热带大西洋公海金枪鱼延绳钓渔获物上钩率的分析

报道 1 994年 1 1月至 1 996年 1 0月 (4～ 7月除外 )金丰 2号延绳钓船在中部大西洋公海 (0 9°N～ 0 5°S ,1 8°W～ 34°W )钓捕渔获物和各月经济鱼种上钩率的状况。经过鉴定共有 2 7种鱼类和一种海龟。在 2月的北纬渔场和 1 2月上半月在南纬西部渔场 (0 1°S～ 0 5°S ,2 4°W以西 ) ,大眼金枪鱼的上钩率达到高峰值 ,均大于 8‰ ,其它期间在钓捕海域上钩率在 2‰～ 8‰之间 ;在 1 1月、1 2月的北纬渔场和 1 2月上半月在南纬西部渔场 ,黄鳍金枪鱼的上钩率均大于 4‰ ,而在南纬中部渔场 (0 1°S～ 0 5°S ,2 4°W～ 1 8°W )黄鳍金枪鱼的上钩率最低 ,小于 1‰ ;箭鱼的上钩率在钓捕海域大体在 2‰以下 ,其它低经济价值的鱼上钩率几乎都小于 1‰。本文探讨了影响上钩率的因素。     

热带大西洋金枪鱼延绳钓兼捕鲨鱼种类组成和渔获率及其与表温的关系

根据2007年12月~2008年3月采集的热带大西洋(05°37′~12°01′N、29°00′~36°51′W)金枪鱼延绳钓渔获物数据,分析了金枪鱼延绳钓兼捕鲨鱼的种类组成、渔获量、渔获率及其与表温的关系。本次调查共捕获鲨鱼8种,隶属3目7科7属,总渔获尾数为633 ind,总渔获量达26 837.4 kg,其中大青鲨为主要兼捕种类。各种鲨鱼渔获率平均值在0.003~1.524 ind/1 000 hooks之间,其中大青鲨最高,其值为1.524 ind/1 000 hooks,大眼砂锥齿鲨最低,其值为0.003 ind/1 000 hooks。各种鲨鱼渔获率月变化不明显(ANOVA,P=0.901)。鲨鱼总渔获率和大青鲨渔获率与表温都呈显著性负相关。大青鲨主要出现渔场的表温范围为24.6~25.8℃。     

基于GAM模型分析水温垂直结构对热带大西洋大眼金枪鱼渔获率的影响

通过模型分析环境变量对延绳钓大眼金枪鱼渔获率的影响,评估适宜垂直活动空间对大西洋大眼金枪鱼延绳钓渔获率的作用。首先采用回归分析检验环境变量对延绳钓渔获率(由单位捕捞努力渔获量(catch per unit fishing effort,CPUE)表示)的影响显著性,结合时空变量,采用GAM(generalized additive model)模型分析各变量对大眼金枪鱼CPUE非线性作用。模型结果表明,环境因子和时空变量对热带大西洋延绳钓大眼金枪鱼渔获率空间分布影响明显。大西洋大眼金枪鱼延绳钓的高渔获率月份出现在夏季和冬季,空间上在赤道以北和30?~50?W。12℃等温线深度对大眼金枪鱼延绳钓渔获率的影响表现为抛物线形状,高渔获率出现在深度较浅的250 m水层,随着12℃等温线深度的增加,大眼金枪鱼延绳钓渔获率降低。温跃层下界深度和深度差对大眼金枪鱼延绳钓渔获率的影响都是穹顶状。随着温跃层下界深度值和深度差由小变大至200 m,延绳钓渔获率递增;温跃层下界深度和深度差超过200 m后,延绳钓渔获率变小。温跃层下界深度和深度差对大眼金枪鱼延绳钓渔获率影响显著的水层分别是200 m和50 m。研究结果显示,12℃等温线深度和温跃层对热带大西洋延绳钓大眼金枪鱼渔获率影响是交叉的,在大眼金枪鱼适宜垂直活动水层受限到和延绳钓作业深度相同时,延绳钓渔获率最高;在适宜垂直活动空间过深或者过浅时,延绳钓渔获率都变小,但可以通过改变作业方式提高渔获率。采用延绳钓CPUE进行渔场和资源评估要考虑金枪鱼适宜垂直活动空间。     

