东京大学

发布日期:2021-01-28

浏览次数:12

鱼类种群动态

 

我们小组从应用各种数学技术的角度着眼于海洋生物的种群动态。该小组的研究解决了广泛的问题,涉及渔业种群管理,保护生态学和进化生态学。我们的研究利用了广泛的建模技术,从渔业种群管理模型(例如VPA和集成模型)到计算机密集型统计方法(例如引导程序,分层贝叶斯模型和MCMC)。我们的方法还包括理论生物学中建立的建模技术,例如矩阵人口模型,PDE人口模型,基于个体的模型,最优性模型和定量遗传模型。我们支持政府库存管理的数值模拟,并通过实证研究的统计咨询实现多学科合作,从而为社会和学术界做出了贡献。

 

Fish Population Dynamics

 

Our group focuses on the population dynamics of marine organisms from the viewpoint of applying various mathematical techniques. Research in the group addresses a wide range of questions broadly concerning fisheries stock management, conservation ecology, and evolutionary ecology. Our research utilizes a wide range of modelling techniques, from the models for fisheries stock management (e.g., VPA and integrated models) to computer-intensive statistical methods (e.g., maximum likelihood estimation, bootstrap, hierarchical Bayesian modelling, and MCMC). Our approach also includes the modelling techniques established in theoretical biology, such as the matrix-population models, PDE-population models, individual-based models, optimality models, and quantitative genetics models. We contribute to both society and academia, by supporting numerical simulations for governmental stock management and by achieving multidisciplinary collaboration through statistical consulting for empirical studies, respectively.

 

http://cod.aori.u-tokyo.ac.jp/english.html

 

 

东京大学

发布日期:2021-01-28

浏览次数:12

鱼类种群动态

 

我们小组从应用各种数学技术的角度着眼于海洋生物的种群动态。该小组的研究解决了广泛的问题,涉及渔业种群管理,保护生态学和进化生态学。我们的研究利用了广泛的建模技术,从渔业种群管理模型(例如VPA和集成模型)到计算机密集型统计方法(例如引导程序,分层贝叶斯模型和MCMC)。我们的方法还包括理论生物学中建立的建模技术,例如矩阵人口模型,PDE人口模型,基于个体的模型,最优性模型和定量遗传模型。我们支持政府库存管理的数值模拟,并通过实证研究的统计咨询实现多学科合作,从而为社会和学术界做出了贡献。

 

Fish Population Dynamics

 

Our group focuses on the population dynamics of marine organisms from the viewpoint of applying various mathematical techniques. Research in the group addresses a wide range of questions broadly concerning fisheries stock management, conservation ecology, and evolutionary ecology. Our research utilizes a wide range of modelling techniques, from the models for fisheries stock management (e.g., VPA and integrated models) to computer-intensive statistical methods (e.g., maximum likelihood estimation, bootstrap, hierarchical Bayesian modelling, and MCMC). Our approach also includes the modelling techniques established in theoretical biology, such as the matrix-population models, PDE-population models, individual-based models, optimality models, and quantitative genetics models. We contribute to both society and academia, by supporting numerical simulations for governmental stock management and by achieving multidisciplinary collaboration through statistical consulting for empirical studies, respectively.

 

http://cod.aori.u-tokyo.ac.jp/english.html