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The viability of spatially structured populations depends on the abundance and connectivity between subpopulations of breeding adults. Yet, for many species, both are extremely difficult to assess. The speartooth shark is a critically endangered elasmobranch inhabiting tropical rivers with only three adults ever recorded in Australia. Close-kin mark-recapture models, informed by sibling pairs among 226 juveniles, were developed to estimate adult abundance and connectivity in two Australian river systems. Sixty-eight sibling pairs were found, and adult abundance was estimated at 892 for the Adelaide River and 1128 for the Alligator Rivers. We found strong evidence for female philopatry, with most females returning to the same river to pup. Adelaide River males appear largely philopatric, whereas Alligator Rivers males are highly connected to the Adelaide River. From only 4 years of sampling, our results demonstrate that juvenile-only kin pairs can inform simultaneous estimates of abundance and connectivity in a rare and threatened species.

20 pages, 3 tables, 5 figures.-- Samantha Andrzejaczek ... et al.-- Distributed under a Creative Commons Attribution NonCommercial License 4.0 (CC BY-NC), 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, Data analysis was funded by the Bertarelli Foundation through the Marine Science program through grants to D.J.C., B.A.B., and S.A. D.J.C. is also funded through Research England, UK. S.A. and B.A.B. thank the Moore Foundation and the Packard Foundation. F.G.-M. thanks the Instituto Politecnico Nacional for fellowships (COFAA, EDI). S.B.W. thanks funding from the Darwin Initiative (DPLUS046). A.D.M.D. acknowledges funding from the Research and Conservation Budget at Georgia Aquarium, including philanthropic gifts from several anonymous donors. K.F. acknowledges funding from the Rolex Awards for Enterprise and the Whitley Fund for Nature

Management of species with wide-ranging migrations is a complex issue, made more challenging when the species is both protected and poses a risk to humans. Understanding the oceanic conditions associated with shark habitat use can help develop mitigation strategies or warning systems that meet both conservation and human safety objectives. Using satellite tracks from 77 juvenile and sub-adult white sharks tagged over 10 yr, we modelled individual movement patterns using hidden Markov models and applied generalised additive (mixed) models to explore correlations between movement patterns (presence-absence, habitat selection and behavioural state) and oceanographic and bathymetric variables. White sharks used the whole of the continental shelf, down to depths of 350 m on the continental slope. Sharks were present over a wide range of sea surface temperatures (SSTs; 10-27°C), with the highest probability of occurring at ~20°C. However, the number of average daily tag positions was greatest when SST was between 14 and 18°C, and sharks were more likely to exhibit area-restricted movement when SST was between ~19 and 23°C. Sharks were more likely to be present and selected habitats in productive areas with moderate to high surface chl a concentrations as well as thermal and productivity fronts. Although mesoscale eddies did not influence the likelihood of individuals being present in an area, there was a higher density of sharks in cold-core eddies compared to warm-core eddies. This study indicates that white shark presence and dispersal may be linked, perhaps via prey distribution, to oceanic conditions, potentially assisting development of suitable shark bite mitigation strategies.

It is well established that juvenile bull sharks (Carcharhinus leucas) use rivers and estuaries as nursery areas; however, there is a large degree of variation in habitat preference (with respect to salinity and distance upstream) between studies at national and international scales. To investigate habitat preference and the influence of water quality on movement of bull sharks, we monitored 36 juveniles using an array of acoustic receivers in the Logan and Albert Rivers, Australia, for 30 months. Acoustic data were used to estimate mean daily distance upstream, and generalized additive models were used to determine the influence of flow, salinity, temperature, dissolved oxygen, turbidity, and chlorophyll a on movement. A model that included flow, salinity, dissolved oxygen, and chlorophyll a explained 89% of the variance. Movement was tightly correlated to both flow and salinity with sharks moving downstream in response to increasing flow/declining salinity and upstream during low flow/increasing salinity. During periods of negligible flow and stable salinity, animals moved upstream and downstream in response to decreasing and increasing dissolved oxygen, respectively. Dissolved oxygen and temperature were strongly negatively correlated and interchangeable within the model. Despite fluctuations in environmental salinity (0–32 psu) and a strong declining gradient in salinity with increasing distance upstream, bull sharks remained within a narrow band of salinity (6–10 psu) throughout the tracking period. The results of this study indicate that habitat choice by juvenile bull sharks is a complex tradeoff between physiology, food availability, and predator avoidance, resulting in large differences between adjacent systems and more broadly across their range.

To understand habitat requirements of green turtles in an important foraging area subject to both anthropogenic and natural perturbations, we examined residency, home range and habitat use of juvenile, sub-adult and adult green turtles (Chelonia mydas) in Port Curtis, Australia, using passive acoustic telemetry. Acoustic tags were attached to turtles at Pelican Banks (n = 33) and Wiggins Island (n = 16). Between May 2013 and September 2014, tagged turtles were detected > 1.3 million times by 46 acoustic receivers. Data demonstrated variability in residence index and home range size between Pelican Banks and Wiggins Island that was largely attributed to larger body size at Pelican Banks and habitat differences. Tide had a significant influence of movement and habitat use. At Pelican Banks turtles moved into intertidal seagrass beds at high tide and retreated to the channel at low tide. At Wiggins Island, high tide 50% KUD area was more than double low tide area and turtles moved into the mangroves at high tide and retreated to channels at low tide. Diet reflected availability of food resources; seagrass dominated diet at Pelican Banks whereas epiphytic red algae dominated diet at Wiggins Island. There was no evidence of a diurnal shift in home range or habitat use. The use of intertidal areas by both turtles and small recreational craft during high tide at Pelican Banks resulted in increased risk of vessel strike. Unusually short residency at Pelican Banks suggested that animals had either relocated to another foraging area or a combination of recent flooding, port development and reduced seagrass coverage during the period of monitoring resulted in higher emigration rates than previously demonstrated for this species. Acoustic telemetry is a valuable tool for obtaining fine-scale, long- term data on movement and residency of green turtles.

Inferences regarding animal presence from passive acoustic receiver arrays are driven by the spatial configuration of receivers. Large, dense arrays provide more information, but maintenance of multiple receivers is costly. Configuring acoustic receiver arrays to maximise coverage while minimising cost is therefore paramount. This study used data from a dense acoustic receiver array within a white shark Carcharodon carcharias nursery area on the east coast of Australia to assess how detection data of tagged white sharks in the area was affected by reducing the array size. Receivers were sub-sampled post hoc by simple random sampling, clustered random sampling, and sampling of the top performing receivers. Using the top performing receivers, array size could be reduced by 60% (10 out of 25 receivers) while still detecting a median of 100% of white sharks detected with the full array. With random and clustered sampling methods, a 40% reduction in array size (15 out of 25 receivers) detected a median of 100% of sharks. Reducing the array size by 60% using the top performing receivers resulted in a 35% decrease in the median number of detections per visit of the tagged sharks (67 out of 102.5 detections). In comparison, reducing the array by the same amount with random and clustered sampling methods resulted in a 57% decrease (44 out of 102.5 detections). The post hoc sampling methods used in this study are an empirical approach for optimising placement of limited receiver resources with broad application for establishing cost-effective monitoring.

