Biologging devices have revolutionised our understanding of aquatic animal movement by enabling the collection of detailed depth and temperature time-series. The advent of pop-up satellite archival tags has been particularly impactful, facilitating the collection of tens of thousands of depth time-series (DTS) datasets, with deployment periods ranging from days to years. Datasets from recovered tags are more detailed than those transmitted via satellite, yet both are commonly reported with rudimentary histograms of time-at-temperature and time-at-depth. Such histograms often fail to capture the complex temporal dynamics of vertical movements that are available from the high sampling frequency time-series in recovered tags. This study describes a robust and effective methodological workflow for the quantitative analysis of large DTS datasets collected from archival tags deployed on gill-breathing aquatic animals, utilising continuous wavelet transformation (CWT), Principal Component Analysis (PCA), and k-means clustering. CWT was employed to detect key periodic patterns within the data. Daily wavelet components were calculated across different wavelet periods (e.g., 5-min through 24-h) and reduced via PCA to characterise daily vertical movement behaviour while preserving variance. Finally, unsupervised k-means clustering was used to classify vertical movement behaviours according to their wavelet components and depth summary statistics. This approach efficiently processed large quantities of data, and validation using simulated data demonstrated its robustness and versatility, with assigned behaviour clusters matching the original simulated behaviour types with high consistency (97.7%). For the empirical data, distinct behavioural clusters were identified across a wide range of species, including an oceanic manta ray Mobula birostris, whale shark Rhincodon typus, Atlantic cod Gadus morhua, and largetooth sawfish Pristis pristis. Down sampling of the DTS revealed the workflow to be somewhat insensitive to the sampling frequency of tags, maintaining 83.9% consistency as sampling frequency decreased from one to 15-minutes. These results not only underscore the workflow’s efficacy but also highlight its broad applicability in diverse settings. To facilitate uptake of this approach, an R package FishDiveR, tailored for the implementation of this analytical methodological workflow has been developed.

Abstract The use of animal-borne devices to measure acceleration has yielded insights into animal locomotion, behaviour and energy expenditure. We present the first systematic review of accelerometry on animals, spanning 60 years, across ecology, biomechanics, agriculture, neurosciences, medical and veterinary sciences from over 400 species and 1520 studies. Most work to date is on terrestrial mammals, particularly domesticated species, while aerial and aquatic animals are relatively under-represented owing to device size and attachment constraints, and just one study has been conducted on amphibians. Despite this, accelerometry research has expanded globally across nearly 100 countries, across all groups of animals including birds, fish, invertebrates, mammals, and reptiles, and across wild and captive animals, including domesticated and non-domesticated species. A variety of software has been used, with open-source software and, more recently, machine learning tools being employed. On-board processing of accelerometry data, including real-time behavioural classification with deep learning to improve accuracy, can reduce power consumption and memory use several-fold, increasing deployment duration. Transfer of device types, sensors and analytical routines between fields in accelerometry offers considerable opportunities for advancing the field. For example, precision livestock farming uses real-time welfare monitoring, which could be adapted for aquaculture or even wild animal monitoring in areas with good data connectivity, while medical sector health monitoring could be used for wild animal disease tracking. The rapid growth in accelerometry requires urgent collaborative approaches to address big data challenges. This includes establishing standardised data repositories, developing open-electronics for low-cost device development and bespoke sensors, fostering capacity building and technical collaboration for device and algorithm advancements. This review also highlights geographic inequities in research accessibility and authorship, with less than 6% of accelerometry studies originating from authors from Africa, South America and Asia (excluding Japan, which contributed the second most studies globally) combined. The field must prioritise translational and inclusive research practices and cross-disciplinary collaboration to maximise scientific value and foster innovation while maximising animal welfare.

