Hokkaido University Graduate School of Fisheries Sciences
Marine Bioresource and Environmental Science Fisheries Engineering
Graduate School of Env. Science
Biosphere Science Marine Biogeochemistry and Biology
Takagi Laboratory・Gomi Laboratory
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Research Projects
Research Projects
How fish are caught is a fundamental question in fisheries science. Fishing technologies are essential for fishery production. Our research focuses on understanding the behavior of both fishes and fishing gear during an operation, and on developing technologies and systems that enables the efficient and selective capture of target species in appropriate quantities.
Specifically, we study fishing systems and the optimal design of fishing gear using a unique original numerical simulation system developed in our laboratory. This system enables us to visualize the dynamic behavior of entire fishing gear geometries during operations and to gain important physical insights. Also, we conduct research on the locomotion, behavioral emergence, and underlying mechanisms in marine organisms to achieve sustainable and responsible fishing practices.
Development of a Net geometry and Load Analysis system (NaLA system)
It is impossible to directly observe the behavior of fishing gear and entire geometry during operation by using optical methods because light gets easily attenuated and fishing gear is often huge such as its length can be thousands meters. Then, we have developed a numerical simulation for dynamics of fishing gear, which is called NaLA system that stands for Net geometry and Load Analysis system. The NaLA system is capable of solving the dynamics of fishing gear numerically and visualizing them.
It is necessary to control the dynamics of fishing gear to achieve selective fishing.
We study on this topic using the NaLA system, control theory, and state estimation method.
To reduce damage to aquaculture net pens caused by natural disasters such as increasingly severe typhoons in recent years, we are conducting research on the dynamic behavior of aquaculture net pens using the NaLA system, as well as developing disaster-prevention technologies to improve their resilience to extreme weather conditions.
In collaboration with research institutions in France, we have also launched an international research project addressing bycatch issues in longline fisheries. Through this project, we are conducting collaborative research using the NaLA system.
Understanding and Control the Fish School Behavior
Understanding and Control the Fish School Behavior
How do fish perceive other individuals and their surrounding environment, and why do they form schools?
How do environmental conditions, such as light intensity, affect their schooling patterns and swimming behavior?
What benefits does swimming in a school provide to individual fish?
We aim to understand the mechanisms underlying fish schooling behavior by addressing these questions through behavioral measurements, mathematical modeling, and hydrodynamic analyses.
We are also developing methods to control the movement of fish schools using external stimuli such as light.
Through a better understanding and control of fish schooling behavior, we aim to develop new fisheries and aquaculture technologies that take advantage of the natural behavioral characteristics of fish.
Digital Twin
Digital Twin
Many bays across Japan are home to numerous set nets and active aquaculture operations.
We are also working on the development of digital twins that use digital technologies to reproduce these bays in a virtual environment.
Through these digital twins, we aim to support practical applications in the field, including real-time monitoring and dynamic analysis of set nets and aquaculture facilities using the NaLA system.
Research on Fish Swimming Performance and Behavioral Analysis
Research on Fish Swimming Performance and Behavioral Analysis
How do fish swim efficiently through water?
The various characteristics of fish—including the shape and flexibility of their bodies and fins, as well as the properties of their body surfaces—contain remarkable adaptations for swimming efficiently in aquatic environments.
Using high-speed imaging, flow visualization, and force measurements, we investigate how fish generate thrust and vortices, and the roles these play in swimming.
By examining the interaction between fish and the surrounding water from a mechanical and hydrodynamic perspective, we aim to uncover the unique mechanisms underlying fish swimming and apply these insights to the development of new underwater technologies.
Research on the early detection of harmful algal blooms (HABs) using machine learning
Research on the early detection of harmful algal blooms (HABs) using machine learning
Harmful algal blooms (HABs) induce mass fish mortality in aquaculture, resulting in significant negative impacts on fisheries. Therefore, predicting the expansion of HABs and mitigating their negative impacts are essential. Recently, a monitoring system for HABs using airplanes has been considered as a new approach. In our laboratory, we have started conducting research on developing a method to predict the expansion of HABs by combining neural network and spectral data in order to distinguish HABs from images and mitigate their negative impacts.
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