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应用栖息地指数对印度洋大眼金枪鱼分布模式的研究

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冯波[1,2] 陈新军[1] 许柳雄[1]

[1]上海水产大学海洋学院,上海200090 [2]广东海洋大学水产学院,广东湛江524006

水产学报
订阅本刊
国际标准刊号:ISSN 1000-0615
国内统一刊号:CN 31-1283

摘  要:

运用分位数回归方法对温度、温差、氧差与印度洋大眼金枪鱼延绳钓钓获率进行二次回归分析,找出最佳上界方程,以最佳上界方程拟合的数值来建立栖息地指数(HSI)模型,从而揭示印度洋大眼金枪鱼栖息地的分布模式。研究表明,温度、温差、氧差与印度洋大眼金枪鱼延绳钓钓获率的最佳上界分位数回归方程分别为HRT0.9=-44.803+7.685T0.9-0.255T0.9^2,HRd70.9=6.234+0.953dT0.9-0.026dT0.9^29和HRdO0.88=7.422+4.25dO0.88-0.727dO0.88^2。10°N-10°S间印度洋海域大眼金枪鱼HSI指数达到0.9以上;10°N以北的波斯湾及10°S~15°S海域的HSI指数为0.8~0.9;15°S~40°S之间海域HSI指数介于0.7~0.8,其中50°E~90°E、15°S~25°S间存在一片季节性HSI指数〈0.7的区域;40°S以南的海域HSI指数〈0.6。[著者文摘]

way to investigate correlation between organism and limiting ecological factors.Key words:Thunnus obesus;quantile regression;habitat suitability index(HSI);Indian Ocean 印度洋大眼金枪鱼(Thunnus obesus)是我国远洋金枪鱼延绳钓船队主捕鱼种之一,2004年产量在8 321,2 t,约占其总产量的62.45%。大眼金枪鱼的空间分布及其与环境关系得到世界渔业管理组织和学者的重视J。在研究鱼类栖息地分布领域,上世纪80年代初期由美国鱼类和野生生物署(US Fish and Wildlife Service)提出的栖息地指数(habitat suitability index,HSI)模型。该模型广泛地被应于预测和显示海洋经济鱼类的栖息地分布,为政府决策层提供管理依据。然而我国在......

文章出处:

《水产学报》-2007年31卷6期 -805-812页

Journal of Fisheries of China

分 类 号:

S931.2

文献标识码:

A

文章编号:

1000-0615(2007)06-0805-08

相关文章:

参考文献(18篇) 耦合文献(18篇)  主题相关

[参考文献]

Study on distribution of Thunnuns obesus in the Indian Ocean based on habitat suitability index

FENG BO, CHEN Xin-jun , XU Liu-xiong (1. College of Marine Science and Technology, Shanghai Fisheries University, Shanghai 200090, China; 2. Fisheries College, Guangdong Ocean University, Zhanjiang 524006, China)

Abstract:

Bigeye tuna Thunnuns obesus is one of key species caught by Chinese tuna longline fleets. Its spatial distribution in relation to environmental factors is highlighted by international organizations and researchers. The aim of this study is to present the analysis of correlation between hooking rates of bigeye tuna longline and environmental factors in the Indian Ocean. Three environmental variables including temperature, temperature difference and dissolved oxygen difference are used to fit habitat suitability model in order to explain the distribution pattern of bigeye tuna in the Indian Ocean. Function expressions of hooking rates and environmental factors are estimated by quantile regression. Data predicted by optimum upper boundary quantile curves are fitted to the habitat suitability model to display quarterly distribution of bigeye tuna via visualization of Surfer 8.0. The optimum upper boundary quantile curves for temperature (T)-hooking rate (HR), temperature difference (dT)-HR and dissolved oxygen difference (dO2)-HR are in the following HRT0.9 = -44. 803 + 7. 685T0.9 -0. 255T0.9^2, HRdT0.9 = 6. 234 + 0. 953dT0.9 -0. 026dT0.9^2 and HRdO0.88 = 7. 422 + 4. 25dO0. 88 -0. 727dO0.88^2 as, respectively. Habitat suitability index is above 0.9 within 10°N-10°S, 0.8-0.9 in the north of 10°N and within 10°S- 15°S, 0.7 -0.8 within 15°S-40°S, and below 0.6 in the south of 40°S. However, a mass of waters occurs seasonally within 50°E-90°E,15°S - 25°S where habitat suitability index is less than 0.7. The habitat suitability model indicates the reliable results and could be improved by integrating more interactive variables. It is proved in this study that quantile regression is a useful way to investigate correlation between organism and limiting ecological factors.[著者文摘]

Key words:

Thunnus obesus ; quantile regression ; habitat suitability index (HSI) ; Indian Ocean

收稿日期: 2006-12-06

基金资助:

国家科技支撑计划(2006BAD09A05);教育部新世纪优秀人才计划(NCET-06-0437);上海市重点学科(T1101) 本文得到集美大学水产学院王家樵老师大力帮助,特此致谢.

作者简介:

冯波(1977-),男,江苏宜兴人,讲师,博士研究生,从事海洋渔业资源研究。Tel:021-65711985 通讯作者:陈新军,E-mail:xjchen@shfu.edu.cn

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