南太平洋长鳍金枪鱼栖息地指数模型的比较研究

根据1994-2010年南太平洋长鳍金枪鱼生产统计数据,结合海表面温度(SST)和海面高度(SSH)等海洋环境数据,将投放钩数(捕捞努力量)作为适应性指数,采用外包络法,利用算术平均法(AM)、几何平均法(GM)、连乘法(CP)、最大值法(Max)和最小值法(Min)等5种方法建立栖息地指数(HSI)模型。研究表明,通过对这5种方法进行比较,最大值法、算术平均法和几何平均法均得到较好的拟合效果,其中最大值法拟合效果最好,模型的准确度可达到85.2%。研究认为,可基于海表面温度和海面高度等海洋遥感因子,利用最大值法栖息地指数模型,较好地预测南太平洋长鳍金枪鱼中心渔场。     

东太平洋长鳍金枪鱼栖息地指数模型的比较

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。     

基于栖息地指数的智利外海茎柔鱼渔场预报模型优化

根据2010~2013年3-5月渔汛期间智利外海茎柔鱼生产统计数据以及海表面温(SST)、海表面盐度(SSS)、海表面高度(SSH)及叶绿素浓度(Chl-a)等海洋环境数据,以外包络法建立基于作业努力量和CPUE的各环境变量适应性指数(SI)。以SST作为建立SI的基准因子,采用算术平均法构建栖息地综合适应性指数模型(HSI),并选择最优栖息地指数模型,以用于茎柔鱼渔场预报,并利用2013年智利外海茎柔鱼生产数据进行验证。结果表明,以SST和SSS为因变量构建的HSI模型为最佳,且基于作业努力量的HSI模型要好于基于CPUE的HSI模型。以作业努力量为SI指标、基于SST和SSS为因子的HSI模型能较好预报智利外海茎柔鱼渔场。     

印度洋西北海域鸢乌贼9-10月栖息地适宜指数研究

印度洋西北部海域的鸢乌贼(Sthenoteuthis oualaniensis)具有一定的开发潜力,可作为商业性捕捞的对象,准确预报中心渔场可为指导生产提供依据。根据2003、2004年9～10月份期间我国鱿钓船在2°～24°N、57°～69°E海域的探捕数据,结合表温、盐度、海表面高度和叶绿素a,以CPUE作为适应性指数,利用算术平均法(AM)和几何平均法(GM)分别建立基于环境因子的综合栖息地指数模型。结果表明,9月份在栖息地指数(HSI)大于0.8的中心渔场作业次数比例超过24%,平均日产量在5.48 t/d左右;10月份在HSI大于0.8的中心渔场作业次数比例在43%以上,平均日产量在5.2 t/d以上。基于表温、盐度、海表面高度和叶绿素a的HSI模型能较好预测印度洋鸢乌贼中心渔场,且AM模型优于GM模型。     

基于频度统计和神经网络的北太平洋柔鱼渔场预报模型比较

利用2004~2010年北太平洋鱿钓船队生产数据和海洋环境数据,以海表温度(SST)1℃、海面高度(SSH)为1 cm、叶绿素a浓度(CHL-a)为0.1 mg/m3的间距,分析作业产量、CPUE与SST、SSH、CHL-a的关系,得到柔鱼渔场适宜环境因子范围,并将生产数据和环境数据匹配组成样本集,建立北太平洋柔鱼空间分布BP神经网络模型;利用2011年环境数据预报柔鱼渔场,并与2011年实际生产数据进行对比。结果表明,6~10月各月实际作业位置落入基于频度统计方法预报渔场的概率达90%以上;而BP模型预报的平均精度为79.2%,最低精度为52.5%。基于多环境因子的频度统计柔鱼渔场预报模型优于神经网络模型。     

基于遥感水质的夏季东海鲐鱼渔情预报研究

根据2007~2009年7~9月渔汛期间我国鲐鱼灯光围网在东海的生产数据,利用海表温、叶绿素浓度、悬浮物浓度和透明度等遥感水质数据,分别将作业网次比例和单网次产量(CPUE)作为适应性指数,利用算术平均数(AM)和几何平均数(GM)分别建立基于海表温、叶绿素浓度、悬浮物浓度和透明度的综合栖息地指数模型。结果表明,AM栖息地指数模型和GM栖息地指数模型拟合效果较好(P<0.01),在HSI大于0.5的海域,2007~2009年7~9月平均作业网次比例在65%以上,各月平均CPUE均高于19.82 t/net。研究认为,AM模型稍优于GM模型。利用2010年7~9月生产数据及遥感水质数据对AM模型进行验证,分析认为,87%以上的作业网次和产量分布在HSI高于0.5的海域,CPUE为14~17 t/net,且较稳定,波动较小。研究认为,基于遥感水质数据的AM栖息地指数模型能较好地预测东海鲐鱼渔场。     

