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.     

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。     

Association between the interannual variation in the oceanic environment and catch rates of bigeye tuna (Thunnus obesus) in the Atlantic Ocean

The environmental processes associated with variability in the catch rates of bigeye tuna in the Atlantic Ocean are largely unexplored. This study used generalized additive models (GAMs) fitted to Taiwanese longline fishery data from 1990 to 2009 and investigated the association between environmental variables and catch rates to identify the processes influencing bigeye tuna distribution in the Atlantic Ocean. The present findings reveal that the year (temporal factor), latitude and longitude (spatial factors), and major regular longline target species of albacore catches are significant for the standardization of bigeye tuna catch rates in the Atlantic Ocean. The standardized catch rates and distribution of bigeye tuna were found to be related to environmental and climatic variation. The model selection processes showed that the selected GAMs explained 70% of the cumulative deviance in the entire Atlantic Ocean. Regarding environmental factors, the depth of the 20 degree isotherm (D20) substantially contributed to the explained deviance; other important factors were sea surface temperature (SST) and sea surface height deviation (SSHD). The potential fishing grounds were observed with SSTs of 22–28°C, a D20 shallower than 150 m and negative SSHDs in the Atlantic Ocean. The higher predicted catch rates were increased in the positive northern tropical Atlantic and negative North Atlantic Oscillation events with a higher SST and shallow D20, suggesting that climatic oscillations affect the population abundance and distribution of bigeye tuna.     

Operational oceanography applied to skipjack tuna (Katsuwonus pelamis) habitat monitoring and fishing in south‐western Atlantic

Skipjack tuna (Katsuwonus pelamis) ranks third among marine resources that sustain global fisheries. This study delimits the spatiotemporal habitat of the species in the south‐western Atlantic Ocean, based on operational oceanography. We used generalized additive models (GAMs) and catch data from six pole‐and‐line fishing vessels operating during 2014 and 2015 fishing seasons to assess the effect of environmental variables on catch. We also analysed Modis sensor images of sea surface temperature (SST) and surface chlorophyll‐α concentration (SCC) to describe fishing ground characteristics in time and space. Catch was positively related to thermocline depth (24–45 m), SST (22–24.5°C), SCC (0.08–0.14 mg/m³) and salinity (34.9–35.8). Through SST images, we identified that thermal fronts were the main surface feature associated with a higher probability to find skipjack. Also, we state that skipjack fishery is tightly related to shelf break because bottom topography drives the position of fronts in this area. Ocean colour fronts and plankton enrichment were important proxies, accessible through SCC, used to delineate skipjack fishing grounds. Catch per unit effort (CPUE) was higher towards summer (median 14 t/fishing day) due to the oceanographic characteristics of the southern region. High productivity in this sector of the Brazilian coast defines the main skipjack feeding areas and, as a consequence, the greatest abundance and availability for fishing.     

中西太平洋金枪鱼围网黄鳍金枪鱼产量的时空分布及与表温的关系

黄鳍金枪鱼是中西太平洋金枪鱼围网渔业中的重要捕捞种类之一。本文根据2003年中西太平洋金枪鱼围网生产统计及其表温数据,利用频次统计分析和地理信息软件Marine Explorer 4.0对黄鳍金枪鱼产量和单位日产量(CPUE)的时空分布进行分析,探讨其与海水表温的关系。结果显示,产量和CPUE最高的是2月份,其次是9月份,5月份为最低。高产量的范围为140~160°E、0°~5°S;CPUE高值区分布在130°E、0°~15°S,140°~160°E、0°~15°S和175°W、0°~15°S;产量经纬度重心分别为150°30′E和3°48′S。产量主要分布在海表温为28~31℃的海域,产量比重高达95.45%,其中29~30℃产量为最高,占69.54%。     

Spatio‐temporal trends of sailfish,Istiophorus platypterus catch rates in relation to spawning ground and environmental factors in the equatorial and southwestern Atlantic Ocean

Spatial and temporal trends of sailfish catch rates in the southwestern and equatorial Atlantic Ocean in relation to environmental variables were investigated using generalized additive models and fishery‐dependent data. Two generalized additive models were fit: (i) ‘spatio‐temporal’, including only latitude, longitude, month, and year; and (ii) ‘oceanographic’, including sea surface temperature (SST), chlorophyll‐a concentration, wind velocity, bottom depth, and depth of mixed layer and year. The spatio‐temporal model explained more (average ~40%) of the variability in catch rates than the oceanographic model (average ~30%). Modeled catch rate predictions showed that sailfish tend to aggregate off the southeast coast of Brazil during the peak of the spawning season (November to February). Sailfish also seem to aggregate for feeding in two different areas, one located in the mid‐west Atlantic to the south of ~15°S and another area off the north coast of Brazil. The oceanographic model revealed that wind velocity and chlorophyll‐a concentration were the most important variables describing catch rate variability. The results presented herein may help to understand sailfish movements in the Atlantic Ocean and the relationship of these movements with environmental effects.     

