BackgroundWelfare challenges in salmon farming highlights the need to improve understanding of the fish’s response to its environment and rearing operations. This can be achieved by monitoring physiological responses such as heart rate (HR) for individual fish. Existing solutions for heart rate monitoring are typically based on Electrocardiography (ECG) which is sensitive to placement and electrode orientation. These factors are difficult to control and affects the reliability of the principle, prompting the desire to find an alternative to ECG for heart rate monitoring in fish. This study was aimed at adapting an optical photoplethysmography (PPG) sensor for this purpose. An embedded sensor unit measuring both PPG and ECG was developed and tested using anesthetized Atlantic salmon in a series of in-vivo experiments. HR was derived from PPG and compared to the ECG baseline to evaluate its efficacy in estimating heart rate.ResultsThe results show that PPG HR was estimated with an accuracy of 0.7 ± 1.0% for 660 nm and 1.1 ± 1.2% for 880 nm wavelengths, respectively, relative to the ECG HR baseline. The results also indicate that PPG should be measured in the anterior part of the peritoneal cavity in the direction of the heart.ConclusionA PPG/ECG module was successfully adapted to measure both ECG and PPG in-vivo for anesthetized Atlantic salmon. Using ECG as baseline, PPG analysis results show that that HR can be accurately estimated from PPG. Thus, PPG has the potential to become an alternative to ECG HR measurements in fish.

Agriculture is becoming increasingly reliant upon accurate data from sensor arrays, with localization an emerging application in the livestock industry. Ground-based time difference of arrival (TDoA) radio location methods have the advantage of being lightweight and exhibit higher energy efficiency than methods reliant upon Global Navigation Satellite Systems (GNSS). Such methods can employ small primary battery cells, rather than rechargeable cells, and still deliver a multi-year deployment. In this paper, we present a novel deep learning algorithm adapted from a one-dimensional U-Net implementing a convolutional neural network (CNN) model, originally developed for the task of semantic segmentation. The presented model (ResUnet-1d) both converts TDoA sequences directly to positions and reduces positional errors introduced by sources such as multipathing. We have evaluated the model using simulated animal movements in the form of TDoA position sequences in combination with real-world distributions of TDoA error. These animal tracks were simulated at various step intervals to mimic potential TDoA transmission intervals. We compare ResUnet-1d to a Kalman filter to evaluate the performance of our algorithm to a more traditional noise reduction approach. On average, for simulated tracks having added noise with a standard deviation of 50 m, the described approach was able to reduce localization error by between 66.3% and 73.6%. The Kalman filter only achieved a reduction of between 8.0% and 22.5%. For a scenario with larger added noise having a standard deviation of 100 m, the described approach was able to reduce average localization error by between 76.2% and 81.9%. The Kalman filter only achieved a reduction of between 31.0% and 39.1%. Results indicate that this novel 1D CNN U-Net like encoder/decoder for TDoA location error correction outperforms the Kalman filter. It is able to reduce average localization errors to between 16 and 34 m across all simulated experimental treatments while the uncorrected average TDoA error ranged from 55 to 188 m.