This study investigates the age-based life-history traits of two groundfish species, the spotted moray eel (Gymnothorax moringa) and squirrelfish (Holocentrus adscensionis), found in Ascension Island and St Helena. Both islands are part of the UK Overseas Territories (UKOTs) and are known for their fish biodiversity. The research aims to provide essential life-history information to support sustainable management of these species within the Marine Protected Areas (MPAs) of Ascension Island and St Helena. A total of 556 fish samples were collected between 2014 and 2021, with 279 individuals of G. moringa and 277 individuals of H. adscensionis. We found significant differences in life span, adult body size, and growth rates between the two islands for both species. G. moringa exhibited longer life spans (32 vs 29 years) and faster growth rates at Ascension Island compared to St Helena, while H. adscensionis showed larger adult sizes at Ascension Island but shorter life spans (21 vs 27 years) compared to St Helena. The study highlights the importance of developing locality-specific species life history data collections to monitor population dynamics in MPA areas. This biological information is essential to allow future assessment programs on the potential impacts of climate change and inshore human activities, including the impacts of inshore fisheries. Future research should focus on reproductive biology, size and age at maturity, and migration patterns to enhance the accuracy of sustainability assessments for these fisheries.

Research on the direct effects of capture and tagging on post-release behaviour is typically limited to short-term deployments. To investigate the initial and longer-term behavioural responses to capture and tagging, we deployed eight Cefas G7 tags (1Hz depth and temperature, and 20 Hz triaxial acceleration) for 21–94 hours and 12 Wildlife Computers MiniPATs (depth, temperature, light and triaxial acceleration, each at 0.2 Hz) for 110–366 days on Atlantic bluefin tuna (ABT) in the English Channel. Post-release, ABT exhibited a strong, highly active initial swimming response, consistent with patterns reported in previous bluefin tuna, billfish and elasmobranch tracking studies. Accelerometry tags revealed that activity (VeDBA g), tailbeat amplitude (g) and dominant stroke frequency (Hz) were greater (2.4, 3.2 and 1.4 times respectively) within the first hour post-release than the subsequent 24 hours, stabilising at lower levels within 5–9 hours. However, lower resolution accelerometry data (0.2 Hz), obtained from longer periods from MiniPATs, revealed that fish then maintained this reduced activity for 11 ± 7.9 days (mean ± 1 SD; range: 2–26 days), during which they displayed disrupted diel patterns of activity and allocated on average 5 minutes of each day to burst energy events, compared to 14 minutes (max 74 minutes) during “recovered” periods. Subsequently, their activity levels increased again and were characterised by higher magnitude acceleration events (which may constitute feeding events) and became more active during the day than at night. Year-long deployments revealed that consistent diel vertical migration, diurnal patterns of activity, and increased time allocation to fast starts are normal for ABT off the British Isles in summer months, and their absence at the start of data collection may be related to the effect of capture and tagging, which may be longer lasting, and more complex than previously appreciated.

The movement ecology of European seabass, Dicentrarchus labrax, remains poorly understood, especially in the northern ranges of its distribution. To investigate migration patterns of seabass from the southern North Sea, we combined data from different projects from four countries using various tagging techniques. This resulted in 146 recaptures (out of 5598 externally marked seabass), 138 detected animals (out of 162 seabass fitted with an acoustic transmitter) and 76 archived depth and temperature series (out of 323 seabass with an archival tag). Using geolocation modelling, we distinguished different migration strategies, whereby individual fish migrated to the eastern English Channel (15.1%), the western English Channel (28.3%), the Celtic Sea and the norther part of the Bay of Biscay (17.0%), or stayed in the North Sea (39.6%). A high number of seabass exhibited fidelity to the North Sea (90.5% of recaptures, 55.3% for acoustic transmitters and 44.7% of archival tags). Although seabass are generally considered to migrate southwards in winter, a large number of individuals (n = 62) were observed in the southern North Sea, where spawning might potentially occur in a particular deep location along the coast of Norfolk in the UK. Our results highlight the need to consider fine-scaled population structuring in fisheries assessment, and indicate that current seasonal fisheries closures are not aligned with the ecology of seabass in the North Sea.

Biologging has been used on a range of wild animals to document spectacular feats of migration and behaviour. We describe the pursuit, capture, and ingestion of an adult Atlantic bluefin tuna (Thunnus thynnus) (175 cm, estimated weight: 81 kg), which was instrumented with a biologging tag, by a predator, most likely an orca (Orcinus orca). The predation event lasted over 19 min, with the tuna exhibiting elevated activity (max acceleration 3.12 g) and a rapid ascent from 126 m at 3.6 m.s- 1 followed by death and handling at the surface. Orca were separately recorded using video tags, capturing and handling tuna cooperatively in a manner consistent with the tuna data. We then present the longest orca accelerometry dataset from the ingested MiniPAT tag, with diel patterns of activity and 77 feeding events. These unique datasets provide insight into the energetic dynamics of two of the ocean's fastest predators.

