Animal Movement Studies Research Articles

The role of acoustic telemetry in assessing fish connectivity within marine seascapes: A global review.

The study of aquatic animal movements is a rapidly growing field of research, with tracking methodology ever developing and refining. Acoustic telemetry is arguably the most popular method used to study the movements of fish. Despite this method being able to elucidate many aspects of movement behavior, including residency, home range, and migration, among others, one aspect that remains challenging is the study and definition of connectivity, particularly within marine seascapes. As such, this review assesses published literature on acoustic telemetry studies, which have specifically assessed some aspect of fish connectivity, and discusses these in terms of study distribution and overall trends, the diversity of taxa and life stage assessed, the role that large-scale acoustic telemetry networks plays in assessing connectivity of marine fishes, how connectivity studies have been used in an applied context, and proposes definitions linked to specific types of connectivity, which will assist future researchers when conceptualizing studies. Further, methods that can be used in conjunction with acoustic telemetry to complement the data are discussed. Given that marine resources and habitats are intricately connected, this review highlights the critical role that acoustic telemetry can play in assessing this link. It is envisaged that our developed framework of connectivity definitions will assist future studies and stakeholders in assessing ecosystem functioning and ultimately contribute to improved conservation and management of marine fish populations and ecosystems.

Network theory and migration: Avoiding misapplications and misinterpretations

Network analysis is becoming a popular tool for the study of animal movement. Proliferation of software enables researchers to use network measures without reflecting on the underlying mathematics and biology. One common use characterizing movement networks, such as migration, with centrality measures. Predominantly developed to evaluate social systems, these measures now appear in applications across disciplines that vary greatly in system properties. Each network measure has a very specific mathematical definition, with implicit assumptions about system properties to which they are applied that often make them inappropriate for migration. We report mismatches between mathematical assumptions and applications of network measures to migration, primarily with bird examples. For example, of 11 trajectory-transmission network-flow processes observed in the real world, only two are applicable to bird migration, neither of which allows valid application of classical centrality measures. We also identify misinterpretations of network measures, such as nodes with the highest degree centrality as locations where individuals intermingle. Other misinterpretations include that a high betweenness score translates to a node that is frequently used or is an important site along a main migratory route. Finally, networks are used in different ways, ranging from descriptive visualization to quantitative prediction and we identify common cases, such as migratory connectivity, where this leads to miscommunication. Network-theoretic approaches to answer ecological research and conservation questions associated with migration are numerous, but new measures need to be developed for animal migration. We provide a guide for researchers of animal movement for measure selection, development, and documentation.

Telemetry without collars: performance of fur- and ear-mounted satellite tags for evaluating the movement and behaviour of polar bears

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.

Move2: R package for processing movement data

Abstract Studying animal movement is key to understanding ecological processes and studying the impacts of global change. The pivotal importance of collecting movement data drives technological development, and as a consequence, movement trajectories are gathered at unprecedented rates. For the analysis of the ever‐increasing volume of movement tracks, software packages that bridge between data storage, analysis and visualization are crucial. To facilitate analysis, it is key that the metadata, as well as projections, measurements units, and attributes for the track as a whole and auxiliary sensor measurements, are retained. At the same time, the software needs to be flexible enough to accommodate data from the multitude of different sources and tracking technologies. Here, we present the newly developed R package move2 that facilitates import, manipulation, analysis and visualization of movement tracks. The package enables the usage of new programming techniques developed in recent years and has been developed based on the experiences made in the past decade with the move package. The package is tightly integrated into the Movebank ‘ecosystem’ by being a key data format in MoveApps and providing a direct download option from movebank. However, move2 allows the integration of movement data sources of any provenance, providing a generic entry point for movement data analysis in R.

