以生產量模式評估資源動態結果之比較 -中西太平洋黃鰭鮪為例

在世界各大鮪類漁場中，中西太平洋漁場的鮪類產量豐富，若能得知此漁場的資源狀況，便可作為漁業管理的依據，且能藉此擬定我國在此海域之發展策略。黃鰭鮪為我國經濟價值相當高的魚種，每年外銷至日本為我國賺取大量的外匯。由上述，因此本研究針對中西太平洋漁場之黃鰭鮪做資源評估的研究。一般而言，名目努力量的代表性較差，容易受漁期、漁區等因素影響，因此本研究以Honma法對影響努力量效率的時間、空間因素加以修正，而經修正後的漁獲努力量便稱為有效努力量。以各年份的有效努力量和漁獲量估算各年份之單位努力漁獲量 ( Catch per unit effort , CPUE ) 以作為資源密度變動的指標。在中西太平...

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Main Authors:	連永祥, Lien, Yung-Hsiang
Other Authors:	王健雄, 臺灣大學：海洋研究所
Format:	Thesis
Language:	Chinese English
Published:	2006
Subjects:	黃鰭鮪生產量模式 Honma法資源評估 yellowfin tuna production model Honma method stock assessment Hampton Pacific Schaefer Tomlinson Arctic
Online Access:	http://ntur.lib.ntu.edu.tw/handle/246246/56503 http://ntur.lib.ntu.edu.tw/bitstream/246246/56503/1/ntu-95-R93241205-1.pdf

id	ftntaiwanuniv:oai:140.112.114.62:246246/56503
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institution	Open Polar
collection	National Taiwan University Institutional Repository (NTUR)
op_collection_id	ftntaiwanuniv
language	Chinese English
topic	黃鰭鮪生產量模式 Honma法資源評估 yellowfin tuna production model Honma method stock assessment
spellingShingle	黃鰭鮪生產量模式 Honma法資源評估 yellowfin tuna production model Honma method stock assessment 連永祥 Lien, Yung-Hsiang 以生產量模式評估資源動態結果之比較 -中西太平洋黃鰭鮪為例
topic_facet	黃鰭鮪生產量模式 Honma法資源評估 yellowfin tuna production model Honma method stock assessment
description	在世界各大鮪類漁場中，中西太平洋漁場的鮪類產量豐富，若能得知此漁場的資源狀況，便可作為漁業管理的依據，且能藉此擬定我國在此海域之發展策略。黃鰭鮪為我國經濟價值相當高的魚種，每年外銷至日本為我國賺取大量的外匯。由上述，因此本研究針對中西太平洋漁場之黃鰭鮪做資源評估的研究。一般而言，名目努力量的代表性較差，容易受漁期、漁區等因素影響，因此本研究以Honma法對影響努力量效率的時間、空間因素加以修正，而經修正後的漁獲努力量便稱為有效努力量。以各年份的有效努力量和漁獲量估算各年份之單位努力漁獲量 ( Catch per unit effort , CPUE ) 以作為資源密度變動的指標。在中西太平洋作業的國家眾多，漁具漁法也大不相同，加上資料的完整性不足、取得他國資料的困難等等，要直接將不同漁業國別的資料標準化至同一水準在實行上是很困難的。因此假設中西太平洋海域的黃鰭鮪皆以我國延繩釣漁業的標準漁具所漁獲，視我國延繩釣漁業之CPUE為漁場的資源密度指標，其值與SPC ( The Secretariat of the Pacific Community ) 漁獲統計資料中的總漁獲量相除，藉此估算出中西太平洋黃鰭鮪資源所承受的總漁獲努力量。以上述之方法求得標準努力量及CPUE，代入生產量模式以評估資源的動態。為了進一步瞭解資源動態，在方法上除了使用傳統的Schaefer模式之外，也嘗試以Pella-Tomlinson模式及Fox模式評估資源動態，以估算最大永續生產量 ( Maximum sustainable yield, MSY )，藉此了解資源的概略狀況，並提供漁業管理機關作為訂定管理目標的依據。生產量模式中，Schaefer模式估算出中西太平洋黃鰭鮪系群的MSY為440827公噸；Fox模式所評估的MSY為393683公噸；Pella- Tomlinson模式當曲線參數m值約等於1時 ( m=1.00001 )，CPUE與努力量之間的相關係數最高，且所評估之結果與 Fox模式相似。此結果顯示中西太平洋黃鰭鮪的系群密度受漁業的開發後會呈指數衰減。由於Pella-Tomlinson模式之曲線參數較無生態意義，且計算上較為複雜，因此本研究使用Fox模式作中西太平洋黃鰭鮪資源變動的進一步研討。將Hampton et. al ( 2004 ) 以MULTIFAN-CL模式所評估之結果與本研究以Fox模式所評估之結果作比較，MULTIFAN-CL模式 ( 以1990年後的平均補充量 ) 和Fox模式 ( 以1990年後漁獲資料 ) 評估之結果分別為350000-464000公噸和430514公噸，兩模式評估之結果相當接近，皆指出現今中西太平洋黃鰭鮪系群已瀕臨過漁水準。因此，須嚴加注意中西太平洋黃鰭鮪漁業之發展，以防止資源過漁。目錄摘要. i 第1章緒言. 1 1-1 黃鰭鮪簡介. 2 1-2 黃鰭鮪之漁獲狀況. 3 1-3 黃鰭鮪與中西太平洋漁場 . 4 1-4 努力量標準化的必要性. 5 1-5 資源評估-生產量模式. 6 1-6 研究動機、目的. 8 第2章材料. 11 第3章方法. 12 3-1 有效努力量修正.13 3-2 Gulland法.14 3-3 Honma法.17 3-4 努力量的標準化.21 3-5 資源評估方法.23 3-6 Schaefer模式.24 3-7 Fox模式.26 3-8 Pella-Tomlinson模式.27 第4章結果.29 4-1 台灣區名目資料變動情形.29 4-2 台灣區資料經Honma修正後之情形.31 4-3 資源動態之分析.33 4-4 Schaefer模式評估之結果. 34 4-5 Fox模式評估之結果. 34 4-6 Pella-Tomlinson模式評估之結果. 35 4-7 生產量模式之比較.37 4-8 Fox模式與資源評估. 38 4-9 Fox模式與MULTIFAN-CL模式之比較.39 第5章討論. 41 第6章結論. 51 參考文獻.56 附表.62 附圖.66 附錄.84
