Acoustic tags versus camera—a case study on feeding behaviour of European seabass in sea cages

IF 3 2区 生物学 Q1 MARINE & FRESHWATER BIOLOGY Frontiers in Marine Science Pub Date : 2025-01-24 DOI:10.3389/fmars.2024.1497336
I-Hao Chen, Dimitra G. Georgopoulou, Lars O. E. Ebbesson, Dimitris Voskakis, Antonella Zanna Munthe-Kaas, Nikos Papandroulakis
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Abstract

IntoductionWith the expansion of the aquaculture industry, the need arises for scalable, reliable, and robust methods to assess fish behaviour in sea cages to guide operational management, which includes feeding optimisation and welfare assessments. Fish cage monitoring utilising either acoustic transmitters or underwater cameras is well-studied. However, the relationship between those two different measurement types seems to have not been explored, nor have they been evaluated together in one experimental site.MethodsIn our 1-month study, we compared the activity of 14 sentinel fish and the artificial intelligence (AI)-inferred speed of individuals from the European seabass (Dicentrarchus labrax) sea cage population in three feeding trials. Comparisons include a maximum activity comparison using persistent peaks, fish behavioural pattern establishment and retention, and periodical behavioural patterns.ResultsOur results demonstrate that under certain circumstances, both technologies are interchangeable from the perspective of persistent peaks and periodicity, but complementary when it comes to behaviour analysis such as food anticipatory behaviour (FAB).DiscussionWe anticipate that our findings will stimulate advances where multiple sensor types are in use to achieve a more holistic understanding of fish behaviour in the aquaculture sector using underwater technologies.
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声学标签与相机——欧洲鲈鱼在海笼中摄食行为的个案研究
随着水产养殖业的扩大,需要可扩展、可靠和强大的方法来评估海网箱中的鱼类行为,以指导运营管理,包括优化喂养和福利评估。利用声发射机或水下摄像机进行鱼笼监测的研究很充分。然而,这两种不同测量类型之间的关系似乎还没有被探索,也没有在一个实验地点一起评估。方法在为期1个月的研究中,采用人工智能(AI)推断的三种欧洲海鲈(Dicentrarchus labrax)网箱饲养试验,比较了14种哨点鱼的活动和个体的速度。比较包括使用持续峰值的最大活动比较,鱼类行为模式的建立和保持以及周期性行为模式。我们的研究结果表明,在某些情况下,从持续峰值和周期性的角度来看,这两种技术是可互换的,但当涉及到行为分析,如食物预期行为(FAB)时,这两种技术是互补的。我们预计,我们的研究结果将刺激使用多种传感器类型的进步,以实现对水产养殖部门使用水下技术的鱼类行为的更全面的了解。
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来源期刊
Frontiers in Marine Science
Frontiers in Marine Science Agricultural and Biological Sciences-Aquatic Science
CiteScore
5.10
自引率
16.20%
发文量
2443
审稿时长
14 weeks
期刊介绍: Frontiers in Marine Science publishes rigorously peer-reviewed research that advances our understanding of all aspects of the environment, biology, ecosystem functioning and human interactions with the oceans. Field Chief Editor Carlos M. Duarte at King Abdullah University of Science and Technology Thuwal is supported by an outstanding Editorial Board of international researchers. This multidisciplinary open-access journal is at the forefront of disseminating and communicating scientific knowledge and impactful discoveries to researchers, academics, policy makers and the public worldwide. With the human population predicted to reach 9 billion people by 2050, it is clear that traditional land resources will not suffice to meet the demand for food or energy, required to support high-quality livelihoods. As a result, the oceans are emerging as a source of untapped assets, with new innovative industries, such as aquaculture, marine biotechnology, marine energy and deep-sea mining growing rapidly under a new era characterized by rapid growth of a blue, ocean-based economy. The sustainability of the blue economy is closely dependent on our knowledge about how to mitigate the impacts of the multiple pressures on the ocean ecosystem associated with the increased scale and diversification of industry operations in the ocean and global human pressures on the environment. Therefore, Frontiers in Marine Science particularly welcomes the communication of research outcomes addressing ocean-based solutions for the emerging challenges, including improved forecasting and observational capacities, understanding biodiversity and ecosystem problems, locally and globally, effective management strategies to maintain ocean health, and an improved capacity to sustainably derive resources from the oceans.
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