库克群岛海域海洋环境因子对大眼金枪鱼渔获率的影响

为了掌握库克群岛海域海洋环境因子对延绳钓渔业中大眼金枪鱼渔获率的影响,实验利用2013年9月8日—12月31日在库克群岛海域作业的延绳钓渔业调查数据,所获数据包括:钓钩深度数据,温度、叶绿素a浓度、三维海流的垂直剖面数据,作业参数,渔获统计数据,采用逐步回归的方法建立钓钩预测深度计算模型,利用统计和聚类分析的方法分析大眼金枪鱼渔获率与海洋环境因子的关系。结果发现,在库克群岛附近海域,大眼金枪鱼渔获率较高的水层、温度、叶绿素a浓度、东西海流、南北海流、水平海流和垂直海流分别为120.0～199.9 m、13.0～14.9 ℃、0.200～0.239 μg/L、0.1～0.2 m/s、-0.2～0 m/s、0.1～0.4 m/s和0.04～0.05 m/s。在该海域作业、以大眼金枪鱼为目标鱼种时,建议在大眼金枪鱼渔获率较高的水层、温度、叶绿素a浓度、水平海流和垂直海流范围内增加钓钩投放数量。     

大西洋中部大眼金枪鱼垂直分布与温度、盐度的关系

根据2001年7月4日至10月27日3艘在大西洋中部公海海域作业的中国金枪鱼延绳钓船上随机观测到的大眼金枪鱼(Thunnus obesus)的上钩钩号,应用悬链线钩深计算公式,分别计算出各钩号的钩深;根据STD仪测得的温度、盐度的垂直分布以钩深为引数,查出该尾鱼捕获时的温度和盐度数据。根据大眼金枪鱼的取样数据,利用频度统计的方法,推算出各水层、水温、盐度范围的渔获率。渔获率最大的水层、水温、盐度范围为大眼金枪鱼的最适水层、水温和盐度范围;渔获率为前3位的水层、水温、盐度范围为大眼金枪鱼活动较频繁的水层、水温和盐度范围。结果表明：大西洋中部,大眼金枪鱼的最适水层为240．00～269．99m水深、最适水温为12．00～12．99℃、最适盐度为35．00～35．09;大西洋中部渔场大眼金枪鱼活动较频繁的水层为240．00～329．99m水深、水温为10．00～12．99℃、盐度为35．00～35．29。     

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。     

磁珠富集法制备大口鲶的微卫星分子标记

2004年3月16日-6月8日，在广东广远渔业集团有限公司玻璃钢大滚筒冷海水金枪鱼延绳钓渔船“华远渔19”号，对印度洋马尔代夫海域进行金枪鱼渔业调查。所获数据资料包括：①CTD测定的温度、盐度和深度数据，TDR测定的实际钩深；②作业参数，包括每次作业的钩数、投绳位置、投绳时间、航向、航速、出绳速度、两浮子间的钩数、起绳位置、起绳时间等；③渔场环境数据，包括风速、风向、钓具对地漂移速度和方向；④渔获统计，包括大眼金枪鱼的渔获尾数以及部分大眼金枪鱼的钓获钩号；⑤生物学数据，包括起捕时已死的大眼金枪鱼的体温。分析计算的方法和步骤为：①由理论公式推算出每次作业时各钩号的理论深度；②应用逐步回归的方法，建立理论钩深与实测的平均钩深之间的数学关系模型；③根据实际平均钩深模型计算出每个钓钩的平均作业深度；④根据CTD测得的作业地点的温度、盐度的垂直分布（41次），获得分布曲线。由此，以计算的钩深，从曲线上查出该尾鱼捕获水深处的温、盐数据；⑤根据121尾大眼金枪鱼的取样数据，推算出各水层、水温段、盐度段的渔获率；⑥根据起捕时已死的34尾大眼金枪鱼（鱼体发硬）的体温、以死鱼体温为引数，在曲线上查出该尾鱼捕获水深和盐度；最后，对钓获的大眼金枪鱼的钓获水层、水温和盐度进行了总体分析。分析结果表明：在马尔代夫海域，捕获大眼金枪鱼的水层为50～210m、水温范围为13．0～29．9℃、盐度范围为35．00～35．79；渔获率最高的水层为70～90m、水温范围为27．0～27．9oC、盐度范围为35．70～35．79；捕获时已死鱼的捕获水层、水温和盐度推算数据为63～203m、14．0～27．0℃和34．94～35．42，主要集中在63～134m、16．0～27．0℃和35．30～35．42。     