金枪鱼延绳钓环形钩和圆形钩钓获率比较

根据"华远渔18号"和"华远渔19号"两艘冰鲜金枪鱼延绳钓渔船2005年9月15日~12月12日在印度洋热带公海水域(0°47′~10°16′N,61°40′~70°40′E)作业期间收集的数据,以每千钩钓获尾数和平均净重,对环型钩与圆型钩对大眼金枪鱼和黄鳍金枪鱼的选择性、钓获率差异等进行了比较研究。结果表明:不同钓具漂移速度下环型钩与圆型钩各自对大眼金枪鱼和黄鳍金枪鱼的选择性无显著差异;不同钓具漂移速度下环型钩与圆型钩之间对大眼金枪鱼和黄鳍金枪鱼的钓获率无显著差异;环型钩与圆型钩之间对大眼金枪鱼和黄鳍金枪鱼渔获物净重无显著差异。     

金枪鱼延绳钓渔获性能研究进展

金枪鱼延绳钓渔获性能主要按目标鱼种和兼捕物种渔获效率进行评价.对其研究有助于改进延绳钓渔具渔法,提高目标鱼种捕捞效率和减少兼捕.本文以时间顺序为主对国内外关于金枪鱼延绳钓渔获性能研究的文献进行梳理,从钓具选择性、钓钩深度、饵料选择性、环境因素以及钓具浸泡时长等方面概括了金枪鱼延绳钓渔获性能的研究进展,并提出存在的不足和...     

西北印度洋延绳钓大眼金枪鱼渔获率的时间序列小波特征

基于西北印度洋日本延绳钓金枪鱼1965-2006年间大眼金枪鱼(Thunnus obesus)每月渔获统计资料,本研究运用小波方法对大眼金枪鱼渔获率变化、印度洋涛动指数(IOI)及两者之间的响应关系进行了分析.研究发现,大眼金枪鱼渔获率在时间序列上存在48～60个月的小波振荡,IOI振荡周期主要为36月和60月,2种尺度振幅具有跷跷板效应.小波交叉分析结果表明,1994年前在36月和60月的时间尺度上大眼金枪鱼渔获率与IOI之间的响应关系是明显的,之后这种关系并不显著.在典型的小波振荡周期为4年的尺度卜,IOI和大眼金枪鱼渔获率的振荡间隔在1～3年之间变化,平均为1.5年左右.IOI振荡周期在3～6年间变化,时快时慢,而大眼金枪鱼渔获率信号振荡较平稳.南于捕捞因素影响,近年来渔获率的振荡幅度不断减弱.研究认为可排除由于较大的捕捞努力量和渔业资源量时空变动导致的捕获率信号变异,从捕捞因素和环境因素上讨论了捕获率信号小波特征及其与环境变动的响应关系.     

大西洋金枪鱼延绳钓渔场的地统计分析

使用地统计方法研究大西洋金枪鱼延绳钓渔场空间变异特征及时空分布,分析数据为1982―2010年日本大西洋大眼金枪鱼(Thunnus obesus)延绳钓渔捞数据。结果表明,大眼金枪鱼渔场分布具有较强的空间相关性,6月、10月和11月空间相关性显著(P<0.05),其他月份空间相关性极显著(P<0.01);指数模型能够较好地表达渔场的空间变异特征,其相关系数介于0.6~0.9之间,模型拟合较好;预测图表明大眼金枪鱼渔场变化呈现出两种轨迹,一种是大西洋中部与美洲近岸之间的循环变化,另一种是大西洋中部与非洲近岸之间的循环变化;预测结果验证表明,地统计能较好地对渔场空间分布进行预测,但是单位捕捞努力量渔获量(CPUE)预测值显著高于2009―2010年实测值,资源状况差异可能是引起本次研究预测值偏高的主要原因。     

利用广义线性模型分析印度洋黄鳍金枪鱼延绳钓渔获率

利用广义线性模型,以年、季节、海区、渔具结构以及渔具材料等效应为主要因子,假设5种方案对日本在印度洋的黄鳍金枪鱼(Thunnus albacares)延绳钓渔获率进行标准化.结果显示,这5种方案对渔获率的变化都具有较好的解释率.其中方案3的解释率最高,达到68%.主效应中,渔区、季节、年份具有最大的F值,表明它们能够解释剩余方差中的最大部分;交互项中,渔区与季节、主绳材料和支绳材料也具有较大的F值.这种情况与日本大眼金枪鱼延绳钓数据标准化的结果很相似.考虑每栏钩数的信息时,可使总方差的解释率提高8%～9%.当分别用每月每次投钩数≥5 000钩和≥10 000钩筛选的数据拟合模型时,可使总方差的解释率分别提高3%和2%,预测残差也更趋正态分布.但本标准化结果仍待进一步完善,在资源评估时,应审慎运用.     