Tracking 4 years in the life of a female whale shark shows consistent migrations in the Gulf of Mexico and Caribbean

Context Satellite telemetry has revolutionised the study of animal movement, particularly for mobile marine animals, whose movements and habitat make consistent, long-term observation difficult. Aims Summarise the movements of Rio Lady, a mature female whale shark (Rhincodon typus), to characterise these movements, and to predict expected behaviour throughout the Gulf of Mexico (GOM). Methods Rio Lady was tracked using satellite telemetry for over 1600 days, generating over 1400 locations and travelling over 40,000 km. State–space and move persistence modelling enabled characterisation of behaviour, and machine learning (ML) enabled the development of habitat-suitability models to predict habitat utilisation, on the basis of location transmissions and their environmental covariates. Key results Rio Lady exhibited annually consistent patterns of movements among three regions within the GOM. Final ML models produced seasonally dynamic predictions of habitat use throughout the GOM. Conclusions The application of these methods to long-term location data exemplifies how long-term movement patterns and core areas can be discovered and predicted for marine animals. Implications Despite our limited dataset, our integrative approach advances methods to summarise and predict behaviour of mobile species and improve understanding of their ecology.

Evaluating habitat-specific interference in automated radio telemetry systems: implications for animal movement studies

Automated radio telemetry systems have become a popular and invaluable tool in tracking the activity and movement of wild animals. However, many environmental conditions can hinder accuracy when tracking with this technology. For instance, study sites may contain multiple habitat types, each habitat uniquely affecting the signal strength received from tagged species. To investigate the influence of a structurally diverse study site on an automated radio telemetry system, we conducted this project at a restored and managed pine barren habitat that consisted of a mix of mature pitch pine, treated pitch pine, scrub oak, and hardwood forests. This site, Montague Plains Wildlife Management Area, Montague, Massachusetts, is also a known breeding ground for Eastern whip-poor-will (Antrostomus vociferus). To measure the relationship of radio signal strength with distance across each habitat, we used radio telemetry equipment manufactured by Cellular Tracking Technologies. We produced negative exponential decay functions measuring radio signal strength over distance and tested for differences among habitat types on radio signal strength (RSS). We found that decay function parameters significantly differed by habitat type, prompting us to investigate if accounting for these differences improved location estimate accuracy. To test this, we estimated known locations using trilateration methods with and without habitat calibration. Comparing these tests indicates that habitat-specific adjustments significantly improved location accuracy. Lastly, we visualized estimated RSS-based locations of 1 week of whip-poor-will data and compared them to GPS data generated from the same individual. Previous studies have accounted for types of environmental interference (like elevation) in the field but have avoided incorporating habitat-specific factors by working with node networks covering a relatively small area, but in this study, we examined the potential to scale up for larger areas and in more complex habitats.

Social interactions and habitat structure in understanding the dynamic space use of invasive wild pigs

Untangling the abiotic and biotic feedback mechanisms driving animal movements and ranges is a core question in ecology, yet progress is hampered by inadequate modelling procedures. Here we show how a recently developed process‐based modelling approach, combining step‐selection functions and individual‐based models, enables a flexible method to infer movement drivers and multi‐scale emergent space use patterns. As a case study, we examine the movement behaviours of a highly invasive social generalist (wild pigs, Sus scrofa) in relation to conspecific space use and multiple land cover types in a complex agricultural landscape, showing that social interactions are predominantly more important to this species than selection for land cover. Thus, animal movement studies should not neglect the effects of sociality when inferring resource driven movements and, crucially, use multi‐scale techniques that incorporate movement processes to untangle drivers of animal space use.

Performance of five statistical methods to infer interactions among moving individuals in a predator–prey system

Abstract Rapid development of tracking technologies allow the collection of high‐quality data on multiple simultaneously moving individuals. This, in turn, initiated the development of several methods to infer interactions among moving animals. However, the performance of these methods has not been studied systematically, especially with regard to the factors that are highly relevant for field ecologists, such as duration of the tracking period, its temporal resolution and the proportion of the tracked community. Here, we assessed the performance of three dynamic interaction indices (Coefficient of sociality, Correlation coefficient and Dynamic interaction) and two novel approaches based on step selection functions (SSF‐occurrence‐distribution and SSF‐distance). We tested these methods on the data simulated with a predator–prey system, reflecting three common types of interactions while on the move: avoidance (prey individuals fleeing from the predator), attraction (predator following and chasing prey) and neutral movement (no interactions between predator and prey). We assessed the ability of each method to correctly detect the modelled interaction type by manipulating the perceptual range of the predator, the proportion of tracked prey individuals, the temporal resolution and the duration of the tracking period. We found that the ability to correctly infer interactions increased for all methods with an increase in the perceptual range of the predator and the proportion of tracked prey individuals. In contrast, the duration of the tracking period affected the methods' performance differently: some methods (Cs and SSF‐distance) were insensitive to it, whereas the performance of other methods improved (DI and SSF‐occurrence‐distribution) and worsened (Cr) with the duration of the tracking period. The three dynamic interaction indices and SSF‐distance were rather robust to changes in data resolution. Despite using the predator–prey system as our study case, our findings are applicable to other systems in which two animals on move may interact. We formulate guidelines for field ecologists studying animal movement to select the most suitable method depending on the availability of tracking devices, the duration and resolution of the tracking they can afford, as well as perceptual ranges of study species.