author2	王健雄臺灣大學：海洋研究所
format	Thesis
author	連永祥 Lien, Yung-Hsiang
author_facet	連永祥 Lien, Yung-Hsiang
author_sort	連永祥
title	以生產量模式評估資源動態結果之比較 -中西太平洋黃鰭鮪為例
title_short	以生產量模式評估資源動態結果之比較 -中西太平洋黃鰭鮪為例
title_full	以生產量模式評估資源動態結果之比較 -中西太平洋黃鰭鮪為例
title_fullStr	以生產量模式評估資源動態結果之比較 -中西太平洋黃鰭鮪為例
title_full_unstemmed	以生產量模式評估資源動態結果之比較 -中西太平洋黃鰭鮪為例
title_sort	以生產量模式評估資源動態結果之比較 -中西太平洋黃鰭鮪為例
publishDate	2006
url	http://ntur.lib.ntu.edu.tw/handle/246246/56503 http://ntur.lib.ntu.edu.tw/bitstream/246246/56503/1/ntu-95-R93241205-1.pdf
long_lat	ENVELOPE(-70.100,-70.100,-69.333,-69.333) ENVELOPE(166.383,166.383,-71.367,-71.367) ENVELOPE(51.183,51.183,-67.250,-67.250)
geographic	Hampton Pacific Schaefer Tomlinson
geographic_facet	Hampton Pacific Schaefer Tomlinson
genre	Arctic
genre_facet	Arctic
op_relation	A non, 2004. Report of the 17th meeting of the Standing Committee on Tuna and Billfish. A non, 2003. Report of the 16th meeting of the Standing Committee on Tuna and Billfish. A non,2002. Report of the 15th meeting of the Standing Committee on Tuna and Billfish. Baranov, F. I. , 1918. On the question of biological basis of fisheries. Nauchn. Issled. Ikhtiologicheskii Inst. Izv. 1 : 81-128. Beverton, R. J. H., and S. J. Holt. 1957 . On the dynamics of exploited fish population. 533p. Boggs, C. H. 1992. Depth, capture time, and hooked longecity of longline caught pelagic fish : Timing bites of fish with chips. Fish. Bull., 90:642-658. Carmer, J. and A. M. Eklund. 1991. Standardized catch rates of yellowfin tuna in the sport fisheries from Virginia to New York. SCRS/91/25, 230-244. Conser, R. J. 1984. An examination of the Honma method and its applicability in developing indices of abundance for Western Atlantic bluefin tuna. SCRS/84/32, 107-115. Fournier, D.A., J. Hampton, and J.R. Sibert, 1998. MULTIFAN-CL: a length-based, age-structured model for fisheries stock assessment, with application to South Pacific albacore, Thunnus alalunga. Can. J. Fish. Aquat. Sci. 55: 2105−2116. Fox, W. W. 1970. An exponential yield model for optimizing exploited fish populations. Trans. Am. Fish. Soc. 99: 80–88. Fry, F. E. J. 1949. Statistics of a lake trout fishery. Biometrics 5:27-67. Garrod, D. J., 1969. Empirical assessments of catch/effort relationships in North Atlantic cod stocks. Int. Comm. Northwest Atl. Fish. Res. Bull. 6 : 26-34. Gulland, J.A. 1965. Estimation of mortality rates. Annex to Arctic Fisheries Working Group Report. ICES CM 1965 Gadoid Fish Committee Doc. 3. Gulland, J. A. 1969 . Manual of method for fish stock assessment, Part 1. FAO Manual of Fishery Science, 4, 154-155. Gulland, J. A. 1983 . Fish Stock Assessment , FAO / Wiley Series on / Food