太平洋大眼金枪鱼延绳钓渔获分布及渔场环境浅析

本文主要根据收集到的渔获量数据、海水表层温度数据和有关文献资料 ,应用GIS技术对太平洋大眼金枪鱼延绳钓渔业进行了定量或定性分析。结果表明 :太平洋大眼金枪鱼延绳钓渔场主要分布在 2 0°N～2 0°S之间的热带海域 ,具纬向分布特征。对渔获产量同海表温度的分月统计显示 :太平洋大眼金枪鱼渔场最适月平均表层水温约 2 8～ 2 9℃ ,渔场出现频次为偏态分布型。最后 ,结合有关文献综合讨论分析了海表温度、溶解氧含量、海流等环境因子与金枪鱼渔场分布和形成机制的关系     

Separation of the Taiwanese regular and deep tuna longliners in the Indian Ocean using bigeye tuna catch ratios

ABSTRACT:   Taiwanese longline (LL) fisheries operating in the Indian Ocean usually target albacore tuna (ALB), swordfish (SWO) and yellowfin tuna (YFT) using regular LL. Bigeye tuna (BET), however, is targeted using deep LL. Thus, these two types of LL are considered to be different gears as they target different tuna species. Regular or deep LL fishing is defined by number of hooks per basket (NHB): regular LL if 6 ≤ NHB ≤ 10 and deep LL if 11 ≤ NHB ≤ 20. However, NHB information was available in only some of the recent LL data (1995–1999). This situation had caused problems of biased results in stock analysis in the past. Thus, the objective of our study was to explore an effective method to separate the two types of LL fishing by considering species composition. Some intervals of BET catch ratios were found to be effective in separating the regular and deep LL catches, i.e. 0.0 ≤ BET/(BET + ALB + SWO) ≤ 0.4 and 0.8 ≤ BET/(BET + ALB) ≤ 1.0, respectively. Using these two separators, the LL known data set (1995–1999) (learning data set) was classified. Correct classification occurred in 67.7% of the data, while 23.1% of the data were unclassified (11.9% due to zero catches and 11.2% due to classification into both LL types), and 9.2% were misclassifications. Then, using the methods developed, the LL unknown data set in the historical data (1979–1999) was classified and nominal CPUE values were calculated for four species. The CPUE trends based on this study were likely to be more reliable than those of previous studies.     

印度洋金枪鱼延绳钓主要渔获种类及分布

根据印度洋金枪鱼管理委员会IOTC的金枪鱼生产数据库,对1967-2004年间印度洋金枪鱼延绳钓主要渔获种类的产量按年进行汇总和基于5度格网进行了空间上的统计,采用GIS软件制作了印度洋金枪鱼延绳钓主要渔获种类的捕捞产量的地理空间分布图,分析了其资源的空间分布特征。分析结果表明,大眼金枪鱼Thunnus obesus、黄鳍金枪鱼Thunnus albacares、长鳍金枪鱼Thun-nus alalunga和剑鱼Xiphias gladius是印度洋金枪鱼延绳钓的主要渔获种类,其产量之和占到总产量的90%,这4种印度洋金枪鱼延绳钓的主要渔获种类从1967-2004年的产量均呈上升趋势,但产量的峰谷变化各不相同;空间分布特征研究表明,尽管在印度洋海域分布范围广泛,但产量丰沛的区域存在明显差异。     

Standardizing catch and effort data of the Taiwanese distant-water longline fishery in the western and central Pacific Ocean for bigeye tuna, Thunnus obesus

Catch per unit effort (CPUE) is often used as an index of relative abundance in fisheries stock assessments. However, the trends in nominal CPUE can be influenced by many factors in addition to stock abundance, including the choice of fishing location and target species, and environmental conditions. Consequently, catch and effort data are usually ‘standardized’ to remove the impact of such factors. Standardized CPUE for bigeye tuna, Thunnus obesus, caught by the Taiwanese distant-water longline fishery in the western and central Pacific Ocean (WCPO) for 1964–2004 were derived using three alternative approaches (GLM, GAM and the delta approach), and sensitivity was explored to whether catch-rates of yellowfin tuna and albacore tuna are included in the analyses. Year, latitude, and the catch-rate of yellowfin explained the most of the deviance (32–49%, depending on model configuration) and were identified consistently among methods, while trends in standardized catch-rate differed spatially. However, the trends in standardized catch-rates by area were found to be relatively insensitive to the approach used for standardization, including whether the catch-rates of yellowfin and albacore were included in the analyses.     

