漁業資源評估和管理研修班(第一輪通知)

發布時間:2015-03-10

浏覽次數:90

一、目的

漁業資源評估是開展科學漁業管理的基礎。為了提高我國漁業科學工作者的理論水平與應用能力,以促進我國漁業資源評估研究水平的提升,推動我國漁業資源評估和管理研究的進一步發展。伟德BETVLCTOR國際海洋研究中心、大洋漁業資源可持續開發省部共建教育部重點實驗室聯合舉辦漁業資源評估和管理研修班,為我國漁業科學工作者建立一個學習和交流的平台。本次研修班分成兩個階段,第一階段為基礎提高班,第二階段為高級應用班。

 

二、招收對象

    基礎提高班:從事漁業資源研究的青年科學工作者、研究生等;

    高級應用班:參加過基礎提高班,或者在漁業資源評估和管理方面具有一定工作經驗的科研和管理人員,以及相關研究生。

 

三、招收人數

    基礎提高班:40

    高級應用班:45

 

四、研修日期

    基礎提高班:2015414-16

    高級應用班:初步定在20159月(5天)

 

五、授課方式

    采用教師主講、互動交流和計算機實例操作(自備筆記本電腦)等方式,授課材料為英文,授課語言為中文。

 

六、主講教師

    1、首席主講教師:陳勇教授,伟德BETVLCTOR國際海洋研究中心首席科學家、美國緬因大學終身教授、《Canadian Journal of Fisheries and Aquatic Sciences》主編、國際著名漁業資源專家。

    2、主講教師:陳新軍教授、官文江副教授和田思泉副教授。

 

七、主要内容

 

基礎提高班

 

Part 1:  Statistic analyses commonly used in fisheries (review and introduction)

(1) Sampling distribution: theoretical and empirical distribution, and summary statistics;

(2) Computation-intensive methods: Monte Carlo method, bootstrap method;

(3) Confidence intervals: classic method and computation-intensive methods;

(4) Linear and nonlinear regression analyses;

(5) Error structures in modeling and their implications;

(6) General liner model (GLM) and general additive model (GAM);

(7) Introduction of R programming language

 

Part 2: Survey/sampling design and relevant data analyses

(1)   Random design;

(2)   Stratified random design;

(3)   Systematic design;

(4)   Cluster design;

(5)   Data analyses and development of R programs

 

Part 3: Modeling fish life history and fishery processes

(1)    Modeling fish growth: growth rates, growth models, growth transition matrix, analyzing tagging data for growth modeling, comparison of growth patterns between populations and sexes;

(2)    Modeling fish maturation: modeling length-specific proportion of fish maturity (for estimating length/age at maturity), modeling fish size-fecundity relationship;

(3)    Modeling length-weight relationship: comparing weight-length models;

(4)    Modeling fishing process: selectivity modeling;

(5)    Quantifying mortality rates;

 

 

高級應用班:

 

Part 1: CPUE standardizations

(1)   Selection of environmental variables;

(2)   Selection of models (general linear models and general abdicative models);

(3)   Statistical property of link functions;

(4)   Result interpretations;

(5)   Development of R programs.

 

Part 2: Per-recruit analyses

(1)   Age- and length-structured yield-per-recruit analyses;

(2)   Age- and length-structured egg-per-recruit analyses;

(3)   Estimating management/biological reference points;

(4)   Development of R programs.

 

Part 3: Production (biomass dynamic) models for stock assessment

(1)   Model structure and biological implications;

(2)   Process-error and observation-error estimators;

(3)   Estimation of management/biological reference points;

(4)   Development of R programs

 

Part 4: Stock-recruitment analysis

(1)   Recruitment and spawning stock biomass;

(2)   Stock-recruitment models, model structures, assumptions, and biolgical implications,

(3)   Stock-recruitment models incorporating environmental variables;

(4)   Estimating management/biological reference points using stock-recruitment models;

(5)   Development of R programs.

 

Part 5: Age-structured stock assessment models

(1)   Virtual Population Analysis (VPA);

(2)   Statistical age-structured models;

(3)   Development of R programs.

 

Part 6: Fisheries bioeconomics analysis

(1)   Fisheries bioeconomics theory and modelling;

(2)   Development of R programs.

 

Part 7: Case studies

(1)   Input data identification;

(2)   Model selections;

(3)   Stock assessment and estimation;

(4)   Sensitivity analysis;

(5)   Stock assessment report writing

(6)   Basic fish population dynamics models:

(7)    Development of R programs.

 

八、費用

基礎提高班:2000

高級應用班:3000

備注:食宿自理,可幫聯系住宿,住宿地點為伟德BETVLCTOR研究生交流與培訓中心或伟德BETVLCTOR悅海賓館。

 

九、聯系人及報名回執

聯系人:

龔彩霞

電話/傳真:021-61900304

E-mail:cxgong@shou.edu.cn

 

田思泉

電話:021-61900221

傳真:021-61900304

E-mail:sqtian@shou.edu.cn

 

 

伟德BETVLCTOR國際海洋研究中心

大洋漁業資源可持續開發省部共建教育部重點實驗室

 

 

 

 

 

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