环境因子对黄海鳀鱼亲体-补充量关系影响的初步研究

鱼类年际资源量的波动可以归因于年间环境条件的变化和该种鱼类亲体数量的变化。文章根据1990～2001年间黄海中南部鳀鱼声学调查评估结果,以及黄海千里岩海区在此年间的表层水温和营养盐统计数据,以Ricker模型（R=αSe^-βS）为基础对黄海鳀鱼（Engraulis japonicas）亲体-补充量关系进行了初步研究。结果表明,黄海千里岩水域表层水温、磷酸盐浓度等环境条件因素对补充量有重要影响。     

辽东湾中国对虾亲体和补充量关系

渤海中国对虾(包括辽东湾)的亲体与补充量之间的关系已有许多报道,有的报告已在国外发表。由于最近几年渤海中国对虾补充数量继续下降,连续几年处于历史上最低水平以下,引起普遍关注。本文主要用渔业统计     

辽东湾海蜇亲体—补充量关系的研究

以渔获量为相对资源量用Ricker模型描绘了辽东湾海蜇(Rhopilema esculenta)亲体—补充量关系,统计分析确定两者存在可置信的关系,其控制程度达58%。没有发现辽东湾海蜇资源因亲体短缺有衰败现象。     

基于GLM和GAM的日本鲭太平洋群体补充量与产卵场影响因子关系分析

依据日本渔业机构提供的1980—2016年日本鲭太平洋群体资源丰度(补充量和亲体量)数据,对补充量的自然对数进行正态性检验,通过正态性检验的时间为1980—1999年,再结合产卵场海洋环境数据,利用广义线性模型(GLM)和广义加性模型(GAM)对1980—1999年日本鲭太平洋群体产卵场的海表面高度(sea surface height,SSH)、海表面盐度(sea surface salinity,SSS)、海表面温度(sea surface temperature,SST)、亲体量[ln(spawning stock biomass),ln(SSB)]与补充量之间的关系进行研究。GLM模型结果显示,考虑因子的综合效应,影响程度依次为ln(SSB)×年、ln(SSB)、SSS×年、SSS对补充量的影响最显著;考虑单因子对补充量的影响,影响程度依次为产卵场SST、SSH、年份、ln(SSB)和SSS。GAM模型研究表明,基于赤池信息准则,包含年份、产卵场SST和SSH的GAM模型为最优模型,模型中各因子的影响程度由大到小依次为年份、产卵场SST、产卵场SSH;考虑单因子对补充量的影响,...     

对虾亲体数量和补充量之间的关系

本文用世代渔获量和春汛产量作为补充量和亲体数量的相对数倍,研究对虾(Penaeusorientalis)亲体数量——补充量之间的关系。用Boverton或Ricker繁殖模式描述两者之间的关系。经数学分析,表明本命题似乎用Beverton模式更为适合。 根据计算最大补充量所需的亲体数(A_(max))、最大补充量(R_(max))和最大持续产量(M_(zy)),以及渔业上记录到的最大补充量和相应的亲体数量。确认现在的产卵亲虾数量太少。如果把产卵亲虾的相对数值112调节到250～300,则世代产量可望增加50～70%,即从1700增加到2500～3000;如果各种条件都充分满足,对虾世代的极限值约为4000。     

伏季休渔条件下东海带鱼的亲体和补充量关系

通过对1995-2007年东海带鱼的亲体和补充量资源状况分析,用Ricker繁殖模型和Beverton-Holt繁殖模型分别拟合了带鱼的亲体和补充量关系.结果表明:在现行伏季休渔条件下,东海带鱼的亲体数量和补充量之间存在着相关关系,Ricker繁殖模型的表达形式为R=6.9347P e(-0.033916A),Beverton-Holt繁殖模型的表达形式为P/R=0.10117(9.1645x10(-3)P,二个模型均能拟合东海带鱼的亲体和补充量关系,且拟合结果相近.实施新的伏季休渔政策以来,带鱼的补充量大幅增加.现阶段保护带鱼资源的主要目标是保护亲体和增加产卵群体数量,有效的措施是推迟伏季休渔开捕时间.     