基于栖息地指数模型的摩洛哥底拖网渔场研究

根据2012—2015年上海某远洋渔业公司的底拖网渔船收集的生产统计数据,结合卫星遥感获得的表温、叶绿素浓度和海面高度距平均值以及实地调查的水深数据,用栖息地指数方法,以几何平均模型(GMM)和算术平均模型(AMM)对摩洛哥底拖网渔场进行比较研究。结果表明,各月基于表温、海面高度距平值、叶绿素和海底水深的适应性指数不一致,各月适宜的海洋环境范围有差异。AMM模型中HSI大于0.6的作业网次占总数的65.92%,作业产量占总数的67.57%;GMM模型中HSI大于0.6的作业网次占总数的只有44.78%,作业产量占总数的49.60%。AMM模型比GMM模型更适合于摩洛哥底拖网渔场的预报。     

基于不同BP神经网络的西南大西洋阿根廷滑柔鱼渔场预报模型比较

根据2003-2011年渔汛期间我国鱿钓船在西南大西洋海域的生产统计数据,结合海洋遥感获得的海表温度(SST)和海面高度(SSH)等数据,以单位捕捞努力量渔获量(CPUE)和作业次数作为中心渔场指标,以月份、经度、纬度、SST和SSH为输入因子,利用BP神经网络方法构建西南大西洋阿根廷滑柔鱼中心渔场预报模型。比较14种不同结构的BP神经网络模型,以CPUE作为中心渔场预报指标的BP模型均较佳,其拟合残差范围为0.004 0~0.005 5,平均值为0.004 7;而以作业次数作为中心渔场预报指标的BP模型,其拟合残差范围为0.009 3~0.011 6,平均值为0.010 4。输入因子为月份、经度、纬度、SST和SSH,输出因子为初值化后的CPUE,网络结构为5-4-1时的BP神经网络模型为最佳,其拟合残差为0.004 025,该模型可用于阿根廷滑柔鱼中心渔场的预报。BP神经网络方法可为准确渔场预报提供新途径。     

水温影响下的印度洋黄鳍金枪鱼亲体补充量关系模拟研究

根据1960-2002年印度洋黄鳍金枪鱼亲体量-补充量(stock-recruitment,SR)及其表层水温资料,利用Ricker模型,水温分期Ricker模型和模糊逻辑Ricker模型,考察表层加权水温与黄鳍金枪鱼亲体量、补充量之间的关系。研究表明,模糊逻辑Ricker模型拟合效果最好,水温分期Ricker模型次之,均优于原始Ricker模型。水温分期Ricker模型中的暖水月补充量比冷水月大,在黄鳍金枪鱼资源量较低时,暖水条件更有利于种群的繁衍。模糊逻辑Ricker模型得出冷水月和暖水月条件下的极端估计,受水温等外界条件影响,黄鳍金枪鱼的补充量在两条SR曲线间波动。水温等环境条件的变化产生了不同于依赖于密度因素的种群动力过程,限制了原始Ricker模型对亲体补充量关系的描述。     

基于BP神经网络的中西太平洋鲣鱼渔场预报模型构建与比较

根据1998-2013年中西太平洋鲣鱼围网生产统计数据以及海洋环境数据,采用BP人工神经网络模型,分别以初值化后的单位捕捞努力量渔获量(CPUE,Catch per unit of effort)和捕捞努力量(Fishing Effort)作为中心渔场的表征因子,并作为BP模型的输出因子,以时间因子、空间因子、海洋环境因子(包括海表温度SST、海面高度SSH、Nino3.4区海表指标及叶绿素浓度Chl-a)等作为输入因子,构建22个BP神经网络模型,以最小拟合残差作为判断标准,比较渔场预报模型优劣。实验结果,以捕捞努力量为输出因子的模型的最小拟合残差均小于以CPUE为输出因子的模型,表明捕捞努力量更适合作为表征中心渔场的因子;同时,拟合残差的平均值随着输入因子的增加而减少,表明本研究所选的时间、空间、海洋环境因子等对鲣鱼中心渔场预报均极为重要。其中,以月份、经度、纬度、SST、SSH、Nino3.4a、Chl-a为输入因子,以初值化后的捕捞努力量为输出因子,结构为7-5-1的BP神经网络模型预报精度为最高,影响因子的重要性从高到低依次是经度、Chl-a、SST、纬度、NINO3.4a、SSH、月份。     