Abstract The movements and behaviour of mature European sea bass (Dicentrarchus labrax L.) in UK waters have not been studied extensively since a series of mark-recapture experiments during the 1970s, 80s and 90s. To better understand the timing and extent of seasonal migrations, 171 mature sea bass > 42 cm were internally tagged with floated electronic tags programmed to record temperature and depth, and released in the English Channel, in the southern North Sea and in the Irish Sea. Among the 48 tags returned to date, sea bass were at liberty for 370 ± 337 days and were recovered 172 ± 200 km from their respective release locations. Most tags were recovered from beaches (54%), or via the fishery (44%). A comparison of the reconstructed tracks from returned electronic tags with the recapture locations of 237 mark-recapture returns (6.5%) from 3615 sea bass released between 1970 and 2020 showed strong overlap. Seasonal movements between shallow areas (Q2–Q3) and deeper spawning areas (Q4–Q1) were accompanied by elevated vertical swimming speeds and average water temperatures of 8.5 °C in the English Channel and Irish Sea, but lower temperatures in the North Sea. Movements between the Celtic Sea/Irish Sea and the North Sea and vice versa demonstrate high levels of connectivity in UK waters. We demonstrate that a proportion of sea bass remained resident within the North Sea throughout the year, with a strong suggestion that spawning might be occurring. These data have significant implications for the future sustainable management of sea bass stocks in UK and surrounding waters.

The size, type and abundance of planktonic organisms influence the efficiency with which carbon is transferred through the lower trophic levels, ultimately affecting dynamics at the higher trophic levels of the marine food web. In temperate shelf sea, such as the waters south-west of the UK, the plankton growing season span from early spring to autumn. While the plankton spring bloom has been extensively studied, the end of the growing season in September-October has received less attention, despite its potential importance for autumn-spawning fish and their larval stage survival. In this study we investigated the variability of the structure and carbon content of the planktonic communities in the waters south-west of the UK in October 2013 and 2014, discussing potential implications of these changes to small pelagic fish and higher trophic levels. Microphytoplankton (20-200 mu m) dominated the plankton community in terms of carbon in 2013, while nanophytoplankton (<20 mu m) in 2014. Ciliates, Copepoda, Decapoda and Cnidaria represented the highest proportion of carbon in the zooplankton component in both years, although ciliates and Copepoda biomass was higher in 2014. Environmental conditions were linked to these changes and were significant in describing the carbon content of the plankton groups. In particular, silicate concentration appeared to be a key variable, affecting diatom/plankton dynamics at the end of the growing season. Other important environmental variables associated with the structure of plankton groups were salinity, sea surface temperature, chlorophyll-a, difference between sea surface temperature and bottom temperature, phosphate and nitrogen concentrations. Although the composition and carbon distribution of the plankton community were different in the two years, cluster and Random Forest analyses showed similarities in the clusters of stations identified, defining an area of higher plankton carbon along the south coast of Cornwall, and an area of lower carbon in the Bristol Channel in both years. Presence of suitable prey for planktivorous small pelagic fish (e.g. Paracalanus and Pseudocalanus), particularly in 2014, provided supporting evidence of the importance of this sea area as a foraging and nursery ground for sardines and other small pelagic fish, as well as for their predators.

Knowledge of the three-dimensional movement patterns of elasmobranchs is vital to understand their ecological roles and exposure to anthropogenic pressures. To date, comparative studies among species at global scales have mostly focused on horizontal movements. Our study addresses the knowledge gap of vertical movements by compiling the first global synthesis of vertical habitat use by elasmobranchs from data obtained by deployment of 989 biotelemetry tags on 38 elasmobranch species. Elasmobranchs displayed high intra- and interspecific variability in vertical movement patterns. Substantial vertical overlap was observed for many epipelagic elasmobranchs, indicating an increased likelihood to display spatial overlap, biologically interact, and share similar risk to anthropogenic threats that vary on a vertical gradient. We highlight the critical next steps toward incorporating vertical movement into global management and monitoring strategies for elasmobranchs, emphasizing the need to address geographic and taxonomic biases in deployments and to concurrently consider both horizontal and vertical movements.

