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Successful marine spatial planning relies on understanding patterns of human use, with accurate, detailed, and up-to-date information about the spatial distribution of fishing effort. In commercial vessels, tracking systems like the vessel monitoring system (VMS) or the automatic identification system (AIS) have helped to maintain and enhance the biodiversity of areas by generating large sources of positional data that served for commercial marine spatial planning. However, there is no regulation regarding location systems such as VMS or AIS for marine recreational fishing boats. Obtaining spatial data on marine recreational fishing can be difficult and time-intensive given the widespread and variable nature of the fleet. Remote cameras and computer vision systems are increasingly used to overcome the cost limitations of these conventional methods. Here we show a novel high-resolution and low-cost tracking system based on photo time-lapses and state-of-the-art computer vision algorithms, including deep learning, to automatically classify and obtain precise trajectories of fishing and cruising boats in coastal areas. Our method contributes to the automatic surveillance of marine protected areas by providing an image-based tool for automatic, real-time monitoring. Our method also allows for determining the intensity and spatial-temporal distribution of recreational fishing effort, important to defining the sustainability of the activity and coastal areas. We finally discuss the opportunities and limitations of computer vision tools applied to marine recreational fisheries spatial planning.

Like terrestrial animals, wild fish exhibit individual differences in daily activity patterns, known as chronotypes. However, monitoring free-living fish has posed challenges in studying chronotypes and their plasticity in response to the environment. To address this issue, we utilized high-throughput telemetry to measure daily activity in a large group of free-living pearly razorfish, Xyrichtys novacula, while also monitoring fine-scale environmental variables. Using hidden Markov models for behavioural segmentation, we quantified four circadian-related traits (awakening time, rest onset, activity duration relative to the daytime and rest midpoint relative to middle of the night) during two biological contexts (prespawning and spawning). We then used linear mixed-effects models to decompose the variation of these traits into individual, ecological (contextual environment) and population components. Our findings revealed the presence of chronotypes in both sexes, with greater between-individual variation in behaviour during spawning. Males exhibited longer activity duration due to an earlier awakening time than females, and temperature, waves and light significantly influenced daily activity behaviours. However, there was considerable individual variation in response to environmental changes, indicating the emergence of behavioural reaction norms (i.e. plasticity), with females showing greater plasticity in rest onset and relative rest midpoint. Our study also identified significant correlations among traits, suggesting that the activity duration continuum defines the pearly razorfish chronotype. Overall, our work represents the most comprehensive description of individual and ecological contextual variation in chronotypes within a wild marine fish population. It underscores the importance of environmental fluctuations in shaping the expression of internal clocks.

Geolocating aquatic animals with acoustic tags has been ongoing for decades, relying on the detection of acoustic signals at multiple receivers with known positions to calculate a 2D or 3D position, and ultimately recreate the path of an aquatic animal from detections at fixed stations. This method of underwater geolocation is evolving with new software and hardware options available to help investigators design studies and calculate positions using solvers based predominantly on time-difference-of-arrival and time-of-arrival. We provide an overview of the considerations necessary to implement positioning in aquatic acoustic telemetry studies, including how to design arrays of receivers, test performance, synchronize receiver clocks and calculate positions from the detection data. We additionally present some common positioning algorithms, including both the free open-source solvers and the ‘black-box’ methods provided by some manufacturers for calculating positions. This paper is the first to provide a comprehensive overview of methods and considerations for designing and implementing better positioning studies that will support users, and encourage further knowledge advances in aquatic systems

One of the most relevant information gaps in worldwide fisheries is related to the origin and consequences of the gender gap. Recreational fisheries show a remarkable gender gap, which has been especially poorly addressed in the scientific literature. In 2021, the Spanish Working Group on Marine Recreational Fishing (MRF) developed a broad diagnosis on the participation of women in MRF and agreed on a roadmap to address negative impacts derived from the gender gap. The network experts concluded that there is an urgent need to include the gender gap in the agendas of scientists, fishery managers, policy-makers, stakeholder organizations, and civil society. There is a need to better understand the gender-related socio-ecological impacts of MRF to improve fisheries governance and to develop policies and initiatives that facilitate the full access of women to the benefits derived from the practice of MRF. Establishing economic incentives, increasing the visibility of female success references, developing fishing-related programs specifically designed for girls, and promoting the perception of MRF as a family leisure activity in contact with nature will increase women’s engagement.