Modeling a habitat suitability index for the eastern fall cohort of Ommastrephes bartramii in the central North Pacific Ocean

The eastern fall cohort of the neon flying squid, Ommastrephes bartramii, has been commercially exploited by the Chinese squid jigging fleet in the central North Pacific Ocean since the late 1990s. To understand and identify their optimal habitat, we have developed a habitat suitability index (HSI) model using two potential important environmental variables - sea surface temperature (SST) and sea surface height anomaly (SSHA) - and fishery data from the main fishing ground (165°-180°E) during June and July of 1999-2003. A geometric mean model (GMM), minimum model (MM) and arithmetic weighted model (AWM) with different weights were compared and the best HSI model was selected using Akaike’s information criterion (AIC). The performance of the developed HSI model was evaluated using fishery data for 2004. This study suggests that the highest catch per unit effort (CPUE) and fishing effort are closely related to SST and SSHA. The best SST- and SSHA-based suitability index (SI) regression models were SISST-based = 0.7SIeffort-SST + 0.3 SICPUE-SST, and SISSHA-based = 0.5SIeffort-SSHA + 0.5SICPUE-SSHA, respectively, showing that fishing effort is more important than CPUE in the estimation of SI. The best HSI model was the AWM, defined as HSI=0.3SISST-based+ 0.7SISSHA-based, indicating that SSHA is more important than SST in estimating the HSI of squid. In 2004, monthly HSI values greater than 0.6 coincided with the distribution of productive fishing ground and high CPUE in June and July, suggesting that the models perform well. The proposed model provides an important tool in our efforts to develop forecasting capacity of squid spatial dynamics.     

Assessment of South Pacific Albacore Stock （Thunnus alalunga ） by Improved Schaefer Model

Based on catch and effort data of tuna longline fishery operating in the South Pacific Ocean, the South Pacific al-bacore stock was assessed by an improved Schaefer model. The results revealed that the intrinsic growth rate was about 1.28374 and carrying capacities vareied in the range from 73734 to 266732 metric tons. The growth ability of this species is remarkable. Stock dynamics mainly depends on environmental conditions. The stock is still in good condition. However, the continuous decreasing of biomass in recent years should be noticed.     

Effect of spatial and temporal scales on habitat suitability modeling: A case study of Ommastrephes bartramii in the northwest pacific ocean

Temporal and spatial scales play important roles in fishery ecology, and an inappropriate spatio-temporal scale may result in large errors in modeling fish distribution. The objective of this study is to evaluate the roles of spatio-temporal scales in habitat suitability modeling, with the western stock of winter-spring cohort of neon flying squid(Ommastrephes bartramii) in the northwest Pacific Ocean as an example. In this study, the fishery-dependent data from the Chinese Mainland Squid Jigging Technical Group and sea surface temperature(SST) from remote sensing during August to October of 2003–2008 were used. We evaluated the differences in a habitat suitability index model resulting from aggregating data with 36 different spatial scales with a combination of three latitude scales(0.5°, 1° and 2°), four longitude scales(0.5°, 1°, 2° and 4°), and three temporal scales(week, fortnight, and month). The coefficients of variation(CV) of the weekly, biweekly and monthly suitability index(SI) were compared to determine which temporal and spatial scales of SI model are more precise. This study shows that the optimal temporal and spatial scales with the lowest CV are month, and 0.5° latitude and 0.5° longitude for O. bartramii in the northwest Pacific Ocean. This suitability index model developed with an optimal scale can be cost-effective in improving forecasting fishing ground and requires no excessive sampling efforts. We suggest that the uncertainty associated with spatial and temporal scales used in data aggregations needs to be considered in habitat suitability modeling.     