南太平洋长鳍金枪鱼延绳钓渔获率与环境因子的关系研究

为掌握不同水层的环境因子对长鳍金枪鱼(Thunnus alalunga)延绳钓渔获率的影响,根据2015-2017年中国大陆在该海域的长鳍金枪鱼延绳钓渔捞日志资料,结合同期海洋环境数据,采用广义可加模型(Generalized additive model,GAM)对渔获率与各因子的关系进行研究。通过相关分析获取各环境因子相关系数,对相关性较大的环境因子分组建模。结果表明:1)海表面温度与120 m水深温度、海表面温度与海表面高度、120 m水深温度与海表面高度、300 m水深温度与300 m水深盐度为高度相关因子,海表面盐度、叶绿素a浓度、海表风场南北分量与其他环境因子之间的相关性均较小;2)模型的总解释偏差介于30%~40%,各环境因子重要性依次为120 m水深温度、海表温度、300 m水深温度、120 m水深盐度、海表面高度、300 m水深盐度、海表盐度、混合层深度、海面风场南北分量、海面风场东西分量、叶绿素a浓度;3)120 m水深温度与单位捕捞努力渔获量(CPUE)在15~30℃呈负相关。海表温度整体趋势与120 m水深温度类似,其中在25~28℃呈正相关。300 m水深温度与CPUE在10~18℃呈现明显的正效应关系。     

基于GAM 的吉尔伯特群岛海域黄鳍金枪鱼栖息地综合指数

为了可持续利用黄鳍金枪鱼(Thunnus albacares)资源,本文利用2009年10月～12月吉尔伯特群岛海域海上实测的34个站点海洋环境垂直剖面数据,黄鳍金枪鱼渔获率数据,应用广义加性模型(generalized additive model,GAM) 进行建模,预测渔获率,并通过wilcoxon检验来判断预测渔获率与名义渔获率是否存在显著相关性。根据预测渔获率估算黄鳍金枪鱼的栖息地综合指数(IHI),通过对各水层IHI均值分析和Pearson相关系数,判断该方法的预测能力。使用2010年11月～2011年1月在吉尔伯特群岛海域实测的16个站点40～80m水层和0～240m水体的环境数据,验证模型。结果表明：(1)拟合的各水层的IHI值分布各不相同,各水层中影响黄鳍金枪鱼分布的因子各不相同,黄鳍金枪鱼主要栖息在40～120m水层;(2)2010年数据验证结果表明,GAM模型的预测能力较好;(3)GAM在筛选影响黄鳍金枪鱼分布的因子时比较有效,能反应黄鳍金枪鱼渔获率与环境因子之间的非线性关系;(4)可通过GAM建立IHI指数模型来分析大洋性鱼类栖息地的空间分布。     

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.     

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     

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。     

山东南部近海秋、冬季星康吉鳗分布与环境因子的关系

根据2016年10月和2017年1月在山东半岛南部海域秋、冬2个航次获取的渔业资源与栖息环境调查数据,分析了星康吉鳗(Conger myriaster)的时空分布特征。运用广义可加模型研究了星康吉鳗数量分布与季节、水深、底层盐度和底层水温等影响因子间的关系。结果表明,该海域星康吉鳗的数量分布有明显的季节变化,秋季的渔获率高于冬季,且分布范围更广。星康吉鳗在近岸海域渔获率较高,分布相对均匀,远岸海域渔获率较低,分布不均匀。广义可加模型显示,对星康吉鳗分布影响显著的环境因子为水深和底层水温(P0.05),其中水深的影响最为明显。星康吉鳗渔获率随水深的增大呈现先增加后减少再增加的趋势,在水深30~40 m处渔获率较高。星康吉鳗渔获率随水温的升高呈现先增加再减少的趋势,最适水温约为10℃。山东南部近海星康吉鳗的空间分布与其洄游习性、黄海暖流的季节变化等引起的海洋环境因子的变动有关。     

