印度洋长鳍金枪鱼资源评估的影响因素分析

多个模型被用于印度洋长鳍金枪鱼(Thunnus alalunga)的资源评估,但这些模型的评估结果均存在较大的不确定性,为此,本文对影响印度洋长鳍金枪鱼资源评估的因素进行了分析。分析结果认为:(1)由于渔业数据存在不报、漏报或混报及采样样本数过低、采样协议出现变化等问题,造成印度洋长鳍金枪鱼渔业的渔获量、体长组成或年龄组成数据存在质量问题;(2)尽管对单位捕捞努力渔获量(catch per unit effort,CPUE)进行了标准化,但目标鱼种变化及捕捞努力量空间分布变化仍严重影响了标准化CPUE数据的质量;(3)印度洋长鳍金枪鱼的种群生态学及繁殖生物学研究仍比较薄弱,种群结构、繁殖、生长、自然死亡信息比较缺乏,在资源评估中,相关参数设置需借用其他洋区的研究结果;(4)海洋环境对印度洋长鳍金枪鱼的资源变动与空间分布具有显著影响,但评估模型较少考虑海洋环境的影响。由于上述问题的存在,导致当前评估结果存在较大不确定性。未来,应继续探索提高资源评估质量的方法,同时研究建立管理策略评价框架,以避免渔业资源评估结果的不确定性对该渔业可持续开发的影响。

应用贝叶斯生物量动态模型评估印度洋黄鳍金枪鱼资源

利用贝叶斯生物量动态模型对印度洋黄鳍金枪鱼(Thunnus albacares)资源进行了评估,并分析了不同标准化单位捕捞努力渔获量(catch per unit effort,CPUE)、内禀增长率(r)先验分布对评估结果的影响。结果表明:(1)模型能较好拟合日本延绳钓渔业的标准化CPUE,但对中国台湾延绳钓渔业的标准化CPUE拟合较差;当模型单独使用日本标准化CPUE时,评估结果显示印度洋黄鳍金枪鱼被过度捕捞;若模型单独使用中国台湾标准化CPUE,则结果相反,显示印度洋黄鳍金枪鱼未被过度捕捞;而当同时使用两个标准化CPUE时,日本标准化CPUE数据获得更大估计权重,因此,评估结果与单独使用日本标准化CPUE的结果类似。(2)当r采用无信息先验时,r估计偏小,而环境容纳量(K)估计则偏大,参数估计不合理;当r采用信息先验时,r与K的后验分布估计相对合理;由于r与K存在显著的负相关关系,生物量动态模型难于同时有效估计这两个参数,特别是在数据质量较差情况下,因而采用信息先验能提高生物量动态模型参数估计的质量。(3)本研究利用偏差信息准则(Deviance Information Criterion,DIC)与均方误差(Mean Square Error,MSE)统计量对模型进行了比较,并选择模型S8用于评价印度洋黄鳍金枪鱼的资源状态。评估结果认为印度洋黄鳍金枪鱼被过度捕捞,既存在捕捞型过度捕捞,也存在资源型过度捕捞,这与资源合成(Stock synthesis version 3,SS3)等模型的评价结果一致。

基于最大熵和栖息地指数模型预测东、黄海日本鲭渔场分布

最大熵模型(Maximum Entropy Model,Maxent)和栖息地指数(Habitat Suitability Index,HSI)模型均广泛应用于渔情预报研究中。为比较两模型渔情预报效果以提升日本鲭(Scomber japonicus)资源的科学管理水平,本研究利用2003-2012年东、黄海日本鲭的渔业数据以及海表温度、海面高度、海表盐度、海表温度梯度等海洋环境数据,构建最大熵模型和HSI模型,以分析、比较两模型对东、黄海日本鲭栖息地的预测效果,并利用受试者工作特征(Receiver Operating Characteristic,ROC)曲线下面积(Area Under Curve,AUC)、模型预测的渔场概率与实际渔获量百分比之间的对应关系对两模型渔情预报效果进行了定量评价。结果表明:(1)最大熵模型预测的渔场发生高概率位置与捕捞位置基本重合,在无历史捕捞数据海域预测渔场发生的概率较低;HSI模型预测的高栖息地指数位置与捕捞位置部分重合,在无历史捕捞数据海域也可获得较高的栖息地指数,将非渔场预测为渔场的概率较高;(2)最大熵模型和HSI模型的月平均AUC值分别为0.95和0.66,故最大熵模型的预测结果相对较好;(3)使用HSI模型时,应在模型中加入非渔场数据,并加强对此类数据的收集,否则该类模型预报渔场时有扩大化的可能;使用最大熵模型时,必须提高渔业数据的空间覆盖率,否则无法全面反映渔场时空分布动态。本文研究结果可为提升东、黄海日本鲭渔情预报精度提供参考。

