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http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/66207完整後設資料紀錄
| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 許建宗 | |
| dc.contributor.author | Fang-Chi Hsueh | en |
| dc.contributor.author | 薛方琪 | zh_TW |
| dc.date.accessioned | 2021-06-17T00:25:40Z | - |
| dc.date.available | 2015-05-14 | |
| dc.date.copyright | 2012-05-14 | |
| dc.date.issued | 2012 | |
| dc.date.submitted | 2012-03-27 | |
| dc.identifier.citation | Abe, M., Oshima1, K., Kai1, M., Ichinokawa, M., Yamazaki1, I., Hsu, C. C., Yoo, J. T., Childers, J., Dreyfus, M., Aires-da-Silva, A. and Takeuchi, Y. 2007. The update of input data of stock assessment of Pacific Bluefin Tuna, Thunnus orientalis for Stock Synthesis III. ISC/10-1/PBFWG/09.
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IEEE Transactions on Pattern Analysis and Machine Intelligence. 6: 721-741. Graham, M. 1935. Modern theory of exploiting a fishery and application to North Sea trawling. J. Cons. Int. Explr. Mer. 10:264-274. Haddon, M. 2001. Modeling and Quantitative Methods in Fisheries. Chapman and Hall/CRC. 406pp. Heidelberger, P. and Welch, P. 1983. Simulation run length control in the presence of an initial transient. Oper. Res. 31: 1109-1144. Jensen, A. L. 1973. Relation between simple dynamic pool and surplus production models for yield from fishery. Journal of the Fisheries Research Board of Canada, 30: 998-1002. Johannesen, A. B. and Skonhoft, A. 2009. Growth and measurement uncertainty in an unregulated fishery. Natural Resource Modeling, 22(3): 370-392. Magnusson, A. and Hilborn, R. 2007. What makes fisheries data informative? Fish and fisheries, 8: 337–358. Pella, J. J. and Tomlinson, P. K. 1969. A generalized stock production model. Bull. Inter-Amer. Trop. Tuna Comm. 13:421-496. Pindyck, B. S. 1984. Risk, inflation, and the stock market. American Economic Review, Vol. 74, pp. 335-51. Pitcher, T. J. and Hart P. J. B. 1982. Fisheries Ecology. Chapman & Hall, London. 414pp. Polacheck, T., Hilborn, R. and Punt, A. E. 1993. Fitting surplus production models: comparing methods and measuring uncertainty. Canadian Journal of Aquatic and Fisheries Sciences, 50:2597-2607. Prager, M. H. 1992. ASPIC- a surplus-production model incorporating covariates. International Commission for the Conservation of Atlantic Tunas, Coll. Vol. Sci. Pap. 38:218-229. Prager, M. H. 1994. A suite of extensions to a nonequilibrium surplus-production model. U.S. Fish. Bull. 92:374-389. Restrepo, V. and Pallares, P. 2003. Use of delay-difference models to assess Atlantic bigeye tuna. Col. Vol. Sci. Pap. ICCAT, 55(5): 2126-2130. Restrepo, V. R. and Legault, C. M. 1998. A stochastic implementation of an age-structured production model. International Commission for the Conservation of Atlantic Tunas, Collective Volumes of Scientific Papers, 48(3):277-288. Ricker, W. E. 1958. Maximum sustainable yields from fluctuating environments and mixed stocks. J. Fish. Res. Board Can. 15:991-1006. Ricker, W. W. 1975. Computation and interpretation of biological statistics of fish populations. Bull. Fish. Res. Board Can. 191:1-382. Roughgarden, J. and Smith, F. 1996. Why fisheries collapse and what to do about it. Proc. Nat. Acad. Sci. (USA) 93: 5078–5083. Russell, E. S. 1931. Some theoretical consideration on the overfishing problem. J. Cons. Int. Explor. Mer. 6:3-20. Schaefer, M. B. 1954. Some aspects of the dynamics of populations important to the management of commercial marine fisheries. Bull. Inter-Amer. Trop. Tuna Commission 1:27-56. Schaefer, M. B. 1957. A study of the dynamics of the fishery for yellowfin tuna in the eastern tropical Pacific Ocean. Bull. Inter-Amer. Trop. Tuna Commission. 2:247-285. Schirripa, M. J. 2011a. Construction and examination of Stock Synthesis assessment model for bigeye tuna. Collect. Vol. Sci. Pap. ICCAT, 66(1): 293-297. Schirripa, M. J. 2011b. Possible stock assessment models for bigeye tuna in the Atlantic ocean up to 2008 using Stock Synthesis III (SS3). Collect. Vol. Sci. Pap. ICCAT, 66(1): 482-495. Schnute, J. 1977. Improved estimates from the Schaefer production model: theoretical considerations. J. Fish. Res. Board Can. 34:583-603. Scudo, F. M. 1971. Vito Volterra and theoretical ecology. Theoretical Population Biology, 2:1-23. Smith, B.J. 2005. Bayesian output analysis program (BOA), Version 1.1.5. The University of Iowa. (available at: http://www.public-health.uiowa.edu/boa) | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/66207 | - |