In Australian and New Zealand waters, current knowledge on white shark (Carcharodon carcharias) movement ecology is based on individual tracking studies using relatively small numbers of tags. These studies describe a species that occupies highly variable and complex habitats. However, uncertainty remains as to whether the proposed movement patterns are representative of the wider population. Here, we tagged 103 immature Australasian white sharks (147–350 cm fork length) with both acoustic and satellite transmitters to expand our current knowledge of population linkages, spatiotemporal dynamics and coastal habitats. Eighty-three sharks provided useable data. Based on individual tracking periods of up to 5 years and a total of 2,865 days of tracking data, we were able to characterise complex movement patterns over ~45° of latitude and ~72° of longitude and distinguish regular/recurrent patterns from occasional/exceptional migration events. Shark movements ranged from Papua New Guinea to sub-Antarctic waters and to Western Australia, highlighting connectivity across their entire Australasian range. Results over the 12-year study period yielded a comprehensive characterisation of the movement ecology of immature Australasian white sharks across multiple spatial scales and substantially expanded the body of knowledge available for population assessment and management.

Large endothermic pelagic sharks are highly migratory and use habitats spanning a broad range of coastal, neritic and oceanic areas. This study aimed to resolve the current lack of information on the movements and habitat use of white sharks, Carcharodon carcharias, between shelf, slope and oceanic areas located off southwestern Australia. Movement behaviours, spatial distribution patterns and vertical habitat use of juvenile, sub-adult and adult white sharks ranging in size from 1.9 to 5.7 m total length were examined using 43 satellite tags deployed over 15 years. Pop-up satellite archival tags and satellite-linked radio tags collected 3663 days and > 109,900 km of tracking data over periods of up to 381 days. We demonstrated sex-based differences in movement and distribution patterns of male (21) and female (19) white sharks. Female dispersal was broader and extended further offshore than males, which largely remained in neritic and gulf habitats. Female white sharks experienced a narrower range of water temperatures (F = 9.0–19.0 °C; M = 10.4–24.8 °C). Despite these subtle differences, both sexes showed an affinity to the Neptune Island Group and the shelf slope canyons of the eastern Great Australian Bight, which are productive and oceanographically complex regions that support known prey of white sharks. This study highlighted that the southern-western Australian population of white sharks use off-shelf habitat to a greater extent than previously identified. Findings have potential implications for: ecological risk assessments of fisheries that operate in these offshore habitats and for monitoring and managing marine protected areas.

State-space models are important tools for quality control of error-prone animal movement data. The near real-time (within 24 h) capability of the Argos satellite system aids dynamic ocean management of human activities by informing when animals enter intensive use zones. This capability also facilitates use of ocean observations from animal-borne sensors in operational ocean forecasting models. Such near real-time data provision requires rapid, reliable quality control to deal with error-prone Argos locations. We formulate a continuous-time state-space model for the three types of Argos location data (Least-Squares, Kalman filter, and Kalman smoother), accounting for irregular timing of observations. Our model is deliberately simple to ensure speed and reliability for automated, near real-time quality control of Argos data. We validate the model by fitting to Argos data collected from 61 individuals across 7 marine vertebrates and compare model-estimated locations to GPS locations. Estimation accuracy varied among species with median Root Mean Squared Errors usually < 5 km and decreased with increasing data sampling rate and precision of Argos locations. Including a model parameter to inflate Argos error ellipse sizes resulted in more accurate location estimates. In some cases, the model appreciably improved the accuracy of the Argos Kalman smoother locations, which should not be possible if the smoother uses all available information. Our model provides quality-controlled locations from Argos Least-Squares or Kalman filter data with slightly better accuracy than Argos Kalman smoother data that are only available via reprocessing. Simplicity and ease of use make the model suitable both for automated quality control of near real-time Argos data and for manual use by researchers working with historical Argos data., 25 pages, 10 figures

Large numbers of juvenile southern bluefin tuna (SBT; Thunnus maccoyii) migrate into the warm shelf waters of the Great Australian Bight (GAB) each austral summer. Whilst in the GAB, they are the focus of a commercially important Australian fishery. Recent expansion of activities associated with oil and gas exploration in the GAB over the last five years has raised concerns that noise associated with geophysical surveys and exploratory drilling activities may impact on the migration and behaviour of SBT, with potential flow-on effects on the commercial fishery and current monitoring of the population for management purposes. As a first step in identifying the potential impacts of expansion of oil and gas exploration activities in the GAB on SBT, we establish the historical extent of these activities in the GAB with a primary focus on geophysical surveys. Potential overlap with the distribution of juvenile SBT in the GAB determined from an archival tag dataset (1998–2011) was then explored. Geophysical surveys have occurred throughout the vast majority of the region since 1960, with the size of energy sources used in surveys and the extent of areas surveyed increasing through time. The use of more complex, higher density 3D surveys has increased gradually since 2000. The timing and distribution of exploration activity has had varying degrees of overlap with SBT occurrence and distribution as described by tagged fish. Determining robust measures of the responses to surveys however, is difficult due to a paucity of data on the hearing capabilities of SBT, uncertainties in the true extent of spatial overlap of activities and tagged fish resulting from geolocation methods used for position estimation from archival tag data, complexities in the drivers of behaviour in SBT, and limitations with using observational data to determine cause-and-effect relationships. These difficulties are typical not just of SBT and the GAB region, but apply to investigations of the responses of marine animals to geophysical surveys more broadly. The data presented in this study, however, represent a first step towards understanding oil and gas exploration within a defined region of the Australian marine environment, and provide important context for exploring the potential impact of such activities on a commercially important top order predator of the GAB ecosystem.

Juvenile southern bluefin tuna (SBT) undertake seasonal migrations to and from the coastal waters of southern Australia until around age 5. In particular, they are present in the waters of the Great Australia Bight (GAB) over the summer months, where they are targeted by a commercial purse seine fishery. Arrival to and departure from the GAB represent important constraints on the valuable fishery, and this information is also now seen as essential for managing other activities within the GAB. As such, understanding the general patterns of the distribution of juvenile SBT and the environmental factors might be driving their distribution is valuable for establishing a baseline against which any future changes to population arrival or departure may be assessed. As part of a large investigation into the ecosystem of the GAB, data from a multi-year archival tagging program focused on juvenile SBT were used to construct statistical models of spatial usage within the residence areas of the GAB. Climatological data describing mixed-layer-depth, sea-surface temperatures, along with distance to the shelf break and coast, spatial position and time of year were used as predictor variables. Generalized additive models were fit which accounted for the seasonal progression of SBT into the GAB throughout their annual cycle and predicted the broad scale environmental features associated with their average distribution. The statistical models predicted habitat use by juvenile SBT in the proximity of the continental shelf break, with a preference for warmer waters in conjunction with deeper mixed layers. The model-generated annual distribution climatology can be used to plan the timing for a range of activities such as fishing, shipping, oil and gas exploration, and also inform development of forecasting applications. The predictions are also useful for determining large scale variation from the typical usage patterns of SBT in the GAB into the future.