Simultaneous estimation of the temporal and spatial extent of animal migration using step lengths and turning angles

BackgroundAnimals of many different species, trophic levels, and life history strategies migrate, and the improvement of animal tracking technology allows ecologists to collect increasing amounts of detailed data on these movements. Understanding when animals migrate is important for managing their populations, but is still difficult despite modelling advancements.MethodsWe designed a model that parametrically estimates the timing of migration from animal tracking data. Our model identifies the beginning and end of migratory movements as signaled by change-points in step length and turning angle distributions. To this end, we can also use the model to estimate how an animal’s movement changes when it begins migrating. In addition to a thorough simulation analysis, we tested our model on three datasets: migratory ferruginous hawks (Buteo regalis) in the Great Plains, barren-ground caribou (Rangifer tarandus groenlandicus) in northern Canada, and non-migratory brown bears (Ursus arctos) from the Canadian Arctic.ResultsOur simulation analysis suggests that our model is most useful for datasets where an increase in movement speed or directional autocorrelation is clearly detectable. We estimated the beginning and end of migration in caribou and hawks to the nearest day, while confirming a lack of migratory behaviour in the brown bears. In addition to estimating when caribou and ferruginous hawks migrated, our model also identified differences in how they migrated; ferruginous hawks achieved efficient migrations by drastically increasing their movement rates while caribou migration was achieved through significant increases in directional persistence.ConclusionsOur approach is applicable to many animal movement studies and includes parameters that can facilitate comparison between different species or datasets. We hope that rigorous assessment of migration metrics will aid understanding of both how and why animals move.

Movement dynamics, sediment turnover and sheltering behaviours of the nocturnal coral reef sea cucumber, Stichopus cf. monotuberculatus

Animal movement and feeding studies shed light on ecological roles and can inform management strategies for fished species. However, the feeding and movement of nocturnal sea cucumbers have been rarely studied. We determined the movement dynamics, feeding ecology and sheltering behaviour of the nocturnal Stichopus cf. monotuberculatus (dragonfish) at One Tree Reef and Heron Island Reef on the southern Great Barrier Reef. The short-term movement of individual sea cucumbers were tracked, and sediment defecation rates were measured. Displacement rates averaged 3–33 cm h−1 across the four sites, with the sea cucumbers moving more slowly approaching sunrise and within patches of organically rich sediment. The movement paths were moderately tortuous, with larger sea cucumbers moving along straighter paths. Rates of sediment turnover averaged 7.8 g h−1 and were greatest for larger individuals. The faecal casts were organically richer and composed of finer grains than the ambient surface sediments, implying that S. cf. monotuberculatus avoids consuming coarse sediments and feeds on nutritionally rich particles. The sea cucumbers sheltered under hard reef substrata and moved non-directionally on the seascape, with a few individuals homing back to their original refuges. The affinity to reef substrata and short nightly net displacements of S. cf. monotuberculatus have implications for the spatial management of this and other similar species. Larger individuals occupied deeper refuges, implying that projected declines in substratum rugosity on coral reefs due to climate change could impact the size structure of sea cucumber populations, with implications for fisheries.

