Understanding animal movement is essential to elucidate how animals interact, survive, and thrive in a changing world. Recent technological advances in data collection and management have transformed our understanding of animal “movement ecology” (the integrated study of organismal movement), creating a big-data discipline that benefits from rapid, cost-effective generation of large amounts of data on movements of animals in the wild. These high-throughput wildlife tracking systems now allow more thorough investigation of variation among individuals and species across space and time, the nature of biological interactions, and behavioral responses to the environment. Movement ecology is rapidly expanding scientific frontiers through large interdisciplinary and collaborative frameworks, providing improved opportunities for conservation and insights into the movements of wild animals, and their causes and consequences.

Recent advances in tracking systems have revolutionized our ability to study animal movement in the wild. In aquatic environments, high-resolution acoustic telemetry systems make it technically possible to simultaneously monitor large amounts of individuals at unprecedented spatial and temporal resolutions, providing a unique opportunity to study the behaviour and social interactions using a reality mining approach. Despite the potential, high-resolution telemetry systems have had very limited use in coastal marine areas due to the limitations that these environments pose to the transmission of acoustic signals. This study aims at designing and testing a high-resolution acoustic telemetry system to monitor, for the first time, a natural fish population in an open marine area. First, we conducted preliminary range tests and a computer simulation study to identify the optimal design of the telemetry system. Then, we performed a series of stationary and moving tests to characterize the performance of the system in terms of positioning efficiency and precision. Finally, we obtained a dataset corresponding to the movements of 170 concurrently tagged individuals to demonstrate the overall functioning of the system with a real study case of the behaviour of a small-bodied coastal species. Our results show that high-resolution acoustic telemetry systems efficiently generate positional data in marine systems, providing a precision of few meters, a temporal resolution of few seconds, and the possibility of tracking hundreds of individuals simultaneously. Data post-processing using a trajectory filter and movement models proved to be key to achieve a sub-meter positioning precision. The main limitation detected for our system was the restricted detection range, which was negatively affected by the stratification of the water column. Our work demonstrates that high-resolution acoustic telemetry systems are an effective method to monitor the movements of free-ranging individuals at the population level in coastal sites. By providing highly precise positioning estimates of large amounts of individuals, these systems represent a powerful tool to study key ecological processes regarding the social interactions of individuals, including social dynamics, collective movements, or responses to environmental perturbations, and to extend the studies to poorly studied small-sized species or life-stages.

The measurement of animal density may take advantage of recent technological achievements in wildlife video recording. Fostering the theoretical links between the patterns depicted by cameras and absolute density is required to exploit this potential. We explore the applicability of the Hutchinson-Waser's postulate (i.e. when animal density is stationary at a given temporal and spatial scale, the absolute density is given by the average number of animals counted per frame), which is a counter-intuitive statement for most ecologists and managers who are concerned with counting the same individual more than once. We aimed to reconcile such scepticism for animals displaying home range behaviour. The specific objectives of this paper are to generalize the Hutchinson-Waser's postulate for animals displaying home range behaviour and to propose a Bayesian implementation to estimate density from counts per frame using video cameras. Accuracy and precision of the method was evaluated by means of computer simulation experiments. Specifically, six animal archetypes displaying well-contrasted movement features were considered. The simulation results demonstrate that density could be accurately estimated after an affordable sampling effort (i.e. number of cameras and deployment time) for a great number of animals across taxa. The proposed method may complement other conventional methods for estimating animal density. The major advantages are that identifying an animal at the individual level and precise knowledge on how animals move are not needed, and that density can be estimated in a single survey. The method can accommodate conventional camera trapping data. The major limitations are related to some implicit assumptions of the underlying model: the home range centres should be homogeneously distributed, the detection probability within the area surveyed by the camera should be known, and animals should move independently to one another. Further improvements for circumventing these limitations are discussed.

Repeatable between-individual differences in the behavioural manifestation of underlying circadian rhythms determine chronotypes in humans and terrestrial animals. Here, we have repeatedly measured three circadian behaviours, awakening time, rest onset and rest duration, in the free-ranging pearly razorfish, Xyrithchys novacula, facilitated by acoustic tracking technology and hidden Markov models. In addition, daily travelled distance, a standard measure of daily activity as fish personality trait, was repeatedly assessed using a State-Space Model. We have decomposed the variance of these four behavioural traits using linear mixed models and estimated repeatability scores (R) while controlling for environmental co-variates: year of experimentation, spatial location of the activity, fish size and gender and their interactions. Between- and within-individual variance decomposition revealed significant Rs in all traits suggesting high predictability of individual circadian behavioural variation and the existence of chronotypes. The decomposition of the correlations among chronotypes and the personality trait studied here into between- and within-individual correlations did not reveal any significant correlation at between-individual level. We therefore propose circadian behavioural variation as an independent axis of the fish personality, and the study of chronotypes and their consequences as a novel dimension in understanding within-species fish behavioural diversity.

