Estimating Natural Mortality of Atlantic Bluefin Tuna Using Acoustic Telemetry

Heart Rate and Acceleration Dynamics during Swim-Fitness and Stress Challenge Tests in Yellowtail Kingfish (Seriola lalandi)

The yellowtail kingfish is a highly active and fast-growing marine fish with promising potential for aquaculture. In this study, essential insights were gained into the energy economy of this species by heart rate and acceleration logging during a swim-fitness test and a subsequent stress challenge test. Oxygen consumption values of the 600-800 g fish, when swimming in the range of 0.2 up to 1 m·s-1, were high-between 550 and 800 mg·kg-1·h-1-and the heart rate values-up to 228 bpm-were even among the highest ever measured for fishes. When swimming at these increasing speeds, their heart rate increased from 126 up to 162 bpm, and acceleration increased from 11 up to 26 milli-g. When exposed to four sequential steps of increasing stress load, the decreasing peaks of acceleration (baseline values of 12 to peaks of 26, 19 and 15 milli-g) indicated anticipatory behavior, but the heart rate increases (110 up to 138-144 bpm) remained similar. During the fourth step, when fish were also chased, peaking values of 186 bpm and 44 milli-g were measured. Oxygen consumption and heart rate increased with swimming speed and was well reflected by increases in tail beat and head width frequencies. Only when swimming steadily near the optimal swimming speed were these parameters strongly correlated.

Spatially explicit estimation of freshwater fish stock biomass with limited data: A case study of an endangered endemic fish on the Tibetan Plateau, China

Accurate evaluation of fish stock biomass is essential for effective conservation management and targeted species enhancement efforts. However, this remains challenging owing to limited data availability. Therefore, we present an integrated modeling framework combining catch per unit effort with ensemble species distribution modeling called CPUESDM, which explicitly assesses and validates the spatial distribution of stock biomass for freshwater fish species with limited data, applied to Herzensteinia microcephalus. The core algorithm incorporates the Leslie regression model, ensemble species distribution modeling, and exploratory spatial interpolation techniques. We found that H. microcephalus biomass in the Yangtze River source area yielded an initial estimate of 113.52 tons. Our validation results demonstrate high accuracy with a Cohen's kappa coefficient of 0.78 and root mean square error of 0.05. Furthermore, our spatially-explicit, global, absolute biomass density map effectively identified areas with high and low concentrations of biomass distribution centers. Additionally, this study offers access to the source code, example raw data, and a step-by-step instruction manual for other researchers using field data to explore the application of this model. Our findings can help inform for future conservation efforts around fish stock biomass estimation, especially for endangered species.

The use of predator tags to explain reversal movement patterns in Atlantic salmon smolts (Salmo salar L.)

Acoustic telemetry has seen a rapid increase in utility and sophistication in recent years and is now used extensively to assess the behavior and survival rates of many aquatic animals, including the Atlantic salmon. As part of the salmon's complex life cycle, salmon smolts are thought to make a unidirectional migration from fresh water to the sea, which is initiated by changes in their physiology. However, some tag movement patterns do not conform with this and can be difficult to explain, particularly if the tagged fish has been eaten by a predator. This study combines the use of predator tags with machine learning techniques to understand the fate of migrating salmon smolts and thereby improve estimates for migration success. Over 3 years between 2020 and 2022, 217 salmon smolts (including wild and hatchery-reared ranched fish) were acoustically tagged and released into an embayment on the west coast of Ireland. Some tagged smolts were observed to return from the estuary back into a saline lagoon through which they had already migrated. To distinguish between the movement of a salmon smolt and that of a predator, predator tags were deployed in migrating smolts in 2021 and 2022. The addition of a temperature sensor in 2022 enabled the determination of predator type causing the returning movement. A significant number of predator tags were triggered, and the patterns of movement associated with these triggered tags were then used with two types of machine learning algorithms (hierarchical cluster analysis and random forest) to identify and validate the behavior of smolts tagged without extra sensors. Both models produced the same outputs, grouping smolts tagged with predator tags with smolts tagged without the additional sensors but showing similar movements. A mammalian predator was identified as the cause of most reversal movement, and hatchery-reared ranched smolts were found to be more likely predated upon by this predator than wild smolts within the lake and the estuary. However, overall migration success estimates were similar for both wild and hatchery-reared ranched fish. This study highlights the value of predator tags as an essential tool in the overall validation of detection data.

