基于空间相关性的西北太平洋柔鱼CPUE标准化研究

CPUE标准化方法通常都假设名义CPUE之间是相互独立且没有相关性,然而鱼类集群分布通常存在着空间相关性,为此本研究以西北太平洋柔鱼的CPUE标准化为例,采用1999-2012年6-11月中国鱿钓生产数据以及对应的海表面温度和叶绿素浓度的环境数据,将空间相关性加入广义线性模型(general linear model,GLM)中.在空间GLM模型中运用4个距离模型(指数模型、球面模型、线性模型和高斯模型),进行标准GLM模型和4种空间GLM模型的CPUE标准化结果比较.结果发现,4种空间GLM模型均比标准GLM模型的最小信息准则(akaike information criterion,AIC)更小,标准化结果更准确.同时,在4个距离模型中,指数模型的AIC值最小,其CPUE标准化结果最佳.研究表明,在CPUE标准化中,鉴于鱼类集群与分布特性,应该充分考虑空间相关性这一因素.     

Recruitment abundance index of Pacific bluefin tuna using fisheries data on juveniles

ABSTRACT:   The recruitment abundance index of Pacific bluefin tuna Thunnus orientalis was estimated from 1980 to 2003 fishing year by using the troll fishery data in Nagasaki Prefecture, western Japan. It has been shown that the troll fishery in Nagasaki Prefecture operates with good time–area coverage of the species habitat, and that the fishing power slightly changed during the period analyzed, based on fisheries statistics, published information, and interviews with the fishers. Average catch per unit effort (CPUEs) were standardized by a generalized linear model (GLM) considering the effects of fishing year, season and landing area. Standardized CPUE of age-0 bluefin tuna showed larger fluctuations year by year than the nominal CPUE combined for all ages. High CPUEs in fishing years of 1981, 1994, 1996 and 1999 were observed. Data from these years agreed with the higher recruitments estimated by virtual population analysis (VPA) or higher catch of age-0 fish reported for the Pacific side. The age-specific standardized CPUE of age-0 bluefin tuna in this study was judged to be a useful indicator of recruitment.     

西南大西洋阿根廷滑柔鱼渔业中国大陆鱿钓船CPUE标准化

阿根廷滑柔鱼是我国重要的头足类渔业之一,对其单位捕捞努力量渔获量( CPUE)进行标准化是对其资源评估的重要内容。本研究根据2000～2010年我国在西南大西洋的产量统计数据和卫星遥感获得的海洋环境数据（表温,表温水平梯度,海面高度,叶绿素浓度）,利用广义线性模型（GLM,general linear model）和广义加性模型（GAM,generalized additive model）对其CPUE进行标准化。GLM模型结果表明,年、纬度、表温以及交互项年与纬度对CPUE影响最大。GAM模型研究结果表明,年、月、经度、纬度、表温、海面高度以及交互项年与纬度、年与经度对CPUE影响较大。根据AIC数值,包含上述8个显著变量的GAM模型为最佳模型,对CPUE的解释率为49.20%。高CPUE出现在夏季表温为12～16°C、海面高为-20~20cm、46.5°～48.5°S海域。研究表明,GAM模型较GLM模型更适合用于西南大西洋阿根廷滑柔鱼CPUE标准化。     

我国东、黄海鲐鱼灯光围网渔业CPUE标准化研究

日本鲐是我国近海重要的中上层鱼类资源之一,评估其资源量需要对单位捕捞努力量渔获量（CPUE）进行标准化。影响CPUE标准化的因素很多，包括季节、区域和海洋环境等。本文利用广义线型模型（GLM）和广义加性模型（GAM），结合时空、捕捞船、表温等因子，对1998-2006年东、黄海大型灯光围网渔业鲐鱼CPUE进行标准化，并评价各因子对CPUE的影响。首先应用GLM模型评价时间、空间、环境以及捕捞渔船参数对CPUE的影响，并确定显著性变量。其次，将显著性变量逐一加入GAM模型，根据Akaike信息法则（AIC），选择最优的GAM模型。最后，利用最优的GAM模型对CPUE标准化，并定量分析时间、空间、环境以及捕捞渔船参数对鲐鱼CPUE的影响。GLM模型结果表明：8个变量对CPUE有重要影响，依次为年、船队、船队与年的交互效应、月、船队与月份的交换效应、经度、纬度和海表温。根据AIC，包含上述8个显著性变量的GAM模型为最优模型，对CPUE偏差的解释为27.78%。GAM模型结果表明：高CPUE分别出现在夏季海表温为28～31 ℃的东海中部和冬季海表温为12～16 ℃的黄海；1998-2006年，标准化后的CPUE呈逐年下降趋势，与持续增长的捕捞努力量有关。     