Movedesign: Shiny R app to evaluate sampling design for animal movement studies

Abstract Projects focused on movement behaviour and home range are commonplace, but beyond a focus on choosing appropriate research questions, there are no clear guidelines for such studies. Without these guidelines, designing an animal tracking study to produce reliable estimates of space‐use and movement properties (necessary to answer basic movement ecology questions), is often done in an ad hoc manner. We developed ‘movedesign’, a user‐friendly Shiny application, which can be utilized to investigate the precision of three estimates regularly reported in movement and spatial ecology studies: home range area, speed and distance travelled. Conceptually similar to statistical power analysis, this application enables users to assess the degree of estimate precision that may be achieved with a given sampling design; that is, the choices regarding data resolution (sampling interval) and battery life (sampling duration). Leveraging the ‘ctmm’ R package, we utilize two methods proven to handle many common biases in animal movement datasets: autocorrelated kernel density estimators (AKDEs) and continuous‐time speed and distance (CTSD) estimators. Longer sampling durations are required to reliably estimate home range areas via the detection of a sufficient number of home range crossings. In contrast, speed and distance estimation requires a sampling interval short enough to ensure that a statistically significant signature of the animal's velocity remains in the data. This application addresses key challenges faced by researchers when designing tracking studies, including the trade‐off between long battery life and high resolution of GPS locations collected by the devices, which may result in a compromise between reliably estimating home range or speed and distance. ‘movedesign’ has broad applications for researchers and decision‐makers, supporting them to focus efforts and resources in achieving the optimal sampling design strategy for their research questions, prioritizing the correct deployment decisions for insightful and reliable outputs, while understanding the trade‐off associated with these choices.

Intermittent rivers and ephemeral streams are pivotal corridors for aquatic and terrestrial animals

Abstract Rivers are efficient corridors for aquatic animals, primarily under the assumption of perennial flow. However, the recognition that river drying is a common and widespread phenomenon requires reexamining animal movement through river networks. Intermittent rivers and ephemeral streams have been overlooked when studying animal movement, even though approximately 60% of the global river network dries. In the present article, we extend the current focus of river ecology by integrating the effects of drying on the movement of aquatic and terrestrial animals. Moreover, we introduce a conceptual model that challenges the current bias, which is focused on perennial waterways, by encompassing animal movement across hydrologic phases (nonflowing, flowing, dry, rewetting) and habitats (aquatic, terrestrial). We discuss their corridor function in conservation and restoration planning and identify emerging research questions. We contend that a more comprehensive and inclusive view of animal movement in dry channels will advance ecological understanding of river networks and respective conservation efforts.

Comparison between strip sampling and laser ablation methods to infer seasonal movements from intra-tooth strontium isotopes profiles in migratory caribou

Strontium isotopes analysis is a powerful tool in the study of past animal movements, notably the sequential analysis of tooth enamel to reconstruct individual movements in a time-series. Compared to traditional solution analysis, high resolution sampling using laser-ablation multi-collector inductively coupled plasma mass spectrometry (LA-MC-ICP-MS) has the potential to reflect fine scale mobility. However, the averaging of the 87Sr/86Sr intake during the enamel mineralization process may limit fine scale inferences. We compared solution and LA-MC-ICP-MS 87Sr/86Sr intra-tooth profiles from the second and third molars of 5 caribou from the Western Arctic herd, Alaska. Profiles from both methods showed similar trends, reflecting the seasonal migratory movements, but LA-MC-ICP-MS profiles showed a less damped 87Sr/86Sr signal than solution profiles. Geographic assignments of the profile endmembers to the known summer and winter ranges were consistent between methods and with the expected timing of enamel formation but showed discrepancy at a finer scale. Variations on LA-MC-ICP-MS profiles, consistent with expected seasonal movements, suggested more than an admixture of the endmember values. However, more work in understanding enamel formation in Rangifer, and other ungulates, and how 87Sr/86Sr daily intake translates into enamel are needed to assess the real resolution that can be achieved with LA-MC-ICP-MS.

Distributing transmitters to maximize population-level representativeness in automated radio telemetry studies of animal movement

