陈勇，男，博士，美国缅因大学海洋科学学院教授。主要研究领域包括渔业种群动力学 (Fisheries population Dynamics), 渔业资源评估(Fisheries Stock Assessment), 渔业资源管理 (Fisheries Management), 渔业生态学 (Fisheries Ecology), Fish Life History, 渔业生物统计 (Statistical and Mathematical Modelling), 及计算机模拟 (Computer Simulations and Computation-intensive Methods)

主要学术成绩及创新点

    在美、加、澳任职期间，在渔业资源评估渔业生态学研究领域进行了系统探索，迄今共发表论文55余篇，其中绝大多数为SCI收录论文，在国际上享有很高声誉。国际合作足迹踏遍美、加、澳, 新西兰、科威特、中国的js6666金沙安全下载, 华东师笵大学、华中农业大学, 台湾大学等。

    •主要从事鱼类的种群动态，以及种群与环境因子间的相互关系研究，并为优化渔业管理中的资源评估和风险分析建立了新的方法。

    •取得的主要成果有：①首次在国际上系统地研究了渔业生产中非典型观测对渔业资源评估与管理的影响，并通过数学建模加以评估、量化；②在国际上第一次提出并建立运用于渔业资源量估算和管理的Robust估算方法；③在国际上首次改进并应用Bayesian的Robust估算方法; (4)发展了美国龙虾资源评估体系。

October 2008

Shanghai Ocean University

 

Orono, Maine 04469                                  

My Lab webpage: http://www.umaine.edu/marine/people/sites/ychen

 

    The development of an effective fisheries management strategy depends upon the high quality of stock assessment and good understanding of the dynamics of fish stocks. Vital fisheries parameters, which define the dynamics of fish populations, such as virgin biomass, population growth rate, fishing and natural mortality rates, recruitment, and current stock size can only be estimated through formal mathematical and statistical modeling based on data collected in fisheries. The uncertainty and risk associated with a fisheries management strategy can be evaluated through extensive computer simulations.

 

    This course is designed to introduce graduate students quantitative fish population dynamics. Students will learn how to use appropriate quantitative methods in analyzing data collected from fisheries, to estimate vital parameters for fisheries, to describe quantitatively the dynamics of fish populations, to quantitatively evaluate current status of a fishery and alternative management strategies through formal stock assessment process, and to understand and interpret uncertainties associated with the assessment in managing fisheries resources.

 

10% class participation

60% homework and assignment

30% final take-home examination

 

Hilborn and Walters.  1992. Quantitative fisheries Stock Assessment,  Choice, Dynamics, & Uncertainty. Chapman and Hall

Quinn and Deriso. 1999. Quantitative Fish Dynamics. Oxford University Press.

Ricker 1975. Computation and Interpretation of Biological Statistics of fish populations. Bulletin of the Fisheries Research Board of Canada 191

Zar, J. H. 1984. Biostatistical Analysis. 2^nd Edition, Prentice-Hall, Englewood, Cliffs, New Jersey

Parsons, L. S. 1993. Management of Marine Fishes in Canada. NRC publication

Smith, S. J. , J. J. Hunt, and D. Rivard. 1995. Risk Evaluation and Biological reference Points for Fisheries Management. Can. Spec. Publ. Fish. Aquat. Sci. 120.

Ratkowsky, D. A. 1990. Handbook of Nonlinear Regression Models. Marcel Dekker, New York.

 

Part I:  Data analysis and basic statistics

Ø  A general review of population dynamics, fisheries data,  and stock assessment;

Ø  A review of basic statistics relevant to this course including data descriptions, random variable distributions, sampling distribution, linear regression analysis, nonlinear regression, test for model significance, hypothesis testing, Type I and II errors, estimation of confidence intervals, t test, and F-test;

Ø  Determining sampling sizes;

Ø  Fisheries survey design;

Ø  Field-survey/experiment based approaches for estimating fish population abundance;

Ø  Monte Carlo methods: bootstrap and jackknife;

Ø  Key Excel functions for statistical analyses, and Excel excises;

Ø  Resampling Stats in Excel

 

 

Part II: Fish life history process: growth, maturation, recruitment, and mortality

Ø  Different rates for life history process;

Ø  Von Bertalanffy growth function (most commonly used);

Ø  Modeling growth for species that are difficult to age.

Ø  Development of an Excel worksheet for the VBGF and growth transition matrix;

Ø  Maturation process;

Ø  Biological recruitment versus fisheries recruitment;

Ø  Different mortality rates and their relations;

Ø  Homework II is assigned

 

Part III: Basic fish population dynamics models

Ø  Symbols used in fisheries;

Ø  Catch equation;

Ø  Exponential survival equation;

Ø  Development of an Excel worksheet for back-calculation or forward projection of fish population dynamics.

 

Part IV: Per-recruit analysis

Ø  Age- and length-based yield-per-recruit analysis;

Ø  Age- and length-based egg-per-recruit analysis;

Ø  Estimating key management parameters from per-recruit analysis;

Ø  Homework III is assigned;

Ø  Development of an Excel worksheet for the models

 

Part V. Assessing fisheries stocks using production model

Ø  Model structure and biological implications;

Ø  Process-error estimator;

Ø  Observational error estimator;

Ø  Management parameters;

Ø  Development of an Excel worksheet for observational error models;

 

Part VI. Stock-recruitment analysis

Ø  Recruitment and spawning stock biomass;

Ø  Rick model and its implications,

Ø  Beverton-Holt model and its implications,

Ø  Models incorporating environmental variables;

Ø  Estimating management parameters in stock-recruitment analyses

Ø  Development of an Excel worksheet for the models 

Ø  Homework IV is assigned

 

Part VII. Age-structured stock assessment

Ø  Virtual Population Analysis (VPA);

Ø  Statistical age-structured models;

Ø  Simulation models

 

Part VIII. Length-structured stock assessment 

Ø  Development of an Excel worksheet for the models

Ø  Homework V is assigned.

 

Part IX. Biological reference points

 

Part X. Statistical decision-making theory and its application in fisheries