and Agricluture Graham, M. 1935. Modern theory of exploiting fishery, and application to North Sea trawling. Journal du Conseil International pour l’Exploration de la Mer 10: 264–274. Hampton, J., P. Kleiber, 2003. Stock assessment of yellowfin tuna in the western and central Pacific Ocean. WP YFT-1, SCTB 16. Hampton , J. , P. Kleiber, A. Langley, K. Hiramatsu, 2004. Stock assessment of yellowfin tuna in western and central pacific ocean ,SCTB17 Working paper SA. Hampton, J., and D. Fournier, 2001. A spatially-disaggregated, length-based, age-structured population model of yellowfin tuna (Thunnus albacares) in the western and central Pacific Ocean. Mar. Freshw. Res. 52: 937−963. Hilborn, R., and Walters, C. J. 1992. Quantitative fisheries stock assessment. Chapman and Hall, New York, NY. 570 p. Holland, K. N., R. W. Brill, and R. K. C. Chang. 1990. Horizontal and vertical movements of yellowfin tuna and bigeye tuna associated with fish aggregating devices. Fish. Bull. 88:493–507 Honma, M. 1974b. Estimation of overall effective fishing intensity of tuna longline fishery. Far Seas Fish. Res. Lab. ,Bull. , : 193-213 Hjort, J., G. Jahn and P. Ottestad. 1933. The optimum catch. Hvalradets Skr. 7 : 92-127. Kleiber, P., M. Hinton, , and Y. Uozumi, 2003. Stock assessment of blue marlin (Makaira nigricans) in the Pacific using MULTIFAN-CL. Mar. Freshw. Res. 54: 349−360. Langley, A., and J. Hampton, 2004. The western and central pacific tuna fishery: 2003 overview and status of stocks. Oceanic Fisheries Programme, Tuna Fisheries Assessment Report No. 6. Lehodey, P. and Leroy B., 1999. A theoretical examination of some aspects of the interaction between longline and surface fisheries for yellowfin tuna, Thunnus albacares. Fish. Bull., 76(4) : 807-825. Ludwig D., C. J. Walters, 1989. A robust method for parameter estimation from catch and effort data. Can. J. Fish. Aquat. Sci., 46, 137-144. Maunder, M. N. 2003. Is it time to discard the Schaefer model from the stock assessment scientist toolbox? Fish. Res. 61 : 145-149. Miyabe, N. 1991. Trends of CPUE for Atlantic bluefin caught by the Janpanese longline fishery up to 1990. ICCAT/SCRS/91/71, 717-730 Nelder and Wedderburn, 1972. Generalized linear models. JRSS, A, 135, 370–384. Pella, J. J., 1967. A study of methods to estimate the Schaefer model parameters with special reference to the yellowfin tuna fishery in the eastern tropical Pacific Ocean.Doctoral dissertation, University of Washington. 156 p. Pella, J. J. and P. K. Tomlinson, 1969. A generalized stock production model . IATTC Bull. Inter-Am. Trop. Tuna Comm. 13:419-496. Pope, J.G. 1972. An investigation of the accuracy of virtual population analysis using cohort analysis. ICNAF Res. Bull. 9:65–74. Prager, M. H. 1992a. ASPIC: A Surplus-Production Model Incorporating Covariates. 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_version_	1766302660634345472