The impact of spatial autocorrelation on CPUE standardization between two different fisheries

Catch per unit of eff ort(CPUE) data can display spatial autocorrelation. However, most of the CPUE standardization methods developed so far assumes independency of observations for the dependent variable, which is often invalid. In this study, we collected data of two fisheries, squid jigging fishery and mackerel trawl fishery. We used standard generalized linear model(GLM) and spatial GLMs to compare the impact of spatial autocorrelation on CPUE standardization for different fisheries. We found that spatialGLMs perform better than standard-GLM for both fisheries. The overestimation of precision of CPUE estimates was observed in both fisheries. Moran's I was used to quantify the level of autocorrelation for the two fisheries. The results show that autocorrelation in mackerel trawl fishery was much stronger than that in squid jigging fishery. According to the results of this paper, we highly recommend to account for spatial autocorrelation when using GLM to standardize CPUE data derived from commercial fisheries.

Application of a Bayesian method to data-poor stock assessment by using Indian Ocean albacore (Thunnus alalunga) stock assessment as an example

It is widely recognized that assessments of the status of data-poor fish stocks are challenging and that Bayesian analysis is one of the methods which can be used to improve the reliability of stock assessments in data-poor situations through borrowing strength from prior information deduced from species with good-quality data or other known information. Because there is considerable uncertainty remaining in the stock assessment of albacore tuna（Thunnus alalunga） in the Indian Ocean due to the limited and low-quality data, we investigate the advantages of a Bayesian method in data-poor stock assessment by using Indian Ocean albacore stock assessment as an example. Eight Bayesian biomass dynamics models with different prior assumptions and catch data series were developed to assess the stock. The results show（1） the rationality of choice of catch data series and assumption of parameters could be enhanced by analyzing the posterior distribution of the parameters;（2） the reliability of the stock assessment could be improved by using demographic methods to construct a prior for the intrinsic rate of increase（r）. Because we can make use of more information to improve the rationality of parameter estimation and the reliability of the stock assessment compared with traditional statistical methods by incorporating any available knowledge into the informative priors and analyzing the posterior distribution based on Bayesian framework in data-poor situations, we suggest that the Bayesian method should be an alternative method to be applied in data-poor species stock assessment, such as Indian Ocean albacore.

Linkages between the biomass of Scomber japonicus and net primary production in the southern East China Sea

Fish biomass is a critical component of fishery stock assessment and management and it is often estimated from ocean primary production（OPP）. However, the relationship between the biomass of a fish stock and OPP is always complicated due to a variety of trophic controls in the ecosystem. In this paper, we examine the quantitative relationship between the biomass of chub mackerel（Scomber japonicus） and net primary production（NPP） in the southern East China Sea（SECS）, using catch and effort data from the Chinese mainland large light-purse seine fishery logbook and NPP derived from remote sensing. We further discuss the mechanisms of trophic control in regulating this relationship. The results show a significant non-linear relationship exists between standardized CPUE（Catch-Per-Unit-Effort） and NPP（P〈0.05）. This relationship can be described by a convex parabolic curve, where the biomass of chub mackerel increases with NPP to a maximum and then decreases when the NPP exceeds this point. The results imply that the ecosystem in the SECS is subject to complex trophic controls. We speculate that the change in abundance of key species at intermediate trophic levels and/or interspecific competition might contribute to this complex relationship.

A New model to forecast fishing ground of Scomber japonicus in the Yellow Sea and East China Sea

The pelagic species is closely related to the marine environmental factors, and establishment of forecasting model of fishing ground with high accuracy is an important content for pelagic fishery. The chub mackerel（Scomber japonicus） in the Yellow Sea and East China Sea is an important fishing target for Chinese lighting purse seine fishery. Based on the fishery data from China＇s mainland large-type lighting purse seine fishery for chub mackerel during the period of 2003 to 2010 and the environmental data including sea surface temperature（SST）, gradient of the sea surface temperature（GSST）, sea surface height（SSH） and geostrophic velocity（GV）, we attempt to establish one new forecasting model of fishing ground based on boosted regression trees. In this study, the fishing areas with fishing effort is considered as one fishing ground, and the areas with no fishing ground are randomly selected from a background field, in which the fishing areas have no records in the logbooks. The performance of the forecasting model of fishing ground is evaluated with the testing data from the actual fishing data in 2011. The results show that the forecasting model of fishing ground has a high prediction performance, and the area under receiver operating curve（AUC） attains 0.897. The predicted fishing grounds are coincided with the actual fishing locations in 2011, and the movement route is also the same as the shift of fishing vessels, which indicates that this forecasting model based on the boosted regression trees can be used to effectively forecast the fishing ground of chub mackerel in the Yellow Sea and East China Sea.