The effects of mesoscale oceanographic structures and ambient conditions on the catch of albacore tuna in the South Pacific longline fishery

Albacore tuna (Thunnus alalunga) exhibit patchy concentrations associated with biological process at a wide range of spatial scales, resulting in variations in their catchability by fishing gears. Here, we investigated the association of catch variation for pelagic longlines in the South Pacific Ocean with oceanographic mesoscale structures (in horizontal dimension) and ambient conditions (in vertical dimension). The distribution of albacore tuna as indicated by catch per unit effort (CPUE) of longlines was significantly related to the presence of mesoscale structures, with higher CPUE found at locations closer to thermal fronts and with greater gradient magnitudes, as well as areas marked by peripheral contour line of the anticyclone indicated by Sea Surface Height Anomalies ~0.05 m. Surface mesoscale current velocity had the negative effect on the catch, probably as a result of decreased catchability by shoaling the hook depth. Vertical distribution of albacore in the survey region of South Pacific Ocean was hardly restricted by ambient temperature and oxygen concentration, though effect of ambient temperature was relevant and showed a negatively linear correlation with CPUE at the range of 20–24°C. On the contrary, albacore distribution was evidently dominated by the water depth and showed strong preference on water depth of 200 m, which was likely a representative feeding layer. The presence of prey resources and their accessibility by albacore revealed by mesoscale structures in the biological and physical processes, and catchability determined by the location of the baited hooks comprehensively contribute to the variability of catch.     

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.     

世界主要金枪鱼捕捞产量分析

根据FA0 1950 ～ 2011年世界主要金枪鱼类渔业生产数据统计,将长鳍金枪鱼、黄鳍金枪鱼、大眼金枪鱼和鲣鱼等8种世界主要金枪鱼类每10年的产量总和按不同鱼种和海域进行了总结.结果显示,鲣鱼的累计总产量最高,其平均年产量涨幅最快;除马苏金枪鱼年平均产量有所下降,北方蓝鳍金枪鱼保持稳定外,其他主要金枪鱼类均有增长,但平均增长率最高的是青干金枪鱼.各主要渔区中以中西太平洋海域累计总产量最高,平均年产量有上升趋势,大西洋海域以中东大西洋为产量最高,印度洋海域以西印度洋为产量最高,平均增长率以印度洋海域为最高,其他海域相对持平.我国（包括台湾省）捕获累计总产量最高的是鲣鱼,为418×104 t,占世界总产量比例最高的是长鳍金枪鱼,为22.9％.我国（包括台湾省）主要金枪鱼类捕获总产量占世界总产量比例最高为东南大西洋海域,最低为东南太平洋海域.论文结合世界主要金枪鱼类以及主要捕捞海域的开发现状和我国国情,提出我国目前面临的几点困难以及发展壮大我国金枪鱼渔业的建议.     

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。     

Standardizing catch and effort data of the Taiwanese distant-water longline fishery in the western and central Pacific Ocean for bigeye tuna, Thunnus obesus

Catch per unit effort (CPUE) is often used as an index of relative abundance in fisheries stock assessments. However, the trends in nominal CPUE can be influenced by many factors in addition to stock abundance, including the choice of fishing location and target species, and environmental conditions. Consequently, catch and effort data are usually ‘standardized’ to remove the impact of such factors. Standardized CPUE for bigeye tuna, Thunnus obesus, caught by the Taiwanese distant-water longline fishery in the western and central Pacific Ocean (WCPO) for 1964–2004 were derived using three alternative approaches (GLM, GAM and the delta approach), and sensitivity was explored to whether catch-rates of yellowfin tuna and albacore tuna are included in the analyses. Year, latitude, and the catch-rate of yellowfin explained the most of the deviance (32–49%, depending on model configuration) and were identified consistently among methods, while trends in standardized catch-rate differed spatially. However, the trends in standardized catch-rates by area were found to be relatively insensitive to the approach used for standardization, including whether the catch-rates of yellowfin and albacore were included in the analyses.     