What acoustic telemetry can and cannot tell us about fish biology

Acoustic telemetry (AT) has become ubiquitous in aquatic monitoring and fish biology, conservation, and management. Since the early use of active ultrasonic tracking that required researchers to follow at a distance their species of interest, the field has diversified considerably, with exciting advances in both hydrophone and transmitter technology. Once a highly specialized methodology, however, AT is fast becoming a generalist tool for those wishing to study or conserve fishes, leading to diversifying application by non-specialists. With this transition in mind, we evaluate exactly what AT has become useful for, discussing how the technological and analytical advances around AT can address important questions within fish biology. In doing so, we highlight the key ecological and applied research areas where AT continues to reveal crucial new insights and, in particular, when combined with complimentary research approaches. We provide a comprehensive breakdown of the state of the art for applications of AT, discussing the ongoing challenges, where its strengths lie, and how future developments may revolutionize fisheries management, behavioral ecology and species protection. Through selected papers we illustrate specific applications across the broad spectrum of fish biology. By bringing together the recent and future developments in this field under categories designed to broadly capture many aspects of fish biology, we hope to offer a useful guide for the non-specialist practitioner as they attempt to navigate the dizzying array of considerations and ongoing developments within this diverse toolkit.

Atlantic bluefin tuna diet variability in the southern Gulf of St. Lawrence, Canada

The abundance of top predators in the southern Gulf of St. Lawrence, Canada, has fluctuated dramatically in recent decades. The associated increase in predation and its effect on the lack of recovery of many fish stocks in the system generates the need for a better understanding of predator-prey relationships and the implementation of an ecosystem approach to fisheries management. This study used stomach content analysis to further describe the diet of Atlantic bluefin tuna in the southern Gulf of St. Lawrence. Teleost fish largely dominated the stomach contents in all years. Previous studies established that Atlantic herring was the main component of the diet by weight, whereas herring was almost absent from the diet in this study. A shift in the diet of Atlantic bluefin tuna has been observed, as it now feeds almost exclusively on Atlantic mackerel. The estimated daily meal varied between years, ranging from 1026 g per day in 2019 to 2360 g per day in 2018. Daily meals and daily rations were calculated and showed substantial year-to-year variation.

Oceans of plenty? Challenges, advancements, and future directions for the provision of evidence-based fisheries management advice

Marine population modeling, which underpins the scientific advice to support fisheries interventions, is an active research field with recent advancements to address modern challenges (e.g., climate change) and enduring issues (e.g., data limitations). Based on discussions during the 'Land of Plenty' session at the 2021 World Fisheries Congress, we synthesize current challenges, recent advances, and interdisciplinary developments in biological fisheries models (i.e., data-limited, stock assessment, spatial, ecosystem, and climate), management strategy evaluation, and the scientific advice that bridges the science-policy interface. Our review demonstrates that proliferation of interdisciplinary research teams and enhanced data collection protocols have enabled increased integration of spatiotemporal, ecosystem, and socioeconomic dimensions in many fisheries models. However, not all management systems have the resources to implement model-based advice, while protocols for sharing confidential data are lacking and impeding research advances. We recommend that management and modeling frameworks continue to adopt participatory co-management approaches that emphasize wider inclusion of local knowledge and stakeholder input to fill knowledge gaps and promote information sharing. Moreover, fisheries management, by which we mean the end-to-end process of data collection, scientific analysis, and implementation of evidence-informed management actions, must integrate improved communication, engagement, and capacity building, while incorporating feedback loops at each stage. Increasing application of management strategy evaluation is viewed as a critical unifying component, which will bridge fisheries modeling disciplines, aid management decision-making, and better incorporate the array of stakeholders, thereby leading to a more proactive, pragmatic, transparent, and inclusive management framework-ensuring better informed decisions in an uncertain world.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s11160-022-09726-7.

