seasonally. We conclude that immature loggerhead sea turtles in the south of the western Mediterranean exhibit a strong fidelity to the Algerian Basin, where distribution is ruled mainly by the bathymetry, without any influence of seasonality. That fidelity to the Algerian Basin matches predictions based on genetic structuring and might result from a combination of factors: surface circulation patterns and habitat selection by the loggerhead sea turtles.

Introduction: Behaviors of swimming rodents are not uniform, exhibiting large variations, which may underlie the individual differences in swimming exercise-induced benefits. The study aimed to monitor individualized swimming behavior and evaluate its biological significance. Methods: A swimming tank which can monitor individualized rodent swimming behavior during exercise was established. A total of 45 mice were subjected to swimming training for 1 month (1h per day) and the swimming behaviors of each mouse were recorded. Results: The swimming behaviors of mice displayed considerable variations in aspects of distance, velocity, and area preference. For example, nearly one-third of mice preferred to swim in central area and most of the mice exhibited an even area distribution. Long-term exercise training improved cardiac systolic function and decreased blood pressure in mice, but hardly changed swimming behaviors. Analyses of the relationship between swimming behavior and cardiovascular adaptations to exercise training revealed that swimming behavior indicated the biological effects of swimming training. Specifically, mice which preferred swimming at the central zone or were trainable in behavior during 1-month training exhibited better outcomes in cardiac function and blood pressure post long-term exercise. Mechanistically, a centralized swimming behavior indicated a smaller stress during exercise, as evidenced by a milder activation of hypothalamic-pituitary-adrenal axis. Discussion: These results suggest that swimming behavior during training indicates individualized adaptations to long-term exercise, and highlight a biological significance of swimming behavior monitoring in animal studies.

Fluoxetine is one of the worlds most prescribed antidepressant, and frequently detected in surface waters. Once present in the aquatic environment, fluoxetine has been shown to disrupt the swimming behaviour of fish and invertebrates. However, swimming behaviour is also known to be highly variable according to experimental conditions, potentially concealing relevant effects. Therefore, the aims of this study were two-fold: i) investigate the swimming and feeding behaviour of Gammarus pulex after exposure to the antidepressant fluoxetine (0.2, 2, 20, and 200 μg/L), and ii) assess to what degree the experimental test duration (short-term and long-term) and test location (laboratory and semi-field conditions) affect gammarid's swimming behaviour. We used automated video tracking and analysis to asses a range of swimming behaviours of G. pulex, including swimming speed, startle responses after light transition, acceleration, curvature and thigmotaxis. We found larger effects on the swimming behaviour of G. pulex due to experimental conditions than due to tested antidepressant concentrations. Gammarids swam faster, more straight and showed a stronger startle response during light transition when kept under semi-field conditions compared to the laboratory. Effects found for different test durations were opposite in the laboratory and semi-field. In the laboratory gammarids swam slower and spent more time at the inner zone of the arena after 2 days compared to 21 days while for the semi-field the reverse was observed. Fluoxetine had only minor impacts on the swimming behaviour of G. pulex, but experimental conditions influenced behavioural outcomes in response to fluoxetine exposure. Overall, our results highlight the importance of standardizing and optimizing experimental protocols that assess behaviour to achieve reproducible results in ecotoxicology.

Early-life stage white sturgeon are sensitive to copper (Cu), with adverse behavioral responses observed during previous studies. The objectives of the present study were to quantify the effects of Cu exposure on white sturgeon swimming and feeding behaviors and determine their time to response. Larval sturgeon (1-2, 28, or 35 d posthatch [dph]) were exposed to Cu (0.5-8 μg/L) for 4 to 14 d. Abnormal behavioral changes were observed within the first few days of exposure including loss of equilibrium and immobilization. Digital video tracking software revealed decreased swimming activity with increasing Cu concentration. Significant changes in behavior and mortality occurred at concentrations of Cu between 1 and 8 μg/L. Juvenile white sturgeon, 58 dph, exposed to 12 μg/L Cu consumed 37 to 60% less food than controls after 3 d of exposure. The present results indicate that behavioral endpoints were more sensitive than some standard toxicity test endpoints and can effectively expand the sensitivity of standard toxicity tests for white sturgeon. Swimming behavior was impaired to the extent that survival in the field would likely be jeopardized. Such data would provide managers a useful metric for characterizing the risks of Cu contamination to white sturgeon. Environ Toxicol Chem 2019;38:132-144. Published 2018 Wiley Periodicals Inc. on behalf of SETAC. This article is a US government work and, as such, is in the public domain in the United States of America.