The pearly razorfish (Xyrichtys novacula), commonly known as raor in the Balearic Islands, is a wrasse within the family Labridae. This fish species has particular biological and socio-cultural characteristics making it an ideal model organism in the fields of behavioural ecology, molecular ecology and conservation biology. In this study, we present the first annotated chromosome-level assembly for this species. Sequencing involved a combination of long reads with Oxford Nanopore Technologies, Illumina paired-end short reads (2 × 151 bp), Hi-C and RNA-seq from different tissues. The nuclear genome assembly has a scaffold N50 of 34.33 Mb, a total assembly span of 775.53 Mb and 99.63% of the sequence assembled into 24 superscaffolds, consistent with its known karyotype. Quality metrics revealed a consensus accuracy (QV) of 42.92 and gene completeness > 98%. The genome annotation resulted in 26,690 protein-coding genes and 12,737 non-coding transcripts. The coding regions encoded 39,613 unique protein products, 93% of them with assigned function. Overall, the publication of the X. novacula's reference genome will broaden the scope and impact of genomic research conducted on this iconic and colourful species.

Further investigation is needed to improve the identification and classification of fish in underwater images using artificial intelligence, specifically deep learning. Questions that need to be explored include the importance of using diverse backgrounds, the effect of (not) labeling small fish on precision, the number of images needed for successful classification, and whether they should be randomly selected. To address these questions, a new labeled dataset was created with over 18,400 recorded Mediterranean fish from 20 species from over 1,600 underwater images with different backgrounds. Two state-of-the-art object detectors/classifiers, YOLOv5m and Faster RCNN, were compared for the detection of the ‘fish’ category in different datasets. YOLOv5m performed better and was thus selected for classifying an increasing number of species in six combinations of labeled datasets varying in background types, balanced or unbalanced number of fishes per background, number of labeled fish, and quality of labeling. Results showed that i) it is cost-efficient to work with a reduced labeled set (a few hundred labeled objects per category) if images are carefully selected, ii) the usefulness of the trained model for classifying unseen datasets improves with the use of different backgrounds in the training dataset, and iii) avoiding training with low-quality labels (e.g., small relative size or incomplete silhouettes) yields better classification metrics. These results and dataset will help select and label images in the most effective way to improve the use of deep learning in studying underwater organisms., Postprint (published version)

Geolocating aquatic animals with acoustic tags has been ongoing for decades, relying on the detection of acoustic signals at multiple receivers with known positions to calculate a 2D or 3D position, and ultimately recreate the path of an aquatic animal from detections at fixed stations. This method of underwater geolocation is evolving with new software and hardware options available to help investigators design studies and calculate positions using solvers based predominantly on time-difference-of-arrival and time-of-arrival. We provide an overview of the considerations necessary to implement positioning in aquatic acoustic telemetry studies, including how to design arrays of receivers, test performance, synchronize receiver clocks and calculate positions from the detection data. We additionally present some common positioning algorithms, including both the free open-source solvers and the ‘black-box’ methods provided by some manufacturers for calculating positions. This paper is the first to provide a comprehensive overview of methods and considerations for designing and implementing better positioning studies that will support users, and encourage further knowledge advances in aquatic systems.

Chronotypes, the individual differences in daily activity timing, have profound associations with numerous physiological processes. Despite this, the covariance between chronotypes and other aspects of an individual's behaviour has been infrequently explored in non-human animals. This study delves into individual's variation across four axes of personality in a controlled environment, utilising the pearly razorfish, a model species for fish chronotype studies. We identified behavioural types across the aggressiveness continuum and established behavioural syndromes amongst exploration, activity, and boldness, irrespective of body size and condition. Subsequent to this, the experimental subjects were reintroduced to their natural habitat and individually tracked using high-resolution technology to ascertain their chronotypes. Our results revealed that whilst the exploration-activity-boldness syndrome bore no correlation with chronotypes, a significant association was observed between aggressiveness and chronotype. Hence, individuals with later awakening times and rest onsets were more aggressive than their counterparts with earlier awakening times and rest onsets. This study provides pioneering evidence linking fish chronotypes with other behavioural traits, such as aggressiveness, suggesting that behavioural variation could be potentially linked to the individuals' variation in internal clocks and the environmental variables influencing their expression.