基于环境因子的日本鲭太平洋群系的亲体—补充量模型比较分析

日本鲭(Scomber japonicus)是有重要经济价值的中上层鱼类,研究其资源变动与海洋环境因子之间的关系有利于该资源的合理开发与利用。根据1982-2014年日本鲭在129°~160°E、28°~45°N海域的生产统计数据,结合海表面温度(sea surface temperature,SST)和太平洋十年涛动(Pacific decadal oscillation,PDO)数据,首先对补充量(recruitment,R)与SST、PDO进行交相关分析,之后用Ricker模型拟合SST、PDO对日本鲭亲体-补充量的影响,并用Akaike信息法则(Akaike information criterion,AIC)对不同模型进行了比较。结果表明:SST、PDO对补充量均有滞后影响,滞后期分别是5年和1年;亲体-补充量模型分析表明,Ricker模型的AIC值为81.979,加入环境因子后AIC值明显降低。同时加入SST和PDO的模型AIC值是71.743,优于单个环境因子模型。结果表明,加入SST、PDO两种环境因子的Ricker模型能更好的描述亲体-补充量关系。     

东平湖刀鲚生物学参数、单位补充量渔获量及产卵亲体量评估

为完善东平湖刀鲚(Coilia nasus)的基础生物学数据, 并为实现其资源的可持续利用提供技术指导和理论依据, 本研究根据 2021—2023 年东平湖定置三层多目刺网调查获得的刀鲚体长、体重数据, 利用 ELEFAN_GA 技术对刀鲚的生长和死亡参数进行估算, 拟合 Von Bertalanffy (VBGF)生长方程, 构建了基于体长结构的单位补充量渔获量(YPR)和单位补充量产卵亲体量(SSBPR)模型。结果显示, 东平湖刀鲚体长范围为 4.9~26.2 cm, 平均体长为 (12.2±2.4) cm, 体重范围 1.1~51.8 g, 平均体重为(6.6±4.5) g; 使用基于 bootstrap 的 ELEFAN_GA 方法估算刀鲚渐进体长 L_∞=31.65 cm, 生长速率 K=0.66, 理论生产起点年龄 t₀= ‒0.23, 季节性生产振幅 C=0.65, 1 年中生产最快的时间段 t_s=0.40; 刀鲚的总死亡系数 Z=2.71, 自然死亡系数 M=1.074, 捕捞死亡系数 F=1.641、开发率 E=0.604, 平均选择体长 L₅₀=9.15 cm; YPR 模型结果显示, 随着 F 增大, YPR 值呈现先上升后下降的趋势, 生物学参考点 F_0.1 和 F_max 的值分别为 0.978 和 2.204; SSBPR 模型结果显示随着捕捞强度的增大, SSBPR 呈下降趋势, 现阶段捕捞强度介于 F_20%(2.848)与 F_40%(1.065)之间, 略大于 F_35%(1.286)。综上所述, 东平湖刀鲚生长表现出明显的季节性变化规律, 在与其他地理群体对比中, 东平湖刀鲚在生物学参数上的差异体现了其生长过程的空间异质性, K 值最大表明其可以用最短的时间生长到接近极限体长, 说明东平湖饵料丰富, 而同时较高的开发率和较低的开捕体长则表明目前东平湖刀鲚已处于过度开发状态, SSBPR 曲线得出现阶段捕捞强度小于极限值 F_20%, 略大于生物学参考点 F_35%。研究结果表明, 为使东平湖刀鲚资源达到生态、经济效益平衡, 可在适当减少渔船数量以降低捕捞强度的情况下, 通过增大网目尺寸以增加开捕体长来保持其可持续发展。     