spelling	ftntaiwanuniv:oai:140.112.114.62:246246/56503 2023-05-15T14:28:30+02:00 以生產量模式評估資源動態結果之比較 -中西太平洋黃鰭鮪為例 Assessing the Stocks by Production model for Yellowfin tuna Distributed in the Western and Central Pacific Ocean 連永祥 Lien, Yung-Hsiang 王健雄臺灣大學：海洋研究所 2006 3516362 bytes application/pdf http://ntur.lib.ntu.edu.tw/handle/246246/56503 http://ntur.lib.ntu.edu.tw/bitstream/246246/56503/1/ntu-95-R93241205-1.pdf zh-TW en_US chi eng A non, 2004. Report of the 17th meeting of the Standing Committee on Tuna and Billfish. A non, 2003. Report of the 16th meeting of the Standing Committee on Tuna and Billfish. A non,2002. Report of the 15th meeting of the Standing Committee on Tuna and Billfish. Baranov, F. I. , 1918. On the question of biological basis of fisheries. Nauchn. Issled. Ikhtiologicheskii Inst. Izv. 1 : 81-128. Beverton, R. J. H., and S. J. Holt. 1957 . On the dynamics of exploited fish population. 533p. Boggs, C. H. 1992. Depth, capture time, and hooked longecity of longline caught pelagic fish : Timing bites of fish with chips. Fish. Bull., 90:642-658. Carmer, J. and A. M. Eklund. 1991. Standardized catch rates of yellowfin tuna in the sport fisheries from Virginia to New York. SCRS/91/25, 230-244. Conser, R. J. 1984. An examination of the Honma method and its applicability in developing indices of abundance for Western Atlantic bluefin tuna. SCRS/84/32, 107-115. Fournier, D.A., J. Hampton, and J.R. Sibert, 1998. MULTIFAN-CL: a length-based, age-structured model for fisheries stock assessment, with application to South Pacific albacore, Thunnus alalunga. Can. J. Fish. Aquat. Sci. 55: 2105−2116. Fox, W. W. 1970. An exponential yield model for optimizing exploited fish populations. Trans. Am. Fish. Soc. 99: 80–88. Fry, F. E. J. 1949. Statistics of a lake trout fishery. Biometrics 5:27-67. Garrod, D. J., 1969. Empirical assessments of catch/effort relationships in North Atlantic cod stocks. Int. Comm. Northwest Atl. Fish. Res. Bull. 6 : 26-34. Gulland, J.A. 1965. Estimation of mortality rates. Annex to Arctic Fisheries Working Group Report. ICES CM 1965 Gadoid Fish Committee Doc. 3. Gulland, J. A. 1969 . Manual of method for fish stock assessment, Part 1. FAO Manual of Fishery Science, 4, 154-155. Gulland, J. A. 1983 . Fish Stock Assessment , FAO / Wiley Series on / Food and Agricluture Graham, M. 1935. Modern theory of exploiting fishery, and application to North Sea trawling. Journal du Conseil International pour l’Exploration de la Mer 10: 264–274. Hampton, J., P. Kleiber, 2003. Stock assessment of yellowfin tuna in the western and central Pacific Ocean. WP YFT-1, SCTB 16. Hampton , J. , P. Kleiber, A. Langley, K. Hiramatsu, 2004. Stock assessment of yellowfin tuna in western and central pacific ocean ,SCTB17 Working paper SA. Hampton, J., and D. Fournier, 2001. A spatially-disaggregated, length-based, age-structured population model of yellowfin tuna (Thunnus albacares) in the western and central Pacific Ocean. Mar. Freshw. Res. 52: 937−963. Hilborn, R., and Walters, C. J. 1992. Quantitative fisheries stock assessment. Chapman and Hall, New York, NY. 570 p. Holland, K. N., R. W. Brill, and R. K. C. Chang. 