The northern pike (Esox lucius) has been intensively studied in terms of behaviour due to its relevance to fisheries and its importance for structuring fish communities in freshwater ecosystems. However, little is known about the behaviour of coastal pike living in brackish lagoons. Freshwater ecosystems, particularly lakes and small rivers, are usually finite in space, which can limit the expression of space use as a function of body size and other traits. Better understanding the spatial behaviour shown by coastal pike in extended brackish lagoons and its relationship to body size, sex, season and vulnerability to fishing is an important step to further our knowledge on brackish pike populations and can inform management. Here, we present two years of acoustic telemetry data acquired on a large sample of coastal pike (n = 210) with an extended size range (480 to 1.210 mm total length) inhabiting six interconnected coastal lagoons bordered by the islands of Fischland-Darß-Zingst, Hiddensee, Rügen and Usedom in the Baltic Sea (area ca. 1.200 km²). Overall, the space used by coastal pike (50 % and 95 % utilization distribution, UD) scaled positively with body size, with larger fish using significantly more space after controlling for co-variates, but this effect was mainly observed at the between lagoon level. Within a given lagoon, body size scaling of space use was only observed for the 50 % UD of males. We also found the ratio of 50 % UD on 95 % UD to scale negatively with size, meaning that larger-sized pike used areas out of their core ranges more intensively regardless of sex. Space use also differed between seasons, with activity spaces being elevated in spring likely due to spawning migrations and increased reproduction-related activity. Study design was an important co-variate for our space use proxies, as we collected proportionally more data on pike that used less space, but fish recaptured by fisheries did not differ in space use from those that were not

Recent technological advances in marine biotelemetry have demonstrated that marine fish species perform activity-rest rhythms that have relevant ecological and evolutionary consequences. The main objective of the present report is to study the circadian rhythm of activity-rest of the pearly razorfish, Xyrichtys novacula in its own habitat, before and during the reproduction season using a novel biotelemetry system. This fish species is a small-bodied marine species that inhabits most shallow soft habitats of temperate areas and has a high interest for commercial and recreational fisheries. The activity of free-living fish was monitored by means of high-resolution acoustic tracking of the motor activity of the fish in one-minute intervals. The obtained data allowed the definition of the circadian rhythm of activity-rest in terms of classical non-parametric values: interdaily stability (IS), intradaily variability (IV), relative amplitude (RA), average activity during the most-active period of consecutive 10 h (M10), and average activity during the least-active period of consecutive 5 h (L5). We observed a well-marked rhythm, with little fragmentation and good synchrony with the environmental cycle of light-darkness, regardless of sex and the period studied. However, the rhythm was found to be slightly more desynchronized and fragmented during reproduction because of variations in the photoperiod. In addition, we found that the activity of the males was much higher than that of the females (p < 0.001), probably due to the peculiar behavior of the males in defending the harems they lead. Finally, the time at which activity began in males was slightly earlier than it was in females (p < 0.001), presumably due to the same fact, as differences in activity or for the individual heterogeneity of this species in the time of awakening are considered to be an independent axis of the fish's personality. Our work is novel, as it is one of the first studies of activity-rest rhyth

Novel insights were provided by contrasting the composition of wild and farmed fish gut microbiomes because the latter had essentially different environmental conditions from those in the wild. This was reflected in the gut microbiome of the wild Sparus aurata and Xyrichtys novacula studied here, which showed highly diverse microbial community structures, dominated by Proteobacteria, mostly related to an aerobic or microaerophilic metabolism, but with some common shared major species, such as Ralstonia sp. On the other hand, farmed non-fasted S. aurata individuals had a microbial structure that mirrored the microbial composition of their food source, which was most likely anaerobic, since several members of the genus Lactobacillus, probably revived from the feed and enriched in the gut, dominated the communities. The most striking observation was that after a short fasting period (86 h), farmed gilthead seabream almost lost their whole gut microbiome, and the resident community associated with the mucosa had a very much reduced diversity that was highly dominated by a single potentially aerobic species Micrococcus sp., closely related to M. flavus. The results pointed to the fact that, at least for the juvenile S. aurata studied, most of the microbes in the gut were transient and highly dependent on the feed source, and that only after fasting for at least 2 days could the resident microbiome in the intestinal mucosa be determined. Since an important role of this transient microbiome in relation to fish metabolism could not be discarded, the methodological approach needs to be well designed in order not to bias the results. The results have important implications for fish gut studies that could explain the diversity and occasional contradictory results published in relation to the stability of marine fish gut microbiomes, and might provide important information for feed formulation in the aquaculture industry.

