Tagging mortality in acoustic telemetry studies: Insights from a multispecies analysis.

The widespread adoption of acoustic telemetry has transformed our understanding of marine species' behavior and movement ecology. However, accurately interpreting telemetry data, especially concerning tagging mortality, is essential for drawing valid conclusions. In this study, we scrutinized tagging mortality in 223 individuals across 14 species and evaluated the impact of tagging methodologies, including capture method and size effects. Results reveal high tagging survival rates overall, attributable to the resiliency of the studied species and the rigorous animal welfare protocols followed during tagging procedures. Our results highlight the importance of tailoring array designs to the specific mobility patterns of the studied species for accurate survival assessments. This research contributes to generalizing mortality assessments and clearing the path for more precise and reliable telemetry studies in the future.

Emigration of post-spawned twaite shad Alosa fallax, an anadromous and iteroparous fish, in a highly fragmented river.

Anthropogenic barriers are widely known to negatively impact the spawning migrations of anadromous fishes, by delaying or preventing passage upstream. Although the impacts of barriers on emigrating post-spawned adults are less well studied, they could potentially impact the fitness and subsequent return rates of iteroparous species. In this study, passive acoustic telemetry was used to track the emigrations of 53 twaite shad Alosa fallax in the River Severn basin in their first spawning migration a year after being tagged, giving insights into their emigration movements and the impacts of anthropogenic weirs on these movements. A. fallax began their emigrations after spending varying amounts of time and migrating various distances within the river, with late-emigrating individuals moving fastest and most directly. Emigrations became faster and more direct the further downstream individuals were from their furthest upstream extent. Downstream passage delays at weirs increased emigration times by a median of 61%, with environmental conditions (i.e., temperature, flow, and tidal influence on river level) having little influence on downstream passage at weirs with no modifications to facilitate fish passage. As weir-induced emigration delays are suggested to deplete energy reserves (when energy levels are already depleted post-spawning), limit spawning opportunities (by preventing access to downstream spawning habitat), and expose individuals to increased predation risk and suboptimal conditions (e.g., high temperatures), these delays can potentially diminish the benefits of iteroparity. The evidence presented here suggests that more consideration should be given to the potential impacts of anthropogenic barriers on the emigrations of iteroparous species when assessing river connectivity or undertaking barrier mitigation.

Acoustic telemetry and fisheries management.

This paper reviews the use of acoustic telemetry as a tool for addressing issues in fisheries management, and serves as the lead to the special Feature Issue of Ecological Applications titled Acoustic Telemetry and Fisheries Management. Specifically, we provide an overview of the ways in which acoustic telemetry can be used to inform issues central to the ecology, conservation, and management of exploited and/or imperiled fish species. Despite great strides in this area in recent years, there are comparatively few examples where data have been applied directly to influence fisheries management and policy. We review the literature on this issue, identify the strengths and weaknesses of work done to date, and highlight knowledge gaps and difficulties in applying empirical fish telemetry studies to fisheries policy and practice. We then highlight the key areas of management and policy addressed, as well as the challenges that needed to be overcome to do this. We conclude with a set of recommendations about how researchers can, in consultation with stock assessment scientists and managers, formulate testable scientific questions to address and design future studies to generate data that can be used in a meaningful way by fisheries management and conservation practitioners. We also urge the involvement of relevant stakeholders (managers, fishers, conservation societies, etc.) early on in the process (i.e., in the co-creation of research projects), so that all priority questions and issues can be addressed effectively.

An effective and robust method for tracking multiple fish in video image based on fish head detection.

BACKGROUND: Fish tracking is an important step for video based analysis of fish behavior. Due to severe body deformation and mutual occlusion of multiple swimming fish, accurate and robust fish tracking from video image sequence is a highly challenging problem. The current tracking methods based on motion information are not accurate and robust enough to track the waving body and handle occlusion. In order to better overcome these problems, we propose a multiple fish tracking method based on fish head detection. RESULTS: The shape and gray scale characteristics of the fish image are employed to locate the fish head position. For each detected fish head, we utilize the gray distribution of the head region to estimate the fish head direction. Both the position and direction information from fish detection are then combined to build a cost function of fish swimming. Based on the cost function, global optimization method can be applied to associate the target between consecutive frames. Results show that our method can accurately detect the position and direction information of fish head, and has a good tracking performance for dozens of fish. CONCLUSION: The proposed method can successfully obtain the motion trajectories for dozens of fish so as to provide more precise data to accommodate systematic analysis of fish behavior.

Fine-scale movement response of juvenile brown trout to hydropeaking.

Juvenile fish are known to be the most impacted during hydropeaking events due to stranding or uncontrolled drift resulting from changes to water depth and flow velocity. To shed light on their response to such hydraulic alterations, we coupled flume experiments with image-based fish tracking and quantified the fine-scale movement behavior of wild (n = 30) and hatchery-reared (n = 38) brown trout (Salmo trutta) parr. We exposed fish to two distinct hydropeaking treatments in a laterally inclined (14 %) flume section stocked with real cobbles to create refuge and heterogeneous hydraulic conditions. Fish were individually acclimated (20 min) to baseflow (Q = 1.6 L s-1) and then exposed to three consecutive hydropeaking events, reaching peakflows tenfold larger than baseflow (Q = 16 L s-1). We found that, within just minutes, fish exhibited fine-scale movement responses to cope with the change of hydrodynamic conditions. Fish moved perpendicular to the main flow direction to shallow areas as these became submerged during discharge increase, holding position at low velocity zones. This resulted in a significant difference (p < 0.001) in lateral occupancy of the experimental section between baseflow and peakflow. During peakflow, fish occupied specific positions around cobbles and exhibited swimming behaviors, including bow-riding and entraining, that allowed them to hold position while likely minimizing energy expenditure. As a result, swimming distance reduced 60-70 % compared to baseflow. During the decrease in discharge following peakflow, fish abandoned areas falling dry by moving laterally. In the treatment with the larger down-ramping rate, the time to initiate relocation was lower while the relocation speed was higher. This study shows that, for the conditions investigated here, brown trout parr is capable of swiftly deploying multiple behavioral responses to navigate rapid changes in hydrodynamic conditions. These findings can be incorporated into habitat modeling and improve our capacity to inform hydropeaking mitigation efforts.

Measuring inter-individual differences in behavioural types of gilthead seabreams in the laboratory using deep learning.

Deep learning allows us to automatize the acquisition of large amounts of behavioural animal data with applications for fisheries and aquaculture. In this work, we have trained an image-based deep learning algorithm, the Faster R-CNN (Faster region-based convolutional neural network), to automatically detect and track the gilthead seabream, Sparus aurata, to search for individual differences in behaviour. We collected videos using a novel Raspberry Pi high throughput recording system attached to individual experimental behavioural arenas. From the continuous recording during behavioural assays, we acquired and labelled a total of 14,000 images and used them, along with data augmentation techniques, to train the network. Then, we evaluated the performance of our network at different training levels, increasing the number of images and applying data augmentation. For every validation step, we processed more than 52,000 images, with and without the presence of the gilthead seabream, in normal and altered (i.e., after the introduction of a non-familiar object to test for explorative behaviour) behavioural arenas. The final and best version of the neural network, trained with all the images and with data augmentation, reached an accuracy of 92,79% ± 6.78% [89.24-96.34] of correct classification and 10.25 ± 61.59 pixels [6.59-13.91] of fish positioning error. Our recording system based on a Raspberry Pi and a trained convolutional neural network provides a valuable non-invasive tool to automatically track fish movements in experimental arenas and, using the trajectories obtained during behavioural tests, to assay behavioural types.