基于不同模型研究环境因子对中西太平洋鲣资源丰度的影响

根据1998—2013年中西太平洋鲣(Katsuwonus pelamis)生产数据,选取时空因子(年、月、经纬度)和环境因子[海表面温度(SST)、海表面高度(SSH)、尼诺指数(ONI)和叶绿素a浓度]Chl-a)],通过两种不同的模型(广义加性模型GAM和提升回归树模型BRT)研究各因子对鲣资源丰度(以CPUE表示)的影响。研究结果认为,GAM模型中,经度对CPUE的影响最大,累计解释偏差超过50%,其次为纬度、年和月;在环境因子中,SSH最为重要,其次为ONI,而SST和Chl-a的影响相对较低。BRT模型分析结果与GAM分析结果类似,时空因子相对占据了重要的地位,其中经度的影响最大,其次为年、纬度和月;而在环境因子中,ONI的重要性相对更高,其次为SSH,SST和Chl-a同样影响较低。研究认为,两种模型均能较好地反映出因子对CPUE的影响。由于厄尔尼诺/拉尼娜现象引起的海洋环境变化会使鲣资源分布产生差异,因此在后续的渔情预报研究中,应该更多地考虑将ONI因子纳入渔情预报模型中,以提高预测精度。     

The relationship between the skipjack tuna (Katsuwonus pelamis) fishery and seasonal temperature variability in the south-western Atlantic

The spatio‐temporal distribution of tuna fishing effort has been related to oceanographic circulation and features in several seas of the world. Understanding the relationship between environmental variables and fishery resource dynamics is important for management decisions and to improve fishery yields. The relationship between sea temperature variability and the pole‐and‐line skipjack tuna (Katsuwonus pelamis) fishery in the south‐western Atlantic Ocean was investigated in this work. Data from logbooks, satellite images (sea surface temperature), and oceanographic surveys were used in the analyses. Skipjack are caught in warm tropical waters of the Brazil Current (BC). The north–south displacement of fishing effort was strongly associated to seasonal variation of the surface temperature, which was coupled to the tropical BC flow. Oceanographic fronts from autumn to spring and a shallow thermocline in summer probably induces the aggregation of skipjack schools over the shelfbreak, favouring fishing operations. Hypotheses are proposed to explain the relationship between peaks of fishing events and the presence of topographic peculiarities of the shelfbreak.     

Environmental influences on Atlantic bluefin tuna (Thunnus thynnus) catch per unit effort in the southern Gulf of St. Lawrence

The Atlantic bluefin tuna (Thunnus thynnus) population in the western Atlantic supports substantial commercial and recreational fisheries. Despite quota establishment and management under the auspices of the International Commission for the Conservation of Atlantic Tunas, only small increases in population growth have been estimated. In contrast to other western bluefin tuna fisheries indices, contemporary estimates of catch per unit effort (CPUE) in the southern Gulf of St. Lawrence have increased rapidly and are at record highs. This area is characterized by the Cold Intermediate Layer (CIL) that is defined by waters <3°C and located at depths of 30–40 m in September. We investigated the influence of several in situ environmental variables on the bluefin tuna fishery CPUE using delta‐lognormal modelling and relatively extensive and consistent oceanographic survey data, as well as dockside monitoring and mandatory logbook data associated with the fishery. Although there is considerable spatial and temporal variation of water mass characteristics, the amount of available habitat in the southern Gulf of St. Lawrence (assuming a > 3°C thermal ambit) for bluefin tuna has been increasing. The percentage of the water column occupied by the CIL was a significant environmental variable in the standardization of CPUE estimates. There was also a negative relationship between the spatial extents of the CIL and the fishery. Properties of the CIL account for variation in the bluefin tuna CPUE and may be a factor in determining the amount of available feeding habitat for bluefin tuna in the southern Gulf of St. Lawrence.     

基于贝叶斯概率的印度洋大眼金枪鱼渔场预报

本文采用贝叶斯概率为模型基础框架,利用来自印度洋金枪鱼管理委员会(IOTC)的大眼金枪鱼延绳钓历史渔获统计数据和美国国家海洋大气管理局(NOAA)的海温最优插值再分析数据,进行适用于印度洋金枪鱼延绳钓渔场的模型参数估算与预报模型构建。模型回报精度验证结果表明,印度洋大眼金枪鱼延绳钓渔场综合预报的准确率达到了65.96%。模型预报结果用概率百分比来表示,符合渔业资源分布的客观特点。利用中分辨率成像光谱仪MODIS提供的SST产品进行业务化运行的渔场预报,利用模型结果每周生成印度洋大眼金枪鱼延绳钓渔场概率预报图,用不同大小的圆形来表示渔场概率的高低,可以为印度洋区域的远洋渔业生产提供信息支持。     