One of the most relevant information gaps in worldwide fisheries is related to the origin and consequences of the gender gap. Recreational fisheries show a remarkable gender gap, which has been especially poorly addressed in the scientific literature. In 2021, the Spanish Working Group on Marine Recreational Fishing (MRF) developed a broad diagnosis on the participation of women in MRF and agreed on a roadmap to address negative impacts derived from the gender gap. The network experts concluded that there is an urgent need to include the gender gap in the agendas of scientists, fishery managers, policy-makers, stakeholder organizations, and civil society. There is a need to better understand the gender-related socio-ecological impacts of MRF to improve fisheries governance and to develop policies and initiatives that facilitate the full access of women to the benefits derived from the practice of MRF. Establishing economic incentives, increasing the visibility of female success references, developing fishing-related programs specifically designed for girls, and promoting the perception of MRF as a family leisure activity in contact with nature will increase women’s engagement.

This dataset encompasses all necessary data required to replicate the study, `Chronotypes-Personality behavioural syndromes in wild fish’. The data were obtained through standardised behavioural tests conducted under laboratory conditions on 63 Pearly Razorfish (Xyrichtys novacula) individuals between April and July of 2019. Over a week, the fish were maintained in isolated aquariums to test their behaviours, including exploration, activity, boldness, and aggression, conducted daily. A Raspberry Pi system, equipped with the YOLOv5 deep-learning automatic tracking algorithm, was used to record these tests and calculate the fish's minute-by-minute position, providing essential data for evaluating exploration and activity. This system also stored videos to retrospectively obtain boldness and aggression data. Each test included only those individuals with at least two measurements. After the laboratory period, the fish were tagged with acoustic tags and returned to the sea to measure their chronotypes; only individuals with at least seven consecutive days of data were considered. The chronotype data, obtained from a previous study, are represented here through the previously derived scores. These laboratory-based experimental data were analysed using R software. In the exploration context, positional data were translated into total active time (TimeOut), minimum distance to the toy (MinDistance), and time spent near the toy (TimeToy). For activity, the data were converted into total active time (TimeOut), total distance covered (Distance), areas (CoreArea and Area), and direction angles (MeanAngle and KappaAngle). A Principal Component Analysis (PCA) was conducted to obtain the scores for exploration, activity, and aggressiveness. Upon acquiring these scores, trait repeatability was computed using a Linear Mixed-Effects Model, fitting the experimental day (Day), the total length of the individual (Size), and the internal condition (Condition) as fixed factors, and the i

Further investigation is needed to improve the identification and classification of fish in underwater images using artificial intelligence, specifically deep learning. Questions that need to be explored include the importance of using diverse backgrounds, the effect of (not) labeling small fish on precision, the number of images needed for successful classification, and whether they should be randomly selected. To address these questions, a new labeled dataset was created with over 18,400 recorded Mediterranean fish from 20 species from over 1,600 underwater images with different backgrounds. Two state-of-the-art object detectors/classifiers, YOLOv5m and Faster RCNN, were compared for the detection of the ‘fish’ category in different datasets. YOLOv5m performed better and was thus selected for classifying an increasing number of species in six combinations of labeled datasets varying in background types, balanced or unbalanced number of fishes per background, number of labeled fish, and quality of labeling. Results showed that i) it is cost-efficient to work with a reduced labeled set (a few hundred labeled objects per category) if images are carefully selected, ii) the usefulness of the trained model for classifying unseen datasets improves with the use of different backgrounds in the training dataset, and iii) avoiding training with low-quality labels (e.g., small relative size or incomplete silhouettes) yields better classification metrics. These results and dataset will help select and label images in the most effective way to improve the use of deep learning in studying underwater organisms