Determining the mechanisms driving range-wide reductions in Atlantic salmon marine survival is hindered by an insufficient understanding of their oceanic ecology and distribution. We attached 204 pop-up satellite archival tags to post-spawned salmon when they migrated to the ocean from seven European areas and maiden North American salmon captured at sea at West Greenland. Individuals migrated further north and east than previously reported and displayed increased diving activity near oceanographic fronts, emphasizing the importance of these regions as feeding areas. The oceanic distribution differed among individuals and populations, but overlapped more between geographically proximate than distant populations. Dissimilarities in distribution likely contribute to variation in growth and survival within and among populations due to spatio-temporal differences in environmental conditions. Climate-induced changes in oceanographic conditions will alter the location of frontal areas and may have stock-specific effects on Atlantic salmon population dynamics, likely having the largest impacts on southern populations.

The yellowfin tuna ( Thunnus albacares: YFT) is a widely distributed, migratory species that supports valuable commercial fisheries. Landings of YFT are seasonally and spatially variable, reflecting changes in their availability and accessibility to different fleets and metiers which, in turn, has implications for sustainable management. Understanding the dynamics of YFT behaviour and how it is affected by biological and ecological factors is therefore of consequence to fisheries management design. Archival and pop-up satellite tags (PSAT) were used in the South Atlantic Ocean around St Helena between 2015 and 2020 to collect information on the movements, foraging and locomotory behaviour of YFT. The study aimed to (1) identify vertical behaviour of YFT within St Helena’s EEZ; (2) assess the timing and depth of potential feeding events and (3) to use the information to inform on the catchability of YFT to the local pole and line fishing fleet. Results indicate that the YFT daytime behaviour shifted between shallow with high incidence of fast starts in surface waters in summer months (December to April), to deep with high incidence of strikes at depth in colder months (May to November). Catchability of YFT was significantly reduced between May and November as YFT spent more time at depths below 100 m during the day, which coincides with a reduction in the quantity of YFT caught by the inshore fleet.

The yellowfin tuna (Thunnus albacares) is a widely distributed, migratory species that supports valuable commercial fisheries throughout their range. Management of migratory species requires knowledge of movement, mixing and key life history parameters such as growth rate, natural and fisheries mortality. Current management is based on the assumptions that the species is highly migratory and populations are well mixed, but these assumptions have been questioned by recent studies. Since November 2015, yellowfin tuna have been tagged with conventional, archival and pop-up satellite tags (PSAT) in the South Atlantic Ocean around St Helena, with the goal of better understanding their movement patterns and ecology in this region. Conventional tags were attached to 4049 yellowfin tuna (size range 24-158 cm fork length, FL), PSAT tags were deployed on 15 yellowfin in inshore St Helena waters (size range 95-138 cm FL) and 7 yellowfin (size range 125-140 cm FL) at Cardno Seamount, and archival tags were deployed on 48 yellowfin tuna in inshore St Helena waters (size range 69-111 cm FL). Most yellowfin tuna remained within 70 km of their release location, suggesting a degree of retention to the region. Although displacement of yellowfin was generally low, the furthest distance travelled between release and recapture location was 2755 km, with other tuna also displaying large-scale movements. Tagging revealed connections between inshore regions and seamounts, as well as links between St Helena waters and key fishing regions and putative spawning grounds in the Gulf of Guinea.