Evaluation of FAD-associated purse seine fishery reduction strategies for bigeye tuna (Thunnus obesus) in the Indian Ocean

In the Indian Ocean, bigeye tuna supports one of the most important fisheries in the world. This fishery mainly consists of two components: longline and purse seine fisheries. Evidence of overfishing and stock depletion of bigeye tuna calls for an evaluation of alternative management strategies. Using an age-structured operating model, parameterized with the results derived in a recent stock assessment, we evaluated the effectiveness of applying constant fishing mortality (CF) and quasi-constant fishing mortality (QCF) strategies to reduce fishing effort of purse seining with fish aggregating devices (FADs) at different rates. Three different levels of productivity accounted for the uncertainty in our understanding of stock productivity. The study shows that the results of CF and QCF are similar. Average SSB and catch during simulation years would be higher if fishing mortality of FAD-associated purse seining was reduced rapidly. The banning or rapid reduction of purse seining with FAD resulted in a mean catch, and catch in the last simulation year, higher than that of the base case in which no change was made to the purse seine fishery. This could be caused by growth overfishing by purse seine fisheries with FADs according to the per-recruit analysis. These differences would be more obvious when stock productivity was low. Transferring efforts of FAD-associated purse seining to longline fisheries is also not feasible. Our study suggests that changes are necessary to improve the performance of the current management strategy.     

西北太平洋柔鱼资源与海洋环境的GIS空间分析

本文根据1995～2001年的西北太平洋地区(35°N～45°N,140°E～170°W)巴特柔鱼资源调查与生产的实际情况对柔鱼渔获量进行了研究,并利用同期遥感反演的海洋表层温度数据(SST)和近表层叶绿素a数据(Chlorophylla),拓展了GIS的空间分析功能,定量地研究了我国远洋柔鱼产量与水温、叶绿素等海洋要素场之间的关系,揭示西北太平洋柔鱼中心渔场的环境特征,以期为我国西北太平洋海区的鱿鱼生产服务。     

多变量分位数回归构建印度洋大眼金枪鱼栖息地指数

以0～300m水层加权平均水温、50～150m水层的温差和氧差及其交互变量为影响因子,运用分位数回归法,寻找出环境变量与大眼金枪鱼(Thunnus obesus)延绳钓钓获率的最佳上界分位数回归方程,计算出栖息地指数(HSI),并应用地理信息系统(GIS)软件绘制各月HSI空间分布图。研究表明:大眼金枪鱼延绳钓钓获率(HR)依加权平均水温(x)、温差(y)、氧差(z)与的最佳上界分位数回归方程为HR0.70=-15.596+2.124x-0.003x3+0.033xyz-0.036y2z+0.107yz2-0.337z3;HSI空间分布为:16°S—10°N印度洋海域HSI高于0.7,HSI>0.8的海域随季节发生显著变化,马达加斯加外海至100°E、16°S—26°S海域常年存在一片HSI<0.4的区域,26°S—40°S海域的HSI介于0.4～0.5,40°S以南海域HSI<0.4,东非外海季节性地出现一片HSI<0.6的海域。利用多个环境变量的栖息地指数模型来预测分析大洋金枪鱼资源分布效果较好。     

Importance of weighting for multi-variable habitat suitability index model: A case study of winter-spring cohort of Ommastrephes bartramii in the Northwestern Pacific Ocean

Weighting values for different habitat variables used in multi-factor habitat suitability index (HSI) modeling reflect the relative influences of different variables on distribution of fish species. Using the winter-spring cohort of neon flying squid (Ommastrephes bartramii) in the Northwestern Pacific Ocean as an example, we evaluated the impact of different weighting schemes on the HSI models based on sea surface temperature, gradient of sea surface temperature and sea surface height. We compared differences in predicted fishing effort and HSI values resulting from different weighting. The weighting for different habitat variables could greatly influence HSI modeling and should be carefully done based on their relative importance in influencing the resource spatial distribution. Weighting in a multi-factor HSI model should be further studied and optimization methods should be developed to improve forecasting squid spatial distributions.     

2006年北太平洋柔鱼作业渔场时空变化及其与表温的关系

<正>柔鱼(Ommastrephes bartramii)广泛分布在北太平洋,20世纪70年代初首先由日本鱿钓船开发,我国大陆于1993年开始利用该资源,1994年进行较大规模地商业性生产。目前北太平洋鱿钓渔业已成为我国远洋渔业的支柱[1]。据估计,历史上北太平洋柔     

Fluctuation in Ommastrephe bartrami yield in the North Pacific

The fluctuation in Ommastrephe bartrami yield from 1995 to 2001 in the North Pacific was shown obvious, on which this study was conducted using data of sea surface temperature (SST), chlorophyll-a (chl-a) and statistical production. The study shows that, cool water and low food abundance caused by abnormal Kuroshio resulted in the reduction in abundance of O. bartrami, which was worsened by excessive catch and the unawareness to local fishery resources protection.