Animal Biotelemetry最新文献

Over the last six decades, the biologging research community has reduced instrument effects on study animals by miniaturizing devices, employing sophisticated release mechanisms, and developing other novel technological advancements. However, biologging devices can still impact animal physiology, behavior, and demography-the very biological metrics the instruments are meant to measure. Recent meta-analyses have emphasized the subjectivity of field-wide "rules of thumb" such as the 3% rule, but opportunities to quantify effects more objectively can be expensive or impossible to implement when instrumenting new species. There is therefore a time-sensitive need for systematic reporting of biologging instrument characteristics based on known effects to animal welfare and data quality. We used 202 biologging impact studies from the last thirty years to draw broad, multispecies connections between instrument characteristics and animal physiology, behavior, and/or demography. We build on impact studies that focus on a single species, instrument type, or attachment method to offer solutions applicable across those taxa, technologies, and methodologies. From the literature, we distilled eight best practices for biologging researchers with a particular focus on minimum reporting standards as a low-cost, high-impact way to promote animal welfare and data quality. We propose a preliminary minimum reporting standard, informed by the literature and presented as a machine-readable checklist, that biologging researchers can include with their manuscripts or data submissions to provide data for future meta-analyses. We also present an example of a completed checklist to demonstrate the feasibility of such a standard and a plan for community input and adoption via the International Bio-Logging Society. Robust biologging infrastructure, beginning with a minimum reporting standard informed by the literature on instrument impacts, will facilitate the expansion of biologging across the globe and across disciplines while ensuring animal welfare and improving data quality. As biologging instruments become less expensive and more accessible, researchers, journals, and funders are better positioned than ever to broaden and implement these standards.

Supplementary information: The online version contains supplementary material available at 10.1186/s40317-025-00438-w.

Background: Positional acoustic telemetry permits high-resolution (2D and 3D) tracking of tagged fish based on the speed of sound and time at which acoustic signals are detected at independent receivers. Such positional data has important implications for understanding fish behavior in hydropower tailraces, where movement and fishway passage may be influenced by complex hydraulic conditions. However, environmental features common to these settings-such as rocks, vegetation, bubbles, and suspended particles-can reflect, scatter, or absorb acoustic signals, contributing to spatial and temporal variation in positioning error. Therefore, validating system performance in tailrace environments is important for study design and interpretation. We evaluated the performance of a 76 kHz positional acoustic telemetry system (LOTEK MAP) in the tailrace (0-500 m downstream) of a large (672 MW generating capacity) hydroelectric dam, an environment characterized by reflective surfaces, complex hydraulics, and ambient noise from power generation.

Methods: We quantified positional accuracy (i.e., Euclidean distance from measured deployment positions) and position efficiency (i.e., position estimates/total transmissions) for six stationary transmitters centered within two hydrophone arrays installed 0-150 m and 200-500 m downstream from the power station. Further, we used generalized linear models to explore how accuracy and position efficiency varied as a function of transmitter location, power station discharge (which represented variation in the acoustic environment at each hydrophone), and the number of receivers that contributed to position estimates.

Results: The array nearest the power station (i.e., 0-150 m downstream) yielded no positional data. Performance improved marginally for the second array (i.e., 200-500 m downstream), but position efficiency was ultimately low (1%), variable across transmitter locations, and negatively correlated with discharge. When position estimates were obtained, positional accuracy was moderate (overall mean = 3 ± 3 m) and increased with the number of contributing receivers, but also varied in direction and magnitude as a function of transmitter location and discharge conditions.

Conclusions: Performance of the telemetry system was limited by environmental conditions that influenced signal propagation at complex spatial and temporal scales and would ultimately challenge the interpretation of positional data for free-swimming fish in the tailrace. The telemetry system is likely not suitable for studies that require frequent and reliable positions in hydropower dam tailrace environments.

Supplementary information: The online version contains supplementary material available at 10.1186/s40317-025-00420-6.

Background: Understanding animal behaviour is critical for the design of effective conservation and management strategies. Animal-borne tri-axial accelerometers constitute a type of biologging device which have the potential to provide continuous high-resolution behavioural data. For marine animals, device attachment position may influence both the accuracy of behavioural predictions and the hydrodynamic profile of the animal. We present a case study on the use of accelerometers for the behavioural classification of two sea turtle species in captivity: the loggerhead (Caretta caretta) and green (Chelonia mydas) turtle. Accelerometers were placed on the first and third scute to represent extreme placement scenarios. We trained Random Forest (RF) models to classify behaviour and assessed the impact of placement and sampling frequency on accuracy. In addition, we assessed the impact of device position on carapace drag coefficient using Computational Fluid Dynamics (CFD).