Large numbers of juvenile southern bluefin tuna (SBT; Thunnus maccoyii) migrate into the warm shelf waters of the Great Australian Bight (GAB) each austral summer. Whilst in the GAB, they aggregate in schools that spend substantial periods in the surface layer of the water column. In this study we investigate biological, temporal and environmental factors influencing this surfacing phenomena using an extensive archival tagging dataset collected between 1998 and 2011. High frequency data on the vertical movement of SBT collected by these tags were used to calculate the proportion of time fish spent in the shallowest 20 m during each day and night period. Estimates of fish location derived from light sensor data on the tags allowed us to investigate the influence that local environmental conditions had on a fish's surfacing behaviour. Although there is high variability in surfacing behaviour within and between individuals, some general patterns emerge. There are clear diel differences in surfacing, with the proportion of time fish spend at the surface tending to be high during most days and either very high (>90%) or very low (

Large scale migrations are a key component of the life history of many marine species. We quantified the annual migration cycle of juvenile southern bluefin tuna (Thunnus maccoyii; SBT) and spatiotemporal variability in this cycle, based on a multi-decadal electronic tagging dataset. Behaviour-switching models allowed for the identification of cohesive areas of residency and classified the temporal sequence of movements within a migration cycle from austral summer foraging grounds in the Great Australian Bight (GAB) to winter foraging grounds in the Indian Ocean and Tasman Sea and back to the GAB. Although specific regions within the Indian Ocean were frequented, individuals did not always return to the same area in consecutive years. Outward migrations from the GAB were typically longer than return migrations back to the GAB. The timing of individual arrivals to the GAB, which may be driven by seasonality in prey availability, was more cohesive than the timing of departures from the GAB, which may be subject to the physiological condition of SBT. A valuable fishery for SBT operates in the GAB, as do a number of scientific research programs designed to monitor SBT for management purposes; thus, understanding SBT migration to and from the area is of high importance to a number of stakeholders.

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.

The deep scattering layer is an ubiquitous aggregation of zooplankton and forage fish in the ocean. It features the striking phenomenon of diel vertical migration, where animals remain in deep, dark water in daylight hours and migrate upwards at dusk. The common explanation for this is that prey avoid vulnerability to visual predators. Here, we develop a game-theoretic explanation for the deep scattering layer and its diel vertical migrations, focusing on one generic predator species and one generic prey species. The model is formulated in continuous time and space, and by neglecting the cost of locomotion, it allows fine-grained predictions of vertical distributions. The Nash equilibrium features a distinct deep scattering layer which undertakes diel vertical migrations, the range of which increases with predator abundance. Maximum feeding rates are predicted to occur at dawn and dusk. Predator interference emerges from the game dynamics in the form of a complicated functional dependency of gross encounter rates on predator abundance. In turn, the growth rate of the prey decreases monotonically with predator abundance. In addition to providing a mechanistic explanation for the striking phenomenon of diel vertical migrations, the model yields quantitative predictions of vertical distributions and diel patterns in feeding intake, which may be compared with acoustic data, observed individual behavior, or stomach data.

Effective ocean management and the conservation of highly migratory species depend on resolving the overlap between animal movements and distributions, and fishing effort. However, this information is lacking at a global scale. Here we show, using a big-data approach that combines satellite-tracked movements of pelagic sharks and global fishing fleets, that 24% of the mean monthly space used by sharks falls under the footprint of pelagic longline fisheries. Space-use hotspots of commercially valuable sharks and of internationally protected species had the highest overlap with longlines (up to 76% and 64%, respectively), and were also associated with significant increases in fishing effort. We conclude that pelagic sharks have limited spatial refuge from current levels of fishing effort in marine areas beyond national jurisdictions (the high seas). Our results demonstrate an urgent need for conservation and management measures at high-seas hotspots of shark space use, and highlight the potential of simultaneous satellite surveillance of megafauna and fishers as a tool for near-real-time, dynamic management., Data analysis was funded in part by the Marine Biological Association (MBA) and the UK Natural Environment Research Council (NERC) (NE/R00997X/1) (to D.W.S.) with additional research support from the Save Our Seas Foundation and the NERC Oceans 2025 Strategic Research Programme, in which D.W.S. was a principal investigator. D.W.S. was supported by an MBA Senior Research Fellowship, N.Q. by European Regional Development Fund (FEDER) via the Programa Operacional Competitividade e Internacionalização (COMPETE), National Funds via Fundação para a Ciência e a Tecnologia (FCT) under PTDC/MAR/100345/2008 and COMPETE FCOMP-01-0124-FEDER-010580 (to N.Q. and D.W.S.), and Norte Portugal Regional Operational Programme (NORTE 2020) under the PORTUGAL 2020 Partnership Agreement through the European Regional Development Fund (ERDF) in project MarInfo (NORTE-01-0145-FEDER-000031). Additional support was provided by an FCT Investigator Fellowship IF/01611/2013 (N.Q.), FCT Doctoral Fellowship PD/BD/52603/2014 (M.V.), PTDC/MAR-BIO/4458/2012, Xunta de Galicia - Isabel Barreto Program 2009-2012 (G.M.), Australian Research Council (ARC) grant DE170100841 and operational funds from the Australian Institute for Marine Science (AIMS) (both to A.M.M.S.).

Satellite telemetry data was used to predict at sea spatial usage of five top order and meso-predators; Antarctic fur seals ( Arctocephalus gazella ), macaroni penguins ( Eudyptes chrysolophus ), king penguins ( Aptenodytes patagonicus ), black browed albatross ( Diomedea melanophrys ), and light mantled albatross ( Phoebetria palpebrata ). All were tagged at Heard Island in the Southern Ocean over a single summer season collecting over 5000 tracking days for 178 individuals. We aimed to predict areas of likely high foraging value from tracking environmental data and also to quantify overlap in foraging range between species. Hidden Markov models were used to differentiate between bouts of Area Restricted Search (ARS) assumed to be associated with areas of higher foraging value, and transit behaviours. Oceanographic and distance metrics associated with ARS activity were then used to calculate a habitat electivity index. A combined bootstrap/Monte Carlo scheme was employed to propagate uncertainty from the Hidden Markov models into the habitat prediction scheme. Distinct differences were predicted in the spatial distribution of foraging locations in different species, reflecting different dispersive abilities and foraging strategy. The extent of usage and foraging distribution was largely contained within Australian the Economic Exclusion Zone (EEZ). In comparison, the smaller Australian Commonwealth Marine Protected Areas (MPAs) contained

Bigeye tuna are known for remarkable daytime vertical migrations between deep water, where food is abundant but the water is cold, and the surface, where water is warm but food is relatively scarce. Here we investigate if these dive patterns can be explained by dynamic optimal foraging theory, where the tuna maximizes its energy harvest rate. We assume that foraging efficiency increases with body temperature, so that the vertical migrations are thermoregulatory. The tuna's state is characterized by its mean body temperature and depth, and we solve the optimization problem numerically using dynamic programming. With little calibration of model parameters, our results are consistent with observed data on vertical movement: we find that small tuna should display constant-depth strategies while large tuna should display vertical migrations. The analysis supports the hypothesis that the tuna behaves such as to maximize its energy gains. The model therefore provides insight into the processes underlying observed behavioral patterns and allows generating predictions of foraging behavior in unobserved environments.

