Review on Quantitative Methods of Fish School Behaviors DOI

Yaoguang Wei,

Lin Ji,

Dong An

et al.

Reviews in Aquaculture, Journal Year: 2025, Volume and Issue: 17(3)

Published: April 23, 2025

ABSTRACT In aquaculture, the quantitative analysis of fish school behavior refers to systematic application mathematical and statistical tools for precise measurement description characteristics through metrics, statistics, modeling. Compared studies on individual behavior, is crucial managing health enhancing aquaculture efficiency. Quantitative deepens our understanding structure interaction patterns, facilitating development more rational efficient feeding strategies. Traditional manual detection methods are time‐consuming, labor‐intensive, have limited accuracy, resulting in inadequate schools difficulties parametrically assessing their physiological states, which pose challenges accurate evaluations. However, recent years, with emergence new technologies quantification indicators, assessment has become objective. This review summarizes three key quantitatively analyzing behavior: computer vision, acoustics, sensors. It outlines types indicators: biomass estimation, environment. Furthermore, it provides insights into response four factors: environmental stress, feeding, disease, reproduction. The study indicates that comprehensive recognition information often requires selecting suitable or integrating multiple based specific needs conditions site. Therefore, future research multimodal data fusion will likely contribute further advancements field aquaculture.

Language: Английский

Revealing the effects of environmental and spatio-temporal variables on changes in Japanese sardine (Sardinops melanostictus) high abundance fishing grounds based on interpretable machine learning approach DOI Creative Commons
Yongchuang Shi,

Lei Yan,

Shengmao Zhang

et al.

Frontiers in Marine Science, Journal Year: 2025, Volume and Issue: 11

Published: Jan. 13, 2025

The construction of accurate and interpretable predictive model for high abundance fishing ground is conducive to better sustainable fisheries production carbon reduction. This article used refined statistical maps visualize the spatial temporal patterns catch changes based on 2014-2021 fishery statistics Japanese sardine Sardinops melanostictus in Northwest Pacific Ocean. Three models (XGBoost, LightGBM, CatBoost) two variable importance visualization methods (model built-in (split) SHAP methods) were comparative analysis determine optimal modeling strategies. Results: 1) From 2014 2021, annual showed an overall increasing trend peaked at 220,009.063 tons 2021; total monthly increased then decreased, with a peak 76, 033.4944 (July), was mainly concentrated regions 39.5°-43°N 146.75°-155.75°E; 2) Catboost predicted than LightGBM XGBoost models, highest values accuracy F1-score, 73.8% 75.31%, respectively; 3) ranking model’s method differed significantly from that method, variables increased. Compared informs magnitude direction influence each global local levels. results research help us select construct prediction grounds Ocean, which will provide scientific basis achieve environmental economically development.

Language: Английский

Citations

0
DNA Barcoding of Museum-Vouchered Samples Collected from Fish Markets Reveals an Unexpected Diversity of Consumed Gastropods in Vietnam DOI
Davin H. E. Setiamarga,

Moe Shimizu,

Satoko Nakashima

et al.

Published: Jan. 1, 2025

Language: Английский

Citations

0
Review on Quantitative Methods of Fish School Behaviors DOI

Yaoguang Wei,

Lin Ji,

Dong An

et al.

Reviews in Aquaculture, Journal Year: 2025, Volume and Issue: 17(3)

Published: April 23, 2025

ABSTRACT In aquaculture, the quantitative analysis of fish school behavior refers to systematic application mathematical and statistical tools for precise measurement description characteristics through metrics, statistics, modeling. Compared studies on individual behavior, is crucial managing health enhancing aquaculture efficiency. Quantitative deepens our understanding structure interaction patterns, facilitating development more rational efficient feeding strategies. Traditional manual detection methods are time‐consuming, labor‐intensive, have limited accuracy, resulting in inadequate schools difficulties parametrically assessing their physiological states, which pose challenges accurate evaluations. However, recent years, with emergence new technologies quantification indicators, assessment has become objective. This review summarizes three key quantitatively analyzing behavior: computer vision, acoustics, sensors. It outlines types indicators: biomass estimation, environment. Furthermore, it provides insights into response four factors: environmental stress, feeding, disease, reproduction. The study indicates that comprehensive recognition information often requires selecting suitable or integrating multiple based specific needs conditions site. Therefore, future research multimodal data fusion will likely contribute further advancements field aquaculture.

Language: Английский

Citations

0