Yellowfin tuna are the mainstay of the traditional tuna fisheries in St Helena waters, but there is limited knowledge of their ecology and feeding behaviour in the area. In this study yellowfin tuna stomach contents were used to assess spatio-temporal changes in feeding strategy and consider the role of tuna in the local ecosystem. Comparisons of the feeding spectra of yellowfin tuna between inshore regions of St Helena and oceanic seamounts demonstrated that in both areas the species was largely piscivorous. In inshore waters yellowfin consumed more neritic fauna, including significant numbers of crab megalopa, whereas around seamounts the diet included a greater diversity of epi- and mesopelagic fish and squids. The most important fish prey species in inshore waters was the St Helena butterflyfish Chaetodon sanctahelenae, and around seamounts was the pufferfish Lagocephalus lagocephalus. Results indicate that the diet spectrum of yellowfin tuna in St Helena waters is relatively similar to those of conspecifics living in waters with relatively low productivity, with strategies indicative of food-poor ecosystems. The availability of coastal fauna may make areas around islands and seamounts more attractive for feeding aggregations of yellowfin tuna, compared to the open ocean. The relatively unselective feeding of yellowfin tuna means that stomachs can provide valuable data on the species diversity, particularly in remote areas with limited opportunities for dedicated research expeditions.

Artificial structures in the marine environment may have direct and/or indirect impact on the behaviour and space use of mobile foragers. This study explores whether environmental and physical features in the North Sea—including artificial structures (wrecks, wind turbines, cables, and oil and gas structures) were associated with local abundance of three fish species: cod (Gadus morhua), plaice (Pleuronectes platessa), and thornback ray (Raja clavata). Generalized additive models (GAMs) were used to compare distributions between data collected by fisheries surveys and electronic tags. Distributions of cod, plaice, and ray were correlated with environmental variables including temperature, depth, and substrate, matching findings from previous studies. All species showed seasonal increases in their abundance in areas with high densities of artificial structures, including oil and gas platforms and wrecks. Independent of whether fish purposefully associate with these features or whether structures happen to coincide with locations frequented by these populations, the strong association suggests that greater consideration needs to be given to regulation of habitat alterations, including decommissioning.

Commercial landings of starry smooth-hound Mustelus asterias in northern European seas are increasing, whilst our knowledge of their ecology, behaviour and population structure remains limited. M. asterias is a widely distributed demersal shark, occupying the waters of the southern North Sea and Irish Sea in the north, to at least the southern Bay of Biscay in the south, and is seasonally abundant in UK waters. There are no species-specific management measures for the northeast Atlantic stock, and the complexity of its population structure is not yet fully understood. To address this issue, we deployed both mark-recapture and electronic tags on M. asterias to gain novel insights into its horizontal and vertical movements. Our data suggest that the habitat use of M. asterias changes on a seasonal basis, with associated changes in geographical distribution, depth utilisation and experienced temperature. We report the first direct evidence of philopatry for this species, and also provide initial evidence of sex-biased dispersal and potential metapopulation-like stock structuring either side of the UK continental shelf. Investigations of finer-scale vertical movements revealed clear diel variation in vertical activity. The illustrated patterns of seasonal space-use and behaviour will provide important information to support the stock assessment process and will help inform any future management options.

The energy savings experienced by fish swimming in a school have so far been investigated in an near-idealised experimental context including a relatively laminar water flow. The effects of explicitly turbulent flows and different group sizes are yet to be considered. Our repeated-measures study is a first step in addressing both of these issues: whether schooling is more energetically economical for fish when swimming in a quantified non laminar flow and how this might be moderated by group size. We measured tail beat frequency (tbf) in sea bass swimming in a group of 3 or 6, or singly. Video data enabled us to approximately track the movements of the fish during the experiments and in turn ascertain the water flow rates and turbulence levels experienced for each target individual. Although the fish exhibited reductions in tbf during group swimming, which may indicate some energy savings, these savings appear to be attenuated, presumably due to the water turbulence and the movement of the fish relative to each other. Surprisingly, tbf was unrelated to flow rate when the fish were swimming singly or in a group of three, and decreased with increasing flow rates when swimming in a group of six. However, the fish increased tbf in greater turbulence at all group sizes. Our study demonstrates that under the challenging and complex conditions of turbulent flow and short-term changes in school structure, group size can moderate the influences of water flow on a fish's swimming kinematics, and in turn perhaps their energy costs. Summary statement: The energy savings that sea bass experience from schooling are affected by flow speed or turbulence, moderated by group size

Chemical pollution of the marine environment from anthropogenic sources is a global concern due to the potential for long term effects on the ecosystem. Chemical monitoring schemes can detect harmful substances in water, sediment or biota. However, the presence of specific determinants gives no information on how individual species or the ecosystem are impacted. Biological effects techniques are therefore used in environmental monitoring schemes to provide a clearer picture of whether the chemicals present are causing deleterious effects on the species sampled, or whether organisms have been exposed to certain classes of organic contaminants that they may be able to metabolise. Using these techniques, we can provide an assessment of the health of our marine environment (Thain et al., 2008).

