課程名稱 |
資源評估模式:理論與實作 Advanced Quantitative Methods in Fisheries Stock Assessment |
開課學期 |
107-2 |
授課對象 |
生命科學院 漁業科學研究所 |
授課教師 |
張以杰 |
課號 |
Ocean7178 |
課程識別碼 |
241EM3860 |
班次 |
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學分 |
3.0 |
全/半年 |
半年 |
必/選修 |
選修 |
上課時間 |
星期一2,3,4(9:10~12:10) |
上課地點 |
海研115 |
備註 |
本課程以英語授課。 總人數上限:8人 |
Ceiba 課程網頁 |
http://ceiba.ntu.edu.tw/1072Ocean7178_ |
課程簡介影片 |
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核心能力關聯 |
核心能力與課程規劃關聯圖 |
課程大綱
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為確保您我的權利,請尊重智慧財產權及不得非法影印
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課程概述 |
This course is a complete review of advanced quantitative methods in fisheries stock assessment. Course covers introduction, decision analysis to evaluate alternative management actions, Bayesian state-space modelling, Meta-analysis, Integrated analysis, and Spatial modelling in stock assessment
Assessment models of biomass dynamics model, age-structured production model, and integrated stock assessment model (e.g., Stock Synthesis, SS) will be included. Student will be familiar with methods in fish population dynamics and stock assessment (e.g.., Bayesian posterior distribution, Markov Chain Monte Carlo, state-space modelling, etc.) and proficient in parameter estimation (e.g., unfished biomass, spawning biomass, MSY), as well as the uncertainty, of an exploited fish population, and evaluation of harvest restrictions for fisheries management problems by using various computer programs and tools (e.g., AD Model Builder [ADMB], WinBUGS/JAGS, SS).
The course draws examples from real fisheries in the world and provides student broad experiences of various fishery data and fish biology. The course is primarily for students of fisheries and marine ecology, but should also appeal to those interested in conservation ecology and advanced ecological modelling.
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課程目標 |
The main objective of the course was to become proficient with background and tools to conduct advanced stock assessment modelling for fisheries. Student will develop professional skills of data analysis, quantitative fish population modelling, and theory and implication of fish harvest management. Student will carry out fisheries data analysis, modelling, and interpretation on a regular basis throughout the course. The course expects student will develop their own model and application. Course will provide basic programming training by following the examples using Excel, R, ADMB, WinBUGS/JAGS. |
課程要求 |
Ocean 7176 Ecological Modeling for Conservation of Fisheries Resources is recommended (not required) prior to this course |
預期每週課後學習時數 |
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Office Hours |
每週一 14:00~16:00 |
指定閱讀 |
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參考書目 |
Haddon, M. 2001. Modelling and Quantitative Methods in Fisheries. Chapman and Hall, London, 406 pp.
F. Funk, T.J. Quinn II, J. Heifetz, J.N. Ianelli, J.E. Powers, J.F. Schweigert, P.J. Sullivan, and C.I. Zhang. 1998. Fishery Stock Assessment Models. Alaska Sea Grant College Program Report No. AK-SG-98-01, University of Alaska Fairbanks.
Millar, R.B. (2011) Maximum Likelihood Estimation and Inference: With Examples in R, SAS and ADMB. John Wiley & Sons, Hoboken, NJ, USA.
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評量方式 (僅供參考) |
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週次 |
日期 |
單元主題 |
第1週 |
02/20 |
Course opening & intro |
第2週 |
02/25 |
Stock assessment process and classification of stock assessment models |
第3週 |
03/04 |
Modelling concepts |
第4週 |
03/11 |
Non-age models |
第5週 |
03/18 |
Age-structured model |
第6週 |
03/25 |
GIS in R |
第7週 |
04/01 |
Per-recruit |
第8週 |
04/08 |
MSY from age-structured models |
第9週 |
04/15 |
Methods of fitting: the equilibrium and regression methods
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第10週 |
04/22 |
Non-linear minimization |
第11週 |
04/29 |
Methods of fitting: the time series fitting method |
第12週 |
05/06 |
Group presentation |
第13週 |
05/13 |
Maximum likelihood method |
第14週 |
05/20 |
Model selection |
第15週 |
05/27 |
Bayesian analysis I |
第16週 |
06/03 |
Bayesian analysis II |
第17週 |
06/10 |
Reserve |
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