Telemetry is a powerful and indispensable tool for evaluating wildlife movement and distribution patterns, particularly in systems where opportunities for direct observation are limited. However, the effort and expense required to track individuals often results in small sample sizes, which can lead to biased results if the sample of tracked individuals does not fully capture spatial, temporal, and individual variability within the target population. To better understand the influence of sampling design on results of automated radio telemetry studies, we conducted a retrospective power analysis of very high frequency (VHF) radio telemetry data from the Motus Wildlife Tracking System for two species of birds along the United States Atlantic coast: a shorebird, the piping plover (Charadrius melodus), and a nearshore seabird, the common tern (Sterna hirundo). We found that ~ 100–150 tracked individuals were required to identify 90% of locations known to be used by the tracked population, with 40–50 additional individuals required to include 95% of used locations. For any number of individuals, the percentage of stations included in the sample was higher for common terns than for piping plovers when tags were deployed within a single site and year. Percentages of stations included increased for piping plovers when birds were tagged over multiple sites and, to a lesser extent, years, and increased with average length of the tracking period. The probability that any given receiver station used by the population would be included in a subsample increased with the number of birds tracked, station proximity to a migratory stopover or staging site, number of receiving antennas per station, and percentage of the tracked population present. Our results provide general guidance for the number and distribution of tagged birds required to obtain representative VHF telemetry data, while also highlighting the importance of accounting for station network configuration and species-specific differences in behavior when designing automated radio telemetry studies to address specific research questions. Our results have broad applications to remotely track movements of small-bodied migratory wildlife in inaccessible habitats, including predicting and monitoring effects of offshore wind energy development.

HaniMob 2022 Workshop Report: The 2nd ACM SIGSPATIAL Workshop on Animal Movement Ecology and Human Mobility

The study of animal and human movement has experienced a remarkable boom over the last decades, mainly due to the continuous development of location-aware sensors (e.g. bio-logging devices for animals; GPS trackers for humans) capable of capturing individual locations at a constantly increasing spatio-temporal resolution [7, 2]. Anthropogenic pressure plays a critical role in shaping animal movement and behavior. Similarly, human movement behavior can largely be influenced by disruptive environmental events causing people to shift their mobility patterns, which eventually may impact wildlife activity patterns in areas where wildlife intersects with human presence.

AbmR: An R package for agent‐based model analysis of large‐scale movements across taxa

Abstract Agent‐based modelling (ABM) shows promise for animal movement studies. However, a robust, open‐source and spatially explicit ABM coding platform is currently lacking. We present abmR, an R package for conducting continental‐scale ABM simulations across animal taxa. The package features two movement functions, each of which relies on the Ornstein–Uhlenbeck (OU) process. The theoretical background for abmR is discussed and the main functionalities are illustrated using example populations. Potential future additions to this open‐source package may include the ability to specify multiple environmental variables or to model interactions between agents. Additionally, updates may offer opportunities for disease ecology and integration with other R movement modelling packages.

The role of context in elucidating drivers of animal movement.

Despite its consequences for ecological processes and population dynamics, intra‐specific variability is frequently overlooked in animal movement studies. Consequently, the necessary resolution to reveal drivers of individual movement decisions is often lost as animal movement data are aggregated to infer average or population patterns. Thus, an empirical understanding of why a given movement pattern occurs remains patchy for many taxa, especially in marine systems. Nonetheless, movement is often rationalized as being driven by basic life history requirements, such as acquiring energy (feeding), reproduction, predator‐avoidance, and remaining in suitable environmental conditions. However, these life history requirements are central to every individual within a species and thus do not sufficiently account for the high intra‐specific variability in movement behavior and hence fail to fully explain the occurrence of multiple movement strategies within a species. Animal movement appears highly context dependent as, for example, within the same location, the behavior of both resident and migratory individuals is driven by life history requirements, such as feeding or reproduction, however different movement strategies are utilized to fulfill them. A systematic taxa‐wide approach that, instead of averaging population patterns, incorporates and utilizes intra‐specific variability to enable predictions as to which movement patterns can be expected under a certain context, is needed. Here, we use intra‐specific variability in elasmobranchs as a case study to introduce a stepwise approach for studying animal movement drivers that is based on a context‐dependence framework. We examine relevant literature to illustrate how this context‐focused approach can aid in reliably identifying drivers of a specific movement pattern. Ultimately, incorporating behavioral variability in the study of movement drivers can assist in making predictions about behavioral responses to environmental change, overcoming tagging biases, and establishing more efficient conservation measures.