Environmental preferences of longlining for yellowfin tuna (Thunnus albacares) in the tropical high seas of the Indian Ocean

A survey of yellowfin tuna, Thunnus albacares , fishing ground was carried out on board of the Chinese longliners from September 15 to December 12, 2005 in the tropical high seas of the Indian Ocean. The depth at which each yellowfin tuna was hooked was estimated using a stepwise regression analysis of theoretical hook depth and observed average hook depth measured using a temperature depth recorder. Water temperature, salinity, chlorophyll  a , dissolved oxygen and thermocline, which are important variables influencing yellowfin tuna habitats, were measured in the survey. Catch rates of yellowfin tuna were then analyzed with respect to depth, temperature, salinity, chlorophyll  a , dissolved oxygen and thermocline. We suggest that the optimum ranges of swimming depth, water temperature, chlorophyll  a and dissolved oxygen concentration for yellowfin tuna are 100.0–179.9 m, 15.0–17.9°C, 0.090–0.099  μ g L⁻¹, 2.50–2.99 mg L⁻¹, respectively; that salinity has less influence on the vertical distribution of adult yellowfin tuna; and that yellowfin tuna are mainly distributed within the thermocline in the high seas of the Indian Ocean. Our results match the yellowfin tuna's vulnerability to deep longline fishing gear well.     

库克群岛海域海洋环境因子对沙氏刺鲅兼捕率的影响

为了减少沙氏刺鲅(Acanthocybium solandri)的兼捕率,文章利用2012年9月~2012年11月在南太平洋库克群岛海域延绳钓渔业调查数据(包括钓钩深度数据,温度、盐度和叶绿素a质量浓度垂直剖面数据,作业参数和渔获统计数据),采用逐步回归的方法建立钓钩预测深度计算模型,利用统计和聚类分析的方法分析沙氏刺鲅的兼捕率与水层和温度的关系,并根据沙氏刺鲅兼捕率最高的水层推断得出其兼捕率最高的盐度和叶绿素a质量浓度范围。结果表明,库克群岛附近海域沙氏刺鲅兼捕率最高的水层和温度分别为40.0~80.0 m和26.0~28.0℃,推断得出沙氏刺鲅兼捕率最高的盐度段为36.30~36.90,叶绿素a质量浓度为0.070~0.243μg·L~(-1)。建议把钓钩深度设置到80 m以深、水温低于26℃、盐度高于36.90、叶绿素a质量浓度高于0.243μg·L~(-1)以减少延绳钓渔业中沙氏刺鲅的兼捕率。     

基于集成学习的大西洋热带水域大眼金枪鱼渔情预报

为提高大西洋大眼金枪鱼渔场预报模型的准确率,实验利用13艘中国延绳钓渔船2013—2019年的渔捞日志数据和对应的海洋环境数据(海表面风速、叶绿素a浓度、涡动能、混合层深度和0～500 m水层的垂直温度、盐度和溶解氧等),以天为时间分辨率、2°×2°为空间分辨率、以数据集的75%为训练数据建立了K最近邻(KNN)、逻辑斯蒂回归(LR)、分类与回归树(CART)、支持向量机(SVM)、人工神经网络(ANN)、随机森林(RF)、梯度提升决策树(GBDT)和Stacking集成(STK)渔情预报模型,以25%的测试数据进行模型性能测试、比较。结果显示,(1) STK (由KNN、RF、GBDT模型集成)模型的大眼金枪鱼渔场预报性能较KNN、LR、CART、SVM、ANN、RF和GBDT模型有所提高且相对稳定,上述模型对应的准确率和ROC曲线下面积(AUC)依次分别为81.62%、0.781,79.44%、0.778,72.81%、0.685,74.84%、0.717,73.67%、0.702,67.70%、0.500,80.96%、0.780和78.13%、0.747;(2) STK模型预测...     