渤海对虾亲体与补充量（SRR）动态特性的研究↑（*）

８０年代以来，渤海对虾的补充量，特别是亲体数量大幅度下降。根据１９８３－１９９４年４月烟威外海对虾亲体资源量指数和渤海秋汛对虾渔获量，按Ｂｅｖｅｒｔｏｎ－Ｈｏｌｔ和Ｒｉｃｋｅｒ模式求得各项参数值，有Ｒ－１ｔ＝３．８６×１０－３＋１．１７×１０－２Ｓ－１ｔＲ２＝０．７４ｐ＜０．００１Ｒｔ＝９０．０５Ｓｔｅ－０．１６２１７ＳｔＲ２＝０．５１ｐ＜０．０１表明：当今渤海对虾亲体对补充量有决定影响，可是８０年代亲体数量的平均值只有６０年代和７０年代的３４．４％和４４．２％；而进入９０年代以来，亲体数量又较８０代下降了２０％。８０年代中期渤海沿岸产卵场的环境条件因对虾养殖业的迅速发展发生了较大变化，养殖面积和单位面积产量大幅度增加。这个新的环境因素对对虾补充量也有一定的影响。渤海对虾亲体数量严重短缺，是恢复和增加对虾补充量的主要限制因素     

北太平洋远东拟沙丁鱼渔场时空分布及其最适环境特征

基于2019—2020年北太平洋灯光敷网渔业数据和海表温度、叶绿素、海面高度等环境数据,采用空间叠加图、频次分析与经验累积分布函数、K-S检验和GAM模型4种方法分析了远东拟沙丁鱼(Sardinops sagax)渔场的单位捕捞努力量(CPUE)时空分布特征及与关键环境因子的相关关系。分析结果显示,作业渔场重心分布范围为147°~153°E、39°~43°N,在4—8月向东北方向移动,9—11月则向西南方向折返。通过频次分析与经验累积分布函数分析,中心渔场区域最适海表温度为10.0~18.0 ℃,最适叶绿素浓度为0.2~0.6 mg/m3,最适海面高度为0.2~0.7 m。K-S检验分析表明,高值CPUE海域和海表温度、叶绿素浓度、海面高度均有密切关系,最适范围分别为10.9~18.9 ℃、0.2~0.6 mg/m3、0.2~0.7 m。GAM模型模拟结果表明,高值CPUE的最适海表温度为11.0~17.0 ℃,最适叶绿素浓度为0.3~0.8 mg/m3,最适海面高度为0.1~0.4 m。综合来说,CPUE高值区海域的最适海表温度为11.0~18.0 ℃,叶绿素浓度为0.2~0.6 mg/m3,海面高度为0.2~0.7 m。     

Incorporating an environmental stock–recruitment relationship in the assessment of Pacific cod (Gadus macrocephalus)

The robustness of a previously described environmentally mediated stock–recruitment relationship for Pacific cod in Hecate Strait, BC, Canada was tested with 10 yr of additional data. The original analysis tested several alternative hypotheses and concluded that water transport through Hecate Strait, as indicated by sea level height, coupled with cod spawning biomass formed the best model. The present analysis indicates the relationship held through the 1990s. The implications of variation in sea level on stock production were investigated with a delay‐difference stock production model that included an environmentally mediated stock–recruitment relationship. The model predicted that the maximum fishery yield would vary between 1750 and 3670 t yr^?1 over the observed range of sea level height, and the estimated unsustainable fishing mortality during periods of low productivity would be only 0.5 times that in periods of high productivity.     

Linking Northeast Pacific recruitment synchrony to environmental variability

We investigated the hypothesis that synchronous recruitment is due to a shared susceptibility to environmental processes using stock–recruitment residuals for 52 marine fish stocks within three Northeast Pacific large marine ecosystems: the Eastern Bering Sea and Aleutian Islands, Gulf of Alaska, and California Current. There was moderate coherence in exceptionally strong and weak year‐classes and correlations across stocks. Based on evidence of synchrony from these analyses, we used Bayesian hierarchical models to relate recruitment to environmental covariates for groups of stocks that may be similarly influenced by environmental processes based on their life histories. There were consistent relationships among stocks to the covariates, especially within the Gulf of Alaska and California Current. The best Gulf of Alaska model included Northeast Pacific sea surface height as a predictor of recruitment, and was particularly strong for stocks dependent on cross‐shelf transport during the larval phase for recruitment. In the California Current the best‐fit model included San Francisco coastal sea level height as a predictor, with higher recruitment for many stocks corresponding to anomalously high sea level the year before spawning and low sea level the year of spawning. The best Eastern Bering Sea and Aleutian Islands model included several environmental variables as covariates and there was some consistent response across stocks to these variables. Future research may be able to utilize these across‐stock environmental influences, in conjunction with an understanding of ecological processes important across early life history stages, to improve identification of environmental drivers of recruitment.     