Association between the interannual variation in the oceanic environment and catch rates of bigeye tuna (Thunnus obesus) in the Atlantic Ocean

The environmental processes associated with variability in the catch rates of bigeye tuna in the Atlantic Ocean are largely unexplored. This study used generalized additive models (GAMs) fitted to Taiwanese longline fishery data from 1990 to 2009 and investigated the association between environmental variables and catch rates to identify the processes influencing bigeye tuna distribution in the Atlantic Ocean. The present findings reveal that the year (temporal factor), latitude and longitude (spatial factors), and major regular longline target species of albacore catches are significant for the standardization of bigeye tuna catch rates in the Atlantic Ocean. The standardized catch rates and distribution of bigeye tuna were found to be related to environmental and climatic variation. The model selection processes showed that the selected GAMs explained 70% of the cumulative deviance in the entire Atlantic Ocean. Regarding environmental factors, the depth of the 20 degree isotherm (D20) substantially contributed to the explained deviance; other important factors were sea surface temperature (SST) and sea surface height deviation (SSHD). The potential fishing grounds were observed with SSTs of 22–28°C, a D20 shallower than 150 m and negative SSHDs in the Atlantic Ocean. The higher predicted catch rates were increased in the positive northern tropical Atlantic and negative North Atlantic Oscillation events with a higher SST and shallow D20, suggesting that climatic oscillations affect the population abundance and distribution of bigeye tuna.     

印度洋大眼金枪鱼延绳钓适宜渔获环境的初步研究

数值分析得出大眼金枪鱼的渔获适宜环境参数值范围：温度14～17℃,盐度34．5～35．4．溶解氧浓度1．5～4．5mg／L,温跃层深度80～160m,营养盐氮、磷、硅浓度分别大于12-μg／L,09μg／L,14μg／L。聚类分析表明,钓获率与营养盐关系最为密切。另外,通过因子分析,深化了对钓获率和渔获环境因子两者间关系的理解。     

Alternative error distribution models for standardization of catch rates of non-target species from a pelagic longline fishery: billfish species in the Venezuelan tuna longline fishery

Alternative error distributions were evaluated for calculating indices of relative abundance for non-target species using catch and effort data from commercial fisheries. A general procedure is presented for testing the underlying assumptions of different error distributions. Catch rates, from an observer program, of billfish caught mainly as bycatch in a pelagic tuna longline fishery in the Western Central Atlantic were standardized. Although catches of billfishes are not common in pelagic tuna longline fisheries, these fisheries are one of the main sources of fishing mortality for these stocks in the central Atlantic due to the magnitude and spatial extent of longline fishing effort. Billfish CPUE data are highly skewed with a large proportion of zero observations. Delta distribution models can accommodate this type of data, and involve modeling the probability of a non-zero observation and the catch rate given that the catch is non-zero separately. Three different Delta models were compared against other error distributions, including the lognormal, log-gamma, and Poisson. Diagnostic checks and deviance table analyses were performed to identify the best error distribution and the set of factors and interactions that most adequately explained the observed variability. The results indicated that the Delta-lognormal model (a binomial error distribution for the probability of a non-zero catch and lognormal error for the positive catch rates) complied best with the underlying characteristics of the data set. Analyses of catch rates for blue marlin, white marlin and sailfish confirmed the spatio-temporal nature of their distribution in the central Atlantic and Caribbean Sea. Also, the analyses indicated that catch rates of billfish differed among fishing vessel types; larger vessels had a higher probability of catching blue marlin, the more oceanic-oriented species, and lower probabilities of catching the more coastal-oriented species white marlin and sailfish. Standardized catch rates indicated in general a lower relative abundance for blue and white marlin in the most recent years, although estimated confidence intervals overlap through the years especially for white marlin.     