Multi‐timescale interactions between pink and chum salmon catch per unit effort in the Bering Sea

Based on generalized linear models, interspecific interactions were identified between chum and pink salmon. In addition, the effects of sea surface temperature and location on the variability of catch per unit effort (CPUE) of chum salmon from gill‐net surveys carried out between 1972 and 2010 were investigated. In the optimal model, interspecific interactions between CPUEs of chum and pink salmon on a year scale were positive for approximately half of all years in the central Bering Sea. In addition, interspecific interactions on a multi‐year scale were positive in even‐numbered years. The effects of location on the CPUE of chum salmon were significant variables in the optimal model. The CPUEs of chum salmon located near the continental shelf in the Bering Sea were higher than those of other locations. This study provides new evidence of positive interspecific interactions between the CPUEs of chum and pink salmon. The results also suggest that the standardized CPUE of chum salmon from the gill‐net surveys reflects relative chum salmon abundance in the North Pacific Ocean in the following year.     

Incorporating spatial autocorrelation into the general linear model with an application to the yellowfin tuna (Thunnus albacares) longline CPUE data

Catch-per-unit-effort (CPUE) data have often been used to obtain a relative index of the abundance of a fish stock by standardizing nominal CPUE using various statistical methods. The theory underlying most of these methods assumes the independence of the observed CPUEs. This assumption is invalid for a fish population because of their spatial autocorrelation. To overcome this problem, we incorporated spatial autocorrelation into the standard general linear model (GLM). We also incorporated into it a habitat-based model (HBM), to reflect, more effectively, the vertical distributions of tuna. As a case study, we fitted both the standard-GLM and spatial-GLM (with or without HBM) to the yellowfin tuna CPUE data of the Japanese longline fisheries in the Indian Ocean. Four distance models (Gaussian, exponential, linear and spherical) were examined for spatial autocorrelation. We found that the spatial-GLMs always produced the best goodness-of-fit to the data and gave more realistic estimates of the variances of the parameters, and that HBM-based GLMs always produced better goodness-of-fit to the data than those without. Of the four distance models, the Gaussian model performed the best. The point estimates of the relative indices of the abundance of yellowfin tuna differed slightly between standard and spatial GLMs, while their 95% confidence intervals from the spatial-GLMs were larger than those from the standard-GLM. Therefore, spatial-GLMs yield more robust estimates of the relative indices of the abundance of yellowfin tuna, especially when the nominal CPUEs are strongly spatially autocorrelated.     

A study on the variability of albacore (Thunnus alalunga) longline catch rates in the southwest Pacific Ocean

Relationships between albacore tuna (Thunnus alalunga) longline catch per unit effort (CPUE) and environmental variables from model outputs in New Caledonia’s Exclusive Economic Zone (EEZ) were examined through generalized linear models at a 1° spatial resolution and 10‐day temporal resolution. At a regional (EEZ) scale, the study demonstrated that a large part of albacore CPUE variability can be explained by seasonal, interannual and spatial variation of the habitat. Results of the generalized linear models indicated that catch rates are higher than average in the northwestern part of the EEZ at the beginning of the year (January) and during the second half of the year (July–December). In the northwestern region of the EEZ, high CPUEs are associated with waters <20.5° in the intermediate layer and with moderate values of primary production. Longline CPUE also appeared to be dependent on prey densities, as predicted from a micronekton model. Albacore CPUE was highest at moderate densities of prey in the epipelagic layer during the night and for relatively low prey densities in the mesopelagic layer during the day. We also demonstrated that the highest CPUEs were recorded from 1986 to 1998, which corresponds to a period with frequent El Niño events.     