Beyond inappropriate fire regimes: A synthesis of fire‐driven declines of threatened mammals in Australia

AbstractFire can promote biodiversity, but changing patterns of fire threaten species worldwide. While scientific literature often describes ‘‘inappropriate fire regimes’’ as a significant threat to biodiversity, less attention has been paid to the characteristics that make a fire regime inappropriate. We go beyond this generic description and synthesize how inappropriate fire regimes contribute to declines of animal populations using threatened mammals as a case study. We developed a demographic framework for classifying mechanisms by which fire regimes cause population decline and applied the framework in a systematic review to identify fire characteristics and interacting threats associated with population declines in Australian threatened land mammals (n = 99). Inappropriate fire regimes threaten 88% of Australian threatened land mammals. Our review indicates that intense, large, and frequent fires are the primary cause of fire‐related population declines, particularly through their influence on survival rates. However, several species are threatened by a lack of fire, and there is considerable uncertainty in the evidence base for fire‐related declines. Climate change and predation are documented or predicted to interact with fire to exacerbate mammalian declines. This demographic framework will help target conservation actions globally and will be enhanced by empirical studies of animal survival, movement, and reproduction.

Data-driven agent-based model building for animal movement through Exploratory Data Analysis

Fields studying animal movement are data-starved due to large monetary and time costs of data collection, and, moreover, not all quantities of interest can be measured. Despite limited data, diverse models have been developed to study animal movement. Many of these models are based on random walks that use Gaussian noise. Examinations of real movement data show that the assumptions made in these models are not always valid on all spatial and time scales, and these shortcomings suggest that new models may be needed. We provide methods for developing and training more realistic models, specifically agent-based models of animal movement, by taking a data-driven approach. We took an exploratory data analysis (EDA) approach that allowed us to develop a model that best reproduced the movement patterns we observed in a real dataset of animal locations. In our EDA, we examined distributions of positions, calculated the autocorrelation of the movement data, used Fourier analysis, calculated mean-squared displacements, and tested for correlations. We introduce the fused-lasso regression-analysis method for identifying large and sudden changes in position through a non-parametric fit that is sensitive to discontinuities. We introduce the copula and kernel-density estimates as methods for approximating coordinate-system-independent movement correlations from the marginal location differences represented in our data set; use of the copula allows us to create correlated, non-Gaussian noise. With the insights gained from our EDA, we created a Langevin model that describes the movements of an individual animal, features non-Gaussian noise and incorporates multiple movement patterns. We extended this model to an agent-based model that describes the movements of several groups of deer. We compared our Langevin model to three models built on different assumptions that result in substantial differences in the area covered by an animal. Using our agent-based model, we simulated three groups of deer with parameters sampled from our data to illustrate the amount of area covered by deer in our model and the ability of groups to overlap in space. This overlapping behavior is an important feature of models of processes driven by interactions between animals, such as infectious diseases; our model could be useful for studying the spread of infectious diseases in animal populations, such as chronic wasting disease. While we have applied our data-driven methods to animal movement, these methods are widely applicable to developing and training models using a wide range of data sources.

Behavioural Responses of a Large, Benthic Elasmobranch to Catch-and-Release Angling

Catch-and-release angling is widespread, but the impacts of this practice for captured individuals are understudied, especially among elasmobranchs. Studies on sub-lethal behavioural impacts are particularly sparse, despite their importance for the interpretation of biologging data and for assessments of species’ tolerance to capture. In this study, the behavioural responses of flapper skate (Dipturus intermedius) to catch-and-release angling were described for the first time, using archival observations (depth and temperature) for 21 tag deployment/retrieval events and five recreational angling events that occurred during tagged individuals’ time at liberty from charter vessels off the west coast of Scotland in 2016–17. During capture (8–50 minutes), the changes in depth and temperature experienced by individuals typically exceeded natural variability. Post-release, behavioural change was apparent from visual inspection, regression and functional data analysis of the time series. Immediately following release, movements into deeper water and short periods of low vertical activity (usually 1–2 hours in duration) were common. However, overall average vertical activity was typically around 38% higher in the 12 hours following release than in undisturbed activity. A small number of individuals (n = 3, 14%) exhibited irregular post-release behaviour in the form of rapid, transient re-ascents towards the surface following release. Collectively, the evidence for limited, short-term behavioural changes suggests that flapper skate behaviour is relatively resilient to catch-and-release angling from charter vessels, but irregular post-release behaviour in 14% of individuals is sufficiently notable to indicate that further research is required on the impacts of this practice. This study clearly demonstrates the value of biologging data and behavioural analyses for examining the impacts of disturbance and separating ‘disturbed’ and ‘undisturbed’ behaviours in studies of animal movement.