Simulation Study on the Interannual Variation of the Transport and Distribution of Chub Mackerel (Scomber japonicus) Larvae and Juveniles Using Individual-Based Model

An individual-based model of Scomber japonicus in the East China Sea(ECS)was developed to simulate the effects of physical environment on the transport and distribution of eggs,larvae and juveniles of S.japonicus from 1978 to 2013.The results showed that there were interannual differences in the transport and distribution of eggs,larvae and juveniles of S.japonicus in the ECS due to different physical environments from 1978 to 2013,and this difference was extremely obvious in some specific years.The current in the drift path of eggs and juveniles controlled and affected the transport process and distribution characteristics.In April,the distribution of eggs and larvae was mainly controlled by the Taiwan Warm Current(TWC).The number of eggs and larvae transported into the northeastern waters of the ECS was positively correlated with the intensity of TWC.In May,it was mainly regu-lated by the TWC and the Tsushima Strait Warm Current(TSWC).In June,the number of larvae and juveniles entering the Tsushima Strait and the Pacific Ocean was determined by the TSWC.In general,in the years with high number of larvae and juveniles into the Tsushima Strait,the catch of 0-year-old S.japonicus was also higher.In addition,the number of larvae and juveniles entering the Tsushima Strait in El Niño years was less than that in La Niña years.In July,the transport was mainly controlled by the Kuroshio Current(KC),and the eddy within the KC strongly affected its distribution.

基于近实时海洋遥感数据的渔场预报系统设计与实现

针对国内渔业企业对于渔场预报系统的需要,设计和开发基于近实时海洋遥感数据的渔场预报系统。系统分为陆地数据服务和渔情预报软件两个模块,其中:陆地服务模块负责收集全球近实时海洋环境数据,并提供环境数据下载服务;渔情预报软件可以从陆地服务器下载海洋环境数据,并通过这些数据,使用栖息地适应性指数模型进行渔场预报,为渔业企业和作业渔船的捕捞决策提供辅助。两个模块之间以国际海事卫星船队宽带系统作为数据传输手段。前期的远洋渔船应用试验表明,该系统能稳定下载海洋环境数据并实现渔场预报,预报结果作为捕捞决策的重要辅助信息,可为渔业生产者选择作业地点提供很好的参考。

剩余产量模型形状参数对印度洋黄鳍金枪鱼资源评估的影响

剩余产量模型中的Schaefer模型与Fox模型在渔业资源评估中被广泛应用,但这两个模型是剩余产量模型一般形式Pella-Tomlinson模型的两个特例,分别由形状参数的两个不同值确定。由于形状参数直接影响种群的生产能力,并与种群的年龄结构、繁殖能力等紧密相关,将形状参数固定为某个值,可能会影响剩余产量模型评估结果的可靠性,为此,本文利用印度洋黄鳍金枪鱼(Thunnus albacares)数据,分析剩余产量模型形状参数对渔业资源评估的影响。结果表明:(1)形状参数较难估计,并随数据时段的不同,形状参数的最佳取值范围会有很大的不同;(2)形状参数会对承载能力、内禀增长率的估计产生显著影响;(3)随形状参数值的增加,资源被掏空率与过度捕捞程度会不断增加,因此,不同形状参数的设置会对渔业资源状态及过度捕捞程度的判断产生重要影响。