Swimming behaviour as an indicator of low growth rate and impaired welfare in Atlantic halibut (Hippoglossus hippoglossus L.) reared at three stocking densities

Catadioptric stereo-vision system for the real-time monitoring of 3D behavior in aquatic animals

Simultaneous monitoring of animal behavior and neuronal activity in the brain enables us to examine the neural underpinnings of behaviors. Conventionally, the neural activity data are buffered, amplified, multiplexed, and then converted from analog to digital in the head-stage amplifier, following which they are transferred to a storage server via a cable. Such tethered recording systems, intended for indoor use, hamper the free movement of animals in three-dimensional (3D) space as well as in large spaces or underwater, making it difficult to target wild animals active under natural conditions; it also presents challenges in realizing its applications to humans, such as the Brain–Machine Interfaces (BMI). Recent advances in micromachine technology have established a wireless logging device called a neurologger, which directly stores neural activity on ultra-compact memory media. The advent of the neurologger has triggered the examination of the neural correlates of 3D flight, underwater swimming of wild animals, and translocation experiments in the wild. Examples of the use of neurologgers will provide an insight into understanding the neural underpinnings of behaviors in the natural environment and contribute to the practical application of BMI. Here we outline the monitoring of the neural underpinnings of flying and swimming behaviors using neurologgers. We then focus on neuroethological findings and end by discussing their future perspectives.

Health monitoring is crucial for early disease detection and prompt intervention to mitigate the disease. Computer vision is one of the novel methods for disease detection, but a significant gap remains in its application for detecting behavioural deviations associated with disease. This study employed YOLOv8s-based behavioural monitoring combined with statistical analysis to evaluate disease detection efficacy in group-housed pigs. Two groups of pigs (Control [CON] and Treatment [TRT]), 9-10 weeks old of a (Large White × Landrace) × Duroc cross, were raised for 21 days. The growing period was divided into three periods (adaptation, challenge, and recovery) and evaluated based on growth performance, health indicators (ear base temperature and faecal score), and behaviour (postures, feeding, and drinking). The TRT group was challenged with Salmonella typhimurium during the challenge period to induce infection, then treated with antibiotics. Two pre-trained YOLOv8s models were employed to quantify postures (Lateral Lying, Sternal Lying, Standing, and Sitting) and nutritive behaviours (Feeding and Drinking). Z-score analyses based on daily data (DZA) and time-specific or 12-h interval (TSZA) data were used to detect behavioural anomalies, with the adaptation period as the baseline. During the challenge period, TRT pigs exhibited a drastic decline in growth, increased ear base temperature, and elevated faecal scores, confirming successful infection. Compensatory growth was observed during the recovery period. Automated behaviour monitoring enabled detailed temporal analysis of responses to infection, treatment, and environmental fluctuations. Notable behavioural deviations in the TRT group emerged at 4 days post-inoculation (DPI), aligning with significant health deterioration. However, health indicators diverged as early as 1 DPI, suggesting that group-based behavioural monitoring may be less sensitive to early individual responses. TSZA detected subtle behavioural anomalies earlier than DZA, with disruptions in the TRT group beginning at 0 DPI. These included sharp fluctuations in sitting, lying, and feeding behaviours, which gradually stabilised after treatment. This study highlights the potential of computer vision-based behavioural monitoring as a non-invasive, high-throughput tool for real-time health surveillance. While effective for group assessments, results emphasise the need for more advanced methods to enhance early disease detection and improve precision in pig health management.

Simple SummaryAutomatic behavior monitoring, also called automated analytics or automated reporting, is the ability of an analytics platform to auto-detect relevant insights—anomalies, trends, patterns—and deliver them to users in real time, without users having to manually explore their data to find the answers they need. An analytics platform with automated behavior monitoring uses algorithms to auto-analyze datasets to search for notable changes in data. It then generates alerts at fixed intervals or triggers (thresholds), and delivers the findings to each user, ready-made. In-aquaculture scoring of behavioral indicators of aquatic animal welfare is challenging, but the increasing availability of low-cost technology now makes the automated monitoring of behavior feasible.Crustacean farming is a fast-growing sector and has contributed to improving incomes. Many studies have focused on how to improve crustacean production. Information about crustacean behavior is important in this respect. Manual methods of detecting crustacean behavior are usually infectible, time-consuming, and imprecise. Therefore, automatic growth situation monitoring according to changes in behavior has gained more attention, including acoustic technology, machine vision, and sensors. This article reviews the development of these automatic behavior monitoring methods over the past three decades and summarizes their domains of application, as well as their advantages and disadvantages. Furthermore, the challenges of individual sensitivity and aquaculture environment for future research on the behavior of crustaceans are also highlighted. Studies show that feeding behavior, movement rhythms, and reproduction behavior are the three most important behaviors of crustaceans, and the applications of information technology such as advanced machine vision technology have great significance to accelerate the development of new means and techniques for more effective automatic monitoring. However, the accuracy and intelligence still need to be improved to meet intensive aquaculture requirements. Our purpose is to provide researchers and practitioners with a better understanding of the state of the art of automatic monitoring of crustacean behaviors, pursuant of supporting the implementation of smart crustacean farming applications.