AIMC Topic: Fisheries

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Dynamic supply-side multipliers in China's marine economy: A neural network-enhanced Ghosh model for sustainable development.

PloS one
With the continuous growth of China's economy, marine economy plays an increasingly important role in the national economy. This study quantifies multiplier effects and supply-side dynamics in China's marine economy (2017-2023) to inform sustainable ...

Identifying fish populations prone to abrupt shifts via dynamical footprint analysis.

Proceedings of the National Academy of Sciences of the United States of America
Fish population biomass fluctuates through time in ways that may be either gradual or abrupt. While abrupt shifts in fish population productivity have been shown to be common, they are rarely integrated into stock assessment or fishery management, in...

Advancing fishery dependent and independent habitat assessments using automated image analysis: A fisheries management agency case study.

PloS one
Advances in artificial intelligence and machine learning have revolutionised data analysis, including in the field of marine and fisheries sciences. However, many fisheries agencies manage sensitive or proprietary data that cannot be shared externall...

Neural network-based identification for scallops (Pecten maximus) in natural marine habitats.

PloS one
The Great Atlantic scallop, or King scallop (Pecten maximus), ranks third in value after mackerel and Nephrops in UK fisheries. Its landings have surged over recent decades, making it the UK's fastest-growing fishery. Scallop stock assessments, cruci...

Little-to-no industrial fishing occurs in fully and highly protected marine areas.

Science (New York, N.Y.)
There is a widespread perception that illegal fishing is common in marine protected areas (MPAs) due to strong incentives for poaching and the high cost of monitoring and enforcement. Using artificial intelligence and satellite-based Earth observatio...

Attention-enhanced and integrated deep learning approach for fishing vessel classification based on multiple features.

Scientific reports
Effective fisheries management is the key to achieve sustainable fisheries globally, while accurate monitoring of fishing vessels is essential to improve the effectiveness of management measures. Self-reported information on vessel types is often lim...

Do China's ecological civilization advance demonstration zones inhibit fisheries' carbon emission intensity? A quasi-natural experiment using double machine learning and spatial difference-in-differences.

Journal of environmental management
China's National Ecological Civilization Demonstration Zone (NECDZ) policy has a significant role in ensuring national ecological security, and it is essential to investigate how the NECDZ policy affects the carbon emissions intensity of fisheries (C...

Enzymes from Fishery and Aquaculture Waste: Research Trends in the Era of Artificial Intelligence and Circular Bio-Economy.

Marine drugs
In the era of the blue bio-economy, which promotes the sustainable utilization and exploitation of marine resources for economic growth and development, the fisheries and aquaculture industries still face huge sustainability issues. One of the major ...

Leveraging deep learning and computer vision technologies to enhance management of coastal fisheries in the Pacific region.

Scientific reports
This paper presents the design and development of a coastal fisheries monitoring system that harnesses artificial intelligence technologies. Application of the system across the Pacific region promises to revolutionize coastal fisheries management. T...

An Integrated Smart Pond Water Quality Monitoring and Fish Farming Recommendation Aquabot System.

Sensors (Basel, Switzerland)
The integration of cutting-edge technologies such as the Internet of Things (IoT), robotics, and machine learning (ML) has the potential to significantly enhance the productivity and profitability of traditional fish farming. Farmers using traditiona...