Summary Due to the substantial progress in tracking technology, recent years have seen an explosion in the amount of movement data being collected. This has led to a huge demand for statistical tools that allow ecologists to draw meaningful inference from large tracking data sets. The class of hidden Markov models (HMMs) matches the intuitive understanding that animal movement is driven by underlying behavioural modes and has proven to be very useful for analysing movement data. For data that involve a regular sampling unit and negligible measurement error, these models usually are sufficiently flexible to capture the complex correlation structure found in movement data, yet are computationally inexpensive compared to alternative methods. The R package moveHMM allows ecologists to process GPS tracking data into series of step lengths and turning angles, and to fit an HMM to these data, allowing, in particular, for the incorporation of environmental covariates. The package includes assessment and visualization tools for the fitted model. We illustrate the use of moveHMM using (simulated) movement of the legendary wild haggis Haggis scoticus. Our findings illustrate the role our software, and movement modelling in general, can play in conservation and management by illuminating environmental constraints.

Summary Electronic tags have revolutionised animal movement studies, but the reliability of subsequent ecological inference hinges on being able to quantify uncertainty in location estimates. Light-based geolocation, which uses the time series of light intensity during twilight events, remains the only viable technology for many species (e.g. fish and small birds) despite its limited accuracy. Modern approaches to movement modelling, such as Kalman filters and gridded hidden Markov models, require a valid likelihood for each observed twilight. It is difficult to directly construct such a likelihood (i.e. the probability density of the light data during a twilight period) given any location on the globe, because of complicated autocorrelation structures and non-standard statistical distributions. We therefore use data from moored tags at known locations to construct a transformation that turns a simple one-dimensional statistic into a quantity with the properties of a log-likelihood. The result is a set of calibration splines that can be used with light data from a similar tag deployed on a real animal: for each twilight, the one-dimensional statistic is calculated for any location (e.g. on a grid of, or all possible, locations) and then transformed into a likelihood using the calibration splines. The likelihoods can then be input to any state-space model to estimate a track. We show an example track from a grid-based hidden Markov model applied to light data from a tag deployed on a southern bluefin tuna. This approach to light-based geolocation provides the flexibility to integrate movement and behaviour modelling in a novel way. The likelihood surfaces from our approach can be used in any state-space model of animal movement and behaviour, irrespective of whether estimation is by maximum-likelihood or Bayesian methods. Our approach is primarily aimed at users interested in developing and fitting their own state-space models to explore biological hypotheses about animal behaviour.

The effects of climate change constitute a major concern in Arctic waters due to the rapid decline of sea ice, which may strongly alter the movements and habitat availability of Arctic marine mammals. We tracked 98 bowhead whales by satellite over an 11-year period (2001–2011) in Baffin Bay - West Greenland to investigate the environmental drivers (specifically sea surface temperature and sea ice) involved in bowhead whale’s movements. Movement patterns differed according to season, with aggregations of whales found at higher latitudes during spring and summer likely in response to sea-ice retreat and increasing sea temperature (SST) facilitated by the warm West Greenland Current. In contrast, the whales moved further south in response to sea temperature decrease during autumn and winter. Statistical models indicated that the whales targeted a narrow range of SSTs from −0.5 to 2 °C. Sea surface temperatures are predicted to undergo a marked increase in the Arctic, which could expose bowhead whales to both thermal stress and altered stratification and vertical transport of water masses. With such profound changes, bowhead whales may face extensive habitat loss. Our results highlight the need for closer investigation and monitoring in order to predict the extent of future distribution changes.

Like many species, movement patterns of southern elephant seals (Mirounga leonina) are being influenced by long-term environmental change. These seals migrate up to 4000 km from their breeding colonies, foraging for months in a variety of Southern Ocean habitats. Understanding how movement patterns vary with environmental features and how these relationships differ among individuals employing different foraging strategies can provide insight into foraging performance at a population level. We apply new fast-estimation tools to fit mixed effects within a random walk movement model, rapidly inferring among-individual variability in southern elephant seal environment-movement relationships. We found that seals making foraging trips to the sea-ice on or near the Antarctic continental shelf consistently reduced speed and directionality (move persistence) with increasing sea ice coverage and had variable responses to chlorophyllaconcentration, whereas seals that foraged pelagically reduced move persistence in regions where circumpolar deep water shoaled. Given future climate scenarios, pelagic foragers may encounter more productive habitat but sea-ice foragers may see reduced habitat availability. Our approach is scalable to large telemetry data sets and allows flexible combinations of mixed effects to be evaluated via model selection, thereby illuminating the ecological context of animal movements that underlie habitat use.

Conservation concerns exist for many sharks but robust estimates of abundance are often lacking. Improving population status is a performance measure for species under conservation or recovery plans, yet the lack of data permitting estimation of population size means the efficacy of management actions can be difficult to assess, and achieving the goal of removing species from conservation listing challenging. For potentially dangerous species, like the white shark, balancing conservation and public safety demands is politically and socially complex, often leading to vigorous debate about their population status. This increases the need for robust information to inform policy decisions. We developed a novel method for estimating the total abundance of white sharks in eastern Australia and New Zealand using the genetic-relatedness of juveniles and applying a close-kin mark-recapture framework and demographic model. Estimated numbers of adults are small (ca. 280–650), as is total population size (ca. 2,500–6,750). However, estimates of survival probability are high for adults (over 90%), and fairly high for juveniles (around 73%). This represents the first direct estimate of total white shark abundance and survival calculated from data across both the spatial and temporal life-history of the animal and provides a pathway to estimate population trend.

© 2015 Elsevier Ltd.Some of the most important development goals for the countries and territories of the Western and Central Pacific Ocean (WCPO) involve the sustainable management of their fisheries in light of environmental, economic and social uncertainties. The responses of fish populations to variability in the marine environment have implications for decision making processes associated with resource management. There is still considerable uncertainty in estimating the responses of tuna populations to short-to-medium-term variability and longer-term change in the oceanic environment. A workshop was organised to examine how advances in oceanography, fisheries science and fisheries economics could be applied to the tuna fisheries of the WCPO and in doing so identify research priorities to improve understanding relevant to progressing management. Research priorities identified included: (i) improved parameterisation of end to end ecosystem model components, processes and feedbacks through expanded biological observations and incorporation of higher resolution climate models; (ii) development of seasonal and inter-annual forecasting tools enabling management responses to short-term variability in tuna distributions and abundances; (iii) improved understanding of the population dynamics of and the energy transfer efficiencies between food web components; (iv) assessment of the optimal value of access rights and overall fishery value under multiple scenarios of tuna distribution and abundance and influences on decision making by fisheries managers and fleets and (v) development of management strategy evaluation frameworks for utilisation in the implementing and testing of fishery management procedures and to help prioritise research directions and investment. Issues discussed and research priorities identified during the workshop have synergies with other internationally managed fisheries and therefore are applicable to many other fisheries.