BackgroundThe internal environment of eggs in most birds is regulated by transferring heat energy through contact incubation, maintaining nest microclimate, and frequent egg turning by the incubating parent on its nest. However, we lack information about egg attendance patterns in birds that breed in polar environments where variations in life history are expected to influence incubation behavior. Moreover, crevice/burrow nesting petrels in high-latitude regions are known for periodically leaving their egg unattended (hereafter ‘egg neglect’), but there is little reporting on the internal condition of unattended eggs. At Dumont d’Urville Station, Antarctica, we studied the incubation behavior of 24 snow (Pagodroma nivea) and 15 Cape (Daption capense) petrel pairs using egg loggers that recorded egg turning rates, orientation changes, and temperatures at 1 Hz for durations of 3–6 days.ResultsEgg turning frequency (1.31 ± 0.33 vs. 1.38 ± 0.39 turns h−1), angle change per turn (43.1 ± 43.2 vs. 48.6 ± 43.7° turn−1), and egg temperature (34.1 ± 2.3 vs. 34.1 ± 2.0 °C) were nearly identical for snow and Cape petrels, respectively. However, egg neglect was only observed in snow petrel nests (based on egg temperature changes) where loggers recorded mean durations of 1.34 ± 1.15 days (maximum duration of 3.63 days). During periods of neglect, eggs cooled to 5.5 ± 1.8 °C over an average of 91 min, but were rewarmed by parents in only 76 min at a rate of 0.33 °C min−1.ConclusionsEgg temperatures of both species during regular incubation were within 1–2 °C of other high-latitude petrel species, but neglected snow petrel eggs remained several degrees above freezing, which was likely attributed to crevice nesting where neglected eggs are buffered by environmental conditions. Using egg rewarming rates, thermal capacity of eggs, and published metabolic rates, we estimate egg rewarming costs in snow petrels to be 1.5 to 1.9 × BMR. Excluding egg neglect periods, turning rates for both petrel species were lower than other seabirds studied using biologging devices, which may be associated with the prolonged incubation periods that are characteristic of procellariiform seabirds.

BackgroundThe establishment of Burmese pythons (Python bivittatus) in Everglades National Park, Florida, USA, has been connected to a > 90% decline in the mesomammal population in the park and is a major threat to native reptile and bird populations. Efforts to control this population are underway, but are hampered by a lack of information about fine-scale activity cycles and ecology of these cryptic animals in the wild. We aimed to establish a technique for monitoring the activity of Burmese pythons in the wild using acceleration data loggers (ADLs), while attempting to identify any behavioral patterns that could be used to help manage this invasive species in the Greater Everglades and South Florida.ResultsWe obtained continuous acceleration and temperature data from four wild snakes over periods of 19 to 95 days (mean 54 ± 33 days). Snakes spent 86% of their time at rest and 14% of their time active, including transiting between locations. All snakes showed at least one period of continuous transiting lasting 10 h or more, with one animal transiting continuously for a period of 58.5 h. Acceleration data logger-derived transiting bout duration was significantly correlated with the distance snakes traveled per hour for two snakes that also carried GPS loggers. Snakes were most active in midday or early-night depending on individual and time of year, but all snakes were least likely to be active in the early mornings (0400–0700 h local time). Very little movement took place at temperatures below 14 °C or above 24 °C, with most movement taking place between 15° and 20 °C. One animal showed a highly unusual rolling event that may be indicative of a predation attempt, but this could not be confirmed.ConclusionsFine-scale activity and some behaviors were apparent from ADL data, making ADLs a potentially valuable, unbiased tool for monitoring large-bodied snakes in the wild. Snakes spent the majority of their time resting, but also moved continuously for several hours at a time during bouts of transiting. Results suggest that individuals may shift their diel activity pattern based on season. Understanding seasonal differences in activity levels can improve the accuracy of population estimates, help detect range expansion, and improve managers’ ability to find and capture individuals.

BackgroundAutonomous underwater vehicles (AUVs) and animal telemetry have become important tools for understanding the relationships between aquatic organisms and their environment, but more information is needed to guide the development and use of AUVs as effective animal tracking platforms. A forward-facing acoustic telemetry receiver (VR2Tx 69 kHz; VEMCO, Bedford, Nova Scotia) attached to a novel AUV (gliding robotic fish) was tested in a freshwater lake to (1) compare its detection efficiency (i.e., the probability of detecting an acoustic signal emitted by a tag) of acoustic tags (VEMCO model V8-4H 69 kHz) to stationary receivers and (2) determine if detection efficiency was related to distance between tag and receiver, direction of movement (toward or away from transmitter), depth, or pitch.ResultsDetection efficiency for mobile (robot-mounted) and stationary receivers were similar at ranges less than 300 m, on average across all tests, but detection efficiency for the mobile receiver decreased faster than for stationary receivers at distances greater than 300 m. Detection efficiency was higher when the robot was moving toward the transmitter than when moving away from the transmitter. Detection efficiency decreased with depth (surface to 4 m) when the robot was moving away from the transmitter, but depth had no significant effect on detection efficiency when the robot was moving toward the transmitter. Detection efficiency was higher when the robot was descending (pitched downward) than ascending (pitched upward) when moving toward the transmitter, but pitch had no significant effect when moving away from the transmitter.ConclusionResults suggested that much of the observed variation in detection efficiency is related to shielding of the acoustic signal by the robot body depending on the positions and orientation of the hydrophone relative to the transmitter. Results are expected to inform hardware, software, and operational changes to gliding robotic fish that will improve detection efficiency. Regardless, data on the size and shape of detection efficiency curves for gliding robotic fish will be useful for planning future missions and should be relevant to other AUVs for telemetry. With refinements, gliding robotic fish could be a useful platform for active tracking of acoustic tags in certain environments.