Comparisons of monthly and geographical variations in abundance and size composition of Pacific saury between the high-seas and coastal fishing grounds in the northwestern Pacific

The monthly and geographical abundances and size compositions of Pacific saury were compared between the high-seas and coastal fishing grounds in the northwestern Pacific during 2000–2005 based on Taiwanese fishery data. The large-sized saury was dominant (44.3–71.4% of the catch) in the beginning of the fishing season, while the medium-sized saury followed and dominated from September to the end of the fishing season (70.1–92.4% of the catch). In the high seas, the total catch per unit effort (CPUE) (about 71.2% of the mean coastal value) and both the large- (about 55.0%) and medium-sized saury CPUEs (about 81.8%) were significantly smaller than those in the coastal waters. The mean proportions of the large- and medium-sized saury in the high-seas catch were about 86.6 and 107.0% of the coastal values, respectively. CPUEs for the total catch and the catch of medium-sized saury varied in a highly consistent way. The total and medium-sized CPUEs were negatively correlated with the sea-water temperature. When the temperature was held the same statistically, the total and medium-sized CPUEs were larger in the shoreward, southward, and shallower waters of the fishing grounds, while the large-sized CPUE was larger in the shoreward waters.     

Albacore (Thunnus alalunga) fishing ground in relation to oceanographic conditions in the western North Pacific Ocean using remotely sensed satellite data

Satellite‐based oceanographic data of sea surface temperature (SST), sea surface chlorophyll‐a concentration (SSC), and sea surface height anomaly (SSHA) together with catch data were used to investigate the relationship between albacore fishing ground and oceanographic conditions and also to predict potential habitats for albacore in the western North Pacific Ocean. Empirical cumulative distribution function and high catch data analyses were used to calculate preferred ranges of the three oceanographic conditions. Results indicate that highest catch per unit efforts (CPUEs) corresponded with areas of SST 18.5–21.5°C, SSC 0.2–0.4 mg m^?3, and SSHA ?5.0 to 32.2 cm during the winter in the period 1998–2000. We used these ranges to generate a simple prediction map for detecting potential fishing grounds. Statistically, to predict spatial patterns of potential albacore habitats, we applied a combined generalized additive model (GAM) / generalized linear model (GLM). To build our model, we first constructed a GAM as an exploratory tool to identify the functional relationships between the environmental variables and CPUE; we then made parameters out of these relationships using the GLM to generate a robust prediction tool. The areas of highest CPUEs predicted by the models were consistent with the potential habitats on the simple prediction map and observation data, suggesting that the dynamics of ocean eddies (November 1998 and 2000) and fronts (November 1999) may account for the spatial patterns of highest albacore catch rates predicted in the study area. The results also suggest that multispectrum satellite data can provide useful information to characterize and predict potential tuna habitats.     

Relationships between CPUE fluctuation of southern bluefin tuna and ocean temperature variability in the Central Indian Ocean

In this study, catch and effort data of southern bluefin tuna (SBT) from Taiwan longliners operating in the Central Indian Ocean (CIO) during 1982 to 2003 were compiled and their catch per unit effort (CPUE) was standardized using the generalized linear model (GLM). The GLM includes factors such as year, season, by-catch, latitude, sea surface temperature (SST) and the interactive effects among factors. The standardized CPUE and its relationship with SST fluctuation were then analyzed to understand the effects of fishing ground SST variations on CPUE of SBT, as well as their connection to El Niño-Southern Oscillation (ENSO) events. The standardized CPUE in the CIO seemed to oscillate with the sea surface temperature anomalies (SSTA) between 30 and 50°S where SSTA fluctuations were prolonged and slower than the ENSO cycle. It is then very likely that fishing conditions at the CIO fishing ground were influenced by the expansion of the cold water mass from the Southern Ocean, and the colder SST is beneficial to increasing SBT catch rate.     

A review of the distribution, ecology and population dynamics of age-0 walleye pollock in the Gulf of Alaska

This review paper synthesizes published research and unpublished data on the abundance and distribution patterns, ecology and population dynamics of walleye pollock ( Theragra chalcogramma ) during their first year of life (age-0) in the Gulf of Alaska. Distribution patterns have been described using mainly trawl catches, but recently, acoustic methodology has been employed, especially in examining vertical distributions. Although age-0 pollock are found throughout the Gulf, the highest catches occurred west of Kodiak Island. Pollock are pelagic for at least their first 6 months of life but show an ontogenetic increase in depth distribution superimposed on a pronounced diel vertical migration at a larger size. Daily growth rates are variable depending on year, season and area, and growth generally ceases during the winter. The diet of age-0 pollock shifts from mainly copepods in early juveniles to euphausiids by fall, with epibenthic organisms becoming important during the winter months. Feeding occurs mainly at night in surface waters. Age-0 pollock are most frequently associated with gelatinous zooplankton (medusae) and older pollock. Many predators on age-0 pollock have been identified; the most important are arrowtooth flounder ( Atheresthes stomias ), adult pollock, puffins ( Fratercula spp.), murres ( Una spp.), harbor seals ( Phoca vitulina richardsi ) and Steller sea lions ( Eumetopiasjubatus ). Modelling provides some insight into the population dynamics of these juveniles and environmental conditions which interannually affect their survival. These results are discussed relative to the importance of age-0 pollock in the recruitment of this species and to their role in the pelagic ecosystem.     