TM and TP received support from IMBER-CLIOTOP and Macquarie University Safety Net Grant 9201401743. SB was supported under an Australia Research Council Super Science Fellowship. IDJ was supported by a Macquarie Vice-Chancellors Innovation Fellowship. TAP was supported by a CSIRO Julius Career Award and the Villum Foundation. The behavior of colony-based marine predators is the focus of much research globally. Large telemetry and tracking data sets have been collected for this group of animals, and are accompanied by many empirical studies that seek to segment tracks in some useful way, as well as theoretical studies of optimal foraging strategies. However, relatively few studies have detailed statistical methods for inferring behaviors in central place foraging trips. In this paper we describe an approach based on hidden Markov models, which splits foraging trips into segments labeled as "outbound", "search", "forage", and "inbound". By structuring the hidden Markov model transition matrix appropriately, the model naturally handles the sequence of behaviors within a foraging trip. Additionally, by structuring the model in this way, we are able to develop realistic simulations from the fitted model. We demonstrate our approach on data from southern elephant seals (Mirounga leonina) tagged on Kerguelen Island in the Southern Ocean. We discuss the differences between our 4-state model and the widely used 2-state model, and the advantages and disadvantages of employing a more complex model. Publisher PDF

Y.Y.W. was funded by Grants‐in‐Aid for Scientific Research from the Japan Society for the Promotion of Science (grant reference 25850138). T.P. was supported by a South African National Research Foundation Scarce Skills Postdoctoral Research Fellowship, and T.P. and Y.P.P. received funding from the MASTS pooling initiative (The Marine Alliance for Science and Technology for Scotland) and their support is gratefully acknowledged. MASTS is funded by the Scottish Funding Council (grant reference HR09011) and contributing institutions. T.P. and M.M. gratefully acknowledge the hardware, software, support and expertise contributed by Prof. Willem Bouten and his research group UvA‐BiTS (University of Amsterdam Bird Tracking System). 1. Use of accelerometers is now widespread within animal biologging as they provide a means of measuring an animal's activity in a meaningful and quantitative way where direct observation is not possible. In sequential acceleration data, there is a natural dependence between observations of behaviour, a fact that has been largely ignored in most analyses. 2. Analyses of acceleration data where serial dependence has been explicitly modelled have largely relied on hidden Markov models (HMMs). Depending on the aim of an analysis, an HMM can be used for state prediction or to make inferences about drivers of behaviour. For state prediction, a supervised learning approach can be applied. That is, an HMM is trained to classify unlabelled acceleration data into a finite set of pre-specified categories. An unsupervised learning approach can be used to infer new aspects of animal behaviour when biologically meaningful response variables are used, with the caveat that the states may not map to specific behaviours. 3. We provide the details necessary to implement and assess an HMM in both the supervised and unsupervised learning context and discuss the data requirements of each case. We outline two applications to marine and aerial systems (shark and eagle) taking the unsupervised learning approach, which is more readily applicable to animal activity measured in the field. HMMs were used to infer the effects of temporal, atmospheric and tidal inputs on animal behaviour. 4. Animal accelerometer data allow ecologists to identify important correlates and drivers of animal activity (and hence behaviour). The HMM framework is well suited to deal with the main features commonly observed in accelerometer data and can easily be extended to suit a wide range of types of animal activity data. The ability to combine direct observations of animal activity with statistical models, which account for the features of accelerometer data, offers a new way to quantify animal behaviour and energetic expenditure and to deepen our insights into individual behaviour as a constituent of populations and ecosystems. Postprint

Understanding the links between external variables such as habitat and interactions with conspecifics and animal space-use is fundamental to developing effective management measures. In the marine realm, automated acoustic tracking has become a widely used method for monitoring the movement of free-ranging animals, yet researchers generally lack robust methods for analysing the resulting spatial-usage data. In this study, acoustic tracking data from male and female broadnose sevengill sharks Notorynchus cepedianus, collected in a system of coastal embayments in southeast Tasmania were analyzed to examine sex-specific differences in the sharks' coastal space-use and test novel methods for the analysis of acoustic telemetry data. Sex-specific space-use of the broadnose sevengill shark from acoustic telemetry data was analysed in two ways: The recently proposed spatial network analysis of between-receiver movements was employed to identify sex-specific space-use patterns. To include the full breadth of temporal information held in the data, movements between receivers were furthermore considered as transitions between states of a Markov chain, with the resulting transition probability matrix allowing the ranking of the relative importance of different parts of the study area. Both spatial network and Markov chain analysis revealed sex-specific preferences of different sites within the study area. The identification of priority areas differed for the methods, due to the fact that in contrast to network analysis, our Markov chain approach preserves the chronological sequence of detections and accounts for both residency periods and movements. In addition to adding to our knowledge of the ecology of a globally distributed apex predator, this study presents a promising new step towards condensing the vast amounts of information collected with acoustic tracking technology into straightforward results which are directly applicable to the management and conservation of any species that meet the assumptions of our model.

Climate and competition influence seabird population size yet are rarely considered simultaneously. Here, we consider the influence of climate on nominal abundance trends, and test for evidence of interspecific competition based on 31 yr of count data from 3 co-occurring gull spe- cies in southeastern Tasmania. The silver gull Chroicocephalus novaehollandiae and Pacific gull Larus pacificus are native, while the kelp gull L. dominicanus established in Tasmania from New Zealand in the 1950s. We applied population growth models where either growth rate or carrying capacity was a function of both large-scale climate variables and local conditions. For the kelp gull, a null model without any climate variables was selected, consistent with recent population establishment and increase. For the 2 native species, climate covariates were included, and for both, wind speed was important; for Pacific gulls, the El Nino-Southern Oscillation and regional sea surface temperature were also included in the selected model. These results are consistent with bottom-up forcing in the southeastern Tasmanian marine ecosystem; increased wind forcing leads to increased productivity and higher abundance of an important euphausiid prey species (Nyctiphanes australis). In years with lower wind speeds, warmer waters and higher water column stability, N. australis production is reduced. Models allowing competition effects by the kelp gull on the 2 native species performed poorly relative to models with climate covariates. Thus, compe- tition alone is not a sufficient explanatory factor for observed changes in the 2 native species, and management strategies to maintain populations of the endemic Pacific gull should seek to reduce other stressors, including factors related to climate change.