Understanding how, where, and when animals move is a central problem in marine ecology and conservation. Key to improving our knowledge about what drives animal movement is the rising deployment of telemetry devices on a range of free-roaming species. An increasingly popular way of gaining meaningful inference from an animal's recorded movements is the application of hidden Markov models (HMMs), which allow for the identification of latent behavioral states in the movement paths of individuals. However, the use of HMMs to explore the population-level consequences of movement is often limited by model complexity and insufficient sample sizes. Here, we introduce an alternative approach to current practices and provide evidence of how the inclusion of prior information in model structure can simplify the application of HMMs to multiple animal movement paths with two clear benefits: (a) consistent state allocation and (b) increases in effective sample size. To demonstrate the utility of our approach, we apply HMMs and adapted HMMs to over 100 multivariate movement paths consisting of conditionally dependent daily horizontal and vertical movements in two species of demersal fish: Atlantic cod (Gadus morhua; n=46) and European plaice (Pleuronectes platessa; n=61). We identify latent states corresponding to two main underlying behaviors: resident and migrating. As our analysis considers a relatively large sample size and states are allocated consistently, we use collective model output to investigate state-dependent spatiotemporal trends at the individual and population levels. In particular, we show how both species shift their movement behaviors on a seasonal basis and demonstrate population space use patterns that are consistent with previous individual-level studies. Tagging studies are increasingly being used to inform stock assessment models, spatial management strategies, and monitoring of marine fish populations. Our approach provides a promising way of adding value to tagging studies because inferences about movement behavior can be gained from a larger proportion of datasets, making tagging studies more relevant to management and more cost-effective.

There is increasing interest in macroalgae farming in European waters for a range of applications, including food, chemical extraction for biofuel production. This study uses a 3-D numerical model of hydrodynamics and biogeochemistry to investigate potential production and environmental effects of macroalgae farming in UK and Dutch coastal waters. The model included four experimental farms in different coastal settings in Strangford Lough (Northern Ireland), in Sound of Kerrera and Lynn of Lorne (north-west Scotland) and in the Rhine plume (the Netherlands), as well as a hypothetical large-scale farm off the UK north Norfolk coast. The model could not detect significant changes in biogeochemistry and plankton dynamics at any of the farm sites averaged over the farming season. The results showed a range of macroalgae growth behaviours in response to simulated environmental conditions. These were then compared with in situ observations where available, showing good correspondence for some farms and less good correspondence for others. At the most basic level, macroalgae production depended on prevailing nutrient concentrations and light conditions, with higher levels of both resulting in higher macroalgae production. It is shown that under non-elevated and interannually varying winter nutrient conditions, farming success was modulated by the timings of the onset of increasing nutrient concentrations in autumn and nutrient drawdown in spring. Macroalgae carbohydrate content also depended on nutrient concentrations, with higher nutrient concentrations leading to lower carbohydrate content at harvest. This will reduce the energy density of the crop and thus affect its suitability for conversion into biofuel. For the hypothetical large-scale macroalgae farm off the UK north Norfolk coast, the model suggested high, stable farm yields of macroalgae from year to year with substantial carbohydrate content and limited environmental effects.

Small-scale pollution events involve the release of potentially harmful substances into the marine environment. These events can affect all levels of the ecosystem, with damage to both fauna and flora. Numerous reporting structures are currently available to document spills, however there is a lack of information on small-scale events due to their magnitude and patchy distribution. To this end, volunteers may provide a useful tool in filling this data gap, especially for coastal environments with a high usage by members of the public. The potential for citizen scientists to record small-scale pollution events is explored using the UK as an example, with a focus on highlighting methods and issues associated with using this data source. An integrated monitoring system is proposed which combines citizen science and traditional reporting approaches.