Trends in fishing indices for the thread herring fishery in northwest Mexico

The initial success of the thread herring fishery in Sinaloa was followed by an increase in the mean fleet capacity, from 50 t in 1972 to 185 t in 1993. However, the efficiency (a measure of the storage utilization by a vessel), the fishing power and catch-per-unit-effort (CPUE), did not increase proportionally. Efficiency showed a declining trend with the vessel's size, and the CPUE stabilized at around 50 t vessel^–1. To standardize the CPUE, a General Linear Model (GLM) incorporating fishing seasons and vessel categories was used. This model showed that the fishing power increased with time, but the differences among vessel categories were lower, ranging from 1–1.14. This model also explained 75.3% of the variation in catch rate. Analysis of the fishing indices trends suggested a reduction of the mean vessel size as the best way to improve the fishery management.     

西北太平洋秋刀鱼CPUE标准化研究

秋刀鱼(Cololabis saira)是西北太平洋海域重要的渔业种类之一,其资源评估工作已成为热点问题,单位捕捞努力量渔获量(CPUE)标准化可以为开展有效的资源评估研究提供科学依据。为此,本研究利用2003~2017年中国大陆西北太平洋秋刀鱼渔业生产统计资料,结合卫星遥感获得的海洋环境数据,如海表面温度、海表温度梯度、海表面高度等,基于广义线性模型(General linear model, GLM)和广义可加模型(Generalized additive model, GAM)对中国大陆西北太平洋秋刀鱼渔业进行CPUE标准化。结果显示,根据BIC准则,在GLM模型结果中,年份、月份、经度、纬度、海表面温度、海表面高度、海表温度梯度及年份与月份对CPUE具有显著影响,并组成了GLM模型的最佳模型,对CPUE偏差的解释率为52.47%;在GAM模型结果中,除上述8个影响变量外,交互项月份与经度和月份与纬度也对CPUE影响较大,GAM的最佳模型对CPUE偏差的解释率为61.9%。通过5-fold交叉验证分析发现,GAM模型标准化结果较优于GLM模型,更适合于西北太平洋秋刀鱼渔业CPUE标准化。     

Density and temperature dependence of gill net catch per unit effort for perch, Perca fluviatilis, and roach, Rutilus rutilus

Abstract  The densities of perch, Perca fluviatilis L., and roach, Rutilus rutilus (L.), were estimated in six and three lakes, respectively, using mark–recapture and ranged from 25–1064 perch ha⁻¹ and 865–2749 roach ha⁻¹. Effects of fish density, net type and water temperature on catch-per-unit-effort (CPUE) were analysed by generalised linear models (GLM) and generalised additive models (GAM). GAMs were fitted to estimate the simultaneous linear and nonlinear effects of temperature and density on CPUE. These models showed significant nonlinear effects of density on CPUE – mostly for perch, and also for both species at high densities. The models also revealed that both species had distinct density–temperature criteria of expected maximum CPUE and zero CPUE values. Because of the nonlinear relationship between CPUE and density, it was concluded that CPUE should be used with caution as a proxy of density.     