利用贝叶斯动态产量模型评估东、黄海日本鲭资源状况

分布于东、黄海的日本鲭(Scomber japonicus)为我国主要经济鱼种之一,其资源现状和开发潜力日益受到重视。加强东、黄海日本鲭的资源评估研究是其科学管理与可持续利用的前提与基础。为此,基于1979—2019年中国福建、浙江、上海、江苏、山东、河北、天津及辽宁6省2市与日本、韩国的日本鲭捕捞产量以及相关文献的资源丰度指数数据,利用贝叶斯动态产量模型对日本鲭进行了资源评估。结果表明:由于内禀增长率(r)与承载能力(K)存在显著的负相关关系,r的先验分布影响模型的参数估计,给出合理的r先验有利于提高模型评估的质量;渔获量数据的观测误差精度对模型参数估计及资源状态的判断具有重要影响;东、黄海日本鲭种群结构的划分仍存在争议,目前无法按种群分别进行资源评估,若按数据统计单元对日本鲭进行资源评估将不利于日本鲭资源的可持续利用;日本鲭有较大概率(大于60%)被过度捕捞,总可捕捞量(total allowable catch, TAC)低于4.82×10^(5)t时,10年后其未被过度捕捞的概率大于60%。基于当前东、黄海日本鲭种群划分存在争议的现状及相应数据收集存在的困难,建议将东、黄海日本鲭作为同一个种群处理,以满足渔业资源评估模型的基本假设、提高该渔业资源的评估质量。而将渔获量控制在4.82×10^(5)t以下则有利于该渔业资源的可持续利用。

基于个体模型水温变动对东海鲐鱼补充量影响模拟研究

日本鲐(Scomber japonicus)是我国近海重要经济鱼种,在生长早期,水温变动对其资源量影响很大。运用基于个体的东海鲐鱼生长初期生态模型,模拟水温变动对其生长和存活率的影响。研究发现,一维条件下,鲐鱼的鱼卵仔幼鱼的生长和生存对水温较敏感,仔幼鱼所处的水温越接近适宜水温(20℃),对鲐鱼的生长和生存越有利,水温高(24℃)比水温低(16℃)对鲐鱼成长和生存更有利一些。三维数值实验结果显示,随着水温的增高,最终幼鱼的体长和存活量均呈"S"型增加,即水温降低不利于东海鲐鱼的仔幼鱼的生长和发育,原因是在死亡率最高的鲐鱼亲体产卵后15～60天(4月份)期间物理环境决定了鲐鱼最终的资源补充量,该期间仔幼鱼所处的平均水温往往低于最适合水温,所以水温的增高对东海鲐鱼仔幼鱼的生长和存活是有利的。

印度洋长鳍金枪鱼栖息地指数模型的构建与验证

长鳍金枪鱼(Thunnus alalunga)因其经济价值、分布广泛,成为世界各国海洋渔业的主要捕捞对象之一。对长鳍金枪鱼进行渔场预报研究,可以提高捕捞效率和渔获产量,为渔业生产提供科学依据。选取了2006—2014年印度洋长鳍金枪鱼的生产数据,结合海洋表层的温度、盐度和叶绿素a浓度等3个环境因子,运用一元非线性指数模型按月份建立了各环境因子的印度洋长鳍金枪鱼单因子栖息地适应性指数(suitability index,SI)后,采用算术平均法获得综合栖息地适应性指数模型(habitat suitability index,HSI),并根据2016年印度洋渔业生产数据及相应海洋环境资料,基于地理信息系统(geographic information system,GIS)软件———ArcGIS对栖息地指数模型进行验证。研究表明该模型对渔场预报准确率约为90.56%,各HSI等级下平均预报准确率为87.46%,对于HSI等级4和5(IHSI>0.5)等较高HSI值渔区所代表的中心渔场,其平均准确率为71.82%,考虑到IHSI>0.5的产量平均比重达69.35%这一事实,说明所建立的HSI模型对印度洋长鳍金枪鱼具有较好的预报效果。

基于蒙特卡洛方法的集鱼灯海面照度模型建立

集鱼灯照度分布计算和模拟是研究灯光渔船集鱼灯合理布置的重要途径。利用海表面风速、相对湿度数据、集鱼灯参数、渔船参数,在分析光子传输特性的基础上,运用蒙特卡洛方法建立灯光渔船集鱼灯海面照度模型。该模型利用米氏散射计算相对湿度与海表面风速对光子的吸收和散射,并考虑光子进入水面时海表风速对菲涅尔反射的影响。研究模型与叠加法比较,结果表明,该模型的理论计算值与实测值线性拟合斜率系数更接近1。计算不同风速及相对湿度的海面照度,结果表明:照度随着与船中线距离的增大而先增大后减小;相对湿度一定,随着与船中线距离的增加,先是风速越大照度越大,随后风速越大照度越小;风速一定,相对湿度对海面照度影响较小。本研究旨在建立一种集鱼灯海面照度模型,为今后灯光配置研究提供理论基础。