基于GAM模型的马鞍列岛海域优势甲壳类与环境因子的关系研究

海洋虾类和虾蛄等甲壳类是许多鱼类的饵料生物,是海洋生态系统的重要组成部分。为了探索马鞍列岛海域优势甲壳类与环境因子之间的关系,文章基于广义加性模型(GAM)建立了甲壳类与环境因子的生态模型,并对甲壳类资源分布进行预测。结果表明,影响细巧仿对虾(Parapenaeopisis tenella)分布的主要因素是时间因素和底质,影响口虾蛄(Squilla orarotia)分布的主要因素包括底质、经度、温度和盐度,而影响葛氏长臂虾(Palaemon gravieri)分布的显著因素是时间因素。从分布格局来看,细巧仿对虾生物量低值出现在研究海域中间区域,高值出现在东北部海域;3月口虾蛄生物量在东南海域较高,而10月在西部海域较高;葛氏长臂虾分布低值出现在研究海域中间区域,高值海域环绕低值海域周围分布。     

基于遥感的黄海中南部越冬鳀资源密度分布与环境因子的关系研究

基于遥感和GIS(Geographic information system)技术,利用2000~2015年的底拖网调查数据和海表温度、叶绿素a浓度以及海水温度梯度等遥感数据,在定性分析黄海中南部越冬鳀(Engraulis japonicus)资源密度分布与环境因子关系的基础上,利用时空和环境因子构建GAM (Generalized additive model)模型进行定量分析。结果显示,时空因子(年、下网时间、经度和纬度)和环境因子对越冬鳀资源密度的总偏差解释率为44.76%,其中,时空因子对其的影响均显著,以空间因子影响最大,对总偏差的解释率为35.4%;环境因子中,水深、海表温度和温度梯度对其影响显著,而叶绿素a浓度影响不显著;越冬鳀分布的最适海表温度、叶绿素a浓度和海表温度梯度范围分别为7~11℃、1.2~2.3 mg/m3和0.7~2.5℃。研究结果对环境变动下的渔业管理具有重要意义。     

Oceanographic factors affecting interannual recruitment variability of Pacific saury (Cololabis saira) in the central and western North Pacific

Pacific saury (Cololabis saira) has a short life span of 2 years and tends to exhibit marked population fluctuations. To examine the importance of sea surface temperature (SST) and mixed layer depth (MLD) as oceanographic factors for interannual variability of saury recruitment in early life history, we analyzed the relationship between abundance index (survey CPUE (catch per unit of effort)) of age‐1 fish and the oceanographic factors in the spawning and nursery grounds of the previous year when they were born, for the period of 1979–2006, in the central and western North Pacific. Applying the mixture of two linear regression models, the variability in the survey CPUE was positively correlated with previous year's winter SST in the Kuroshio Recirculation region (KR) throughout the survey period except 1994–2002. In contrast, the survey CPUE was positively correlated with the previous year's spring MLD (a proxy of spring chlorophyll a (Chl‐a) concentration) in the Kuroshio‐Oyashio Transition and Kuroshio Extension (TKE) during 1994–2002. This period is characterized by unusually deep spring MLD during 1994–1997 and anomalous climate conditions during 1998–2002. We suggest that saury recruitment variability was generally driven by the winter SST in the KR (winter spawning/nursery ground), or by the spring Chl‐a concentration (a proxy of prey for saury larvae) in the TKE (spring spawning/nursery ground). These oceanographic factors could be potentially useful to predict abundance trends of age‐1 saury in the future if the conditions leading to the switch between SST and MLD as the key input variable are elucidated further.     