热带印度洋大眼金枪鱼垂直分布空间分析

为了解热带印度洋大眼金枪鱼(Thunnus obesus)适宜的垂直和水平空间分布范围,采用Argo浮标剖面温度数据重构热带印度洋10℃、12℃、13℃和16℃月平均等温线场,网格化计算了12℃、13℃等温线深度值和温跃层下界深度差,并结合印度洋金枪鱼委员会(IOTC)大眼金枪鱼延绳钓渔业数据,绘制了12℃、13℃等温线深度与月平均单位捕捞努力渔获量(CPUE)的空间叠加图,用于分析热带印度洋大眼金枪鱼中心渔场 CPUE 时空分布和高渔获率水温的等温线时空分布的关系.结果表明,从垂直分布来看,热带印度洋中心渔场延绳钓高渔获率区域垂直分布在温跃层下界以下,在表层以下150~400 m 深度区间.从水平分布来看,12℃等温线,高 CPUE 区域大多深度值<350 m,众数为225~350 m;深度值超过500 m的区域CPUE普遍较低.13℃等温线,高值CPUE出现的地方大多深度值<300 m,众数为190~275 m;深度值超过400 m的区域CPUE普遍较低.全年在15oS以北区域,高渔获率的垂直分布深度更加集中.采用频次分析和经验累积分布函数,计算其最适次表层环境因子分布,12℃等温线250~340 m;13℃等温线190~270 m;12℃深度差30~130 m;13℃深度差0~70 m.研究初步得出热带印度洋大眼金枪鱼中心渔场适宜的水平、垂直深度值分布区间,可以辅助寻找中心渔场位置,同时指导投钩深度,为热带印度洋金枪鱼实际生产作业和资源管理提供理论支持.     

金枪鱼延绳钓渔捞日志管理现状与趋势

金枪鱼渔捞日志作为金枪鱼数据收集系统的一部分,在区域性国际渔业组织履约中扮演了重要的角色.本文梳理了国际渔业组织涉及金枪鱼延绳钓渔捞日志的履约要求,分析了部分国家或地区金枪鱼渔捞日志管理要求,论述了我国金枪鱼延绳钓渔捞日志管理中存在的问题,并提出了改进建议和发展方向:(1)渔捞日志嵌入船位监控系统,缩短渔捞日志上交的时效性,提高日志填写的准确性;(2)统一金枪鱼渔业数据收集系统,建立大型金枪鱼数据库,使渔业数据规模化、标准化.     

热带大西洋西部水域大眼金枪鱼延绳钓渔场分布及其与表温之间的关系

根据2004年9月至2005年3月农业部渔业观察员项目在热带大西洋西部水域调查所获得的渔业数据和现场表温数据,结合哥伦比亚大学网站下载的1°×1°表温资料,利用地理信息系统(GIS)软件Marineexplore 4.0图示了各月钓获率及钓获率与表温关系的分布并进行分析。结果表明,2004年11月的产量和CPUE均达到最高,分别为24.539 t和0.332 t/v.d。调查期间,各月钓获率大部分(80.3%)分布在表温高于26.0℃。     

The effects of mesoscale oceanographic structures and ambient conditions on the catch of albacore tuna in the South Pacific longline fishery

Albacore tuna (Thunnus alalunga) exhibit patchy concentrations associated with biological process at a wide range of spatial scales, resulting in variations in their catchability by fishing gears. Here, we investigated the association of catch variation for pelagic longlines in the South Pacific Ocean with oceanographic mesoscale structures (in horizontal dimension) and ambient conditions (in vertical dimension). The distribution of albacore tuna as indicated by catch per unit effort (CPUE) of longlines was significantly related to the presence of mesoscale structures, with higher CPUE found at locations closer to thermal fronts and with greater gradient magnitudes, as well as areas marked by peripheral contour line of the anticyclone indicated by Sea Surface Height Anomalies ~0.05 m. Surface mesoscale current velocity had the negative effect on the catch, probably as a result of decreased catchability by shoaling the hook depth. Vertical distribution of albacore in the survey region of South Pacific Ocean was hardly restricted by ambient temperature and oxygen concentration, though effect of ambient temperature was relevant and showed a negatively linear correlation with CPUE at the range of 20–24°C. On the contrary, albacore distribution was evidently dominated by the water depth and showed strong preference on water depth of 200 m, which was likely a representative feeding layer. The presence of prey resources and their accessibility by albacore revealed by mesoscale structures in the biological and physical processes, and catchability determined by the location of the baited hooks comprehensively contribute to the variability of catch.