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.     

Oceanographic investigation of the American Samoa albacore (Thunnus alalunga) habitat and longline fishing grounds

The American Samoa fishing ground is a dynamic region with strong mesoscale eddy activity and temporal variability on scales of <1 week. Seasonal and interannual variability in eddy activity, induced by baroclinic instability that is fueled by horizontal shear between the eastward‐flowing South Equatorial Counter Current (SECC) and the westward‐flowing South Equatorial Current (SEC), seems to play an important role in the performance of the longline fishery for albacore. Mesoscale eddy variability in the American Samoa Exclusive Economic Zone (EEZ) peaks from March to April, when the kinetic energy of the SECC is at its strongest. Longline albacore catch tends to be highest at the eddy edges, while albacore catch per effort (CPUE) shows intra‐annual variability with high CPUE that lags the periods of peak eddy activity by about 2 months. When CPUE is highest, the values are distributed toward the northern half of the EEZ, the region affected most by the SECC. Further indication of the possible importance of the SECC for longline performance is the significant drop in eddy variability in 2004 when compared with that observed in 2003 – resulting from a weak SECC – which was accompanied by a substantial drop in albacore CPUE rates and a lack of northward intensification of CPUE. From an ecosystem perspective, evidence to support higher micronekton biomass in the upper 200 m at eddy boundaries is inconclusive. Albacore's vertical distribution seems to be governed by the presence of prey. Albacore spend most of their time between 150 and 250 m, away from the deep daytime and shallow nighttime sonic scattering layers, at depths coinciding with those of small local maxima in micronekton biomass whose backscattering properties are consistent with those of albacore's preferred prey. Settling depths of longline sets during periods of decreased eddy activity correspond to those most occupied by albacore, possibly contributing to the lower CPUE by reducing catchability through rendering bait less attractive to albacore in the presence of prey.     

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.     

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.     

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.     

Environmental effects on forage and longline fishery performance for albacore (Thunnus alalunga) in the American Samoa Exclusive Economic Zone

The South Equatorial Counter Current (SECC) strongly influences the American Samoa Exclusive Economic Zone (EEZ) and changes strength on a seasonal and ENSO cycle. A strong SECC is associated with a predominantly anticyclonic eddy field as well as increased micronekton biomass and catch-per-unit-effort (CPUE) for albacore tuna, the economically important target species of the local longline fishery. A strong SECC carries chlorophyll a -rich waters from upwelling regions at the north coast of New Guinea towards the EEZ, most likely resulting in the observed increase in micronekton biomass, forage for albacore. Relatively stable anticyclonic eddies show a further increase in micronekton biomass, apparently advected from neighboring SECC waters. The presence of forage presumably concentrates albacore, thus resulting in the observed increase in CPUE. High shear regions of neither anticyclonic nor cyclonic eddies correlate with increased micronekton biomass. Areas characterized by South Equatorial Current (SEC) waters correspond to areas with the lowest micronekton biomass and the highest number of aggregative structures, which are most likely small pelagic fish shoals. Micronekton composition in SEC waters differs from that in the SECC. During El Niños, the seasonal signals at the north shore of New Guinea and in the SECC are exceptionally strong and correspond to higher albacore CPUE in the EEZ. My results suggest that the strength of upwelling and the resulting increase in chlorophyll a at New Guinea, as well as the Southern Oscillation Index, could be used to predict the performance of the local longline fishery for albacore tuna in the American Samoa EEZ.     

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.     

Distribution of albacore (Thunnus alalunga) in the Indian Ocean and its relation to environmental factors

The distribution pattern of albacore, Thunnus alalunga, in the Indian Ocean was analyzed based on catch data from the Taiwanese tuna longline fishery during the period 1979–85. The Taiwanese tuna fishery began operating in the Indian Ocean in 1967. We used a geographic information system to compile a fishery and environmental database and statistically explored the catch per unit effort (CPUE) distribution of albacore. Our results indicated that immature albacore were mainly distributed in areas south of 30°S although some displayed a north–south seasonal migration. Mature albacore, which were mainly concentrated between 10°S and 25°S, also showed a north–south migration. Within 10°S and 30°S, the separation of mature, spawning, and immature albacore life history stages roughly coincided with the boundaries of the three oceanic current systems in the Indian Ocean. The optimal environmental variables for CPUE prediction by stepwise discriminant analysis differed among life history stages. For immature albacore, the sea surface variables sea surface temperature (SST), chlorophyll concentration and surface salinity were significant. For mature albacore, SST was significant, while for spawning albacore, the sub‐surface variables temperature at 100 m and oxygen at 200 m were significant. Spawning albacore evidently prefer deep oceanographic conditions. Our results on the oceanographic conditions preferred by different developmental stages of albacore in the Indian Ocean were compatible with previous studies found in the Pacific Ocean.     

A nonlinear,low data requirement model for producing spatially explicit fishery forecasts

Spatial variability can confound accurate estimates of catch per unit effort (CPUE), especially in highly migratory species. The incorporation of spatial structure into fishery stock assessment models should ultimately improve forecasts of stock biomass. Here, we describe a nonlinear time series model for producing spatially explicit forecasts of CPUE that does not require ancillary environmental or demographic data, or specification of a model functional form. We demonstrate this method using spatially resolved (1° × 1° cells) CPUE time series of North Pacific albacore in the California Current System. The spatial model is highly significant (P < 0.00001) and outperforms two spatial null models. We then create a spatial forecast map for years beyond the range of data. Such approaches can guide spatial management of resources and provide a complement to more data‐intensive, highly parameterized population dynamics and ecosystem models currently in use.     