| dc.description.abstract | 剩餘生產量模式將成長、補充群的加入及自然死亡三種因子的效應包含在一個簡單的成長方程式中解釋,分析時也只需要簡單的漁獲資料,因此剩餘生產量模式廣泛的應用在漁業資源評估。然而事實上,成長、補充群的加入及自然死亡對生產力或族群成長的影響各不相同。另外,自然界中會對生產力或是生物量變化造成影響的生物或生態的因素也有所差異。我們將這些存在於自然界中差異稱為生態不確定性。有些學者對剩餘生產量模式作修飾,來探討生態不確定性的問題,但是在實際的資源評估中,尚未將生態不確定性納入討論。在本研究中,利用Schaefer model 作為基準模式。而包含生態不確定性的生產量模式則是參考2009年Johannesen and Skonhoft 的報告,利用隨機變數來處理生態不確定性的問題。資料部分以大西洋大目鮪(Thunnus obesus)漁業作為範例,漁獲資料從1961到2008年。由基準模式估計而得的成長率是0.19,環境負載力是1,530,000公噸,最大持續生產量為74,200公噸,2008年漁獲死亡率與最大生產量時的漁獲死亡率的比例是1.326。包含生態不確定性的生產量模式估計得的最大持續生產量大約為66,700公噸,2008年漁獲死亡率與最大生產量時的漁獲死亡率的比例則等於1.43。2008年大西洋大目鮪的總漁獲量大於本研究中兩種模式所估計的最大持續產量,並由結果可以推測近幾年大西洋大目鮪族群處於過漁的狀態。而當我們將生態不確定性加入模式中分析時,發現相對於基準模式,魚群更可能達到過漁的狀態。因此,建議將大西洋大目鮪漁獲量的配額降低。 | zh_TW |
| dc.description.abstract | Surplus production models have been used in fisheries stock assessment for more than a half century. These models simply pool the overall effect of growth, recruitment, and mortality into the productivity function, and just use simple data. But these three surplus components may be with different effect on the productivity, and the biological or ecological factors influencing the productivity may also be diversified. All of those diversified factors may be called “ecological uncertainty”. Some scientist introduces reconstructing surplus production models to address the ecological uncertainty. But in the actual stock assessment, it does not take the ecological uncertainty into account. Use the Schaefer model, one of the classic surplus production models, as the baseline model. And the production model with ecological uncertainty refers to the study of Johannesen and Skonhoft (2009). As they formulated, ecological uncertainty was captured by the random variable. The Atlantic Ocean bigeye tuna (Thunnus obesus) fishery was used as example to demonstrate the baseline model and the production model with ecological uncertainty, and the data was from 1961 to 2008. For the baseline model, the estimated parameters were r=0.19 and K=1,530,000 tons. Biological reference points were MSY=74,200 tons, F2008/FMSY=1.326. For the production model with ecological uncertainty, the estimated average MSY was about 66,700 tons and F2008/FMSY=1.43. The total catch of the Atlantic bigeye tuna was larger than the MSY in 2008. As the Kobe matrix illustrates, both the result of the baseline model and the production model with ecological uncertainty, the Atlantic Ocean bigeye tuna stock is overfished and overfishing in the last few years. And the Kobe matrix also shows the upward shift from the baseline model to the production model with ecological uncertainty. It implies that when take ecological uncertainty into account, the status of the stock is more likely to be overfishing than the baseline model. Therefore, the reduction of the Atlantic bigeye tuna catch quota is necessary to make the bigeye tuna stock status become healthier. | en |
| dc.description.provenance | Made available in DSpace on 2021-06-17T00:25:40Z (GMT). No. of bitstreams: 1 ntu-101-R98241205-1.pdf: 953414 bytes, checksum: bb0d4253c8028441c0a74b6ff2fb54c6 (MD5) Previous issue date: 2012 | en |
| dc.description.tableofcontents | Contents
口試委員會審定書 i 誌謝 ii 摘要 iii Abstract iv Contents v 1. Introduction 1 2. Materials and methods 7 2.1 Models specification 7 2.1.1 Baseline model specification 7 2.1.2 Specification of the production model with ecological uncertainty 11 2.2 Illustration of fishery data 14 2.3 Parameter estimation 16 2.3.1 Parameter estimation of the baseline model 16 2.3.2 Parameter estimation of the production model with ecological uncertainty 17 3. Results 19 3.1 Basic fishery information 19 3.2 Baseline model 20 3.3 Production model with ecological uncertainty 21 4. Discussion 23 4.1 ASPIC model of the ICCAT report vs. the baseline model 23 4.2 Estimation of Atlantic bigeye tuna status by the baseline model 24 4.3 Estimation of Atlantic bigeye tuna status with ecological uncertainty 25 4.4 General discussion 28 References 32 Figures 37 Tables 48 | |
| dc.language.iso | en | |
| dc.subject | 剩餘生產量模式 | zh_TW |
| dc.subject | 大西洋大目鮪 | zh_TW |
| dc.subject | 生態不確定性 | zh_TW |
| dc.subject | surplus production model | en |
| dc.subject | Atlantic bigeye tuna | en |
| dc.subject | ecological uncertainty | en |
| dc.title | 利用合併生態不確定性之生產量模式評估大西洋大目鮪族群 | zh_TW |
| dc.title | Incorporated ecological uncertainty on growth productivity of the production model to assess the Atlantic bigeye tuna stock | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 100-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 劉錫江,李英周,陳志遠,葉裕民 | |
| dc.subject.keyword | 大西洋大目鮪,生態不確定性,剩餘生產量模式, | zh_TW |
| dc.subject.keyword | Atlantic bigeye tuna,ecological uncertainty,surplus production model, | en |
| dc.relation.page | 56 | |
| dc.rights.note | 有償授權 | |
| dc.date.accepted | 2012-03-27 | |
| dc.contributor.author-college | 理學院 | zh_TW |
| dc.contributor.author-dept | 海洋研究所 | zh_TW |
| 顯示於系所單位: | 海洋研究所 | |
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