Climate change is acknowledged as an emerging threat for top-order marine predators, yet obtaining evidence of impacts is often difficult. In south-eastern Australia, a marine global warming hotspot, evidence suggests that climate change will profoundly affect pinnipeds and seabirds. Long-term data series are available to assess some species’ responses to climate. Researchers have measured a variety of chronological and population variables, such as laying dates, chick or pup production, colony-specific abundance and breeding success. Here, we consider the challenges in accurately assessing trends in marine predator data, using long-term data series that were originally collected for other purposes, and how these may be driven by environmental change and variability. In the past, many studies of temporal changes and environmental drivers used linear analyses and we demonstrate the (theoretical) relationship between the magnitude of a trend, its variability, and the duration of a data series required to detect a linear trend. However, species may respond to environmental change in a nonlinear manner and, based on analysis of time-series from south-eastern Australia, it appears that the assumptions of a linear model are often violated, particularly for measures of population size. The commonly measured demographic variables exhibit different degrees of variation, which influences the ability to detect climate signals. Due to their generally lower year-to-year variability, we illustrate that monitoring of variables such as mass and breeding chronology should allow detection of temporal trends earlier in a monitoring programme than observations of breeding success and population size. Thus, establishing temporal changes with respect to climate change from a monitoring programme over a relatively short time period requires careful a priori choice of biological variables.

Understanding the patterns of large-scale movements of highly mobile marine predators is essential to understanding the impacts of anthropogenic pressures on the animals and the ecosystems they frequent. The broadnose sevengill shark Notorynchus cepedianus is one of the most important apex predators in temperate coastal areas around the world, yet little is known of its seasonal large-scale movements. Five male and five female sevengill sharks were equipped with pop-up satellite archival tags (PSATs) in a coastal embayment in southern Tasmania, that collected depth and temperature data during winter, when the animals leave the coastal embayment, resulting in a dataset covering a total of 818 d. Animal tracks indicated that males moved northwards into warmer waters, whereas females remained in southern waters. Three of the females stayed in the Tasmanian coastal areas while the other two left, with one of them moving into deeper waters of up to 360 m depth at the southern edge of the Tasmanian shelf before returning to the Tasmanian coast. These sex-specific differences in large-scale movement could potentially lead to the differential exploitation of the sexes when the sharks leave the protected areas where they were tagged. Both males and females switched between diel vertical migration and reverse diel vertical migration over the course of their tracks and displayed oscillatory vertical movements, probably linked to foraging. These vertical movements persisted throughout the tracks, suggesting that sevengill sharks foraged continuously during their migration rather than switching between transiting and foraging modes.

The deployment of an ever-evolving array of animal-borne telemetry and data logging devices is rapidly increasing our understanding of the movement, behaviour and physiology of a variety species and the complex, and often highly dynamic, environments they use and respond to. The rapid rate at which new technologies, improvements to current technologies and new analytical techniques are being developed has meant that movements, behaviour and physiological processes are being quantified at finer spatial and temporal scales than ever before. The Fourth International Symposium on Bio-logging Science, held on 14–18 March in Hobart, Australia, brought together scientists across multiple disciplines to discuss the latest innovations in technology, applications and analytical techniques in bio-logging science, building on research presented at three previous conferences. Here we present an update on the state of bio-logging research and provide some views on the future of this field of research. Papers were grouped into five theme areas: (i) Southern Ocean ecosystems; (ii) fishery and biodiversity management applications; (iii) from individuals to populations—inferences of population dynamics from individuals; (iv) conservation biology and (v) habitat modelling. Papers reflected wider uptake of newer technologies, with a greater proportion of studies utilising accelerometry and incorporating advances in statistical modelling of behaviour and habitats, especially via state space modelling methods. Environmental data collected by tags at increasing accuracies are now having wider application beyond the bio-logging community, providing important oceanographic data from regions difficult to sample using traditional methodologies. Partnerships between multiple organisations are also now enabling regional assessments of species movements, behaviour and physiology at population scales and will continue to be important for applying bio-logging technologies to species conservation and management applications.

Aggregations in the distribution of individuals are an almost universal phenomenon in living organisms. Groups of animals that display collective coordinated movement without forming stable social bonds such as fish schools are a special type of aggregation. In tropical tuna fisheries, aggregating behaviour is directly exploited through the use of artificial fish aggregating devices (FADs). Hence, understanding the dynamics of schooling behaviour and the potential impacts of FADs upon it may have ramifications for tuna management. As a novel way of quantifying spatiotemporal co-occurrences of animals, we applied network statistics to acoustic tracking data to identify the co-occurrences of individual yellowfin tuna, Thunnus albacares, in an array of FADs and determine the frequency and temporal dynamics of these co-occurrences. We observed large interannual variation in movement rates of tuna between FADs, and corresponding interannual variability in the mean number of spatiotemporal associates for each individual as well as the temporal stability of associations. When movement rates were high, associations within FAD aggregations decayed to randomness three times faster than when movement rates were lower. This raises the possibility that if FADs are sufficiently close for fish to perform frequent between- FAD movements, school mixing may be increased and cohesion reduced.

Ecologists have an unprecedented array of bio-logging technologies available to conduct in situ studies of horizontal and vertical movement patterns of marine animals. These tracking data provide key information about foraging, migratory, and other behaviours that can be linked with bio-physical datasets to understand physiological and ecological influences on habitat selection. In most cases, however, the behavioural context is not directly observable and therefore, must be inferred. Animal movement data are complex in structure, entailing a need for stochastic analysis methods. The recent development of state-space modelling approaches for animal movement data provides statistical rigor for inferring hidden behavioural states, relating these states to bio-physical data, and ultimately for predicting the potential impacts of climate change. Despite the widespread utility, and current popularity, of state-space models for analysis of animal tracking data, these tools are not simple and require considerable care in their use. Here we develop a methodological ‘‘road map’’ for ecologists by reviewing currently available state-space implementations. We discuss appropriate use of state-space methods for location and/or behavioural state estimation from different tracking data types. Finally, we outline key areas where the methodology is advancing, and where it needs further development.