BackgroundCobia (Rachycentron canadum) is a cosmopolitan marine fish that inhabits tropical, sub-tropical, and temperate marine and estuarine waters and supports a major recreational fishery along the U.S. Atlantic and Gulf of Mexico coasts. Recent changes in U.S. cobia management have sparked controversy and highlighted limitations in our understanding of the species’ biology. This study utilized pop-up satellite archival tags (PSATs) to assess the movements, habitat utilization, and post-release survival of cobia that summer in Virginia waters.ResultsPSATs were deployed on 36 cobia caught in Virginia state waters using standard recreational techniques in August 2016 and August–September 2017. All fish larger than 37-in total length were tagged, and several of these were hooked deeply. No mortalities were inferred for the 20 cobia whose PSATs reported and remained attached for at least 10 days. Premature release of tags was an issue, and only five PSATs remained attached for the full 180-day deployment period. Some fish undertook long seasonal movements, with one individual entering Florida waters well beyond the current stock demarcation boundary. Several fish overwintered in waters offshore of North Carolina near the continental shelf break. Cobia demonstrated a strong affinity for waters ≥ 20 °C, even in the coldest months. They displayed distinct seasonal differences in habitat utilization, spending high proportions of their time near the surface during the summer months and extended periods at depths ≥ 20 m in the winter months.ConclusionsCobia are hardy fish with low post-release mortality when handled respectfully. Their migratory patterns are clearly temperature driven, and seasonal changes in habitat utilization means varied vulnerability to fishing gears. Further understanding of cobia migratory patterns, particularly in conjunction with spawning activity, is needed to best manage this species.

BackgroundFixed radio telemetry stations are used to study the movement ecology of fishes in streams and rivers. A common assumption of such studies is that detection efficiency remains constant through space and time. The objective of this study was to understand how site characteristics and tag distance can influence the detection efficiency of a fixed receiver when used for fisheries research in a small stream. Field tests included a fixed receiver station on Forty Mile Creek, in Banff National Park, AB, Canada that recorded signals from radio tags over specified distances (i.e., 0 m, 27 m, 53 m, 80 m) within the expected detection range from July to October, 2016. Model selection was used to test which parameters may influence detection efficiency.ResultsThe fixed receiver was able to record an average of 89% of transmissions over the study period. Detection efficiency was greater or equal to 0.97 at tag distances of ≤ 53 m. Detection efficiency significantly declined by 36% to a rate of 0.62 for tags placed 80 m from the fixed receiver. Water temperature and water depth also reduced detection efficiency, but only at the critical threshold of 80 m from the tag. Interestingly, turbidity had no influence on detection efficiency in this study.ConclusionsThis study provided insights into the reliability of fixed receiver stations as a passive tracking technique in small streams. The abrupt change in detection efficiency observed in this study presumably occurs in other systems. Identifying critical detection distance thresholds would appear to be a useful strategy for avoiding false-negative results. It is recommended that researchers who conduct radio tracking studies with fixed arrays should consider the deployment of sentinel tags over the study to understand the system performance.

