东太平洋长鳍金枪鱼栖息地指数模型的比较
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摘要
根据2009–2011年东太平洋海域长鳍金枪鱼延绳钓的生产数据,结合海洋遥感获得的表温(SST)和海面高度(SSH)的数据,采用外包络法,以投钩数、单位捕捞努力量渔获量(CPUE)为适应性指数,按月份分别建立基于SST和SSH的长鳍金枪鱼栖息地适应性指数(SI)。采用算术平均法(AMM)和几何平均法(GMM)获得基于SST和SSH环境因子的栖息地指数(HSI)综合模型,并以2012年各月生产数据进行模型验证。结果表明,基于两种HSI模型所得的长鳍金枪鱼栖息地综合指数不相同,通过算术平均法的HSI模型,当HSI为0.6以上时,渔获量占总渔获量的87.9%,通过几何平均法的HSI模型,当HSI为0.6以上时,渔获量所占比例为87.2%。算术平均法较GMM更适于东太平洋长鳍金枪鱼栖息地指数模型。
Albacore tuna(Thunnus alalunga) is one of important tunas in the eastern Pacific, and also one of the main target species for Chinese tuna longline fishing fleets. Based on the statistical data of Thunnus alalunga longline fishery in the eastern Pacific Ocean from 2009 to 2011, combined with the data of surface temperature(SST) and sea surface height(SSH) obtained by ocean remote sensing, using the outer envelope method, The fishing effort(CPUE) was the adaptive index, and the Thunnus alalunga habitat suitability index(SI) based on SST and SSH was established in each month. The comprehensive model of habitat suitability index was obtained by arithmetic mean method(AMM) and geometric mean method(GMM), and validated by monthly production statistics in 2012. The results showed that the HSI model of the albacore tuna habitat index was different from the HSI model. When the HSI was above 0.6, the HSI model accounted for 87.9% of the total. By HSI model of geometric average method, when the HSI is 0.6 or more, 87.2% of the total. Arithmetic mean method is fit for the habitat index model of albacore tuna in the East Pacific, and it can guide the fishery production and fishing.
Albacore tuna(Thunnus alalunga) is one of important tunas in the eastern Pacific, and also one of the main target species for Chinese tuna longline fishing fleets. Based on the statistical data of Thunnus alalunga longline fishery in the eastern Pacific Ocean from 2009 to 2011, combined with the data of surface temperature(SST) and sea surface height(SSH) obtained by ocean remote sensing, using the outer envelope method, The fishing effort(CPUE) was the adaptive index, and the Thunnus alalunga habitat suitability index(SI) based on SST and SSH was established in each month. The comprehensive model of habitat suitability index was obtained by arithmetic mean method(AMM) and geometric mean method(GMM), and validated by monthly production statistics in 2012. The results showed that the HSI model of the albacore tuna habitat index was different from the HSI model. When the HSI was above 0.6, the HSI model accounted for 87.9% of the total. By HSI model of geometric average method, when the HSI is 0.6 or more, 87.2% of the total. Arithmetic mean method is fit for the habitat index model of albacore tuna in the East Pacific, and it can guide the fishery production and fishing.
引文
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[17]DAGORN L,HOLLAND K N,HALLIER J P,et al.Deep diving behavior observed in yellowfin tuna(Thunnus albacares)[J].Aquatic Living Resources,2006,19(1):85-88.
[2]陈新军.渔业资源与渔场学[M].北京:海洋出版社,2004.
[3]范江涛,陈新军,钱卫国,等.南太平洋长鳍金枪鱼渔场预报模型研究[J].广东海洋大学学报,2011,31(6):61-67.
[4]戴芳群,李显森,王凤臣,等.中东太平洋长鳍金枪鱼延绳钓作业分析[J].海洋水产研究,2006,27(6):37-42.
[5]任中华,陈新军,方学燕.基于栖息地指数的东太平洋长鳍金枪鱼渔场分析[J].海洋渔业,2014(5):385-395.
[6]方学燕,陈新军,丁琪.基于栖息地指数的智利外海茎柔鱼渔场预报模型优化[J].广东海洋大学学报,2014,34(4):67-73..
[7]GORE J A,HAMILTON S W.Comparison of flow-related habitat evaluations Comparison of flow-related habitat evaluations downstream of low-head weirs on small and large fluvial ecosystems[J].Regulated Rivers:Research&Management,1996,12(12):459-469
[8]MADDOCK I.The importance of physical habitat assessment for evaluating river health[J].Freshwater Biology,1999,41(2):373-391.
[9]高峰,陈新军,范江涛,等.西南大西洋阿根廷滑柔鱼中心渔场预报的实现及验证[J].上海海洋大学学报,2011,20(5):754-758.
[10]ZAINUDDIN M,SAITOH K,SAITOH S I.Albacore(Thunnus alalunga)fishing ground in relation to oceanographic conditions in the western North Pacific Ocean using remotely sensed satellite data[J].Fisheries Oceanography,2008,17(2):61-73.
[11]HESS G R,BAY J M.A regional assessment of wind break habitat suitability[J].Environmental Monitoring and Assessment,2000,61(2):239-256.
[12]ZAINUDDIN M,SAITOH K,SAITOH S I.Albacore(Thunnus alalunga)fishing ground in relation to oceanographic conditions in the western North Pacific Ocean using remotely sensed satellite data[J].Fisheries Oceanography,2008,17(2):61-73.
[13]WANG C H,WANG S B.Assessment of South Pacific albacore stock(Thunnus alalunga)by improved Schaefer model[J].Journal of Ocean University of China,2006,5(2):106-114.
[14]VI?AS J,ALVARADO BREMER JR,PLA C.Inter-oceanic genetic differentiation among albacore(Thunnus alalunga)populations[J].Marine Biology,2004,145(2):225-232.
[15]HOLLAND K N,BRILL R W,CHANG R K C.Horizontal and vertical movements of yellowfin and bigeye tuna associated with fish aggregating devices[J].Fisheries Bulletin,1990,88(3):493-507.
[16]BRILL R W,BLOCK B A,BOGGS C H,et al.Horizontal movements and depth distribution of large adult yellowfin tuna(Thunnus albacares)near the Hawaiian Islands,recorded using ultrasonic telemetry:implications for the physiological ecology of pelagic fishes[J].Marine Biology,1999,133(3):395-408.
[17]DAGORN L,HOLLAND K N,HALLIER J P,et al.Deep diving behavior observed in yellowfin tuna(Thunnus albacares)[J].Aquatic Living Resources,2006,19(1):85-88.