1990. Horizontal and vertical movements of yellowfin tuna and bigeye tuna associated with fish aggregating devices. Fish. Bull. 88:493–507 Honma, M. 1974b. Estimation of overall effective fishing intensity of tuna longline fishery. Far Seas Fish. Res. Lab. ,Bull. , : 193-213 Hjort, J., G. Jahn and P. Ottestad. 1933. The optimum catch. Hvalradets Skr. 7 : 92-127. Kleiber, P., M. Hinton, , and Y. Uozumi, 2003. Stock assessment of blue marlin (Makaira nigricans) in the Pacific using MULTIFAN-CL. Mar. Freshw. Res. 54: 349−360. Langley, A., and J. Hampton, 2004. The western and central pacific tuna fishery: 2003 overview and status of stocks. Oceanic Fisheries Programme, Tuna Fisheries Assessment Report No. 6. Lehodey, P. and Leroy B., 1999. A theoretical examination of some aspects of the interaction between longline and surface fisheries for yellowfin tuna, Thunnus albacares. Fish. Bull., 76(4) : 807-825. Ludwig D., C. J. Walters, 1989. A robust method for parameter estimation from catch and effort data. Can. J. Fish. Aquat. Sci., 46, 137-144. Maunder, M. N. 2003. Is it time to discard the Schaefer model from the stock assessment scientist toolbox? Fish. Res. 61 : 145-149. Miyabe, N. 1991. Trends of CPUE for Atlantic bluefin caught by the Janpanese longline fishery up to 1990. ICCAT/SCRS/91/71, 717-730 Nelder and Wedderburn, 1972. Generalized linear models. JRSS, A, 135, 370–384. Pella, J. J., 1967. A study of methods to estimate the Schaefer model parameters with special reference to the yellowfin tuna fishery in the eastern tropical Pacific Ocean.Doctoral dissertation, University of Washington. 156 p. Pella, J. J. and P. K. Tomlinson, 1969. A generalized stock production model . IATTC Bull. Inter-Am. Trop. Tuna Comm. 13:419-496. Pope, J.G. 1972. An investigation of the accuracy of virtual population analysis using cohort analysis. ICNAF Res. Bull. 9:65–74. Prager, M. H. 1992a. ASPIC: A Surplus-Production Model Incorporating Covariates. Collected Volume of Scientific Papers, International Commission for the Conservation of Atlantic Tunas 28: 218–229. Prager, M. H. 1992b. Recent developments in extending the ASPIC production model. ICCAT Working Document SCRS/92/127. 10 p. Ricker, W.E. 1975. Computation and interpretation of biological statistics of populations. Bull. Fish. Res. Board Can. 191 : 382p. Russel, F. S. 1931. Some theoretical considerations on the overfishing problem. J. Cons. Explor. Mer., 6: 3-27. Scaefer, M. B. 1954. Some aspects of the dynamics of populations important to the management of commercial marine fisheries. Bull. Inter-Am. Trop. Tuna Comm. Bull. 1:27-56. Schaefer M. 