Changes to vertical thermoregulatory movements of juvenile bigeye tuna (Thunnus obesus) in the northwestern Pacific Ocean with time of day,seasonal ocean vertical thermal structure,and body size

Vertical movements related to the thermoregulation were investigated in 12 juvenile bigeye tuna (Thunnus obesus) in Japanese waters using archival tag data. Movements changed with time of day, season, and body size. During daytime, bigeye tuna descended to greater depths, presumably to feed in the deep scattering layer (DSL). Thereafter, they repeatedly ascended to shallower layers, suggesting attempts at behavioral thermoregulation, although the beginning of vertical thermoregulatory ascents might reflect a shift in DSL depth. By the end of such movement, the whole‐body heat‐transfer coefficient might decrease because, although the depth and ambient temperature of the upper layers did not change, the body temperature gradually decreased significantly just after ascent for thermoregulation. Seasonal patterns indicated that the vertical thermal structure of the ocean might influence this ascent behavior. For example, from January to May, bigeye tuna made fewer ascents to less shallow waters, suggesting that they respond to increasing depths of the mixed surface layer by reducing energy expenditure during vertical migration. In addition, as body size increased, fewer thermoregulatory ascents were required to maintain body temperature, and fish remained deeper for longer periods. Thus, vertical thermoregulatory movements might change with body size as bigeye tuna develop better endothermic and thermoregulatory abilities. We hypothesize that bigeye might also increase cold tolerance as they grow, possibly due to ontogenetic shifts in cardiac function.     

Bigeye tuna (Thunnus obesus) vertical movements in the Azores Islands determined with pop-up satellite archival tags

Movement patterns of 17 bigeye tuna (Thunnus obesus) near the Azores Islands were analyzed between April and May 2001 and 2002 using pop‐up satellite archival tags. Despite short attachment durations (1 to 21 days, 8.2 days on average), their vertical movements revealed much shallower distribution of bigeye tuna in comparison with previous studies in the tropical Pacific and tropical Atlantic. Depth and temperature histograms were unimodal, although overall depth distribution during the day was deeper than during the night due to daily incursions in deeper waters. Although generalized additive models showed significant non‐linear relationships with weight of the fish and sea level anomaly (as a proxy for variability of thermocline depth), the effect of these variables on bigeye depth appeared minor, suggesting that vertical movements of bigeye in the Azores during the spring migration may be influenced by food availability in upper water layers.     

金枪鱼延绳钓钓具的最适浸泡时间

根据2010年10月—2011年1月金枪鱼延绳钓海上调查数据,分两种起绳方式,建立每次作业每一根支绳的浸泡时间计算模型。将钓具的浸泡时间以1 h为间隔分别统计每个区间的支绳数量及大眼金枪鱼(Thunnus obesus)、黄鳍金枪鱼(Thunnus albacores)的渔获尾数,并计算其钓获率(CPUE)。结果表明:1)大眼金枪鱼和黄鳍金枪鱼的CPUE都随浸泡时间的增加呈现先增后减的趋势,这是由于饵料的诱引效果变化及渔获的丢失引起的;2)二次曲线可拟合浸泡时间与大眼金枪鱼和黄鳍金枪鱼CPUE的关系;3)大眼金枪鱼和黄鳍金枪鱼CPUE最高的浸泡时间分别为9.9 h和10.1 h。建议:1)今后在金枪鱼延绳钓作业中,保证每一根支绳在水中的浸泡时间为9.5~10.5 h,以提高捕捞效率并减少副渔获物;2)可把延绳钓钓具的浸泡时间作为有效捕捞努力量,并用于CPUE的标准化。研究结果可用于提高捕捞效率并减少副渔获物的技术方案制订,并为渔业生产和CPUE的标准化提供科学参考。     

Spatial variability of bigeye tuna habitat in the Pacific Ocean: Hindcast from a refined ecological niche model