Results: We achieved a high accuracy for behavioural classification (0.86 for loggerhead and 0.83 for green turtles). We determined that overall RF accuracy for both species is significantly higher for devices positioned on the third scute compared to the first scute (P < 0.001) and with a smoothing window of 2 s compared to 1 s (P < 0.001). We found no significant effect of sampling frequency and therefore recommend the use of 2 Hz in future work to optimise battery life and device memory. CFD modelling indicated an increase in drag coefficient from a maximum of 0.028 without a device to a maximum of 0.064 with a device for an isolated turtle carapace. Attachment to the first scute significantly (P < 0.001) increased drag coefficient relative to the third scute.

Conclusions: Moving forward, the attachment and sampling protocols we present here may be adopted in future studies involving captive sea turtles. Further research is needed to assess their applicability and effectiveness under free-ranging conditions to enable their use in wild populations.

Supplementary information: The online version contains supplementary material available at 10.1186/s40317-025-00415-3.

Background: Identifying key areas of animal distribution using individual movement data is fundamental for conservation planning, threat mitigation, and spatial management. Methodologies which define these areas based on measures of high density and abundance may overlook spatial heterogeneity in behaviour-specific distributions. This is particularly relevant for behaviours that occur at lower densities but are associated with increased exposure to specific environmental threats. We used a dataset of 566 GPS tracked individuals and 14 colonies of a vulnerable species of seabird, the black-legged kittiwake (Rissa tridactyla), to compare two methods for delineating key areas. The first method applies kernel density estimates, based on 50% ('core area') utilisation distributions, to all movement data during an at-sea trip. This reflects a widely used density-based approach to identify high-use spatial areas. The second method incorporates hidden Markov modelling to classify movement data into three dominant behaviour states: resting, foraging, and transiting, to identify behaviour-specific high-use areas. We then compare population-level estimates of key areas based on each method using the BirdLife International Key Biodiversity Area framework. We also explore how the selection of an intermediate (70%) and home range (95%) utilisation distribution influences the capture of different behaviours.

Results: We found that individual-level kernel density estimates based on core areas of all movement data fail to adequately capture the core distribution of transiting, a widespread and dispersed behaviour. Moreover, population-level estimates of key areas derived from transiting behaviour are significantly larger than those identified using all tracking data, suggesting that conventional methods likely underestimate exposure to threats encountered during transit. Conversely, key areas for resting and foraging behaviour are more spatially constrained than those derived from all movement data, implying that behaviour-specific analyses may improve the precision of conservation planning. Both individual and population-level key area estimates based on larger utilisation distributions (i.e. 75% and 95%) better capture the distribution of transiting behaviour as these larger distributions probabilistically encompass a greater fraction of observed movement trajectories.

Conclusion: These results highlight the importance of labelling movement data by behavioural state to enhance the utility of GPS data for conservation applications. By incorporating behavioural state differentiation into spatial analyses, threat exposure assessments can be refined to focus conservation resources more effectively. Furthermore, this approach has direct implications for environmental impact assessments, particularly in the context of expanding marine industries such as offshore renewable energy developments.

The study of animal movement provides insights into underlying ecological processes and informs analyses of behaviour and resource use, which have implications for species management and conservation. The tools used to study animal movement have evolved over the past decades, allowing for data collection from a variety of species, including those living in remote environments. Satellite-linked radio and GPS collars have been used to study polar bear (Ursus maritimus) ecology and movements throughout the circumpolar Arctic for over 50 years. However, due to morphology and growth constraints, only adult female polar bears can be reliably collared. Collars have proven to be safe, but there has been opposition to their use, resulting in a deficiency in data across much of the species' range. To bolster knowledge of movement characteristics and behaviours for polar bears other than adult females, while also providing an alternative to collars, we tested the use of fur- and ear-mounted telemetry tags that can be affixed to polar bears of any sex and age. We tested three fur tag designs (SeaTrkr, tribrush and pentagon tags), which we affixed to 15 adult and 1 subadult male polar bears along the coast of Hudson Bay during August-September 2021-2022. Fur tags were compared with ear tags deployed on 42 subadult and adult male polar bears captured on the coast or the sea ice between 2016 and 2022. We used data from the tags to quantify the amount of time subadult and adult males spent resting versus traveling while on land. Our results show the three fur tag designs remained functional for shorter mean durations (SeaTrkr = 58 days; tribrush = 47 days; pentagon = 22 days) than ear tags (121 days), but positional error estimates were comparable among the Argos-equipped tags. The GPS/Iridium-equipped SeaTrkr fur tags provided higher resolution and more frequent location data. Combined, the tags provided sufficient data to model different behavioural states. Furthermore, as hypothesized, subadult and adult male polar bears spent the majority of their time resting while on land, increasing time spent traveling as temperatures cooled. Fur tags show promise as a short-term means of collecting movement data from free-ranging polar bears.

Supplementary information: The online version contains supplementary material available at 10.1186/s40317-024-00373-2.