In the Southern Ocean, wide-ranging predators offer the opportunity to quantify how animals respond to differences in the environment because their behavior and population trends are an integrated signal of prevailing conditions within multiple marine habitats. Southern elephant seals in particular, can provide useful insights due to their circumpolar distribution, their long and distant migrations and their performance of extended bouts of deep diving. Furthermore, across their range, elephant seal populations have very different population trends. In this study, we present a data set from the International Polar Year project; Marine Mammals Exploring the Oceans Pole to Pole for southern elephant seals, in which a large number of instruments (N = 287) deployed on animals, encompassing a broad circum-Antarctic geographic extent, collected in situ ocean data and at-sea foraging metrics that explicitly link foraging behavior and habitat structure in time and space. Broadly speaking, the seals foraged in two habitats, the relatively shallow waters of the Antarctic continental shelf and the Kerguelen Plateau and deep open water regions. Animals of both sexes were more likely to exhibit area-restricted search (ARS) behavior rather than transit in shelf habitats. While Antarctic shelf waters can be regarded as prime habitat for both sexes, female seals tend to move northwards with the advance of sea ice in the late autumn or early winter. The water masses used by the seals also influenced their behavioral mode, with female ARS behavior being most likely in modified Circumpolar Deepwater or northerly Modified Shelf Water, both of which tend to be associated with the outer reaches of the Antarctic Continental Shelf. The combined effects of (1) the differing habitat quality, (2) differing responses to encroaching ice as the winter progresses among colonies, (3) differing distances between breeding and haul-out sites and high quality habitats, and (4) differing long-term regional trends in sea ice extent can explain the differing population trends observed among elephant seal colonies. Publisher PDF

The bowhead whale Balaena mysticetus is the only mysticete species endemic to the Arctic. The Eastern Arctic-West Greenland (EA-WG) population is considered of special concern in Canada as these whales remain at risk of becoming threatened or endangered due to their slow rate of growth and low fecundity, and ongoing environmental changes in the Arctic. In this context, we used satellite-linked time-depth recorders (SDR-T16) to investigate their movements and dive behaviour and identify plausible summer feeding areas in the Canadian Arctic. Seven individuals from the northern Foxe Basin (FB) (n = 4 in July 2003) and Cumberland Sound (CS) (n = 3 in July 2006) were tracked by satellite for 17 to 293 d. Movement patterns from 4 whales were analyzed using a hidden Markov model (HMM) to inform the probability of whales being in one of 2 behavioural modes: transient or resident. Comparing dive characteristics during transient and resident periods, we observed that the Gulf of Boothia (GB) with moderate ice coverage (54−62%) was used as a summer foraging area by all 4 whales even though they came from different regions. All animals transited rapidly through Fury and Hecla Strait, an area of heavy ice coverage (80−98%). Whales spent most of their time at shallow depths (8−16 m) regardless of time of day when in resident mode, likely feeding on near-surface aggregations of zooplankton. Considering the apparent importance of the GB as a feeding area for this population, every effort should be made to maintain the integrity of this ecosystem.

Satellite telemetry is used routinely to collect and transmit movement, behaviour and environmental data from free-ranging animals. Satellite tags (hereafter SATs) are essential for collecting in situ data from animals where manual retrieval of a data logger is impossible. The collected data is fundamental for scientific and many management applications. However, the amount of data a SAT can transmit is limited by its battery life, transmission opportunities, bandwidth and satellite coverage. When designing a SAT study, these factors should be taken into account to ensure that limited transmissions are utilized as effectively as possible. In this paper we present a theoretical discussion of the factors that influence the data transmission and present tools for designing effective SAT studies. We calculate the optimal sampling period for the tag given its expected lifetime and regional variation in satellite coverage. Taking these factors into account allows prediction of the expected number of tags required to meet targets for a deployment. These methods are applied to a case study of a highly migratory pelagic fish tagged with popup archival satellite tags (PSATs). Our findings will be useful for SAT study design in general and demonstrate an approach which can reduce the ad hoc nature of SAT deployments.

We present a process-based approach to estimate residency and behavior from uncertain and temporally correlated movement data collected with electronic tags. The estimation problem is formulated as a hidden Markov model (HMM) on a spatial grid in continuous time, which allows straightforward implementation of barriers to movement. Using the grid to explicitly resolve space, location estimation can be supplemented by or based entirely on environmental data (e.g. temperature, daylight). The HMM method can therefore analyze any type of electronic tag data. The HMM computes the joint posterior probability distribution of location and behavior at each point in time. With this, the behavioral state of the animal can be associated to regions in space, thus revealing migration corridors and residence areas. We demonstrate the inferential potential of the method by analyzing satellite-linked archival tag data from a southern bluefin tuna Thunnus maccoyii where longitudinal coordinates inferred from daylight are supplemented by latitudinal information in recorded sea surface temperatures.

Foraging theory predicts that mobile predators should target high profitability areas with plentiful resources and minimize time spent moving between these areas. This has led to a focus in recent literature on the identification of "hotspots" important for migratory marine predators, i.e., regions where predators spend disproportionate amounts of time ostensibly due to high prey abundance; and determination of the environmental features characteristic of such areas. We investigated factors predicting foraging success in southern bluefin tuna (SBT; Thunnus maccoyii ), by integrating telemetry-based feeding and movement data ( n = 19 fish, length to caudal fork [LCF] = 99 ± 3 cm) with environmental data over the scale of their annual oceanic migrations during 1998–2000. We used widely available statistical modeling techniques, generalized linear models, and generalized linear mixed models, formulated to represent feeding as a Markov process. The results showed increased feeding and predictability of feeding occurs in the coastal waters of southern Australia, providing some evidence that this area represents a fixed foraging "hotspot" for juvenile tuna during the austral summer. However, in oceanic waters southern bluefin tuna did not fit the common model of migration, but rather showed a pattern of relatively high foraging success throughout their migratory range, especially during periods of continuous travel. Interestingly, foraging "coldspots" (prolonged low-feeding periods) as well as "hotspots" were apparent across individual tracks, predicted most strongly by warm ocean temperatures. These results provide a new perspective on the ecology of large-scale feeding migrations within the context of the heterogeneous ocean environment, where the continuous and opportunistic feeding of generalist predators may be more common, particularly in predatory large pelagic fishes, than is currently documented.

Data on the depth and temperature preferences of bigeye tuna (Thunnus obesus) derived from archival tags were integrated with data on the spatial and temporal distribution of catches from an eastern Australian longline fishery to investigate the relationship between bigeye tuna behaviour and the fishery. Tagged individuals demonstrated variability in depth and water temperature preferences on diurnal, lunar, and seasonal scales. Deeper, cooler waters were frequented dur- ing the day, and shallower, warmer waters were frequented at night, with nighttime preferences often deeper around the full moon, although this was not consistent between individuals or temporally within individuals. Marked individual varia- bility in depth and water temperature preferences suggest bigeye tuna are flexible in foraging strategies utilized, thereby al- lowing individuals to maximize their ability to successfully forage in a patchy environment. Catches of bigeye tuna corresponded with the spatial and temporal overlap of bigeye tuna distributions within the fishery on similar scales, sug- gesting clear influence of bigeye tuna behaviour on the behaviour of the fishery and catches. However, variability in these relationships suggests that the factors influencing the relative catchability of bigeye tuna are complex, and there are likely to be a range of additional environmental, behavioural, and operational factors that influence bigeye tuna catchability. Resume´ : Afin d'etudier la relation entre le comportement et la peche commerciale chez le thon ventru (Thunnus obesus), nous avons integredes donnees sur les preferences de profondeur et de temperature des thons provenant d'etiquettes enre- gistreuses avec des informations sur la repartition spatiale et temporelle des captures dans une peche commerciale ala pal- angre dans l'est de l'Australie. Les individus marques montrent une variabilitede leurs preferences de profondeur et de temperature de l'eau sur des echelles diurnes, lunaires et saisonnieres. Ils frequentent les eaux plus profondes et plus fraoˆches durant le jour et les eaux moins profondes et plus chaudes durant la nuit, avec souvent des preferences pour les eaux plus profondes la nuit au moment de la pleine lune, bien que ce comportement ne soit coherent ni chez les differents individus, ni dans le temps chez un meme individu. La variabiliteindividuelle importante dans les preferences de profon- deur et de temperature de l'eau laisse croire que les strategies de recherche de nourriture des thons ventrus sont flexibles, ce qui permet aux individus de maximiser leur capaciteachercher leur nourriture dans les environnements parcellaires. Les captures de thons ventrus correspondent au recouvrement des repartitions des thons dans les sites de peche sur les memes echelles, ce qui indique qu'il y a une nette influence du comportement des thons ventrus sur le deroulement de la peche et les captures. Cependant, la variabilitede ces relations indique que les facteurs qui influencent la capturabilitedes thons sont complexes et qu'il y a vraisemblablement une gamme de facteurs additionnels environnementaux, comporte- mentaux et operationnels qui influencent la capturabilitedes thons ventrus. (Traduit par la Redaction)