Consistent between‐individual differences in movement are widely recognised across taxa. In addition, foraging plasticity at the within‐individual level suggests a behavioural dependency on the internal energy demand. Because behaviour co‐varies with fast‐slow life history (LH) strategies in an adaptive context, as theoretically predicted by the pace‐of‐life syndrome hypothesis, mass/energy fluxes should link behaviour and its plasticity with physiology at both between‐ and within‐individual levels. However, a mechanistic framework driving these links in a fluctuating ecological context is lacking. Focusing on home range behaviour, we propose a novel behavioural‐bioenergetics theoretical model to address such complexities at the individual level based on energy balance. We propose explicit mechanistic links between behaviour, physiology/metabolism and LH by merging two well‐founded theories, the movement ecology paradigm and the dynamic energetic budget theory. Overall, our behavioural‐bioenergetics model integrates the mechanisms explaining how (1) behavioural between‐ and within‐individual variabilities connect with internal state variable dynamics, (2) physiology and behaviour are explicitly interconnected by mass/energy fluxes, and (3) different LHs may arise from both behavioural and physiological variabilities in a given ecological context. Our novel theoretical model reveals encouraging opportunities for empiricists and theoreticians to delve into the eco‐evolutionary processes that favour or hinder the development of between‐individual differences in behaviour and the evolution of personality‐dependent movement syndromes.

In the Balearic Islands, different trammel net designs have been adopted to promote fisheries sustainability and reduce discards. Here, we compare the catch performance of three trammel net designs targeting the spiny lobster Palinurus elephas in terms of biomass, species composition and revenue from commercial catches and discards. Designs differ in the netting fiber type (standard polyfilament, PMF, or a new polyethylene multi-monofilament, MMF) and the use of a guarding net or greca, a mesh piece intended to reduce discards. Catches were surveyed by an on-board observer from 1,550 netting walls corresponding to 70 nets. The number of marketable species captured indicated that the lobster trammel net fishery has multiple targets, which contribute significantly to the total revenue. The discarded species ranged from habitat-forming species to elasmobranches, but the magnitude of gear-habitat interactions on the long term dynamics of benthos remains unclear. No relevant differences in revenue and weight of discards were detected after Bayesian analyses. However, the species composition of discards was different when using greca. Interestingly, high immediate survival was found for discarded undersized lobsters, while a seven day survival assessment, using captive observation, gave an asymptotic estimate of survival probability as 0.64 (95% CI [0.54–0.76]). Therefore, it is recommended that it would be beneficial for this stock if an exemption from the EU landing obligation regulation was sought for undersized lobsters in the Balearic trammel net fishery.

2Technological advances in underwater video recording are opening novel opportunities for monitoring wild fish. However, extracting data from videos is often challenging. Nevertheless, it has been recently demonstrated that accurate and precise estimates of density for animals (whose normal activities are restricted to a bounded area or home range) can be obtained from counts averaged across a relatively low number of video frames. The method, however, requires that individual detectability (P ID , the probability of detecting a given animal provided that it is actually within the area surveyed by a camera) has to be known. Here we propose a Bayesian implementation for estimating P ID after combining counts from cameras with counts from any reference method. The proposed framework was demonstrated using Serranus scriba as a case-study, a widely distributed and resident coastal fish. Density and P ID were calculated after combining fish counts from unbaited remote underwater video (RUV) and underwater visual censuses (UVC) as reference method. The relevance of the proposed framework is that after estimating P ID , fish density can be estimated accurately and precisely at the UVC scale (or at the scale of the preferred reference method) using RUV only. This key statement has been extensively demonstrated using computer simulations yielded by real empirical data. Finally, we provide a simulation tool-kit for comparing the expected precision attainable for different sampling effort and for species with different levels of P ID .Overall, the proposed method may contribute to substantially enlarge the spatio-temporal scope of density monitoring programs for many resident fish.

The selective properties of fishing that influence behavioural traits have recently gained interest. Recent acoustic tracking experiments have revealed between-individual differences in the circadian behavioural traits of marine free-living fish; these differences are consistent across time and ecological contexts and generate different chronotypes. Here, we hypothesised that the directional selection resulting from fishing influences the wild circadian behavioural variation and affects differently to individuals in the same population differing in certain traits such as awakening time or rest onset time. We developed a spatially explicit social-ecological individual-based model (IBM) to test this hypothesis. The parametrisation of our IBM was fully based on empirical data; which represent a fishery formed by patchily distributed diurnal resident fish that are exploited by a fleet of mobile boats (mostly bottom fisheries). We ran our IBM with and without the observed circadian behavioural variation and estimated selection gradients as a quantitative measure of trait change. Our simulations revealed significant and strong selection gradients against early-riser chronotypes when compared with other behavioural and life-history traits. Significant selection gradients were consistent across a wide range of fishing effort scenarios. Our theoretical findings enhance our understanding of the selective properties of fishing by bridging the gaps among three traditionally separated fields: fisheries science, behavioural ecology and chronobiology. We derive some general predictions from our theoretical findings and outline a list of empirical research needs that are required to further understand the causes and consequences of circadian behavioural variation in marine fish.