黄海大头鳕0龄幼体分布及其与环境因子的关系

大头鳕是广泛分布于太平洋北部沿岸海域的重要经济和生态种,研究其幼体的生物学特性和分布有助于了解大头鳕的种群动态。本实验根据2016年6月、8月、10月、12月在黄海进行的渔业资源和环境调查数据,研究了黄海大头鳕种群幼体的生长规律;并运用广义可加模型(GAM)方法,分析了该海域大头鳕幼体分布及其与环境因子的关系。结果显示,黄海大头鳕幼体为正异速增长,体质量增长较快,b值为3.316 1。黄海大头鳕0龄幼体主要在底层盐度31.7~33.3、底层水温6.6~12.1°C、深度35.8~87.2 m、底质为细粉砂或黏土质软泥底质的海域中生活。研究表明,大头鳕幼体分布的季节变化与黄海冷水团的季节演变过程具有同步性。对大头鳕幼体密度有显著影响的环境因子依次为底层水温、底质、底层盐度,而深度对大头鳕幼体密度的影响不显著。     

Non‐parametric modeling reveals environmental effects on bluefin tuna recruitment in Atlantic,Pacific, and Southern Oceans

Environment–recruitment relationships can be difficult to delineate with parametric statistical models and can be prone to misidentification. We use non‐parametric time‐series modeling which makes no assumptions about functional relationships between variables, to reveal environmental influences on early life stages of bluefin tuna and demonstrate improvement in prediction of subsequent recruitment. The influence of sea surface temperature, which has been previously associated with larval growth and survival, was consistently detected in recruitment time series of bluefin tuna stocks that spawn in the Mediterranean Sea, the North Pacific, and the Southern Ocean. Short time series for the Gulf of Mexico stock may have precluded a clear determination of environmental influences on recruitment fluctuations. Because the non‐parametric approach does not require specification of equations to represent system dynamics, predictive models can likely be developed that appropriately reflect the complexity of the ecological system under investigation. This flexibility can potentially overcome methodological challenges of specifying structural relationships between environmental conditions and fish recruitment. Consequently, there is potential for non‐parametric time series modeling to supplement traditional stock recruitment models for fisheries management.     

Pacific herring, Clupea pallasi, recruitment in the Bering Sea and north-east Pacific Ocean, II: relationships to environmental variables and implications for forecasting

Previous studies have shown that Pacific herring populations in the Bering Sea and north-east Pacific Ocean can be grouped based on similar recruitment time series. The scale of these groups suggests large-scale influence on recruitment fluctuations from the environment. Recruitment time series from 14 populations were analysed to determine links to various environmental variables and to develop recruitment forecasting models using a Ricker-type environmentally dependent spawner–recruit model. The environmental variables used for this investigation included monthly time series of the following: southern oscillation index, North Pacific pressure index, sea surface temperatures, air temperatures, coastal upwelling indices, Bering Sea wind, Bering Sea ice cover, and Bering Sea bottom temperatures. Exploratory correlation analysis was used for focusing the time period examined for each environmental variable. Candidate models for forecasting herring recruitment were selected by the ordinary and recent cross-validation prediction errors. Results indicated that forecasting models using air and sea surface temperature data lagged to the year of spawning generally produced the best forecasting models. Multiple environmental variables showed marked improvements in prediction over single-environmental-variable models.     

环境因子对东南太平洋智利竹䇲鱼渔场时空分布异质性影响

基于2012—2018 年4—8 月我国东南太平洋智利竹?鱼 (Trachurus murphyi) 渔捞日志数据,应用地理权重回归模型 (GWR) 探究智利竹?鱼渔场资源分布与环境因子的空间异质性关系.结果表明,环境因子海面温度基于GWR 模型回归的拟合优度为0.54,校正的拟合优度为0.34,赤池信息准则 (Aka...