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Acta Oceanographica Taiwanica, 35(2), 125-139. 王尉任，2004。西太平洋黃鰭鮪生殖生物學研究。國立台灣大學海洋研究所碩士論文。李存富，1995。漁業開發前後黃鰭鮪成長之比較。國立台灣大學海洋研究所碩士論文。沈世傑、李信徹、邵廣昭、莫顯蕎、陳春暉、陳哲聰，1993。台灣魚類誌。邱文毓，2004。台灣近海鮪延繩釣黃鰭鮪資源分布與海洋環境因子關係之探討。國立台灣大學海洋研究所碩士論文。邵廣昭、陳天任、賴景陽、何平合、柳芝蓮、陳章波，1996。台灣常見魚介貝類圖說(下)-魚類。姚菊芳，1991。台灣近海以屏東及高雄為主之鮪延繩釣漁業黃鰭鮪的漁場變動與資源解析。國立台灣大學海洋研究所碩士論文。葉裕民，1995。南太平洋長鰭鮪資源變動分析-努力量修正結果的影響。國立台灣大學海洋研究所碩士論文。廖錦焜，2001。台灣南部海域黃鰭鮪鱗片膠質纖維層作年齡查定形質可行性之研究。國立台灣大學海洋研究所碩士論文。劉正文，2004。東港小型鮪延繩釣漁業漁況分析及黃鰭鮪資源評估。國立台灣大學海洋研究所碩士論文。鐘榮峰，1981。西部太平洋黃鰭鮪胃內含物之研究。國立台灣大學海洋研究所碩士論文。蘇楠傑，2003。台灣近海鮪延繩釣漁業黃鰭鮪的年齡、成長、死亡率與單位加入生產量。國立台灣大學海洋研究所碩士論文。黃鰭鮪生產量模式 Honma法資源評估 yellowfin tuna production model Honma method stock assessment thesis 2006 ftntaiwanuniv 2016-02-20T00:03:51Z 在世界各大鮪類漁場中，中西太平洋漁場的鮪類產量豐富，若能得知此漁場的資源狀況，便可作為漁業管理的依據，且能藉此擬定我國在此海域之發展策略。黃鰭鮪為我國經濟價值相當高的魚種，每年外銷至日本為我國賺取大量的外匯。由上述，因此本研究針對中西太平洋漁場之黃鰭鮪做資源評估的研究。一般而言，名目努力量的代表性較差，容易受漁期、漁區等因素影響，因此本研究以Honma法對影響努力量效率的時間、空間因素加以修正，而經修正後的漁獲努力量便稱為有效努力量。以各年份的有效努力量和漁獲量估算各年份之單位努力漁獲量 ( Catch per unit effort , CPUE ) 以作為資源密度變動的指標。在中西太平洋作業的國家眾多，漁具漁法也大不相同，加上資料的完整性不足、取得他國資料的困難等等，要直接將不同漁業國別的資料標準化至同一水準在實行上是很困難的。因此假設中西太平洋海域的黃鰭鮪皆以我國延繩釣漁業的標準漁具所漁獲，視我國延繩釣漁業之CPUE為漁場的資源密度指標，其值與SPC ( The Secretariat of the Pacific Community ) 漁獲統計資料中的總漁獲量相除，藉此估算出中西太平洋黃鰭鮪資源所承受的總漁獲努力量。以上述之方法求得標準努力量及CPUE，代入生產量模式以評估資源的動態。為了進一步瞭解資源動態，在方法上除了使用傳統的Schaefer模式之外，也嘗試以Pella-Tomlinson模式及Fox模式評估資源動態，以估算最大永續生產量 ( Maximum sustainable yield, MSY )，藉此了解資源的概略狀況，並提供漁業管理機關作為訂定管理目標的依據。生產量模式中，Schaefer模式估算出中西太平洋黃鰭鮪系群的MSY為440827公噸；Fox模式所評估的MSY為393683公噸；Pella- Tomlinson模式當曲線參數m值約等於1時 ( m=1.00001 )，CPUE與努力量之間的相關係數最高，且所評估之結果與 Fox模式相似。此結果顯示中西太平洋黃鰭鮪的系群密度受漁業的開發後會呈指數衰減。由於Pella-Tomlinson模式之曲線參數較無生態意義，且計算上較為複雜，因此本研究使用Fox模式作中西太平洋黃鰭鮪資源變動的進一步研討。將Hampton et. al ( 2004 ) 以MULTIFAN-CL模式所評估之結果與本研究以Fox模式所評估之結果作比較，MULTIFAN-CL模式 ( 以1990年後的平均補充量 ) 和Fox模式 ( 以1990年後漁獲資料 ) 評估之結果分別為350000-464000公噸和430514公噸，兩模式評估之結果相當接近，皆指出現今中西太平洋黃鰭鮪系群已瀕臨過漁水準。因此，須嚴加注意中西太平洋黃鰭鮪漁業之發展，以防止資源過漁。目錄摘要. i 第1章緒言. 1 1-1 黃鰭鮪簡介. 2 1-2 黃鰭鮪之漁獲狀況. 3 1-3 黃鰭鮪與中西太平洋漁場 . 4 1-4 努力量標準化的必要性. 5 1-5 資源評估-生產量模式. 6 1-6 研究動機、目的. 8 第2章材料. 11 第3章方法. 12 3-1 有效努力量修正.13 3-2 Gulland法.14 3-3 Honma法.17 3-4 努力量的標準化.21 3-5 資源評估方法.23 3-6 Schaefer模式.24 3-7 Fox模式.26 3-8 Pella-Tomlinson模式.27 第4章結果.29 4-1 台灣區名目資料變動情形.29 4-2 台灣區資料經Honma修正後之情形.31 4-3 資源動態之分析.33 4-4 Schaefer模式評估之結果. 34 4-5 Fox模式評估之結果. 34 4-6 Pella-Tomlinson模式評估之結果. 35 4-7 生產量模式之比較.37 4-8 Fox模式與資源評估. 38 4-9 Fox模式與MULTIFAN-CL模式之比較.39 第5章討論. 41 第6章結論. 51 參考文獻.56 附表.62 附圖.66 附錄.84 Thesis Arctic National Taiwan University Institutional Repository (NTUR) Hampton ENVELOPE(-70.100,-70.100,-69.333,-69.333) Pacific Schaefer ENVELOPE(166.383,166.383,-71.367,-71.367) Tomlinson ENVELOPE(51.183,51.183,-67.250,-67.250)

以生產量模式評估資源動態結果之比較 -中西太平洋黃鰭鮪為例

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