Toward a decade of ocean science for sustainable development through acoustic animal tracking

The ocean is a key component of the Earth's dynamics, providing a great variety of ecosystem 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 management, 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 Nations.

First tagging data on large Atlantic bluefin tuna returning to Nordic waters suggest repeated behaviour and skipped spawning

Atlantic bluefin tuna (Thunnus thynnus; ABFT) is one of the most iconic fish species in the world. Recently, after being very rare for more than half a century, large bluefin tunas have returned to Nordic waters in late summer and autumn, marking the return of the largest predatory fish in Nordic waters. By tagging 18 bluefin tunas with electronic tags (pop-up satellite archival tags), we show that bluefin tuna observed in Nordic waters undertake different migration routes, with individuals migrating into the western Atlantic Ocean, while others stay exclusively in the eastern Atlantic and enter the Mediterranean Sea to spawn. We additionally present evidence of possible skipped spawning inferred from behavioural analyses. In Nordic waters, ABFT are primarily using the upper water column, likely reflecting feeding activity. The results support the hypothesis that ABFT migrating to Nordic waters return to the same general feeding area within the region on an annual basis. These observations may have important implications for management because (1) tunas that come into Nordic waters might represent only a few year classes (as evidenced by a narrow size range), and thus may be particularly vulnerable to area-specific exploitation, and (2) challenge the assumption of consecutive spawning in adult Atlantic bluefin tuna, as used in current stock assessment models. Without careful management and limited exploitation of this part of the ABFT population, the species’ return to Nordic waters could be short-lived.

Global trends in aquatic animal tracking with acoustic telemetry

Acoustic telemetry (AT) is a rapidly evolving technique used to track the movements of aquatic animals. As the capacity of AT research expands it is important to optimize its relevance to management while still pursuing key ecological questions. A global review of AT literature revealed region-specific research priorities underscoring the breadth of how AT is applied, but collectively demonstrated a lack of management-driven objectives, particularly relating to fisheries, climate change, and protection of species. In addition to the need for more research with direct pertinence to management, AT research should prioritize ongoing efforts to create collaborative opportunities, establish long-term and ecosystem-based monitoring, and utilize technological advancements to bolster aquatic policy and ecological understanding worldwide.

Feeding ecology of Atlantic bluefin tuna (Thunnus thynnus) in the Gulf of Saint Lawrence, Canada

Feeding ecology of Atlantic bluefin tuna (ABFT, Thunnus thynnus), from the Gulf of Saint Lawrence, Canada, was assessed by stomach content and stable isotope analyses. Stomachs were collected from 161 individuals averaging 249 ± 20 cm in curved fork length and 248 ± 64 in round weight. The fish were caught by commercial fishing boats using rod and reel gear during fall 2015-2017. Liver and muscle samples were taken from 133 fish for stable isotope analysis. Atlantic mackerel (Scomber scombrus) was the most abundant prey item in 2015 (%Alimentary index, %AI = 88.94), whereas in 2016 and 2017 the ABFT diet was mainly composed of Atlantic herring (Clupea harengus) (%AI = 56.73 and %AI = 77.23, respectively). PERMANOVA analysis revealed significant differences in the dietary composition between years. δ¹⁵N values varied between 12.3 and 15.4‰ for muscle and between 11.1 and 14.6‰ for liver. δ¹³C values ranged from -19.9 to -16.5‰ for muscle and from -20.7 to -17.3‰ for liver. PERMANOVA analysis also detected inter-annual isotopic differences in both muscle and liver samples (p < 0.05). Daily rations (DR) were similar in 2015 and 2016 (DR = 1.02 ± 0.32 and DR = 1.10 ± 0.21, respectively), but higher in 2017 (DR = 1.73 ± 0.54).