BackgroundAcoustic telemetry is an increasingly common method used to address ecological questions about the movement, behaviour, and survival of freshwater and marine organisms. The variable performance of acoustic telemetry equipment and ability of receivers to detect signals from transmitters have been well studied in marine and coral reef environments to inform study design and improve data interpretation. Despite the growing use of acoustic telemetry in large, deep, freshwater systems, detection efficiency and range, particularly in relation to environmental variation, are poorly understood. We used an array of 90 69-kHz acoustic receivers and 8 sentinel range transmitters of varying power output deployed at different depths and locations approximately 100–9500 m apart for 215 days to evaluate how the detection efficiency of acoustic receivers varied spatially and temporally in relation to environmental conditions.ResultsThe maximum distance that tags were detected ranged from 5.9 to 9.3 km. Shallow tags consistently had lower detection efficiency than deep tags of the same power output and detection efficiency declined through the winter months (December–February) of the study. In addition to the distance between tag and receiver, thermocline strength, surface water velocity, ice thickness, water temperature, depth range between tag and receiver, and number of fish detections contributed to explaining variation in detection efficiency throughout the study period. Furthermore, the most significant models incorporated interactions between several environmental variables and tag–receiver distance, demonstrating the complex temporal and spatial relationships that exist in heterogeneous environments.ConclusionsRelying on individual environmental variables in isolation to interpret receiver performance, and thus animal behaviour, may be erroneous when detection efficiency varies across distances, depths, or tag types. As acoustic telemetry becomes more widely used to study ecology and inform management, it is crucial to understand its limitations in heterogeneous environments, such as freshwater lakes, to improve the quality and interpretation of data. We recommend that in situ range testing and retrospective analysis of detection efficiency be incorporated into study design for telemetry projects. Furthermore, we caution against oversimplifying the dynamic relationship between detection efficiency and environmental conditions for the sake of producing a correction that can be applied directly to detection data of tagged animals when the intended correction may not be justified.

BackgroundIn fish tagging studies, tag size limits the size of fish that can be tagged, the fraction of a population that can be represented, and ultimately inferences that can be made about the study population, particularly when juvenile fish are the subject of interest. Introduction of an 8-mm passive integrated transponder (PIT) reduced the minimum taggable size of fish, but it has not been evaluated in field trials. We evaluated the growth and survival of age-0 Oncorhynchus mykiss tagged with 8-mm PIT tags in four streams in southwest Washington, USA.ResultsA total of 351 PIT tagged fish and 340 control fish (marked with pelvic fin clips) were released, but recapture rates were low, particularly for control fish. Growth in length and mass did not differ between small (42–54 mm) and large (55–64 mm) PIT tagged fish. There was a slightly positive, but weak, relation between tag burden and growth in mass; however, there was considerable variability in this relation (R2 = 0.115). Summer to autumn joint probability of fish surviving and remaining in the study area estimated with a Bayesian mark-recapture model ranged from 0.228 to 0.478 in study streams. We found no significant relation between tag burden and survival, suggesting neither tag burden nor fish size at tagging affected survival.ConclusionsAlthough this study was limited in scope, it provided insight into how age-0 O. mykiss tagged with 8-mm PIT tags grew and survived under natural conditions. We showed that fish as small as 42 mm could be tagged without detrimental effects, which should allow researchers to represent a larger portion of study populations through PIT tagging.

The desire of animal behaviorists for more flexible methods of conducting inter-study and inter-specific comparisons and meta-analysis of various animal behaviors compelled us to design an automated, animal behavior peak detection method that is potentially generalizable to a wide variety of data types, animals, and behaviors. We detected the times of feeding attempts by 12 Risso’s dolphins (Grampus griseus) and 36 blue whales (Balaenoptera musculus) using the norm-jerk (rate of change of acceleration) time series. The automated peak detection algorithm identified median true-positive rates of 0.881 for blue whale lunges and 0.410 for Risso’s dolphin prey capture attempts, with median false-positive rates of 0.096 and 0.007 and median miss rates of 0.113 and 0.314, respectively. Our study demonstrates that our peak detection method is efficient at automatically detecting animal behaviors from multisensor tag data with high accuracy for behaviors that are appropriately characterized by the data time series.