The ocean is a key component of the Earth’s dynamics, providing a great variety of ecosys- tem services to humans. Yet, human activities are globally changing its structure and major components, including marine biodiversity. In this context, the United Nations has proclaimed a Decade of Ocean Science for Sustainable Development to tackle the scientific challenges necessary for a sustainable use of the ocean by means of the Sustainable Development Goal 14 (SDG14). Here, we review how Acoustic animal Tracking, a widely distributed methodology of tracking marine biodiversity with electronic devices, can provide a roadmap for implementing the major Actions to achieve the SDG14. We show that acoustic tracking can be used to reduce and monitor the effects of marine pollution including noise, light, and plastic pollution. Acoustic tracking can be effectively used to monitor the responses of marine biodiversity to human-made infrastructures and habitat restoration, as well as to determine the effects of hypoxia, ocean warming, and acidification. Acoustic tracking has been historically used to inform fisheries man- agement, the design of marine protected areas, and the detection of essential habitats, rendering this technique particularly attractive to achieve the sustainable fishing and spatial protection target goals of the SDG14. Finally, acoustic tracking can contribute to end illegal, unreported, and unregulated fishing by providing tools to monitor marine biodiversity against poachers and promote the development of Small Islands Developing States and developing countries. To fully benefit from acoustic tracking supporting the SDG14 Targets, trans-boundary collaborative efforts through tracking networks are required to promote ocean information sharing and ocean literacy. We therefore propose acoustic tracking and tracking networks as relevant contributors to tackle the scientific challenges that are necessary for a sustainable use of the ocean promoted by the United N

In the marine realm, few barriers exist to limit the extent of animal migrations. As a result, mobile marine animals can occupy vast home ranges and undertake migrations that span across entire ocean basins. These large-scale movements can in turn, complicate both research and management occurring at local or regional scales. Advances in aquatic telemetry are continuing to allow researchers to monitor marine animal movements across greater distances and with increasing resolutions. However, for acoustic telemetry studies that typically use an array of fixed receivers to detect presence of tagged animals moving within a defined region, the spatial scale of acquired movement data is often restricted to regions delimited by invisible geographic or jurisdictional boundaries. To overcome this limitation, acoustic telemetry networks such as the European Tracking Network have been established to facilitate collaboration among movement ecologists and to house archives of detection data for more efficient data sharing. By combining the detections of individual tagged animals recorded across multiple discrete arrays, the extent of monitoring can be greatly expanded to reflect more ecologically-relevant spatial and temporal scales. To exemplify the benefit of the acoustic telemetry networks for large-scale collaboration and fundamental research on migratory fish, we have compiled examples of movement trajectories collected by an international group of researchers using multiple acoustic arrays and spanning national or international boundaries. From basin-wide migrations to cross-continental displacements, this diverse dataset demonstrates how connectivity between acoustic telemetry arrays and research institutes can lead to novel insights in movement ecology for a range of fish species

This dataset contains the necessary data to replicate the work entitled 'Circadian-related behavioural types in free-living marine fish revealed by high-throughput telemetry'. The data were obtained through a high-resolution acoustic telemetry experiment tracking a population of pearly razorfish between April and September 2019. The time series of detections were imported into the R computing environment. We discretized the detections generated by the individuals into bins of 5 minutes (time-steps). We fitted a Hidden Markov Model (HMM) to probabilistically assign two behavioural states to each temporal bin: rest (R) or active (A). We used a zero-inflated Poisson HMM implemented in the ziphsmm package. During these months, two different periods in the reproduction of this species were included: the pre-spawning period and the spawning period. For this purpose, the data were separated into two different datasets: the pre-spawning period dataset, which contains all individuals tracked for at least seven days between April 30 and May 31, and the spawning period dataset, which includes all individuals tracked for at least seven days between June 15 and July 31. The data between June 1 and June 15 were discarded due to maintenance tasks on the acoustic receivers. The data from August and September were discarded due to low data yields. Finally, a third dataset was created, which includes individuals tracked for at least seven days in each period. The three datasets are configured in the same manner, with ID as the identifier for each individual, Day as the tracking date, Dayn as the day of the trial, Awakening Time as the activity onset time in minutes relative to sunrise, Rest Onset as the rest onset time in minutes relative to sunset, RelActivityDuration as the active hours (calculated as the difference between the awakening time and rest onset) relative to daylight hours (calculated as the difference between sunrise and sunset), RelRestDuration as the resting hours (c