1. Seasonal long-distance migrations are often expected to be related to resource distribution, and foraging theory predicts that animals should spend more time in areas with relatively richer resources. Yet for highly migratory marine species, data on feeding success are difficult to obtain. We analysed the temporal feeding patterns of wild juvenile southern bluefin tuna from visceral warming patterns recorded by archival tags implanted within the body cavity. 2. Data collected during 1998-2000 totalled 6221 days, with individual time series (n = 19) varying from 141 to 496 days. These data span an annual migration circuit including a coastal summer residency within Australian waters and subsequent migration into the temperate south Indian Ocean. 3. Individual fish recommenced feeding between 5 and 38 days after tagging, and feeding events (n = 5194) were subsequently identified on 76.3 +/- 5.8% of days giving a mean estimated daily intake of 0.75 +/- 0.05 kg. 4. The number of feeding events varied significantly with time of day with the greatest number occurring around dawn (58.2 +/- 8.0%). Night feeding, although rare (5.7 +/- 1.3%), was linked to the full moon quarter. Southern bluefin tuna foraged in ambient water temperatures ranging from 4.9 degrees C to 22.9 degrees C and depths ranging from the surface to 672 m, with different targeting strategies evident between seasons. 5. No clear relationship was found between feeding success and time spent within an area. This was primarily due to high individual variability, with both positive and negative relationships observed at all spatial scales examined (grid ranges of 2 x 2 degrees to 10 x 10 degrees ). Assuming feeding success is proportional to forage density, our data do not support the hypothesis that these predators concentrate their activity in areas of higher resource availability. 6. Multiple-day fasting periods were recorded by most individuals. The majority of these (87.8%) occurred during periods of apparent residency within warmer waters (sea surface temperature15 degrees C) at the northern edge of the observed migratory range. These previously undocumented nonfeeding periods may indicate alternative motivations for residency. 7. Our results demonstrate the importance of obtaining information on feeding when interpreting habitat utilization from individual animal tracks.

Pop-up satellite archival tags (PSATs) were deployed on 52 large (156–200 cm length to caudal fork) southern bluefin tuna (Thunnus maccoyii) in the western Tasman Sea during the austral winters of 2001–2005. Southern bluefin tuna (SBT) were resident in the Tasman Sea for up to 6 months with movements away from the tagging area occurring at highly variable rates. The data indicated a general tendency for SBT to move south from the tagging area in the Western Tasman Sea. Four individuals migrated west along the southern continental margin of Australia and into the Indian Ocean. Three individuals moved east into the central Tasman Sea, with one individual reaching New Zealand. We also describe the first observed migration of an SBT from the Tasman Sea to the Indian Ocean spawning grounds south of Indonesia. Individuals spent most of their time relatively close to the Australian coast, with an estimated 84% of time spent in the Australian Fishing Zone. SBT favored temperatures between 19 and 21°C, adjusting their depth to the vertical temperature distribution. Distinct diurnal diving patterns were observed and adjustment of depth to maintain constant ambient light levels over a 24-h period. The findings of this study are a significant advance toward greater understanding of the spatial dynamics of large SBT and understanding the connectivity between distant regions of their distribution.

Analysis of complex time-series data from ecological system study requires quantitative tools for objective description and classification. These tools must take into account largely ignored problems of bias in manual classification, autocorrelation, and noise. Here we describe a method using existing estimation techniques for multivariate-normal hidden Markov models (HMMs) to develop such a classification. We use high-resolution behavioral data from bio-loggers attached to free-roaming pelagic tuna as an example. Observed patterns are assumed to be generated by an unseen Markov process that switches between several multivariate-normal distributions. Our approach is assessed in two parts. The first uses simulation experiments, from which the ability of the HMM to estimate known parameter values is examined using artificial time series of data consistent with hypotheses about pelagic predator foraging ecology. The second is the application to time series of continuous vertical movement data from yellowfin and bigeye tuna taken from tuna tagging experiments. These data were compressed into summary metrics capturing the variation of patterns in diving behavior and formed into a multivariate time series used to estimate a HMM. Each observation was associated with covariate information incorporating the effect of day and night on behavioral switching. Known parameter values were well recovered by the HMMs in our simulation experiments, resulting in mean correct classification rates of 90-97%, although some variance-covariance parameters were estimated less accurately. HMMs with two distinct behavioral states were selected for every time series of real tuna data, predicting a shallow warm state, which was similar across all individuals, and a deep colder state, which was more variable. Marked diurnal behavioral switching was predicted, consistent with many previous empirical studies on tuna. HMMs provide easily interpretable models for the objective classification of many different types of noisy autocorrelated data, as typically found across a range of ecological systems. Summarizing time-series data into a multivariate assemblage of dimensions relevant to the desired classification provides a means to examine these data in an appropriate behavioral space. We discuss how outputs of these models can be applied to bio-logging and other imperfect behavioral data, providing easily interpretable models for hypothesis testing.

International audience; We review present understanding of the spatial and temporal diet variability (trophodynamics) of a range of pelagic marine top predators, at both early and adult life history stages. We begin with a review of methodologies used to advance our understanding of the trophodynamics of marine top predators, particularly in relation to climate change. We then explore how these developments are informing our understanding of the major trophic groups in food webs leading to, and including, marine top predators. We examine through specific examples how the impacts of ocean warming may affect pelagic food web relationships from both top-down and bottom-up perspectives. We examine the potential, in the absence of long-term data sets, of using large-scale spatial studies to examine how potential changes in biological oceanography could impact the biomass and composition of prey species, particularly the role of phytoplankton size spectra. We focus on examples from regions where biotic change with respect to climate change is likely. In particular, we detail the effects of climate change on oceanographic and bathymetric "hotspots" and provide the example involving seabirds in the Benguela Current system. We end by urging the development of international collaborations and databases to facilitate comprehensive ocean-scale understanding of climate impacts on marine top predators.