北太平洋长鳍金枪鱼卵巢的发育特征

根据2013年10月–2014年2月在北太平洋海域(29°08′~41°08′N,163°50′~144°19′W)采集的364尾长鳍金枪鱼的卵巢样本,利用组织学分析,详细描述了长鳍金枪鱼卵巢、卵细胞的发育阶段。结果显示,北太平洋长鳍金枪鱼卵巢内同时存在不同时相的卵细胞,为分批产卵类型;组织学上,长鳍金枪鱼的卵细胞发育过程分为6个时相,卵巢发育过程分为6个时期;卵巢成熟指数在成熟期为Ⅰ~Ⅴ期时逐渐增大,在Ⅵ期时减小;北太平洋长鳍金枪鱼产卵高峰为12月中旬和1月初,其卵巢成熟指数随纬度的升高呈递减趋势,随经度变化规律不明显。研究表明,通过对北太平洋长鳍金枪鱼卵巢的发育特征的分析与探讨,可为北太平洋长鳍金枪鱼的资源状况评估及渔业可持续发展提供生物学信息。     

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.     

Tuna and swordfish catch in the U.S. northwest Atlantic longline fishery in relation to mesoscale eddies

To analyze the effects of mesoscale eddies, sea surface temperature (SST), and gear configuration on the catch of Atlantic bluefin (Thunnus thynnus), yellowfin (Thunnus albacares), and bigeye tuna (Thunnus obesus) and swordfish (Xiphias gladius) in the U.S. northwest Atlantic longline fishery, we constructed multivariate statistical models relating these variables to the catch of the four species in 62 121 longline hauls made between 1993 and 2005. During the same 13‐year period, 103 anticyclonic eddies and 269 cyclonic eddies were detected by our algorithm in the region 30–55°N, 30–80°W. Our results show that tuna and swordfish catches were associated with different eddy structures. Bluefin tuna catch was highest in anticyclonic eddies whereas yellowfin and bigeye tuna catches were highest in cyclonic eddies. Swordfish catch was found preferentially in regions outside of eddies. Our study confirms that the common practice of targeting tuna with day sets and swordfish with night sets is effective. In addition, bluefin tuna and swordfish catches responded to most of the variables we tested in the opposite directions. Bluefin tuna catch was negatively correlated with longitude and the number of light sticks used whereas swordfish catch was positively correlated with these two variables. We argue that overfishing of bluefin tuna can be alleviated and that swordfish can be targeted more efficiently by avoiding fishing in anticyclonic eddies and in near‐shore waters and using more light sticks and fishing at night in our study area, although further studies are needed to propose a solid oceanography‐based management plan for catch selection.     

利用GIS分析中西太平洋金枪鱼围网渔场的时空变动

根据中西太平洋1984~2003年金枪鱼围网渔业的渔获量统计资料,利用G IS定性分析方法和数值分析方法对中西太平洋海区的金枪鱼围网渔场的时空变动进行研究。研究结果表明:1984年到1991年,CPUE值在12.0~17.3 t/(d.n)之间;1992年至2003年,CPUE值在19.1~27.9 t/(d.n)之间,两个阶段的CPUE差异显著;Ⅰ、Ⅱ和Ⅲ类渔场基本上全部分布在5°S~5°N、140°E~180°之间,但Ⅲ类渔场在南半球略往东延伸,在10~5°S、155°~160°E之间也有分布;Ⅳ、Ⅴ类渔场则分布在Ⅰ、Ⅱ和Ⅲ类渔场的周边,其中Ⅳ类渔场主要位于东经地区,Ⅴ类渔场主要位于西经地区。     

Relationship between albacore (Thunnus alalunga) fishing grounds in the Indian Ocean and the thermal environment revealed by cloud-free microwave sea surface temperature

Using cloud-free Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E) sea surface temperature (SST) and daily set longline fishery data, we studied the relationship between albacore (ALB) fishing grounds and thermal conditions in the southern Indian Ocean. SST and Jensen-Shannon divergence (JSD) maps with a daily spatiotemporal resolution were related to sites with high catches per unit effort (CPUE) (>11 fish/10³ hooks). A high JSD is considered to be an index of a SST front. In winter, high CPUE occurred in the vicinity of the North Subtropical Front (Belkin and Gordon, 1996), where SST was 15-19 °C and JSD was 0.3-0.9. Histograms of the high CPUE plotted against SST and JSD indicated that 95% of the high CPUEs were in the 16-18.5 °C SST range and 97% were in the 0.4-0.9 JSD range. These ranges of SST and JSD are optimum ranges. These cloud-free SST/JSD analyses clearly demonstrate the seasonal north-south movement of the optimum SST and JSD band, which corresponds to the North Subtropical Front in the southern Indian Ocean. Monthly maps of joint probability density (JPD) with the optimum ranges of SST and JSD revealed that high CPUEs are located in the narrow bands with high JPD (>50%).