Habitat distribution is critically informative for stock assessment, since incorporating its variabilities can have important implications for the estimation of stock biomass or the relative abundance index. A refined ecological niche model with habitat characteristic parameterization was developed to reconstitute a 3‐D ecological map of bigeye tuna in the Pacific Ocean. We determined the boundaries and hierarchies of oceanographic features and hydrological conditions at horizontal and vertical scales to define the habitat preference of bigeye tuna associated with their feeding and physiological requirements. Ecogeographic projections underlined the depth‐ and region‐specific habitat distribution of bigeye tuna, with noticeable dynamic variations in the response to climate variability. Depths from 300 to 400 m represented layers of the most productive habitat, which was widespread through the equatorial Pacific Ocean and extended to the north‐central Pacific Ocean. The proportion of high‐quality habitat size in the north Pacific had a strictly regular intra‐annual cycle with peaks during the winter. Climate variability appeared to disturb the balance of the regular fluctuations in habitat size in the equatorial Pacific. Habitat hotspots during an El Niño period were characterized by their expansion to the north of the Hawaiian islands, shrinkage in the west for the hotspot band north of the Equator, and an eastern shift for the band south of the Equator. This variability may be the consequence of the incorporated fluctuations of the oxygen minimum zones (OMZ), current systems, and stratification in the open ocean.     

Considerations on diving patterns of bigeye tuna Thunnus obesus based on archival tag data

Swimming depth and selected environmental factors were examined using 2764 days of archival tag data for 18 bigeye tuna Thunnus obesus (fork length at release 58.5 ± 7.2 cm) that were captured, tagged, and released into Japanese waters. Daytime swimming depth was deeper with increasing body length. The lowest temperature encountered was usually about 10 °C or slightly higher. A positive correlation between swimming depth and light intensity at the ocean surface was dominant for during both daytime and nighttime. Synchronicity of swimming depth with deep scattering layer (DSL) was observed, except around midday. Deep diving to depths exceeding 550 m was observed a mean of 0.30 dives/fish/day. Based on the classification and analyses of deep diving pattern and consideration of environmental data, deep diving was assumed to be undertaken for the purposes of foraging, predator avoidance, and exploration of bathymetry, as well as due to aberrant behavior. Occasionally, extremely deep diving events exceeding 1000 m (maximum 1616 m) were recorded. Bigeye tuna appear to have high visual acuity and tolerance of both low and wide temperature ranges, and low dissolved oxygen content. Thus, probably bigeye tuna swimming depth is primarily adjusted based on prey distribution.     

Do habitat models accurately predict the depth distribution of pelagic fishes?

Habitat models are used to correct estimates of fish abundance derived from pelagic longline fishing gear. They combine information on hook depth with the species’ preferences for ambient environmental conditions to adjust the gear's catchability. We compare depth distributions of bigeye tuna (Thunnus obesus) catch predicted by a habitat model with distributions derived from data collected by observers on longliners in the tropical Pacific Ocean. Our analyses show that the habitat model does not accurately predict the depth distribution of bigeye tuna; its predictions are worse than those from models that assume no effect of depth on catches. Statistical models provided superior fits to the observed depth distribution. The poor performance of the habitat model is probably due to (1) problems in estimating hook depth, (2) fine‐scale variations in environmental conditions, (3) incomplete knowledge of habitat preferences and (4) differences between the distribution of bigeye tuna and their vulnerability to longline gear.     

Acoustic telemetry versus monitored longline fishing for studying the vertical distribution of pelagic fish: bigeye tuna (Thunnus obesus) in French Polynesia

This study compares detailed, nearly continuous, observations on bigeye tuna, Thunnus obesus equipped with electronic tags, with discrete observations on a larger number of individuals from fishing experiments in order to validate the use of instrumented longlines to study the vertical distribution of fish. We show that the depth distributions obtained from the two different observation techniques regarding different environmental variables (temperature, dissolved oxygen (DO), prey distribution) are similar. Bigeye tuna do not seem to be attracted by baits in the vertical dimension (no modification of their vertical distribution by the fishing gear), which allows the use of instrumented longlines to study the vertical behaviour of pelagic species. This technique, when used with appropriate deployment strategy, could therefore represent an alternative to electronic tags (acoustic or archival tags) when there is a need to determine the vertical distribution of fish species by size or sex, in different environments for the study of fishery interactions.