Skipjack tuna fishery in relation to sea surface temperature off the southern Brazilian coast

Several oceanographic studies have associated tuna fisheries to sea surface temperature (SST) fields, although catch per unit of effort (CPUE) has not shown a clear relationship with SST. However, most results concerned species that occur deep in the water column. In this paper, we present a study on the relationship between SST and CPUE for the skipjack tuna fisheries off the southern Brazilian coast, which take place at the sea surface. We use historical data from the Japanese fleet, which operated in the area from July 1982 to June 1992. Fishing sets occurred only in areas where SST ranged from 17°C to 30°C. Frequency of occurrence vs. SST showed a Gaussian distribution, with highest CPUEs in waters of SST 22°-26.5°C. The relationship between CPUE (or fishing set occurrence) and SST varied seasonally. Largest CPUEs occurred in summer, independently of SST. Therefore, temperature alone could not be used as a determinant of CPUE, suggesting that seasonal variability of other environmental parameters has a stronger effect on the CPUE than does SST. However, when the seasonal cycle was excluded from the data sets, a relationship between the interannual variability of SST and CPUE became apparent. Cross-correlation analysis between CPUE and SST has shown that oscillations in CPUE anomalies precede oscillations in SST anomalies by a month, but the mechanism relating them in this way is unknown.     

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。     

A generalized linear mixed model analysis of a multi-vessel fishery resource survey

A generalized linear mixed model (GLMM) that treats year and spatial cell as fixed effects while treating vessel as a random effect is used to examine fishing power among chartered industry-based vessels and a research trawler, the FRV Miller Freeman, for bottom trawl surveys on the upper continental slope of U.S. West coast. A Bernoulli distribution is used to model the probability of a non-zero haul and the gamma distribution to model the non-zero catch rates of four groundfish species. The use of vessel as a random effect allows the data for the various vessels to be combined and a single continuous time-series of biomass indices to be developed for stock assessment purposes. The GLMMs fit the data reasonably well. Among the different models examined, the GLMM incorporating a random vessel × year effect had the smallest ΔAIC and was thus chosen as the best model. Also, estimated random effects coefficients associated with the industry-based vessels and the FRV Miller Freeman for each year suggests that these vessels can be assumed to be from a common random effects distribution. These results suggest that combining data from the chartered industry-based vessels and from the research trawler may be appropriate to develop indices of abundance for stock assessment purposes. Finally, an evaluation of variances associated with abundance indices from the different models indicate that analyzing these data as a fixed effect GLM may underestimate the level of variability due to ignoring the grouped nature of tows within vessels. As such, use of a mixed model approach with vessel as a random effect is a reasonable approach to developing abundance indices and their variances.     

秘鲁沿岸秘鲁鳀渔场及渔汛分析

秘鲁鳀(Engraulis ringens)是栖息于东南太平洋沿岸的小型中上层鱼类,了解秘鲁鳀渔场和渔汛的状况有助于渔情预报工作的开展进而实现资源的合理利用。利用2005~2014年秘鲁各港口的上岸量数据,以上岸量(landings)、总捕捞努力量(fishing effort)和单位捕捞努力量渔获量(CPUE)为指标分析秘鲁鳀渔场分布及渔汛;结合二因素方差分析(two-factor analysis of variance)探究渔场月份和纬度上的显著性差异;利用分位数的方法,找出各年的旺汛时间。研究表明,每年的4~6月和11~12月为秘鲁鳀的主汛期;主要的捕捞区域分布在7°S~13°S;渔汛的前中期,上岸量和捕捞努力量有着明显的年间差异,而CPUE在渔汛后期年间差异明显。方差分析表明,不同月份和不同纬度对捕捞努力量[ln(effort+1)]有极显著的影响(P0.01);5月为一年中最主要的捕捞阶段。旺汛期分析表明,第一渔汛阶段的旺汛一般在5月出现,而第二渔汛阶段的旺汛一般在11月出现。研究结果有助于对秘鲁沿岸秘鲁鳀渔场及渔汛的认识。     

The relative importance of lunar phase and environmental conditions on striped marlin (Tetrapturus audax) catches in sport fishing

We used generalized additive mixed models to analyze data on striped marlin (Tetrapturus audax) catches in Baja California sport fisheries (1987–1989) to investigate the relative importance of lunar phase, sea surface temperature (SST), El Niño/Southern Oscillation (ENSO) index, and vessel effects on catch per unit effort (CPUE). The results indicate that the moon phase has no or little (<1% of variance explained) influence on CPUE. In contrast, both SST (10%) and ENSO (6%) influenced CPUE positively. While most of the variation in CPUE remains unexplained (53%), the vessel identity explained small (ca. 1.5%) but significant amount of variance in CPUE. Hence, sport fishermen wishing to maximise their striped marlin catches would best plan their trips on the basis of weather conditions and boat/crew identities, rather than on the basis of lunar phase.