The rise of nature-based tourism has provided a new avenue for disturbing animal behaviour, especially in protected areas. One of the most important tourism sectors in aquatic environments is scuba diving, an activity considered sustainable given its non-extractive nature and capability of bringing relevant socio-economic benefits to local communities. However, knowledge about its impact on the activity patterns of aquatic animals is still scarce. Here, we used biotelemetry techniques to assess the importance of scuba diving in modulating the activity patterns of the dusky grouper (Epinephelus marginatus, Lowe, 1834), a marine predatory fish of high interest for fishing and tourism. We implemented Hidden Markov Models (HMMs) on high-resolution acceleration data using a temporal and spatial control while controlling for a set of environmental variables (i.e. photoperiod, time-of-day, moon phase, temperature, wave height, and intensity and direction of marine currents) within a multiple-use marine protected area, and diving tourism hot-spot, of the western Mediterranean Sea. Our results underlined the more decisive influence of environmental-related stressors on the activity patterns of the dusky grouper compared to the impact of scuba diving. A high heterogeneity existed in the response against most of the stressors, including the presence of scuba divers. Overall, the activity of dusky grouper was higher at night than at day, showing a positive relationship with wave height, water temperature, and current intensity and a negative one with the moon phase. Remarkably, our findings, based on novel biotelemetry tools, differed substantially from the common wisdom accepted for this species. In conclusion, there is no clear evidence of scuba divers influence on the general activity patterns of the dusky grouper. Beyond their relevance from an ecological perspective, these results provide useful insights for the sustainable management of coastal resources, suggesting that

Recreational fishing (RF) is a large yet undervalued component of fisheries globally. While progress has been made in monitoring, assessing, and managing the sector in isolation, integration of RF into the management of multi-sector fisheries has been limited, particularly relative to the commercial sector. This marginalises recreational fishers and reduces the likelihood of achieving the sector's objectives and, more broadly, achieving fisheries sustainability. We examined the nature and extent of RF inclusion in harvest strategies (HSs) for marine fisheries across 15 regions in 11 nations to define the gap in inclusion that has developed between sectors. We focused on high-income nations with a high level of RF governance and used a questionnaire to elicit expert knowledge on HSs due to the paucity of published documents. In total, 339 HSs were considered. We found that RF inclusion in HSs was more similar to the small-scale sector (i.e., artisanal, cultural, or subsistence) than the commercial sector, with explicit operational objectives, data collection, performance indicators, reference points, and management controls lacking in many regions. Where specified, RF objectives focused on sustainability, economic value and catch allocation rather than directly relating to the recreational fishing experience. Conflicts with other sectors included competition with the commercial sector for limited resources, highlighting the importance of equitable resource allocation policies alongside HSs. We propose that RF be explicitly incorporated into HSs to ensure fisheries are ecologically, economically, and socially sustainable, and we recommend that fisheries organisations urgently review HSs for marine fisheries with a recreational component to close the harvest strategy gap among sectors.

Despite the widespread use of stock enhancements to improve fisheries across the world, there is a lack of robust knowledge under which conditions fish stocking provides additive effects rather than merely replacing a fraction of natural recruitment. Fully controlled and replicated studies at the level of entire ecosystems are needed to provide answers. Properly monitored experimental releases also allow testing mechanisms of density- and size-dependent population regulation. In this study, the population-level outcome of stocking juvenile pike (Esox lucius L.) in naturally reproducing lentic stocks was investigated. We used a replicated before-after-control-impact design in 15 experimental lakes involving two stocking densities and unstocked controls. Releasing age-0 pike failed to generate additive effects at the age-2 cohort. As expected from theory, we observed density-dependent mortality and differential survival of wild and stocked pike. Stocked and wild fishes showed contrasting responses in terms of growth to variation in predator density, competitor density and the forage base, suggesting both subpopulations differed in their response to stocking-induced changes in population traits (e.g., density). Despite the lack of additive effects caused by stocking, a fraction of the stocked individuals established in the stock-enhanced cohort, indicating that replacement of wild recruits by stocked conspecifics had occurred. Depending on the origin of the stocking material, pike stocking thus has the potential for genetic hybridization, while not necessarily benefiting fisheries catch. We conclude that whenever a natural pike population exists, stocking juvenile pike will not produce additive effects in lakes and that enhanced pike populations will be strongly regulated by size- and density-dependent juvenile mortality and less by density-dependent growth.