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。     

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%).     

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.     

北太平洋公海秋刀鱼渔场初步分析

根据2004年7~11月“中远渔1号”调查船北太平洋公海秋刀鱼渔场探捕调查的生产情况,对秋刀鱼渔场进行分析。结果发现:①秋刀鱼渔场可根据渔场位置分为北部渔场和南部渔场,北部渔场范围为44°~45°N、156°~158°E,南部渔场范围为41°~42°N、150°~151°E,南部渔场的分布范围小于北部渔场。②秋刀鱼的生产以11月份生产最好,平均日产量达22.7t,其中最高日产量为60.42t;8月份的秋刀鱼生产最差,平均日产量为2.95t,与2003年的12.05t反差较大,主要是由于受到渔场环境因子变化的影响,鱼发位置偏至俄罗斯专属经济区内的缘故。③秋刀鱼舷提网作业平均日放网次数达7.6次,最高1天放网次数达到16次,而最高网次产量为11.05t。④秋刀鱼渔获组成以中小型鱼为主,占80%以上,除7月份渔获中特大型秋刀鱼占有较大比例外,其余月份很少有特大级秋刀鱼。⑤在相近的渔场位置,秋刀鱼个体随着生产月份的推迟,鱼体呈变小的趋势。     

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.     

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%。     

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。     

中西太平洋鲣渔场时空分布研究

中西太平洋海域是全球鲣(Katsuwonus pelamis)作业的主要渔场,该海域鲣渔场的时空分布规律,尤其是高产海域,是渔情预报研究的基础和前提。根据太平洋共同体秘书处提供的1995-2014年中西太平洋鲣围网捕捞生产统计数据,对各年各月的鲣产量和捕捞努力量渔获量(CPUE)进行统计分析,通过产量重心分析和聚类分析,找出渔场重心变化规律,同时选取高产的22个渔区(分辨率5°×5°),研究时间和空间因素对CPUE的影响。研究结果表明,中西太平洋鲣历年产量逐步上升,CPUE波动较大,而各月产量和CPUE差异较大,高产月份主要集中在上半年;历年产量重心分布不均,经度方向上分布差异较大,聚类分析可分为4类;各月产量重心变化呈现顺时针变化规律,从南到北,自西向东,再从北向南移动,聚类分析可分为3类;渔获量主要分布于5°S～5°N、120°～175°E,因此对该海域CPUE进行统计,以年份、月份和渔区为影响因素,分析发现,极端气候年份与其它年份的CPUE有明显不同,月份间的变化与产量月间重心变化类似,上、下半年有着明显不同;不同空间下,经度间差异大于纬度间差异,135°～145°E为经度CPUE差异的分界线,而南北纬间的差异不明显。上述鲣的时空分布变化主要与ENSO现象引起的西太平洋暖池的变化有着密切关系,同时太平洋岛国的相关入渔政策也对其产生一定的影响。     

Spatio‐temporal distribution of albacore (Thunnus alalunga) catches in the northeastern Atlantic: relationship with the thermal environment

When the spring seasonal warming starts, North Atlantic albacore (Thunnus alalunga) juveniles and pre‐adults perform a trophic migration to the northeastern Atlantic, to the Bay of Biscay and to the southeast of Ireland. During this migration, they are exploited by Spanish trolling and baitboat fleets. The present study analyzes the relationship between the albacore spatio‐temporal distribution and the thermal environment. For this approach, several analyses have been performed on a database including fishing logbooks and sea surface temperature (SST) images, covering the period between 1987 and 2003. SST values and the SST gradients at the catch locations have been statistically compared to broader surrounding areas to test whether the thermal environment determines the spatial distribution of albacore. General additive models (GAM) have been used also to evaluate the relative importance of environmental variables and fleet behaviour. The results obtained show that, although juvenile albacore catch locations are affected by fleet dynamics, there is a close spatial and temporal relationship with the seasonal evolution of a statistically significant preferential SST window (16–18°C). However, differences have been identified between the relationship of albacore with SST within the Bay of Biscay in July and August (higher temperature). Such differences are found also in the spatial distribution of the catch locations; these reflect clearly the presence of two groups, differentiated after the third week of the fishing campaign at the end of June. The analysis undertaken relating the distribution of North Atlantic albacore juveniles with thermal gradients did not provide any evidence of a relationship between these catch locations and the nearby occurrence of thermal gradients.     

基于GAM和权重分析的西北太平洋秋刀鱼渔情预报研究

为了提高秋刀鱼(Cololabis saira)渔情预报模型的时空分辨率, 提升生产经济效益, 本研究基于 2013─2016 年 7—11 月中国在西北太平洋公海的秋刀鱼生产数据及海洋环境数据, 利用广义可加模型(generalized additive models, GAM)分别拟合单位捕捞努力量渔获量(catch per unit effort, CPUE)的适宜性指数(suitability index, SI)与各海洋环境变量之间的 SI 模型, 结合提升回归树模型(boosting regression tree, BRT)进行权重分析, 建立以月份为周期的秋刀鱼栖息地适宜性指数(habitat suitability index, HSI)模型。结果表明, (1) GAM 能较好地拟合适宜性指数与环境变量的关系, 获得最优环境变量参数值;(2) 环境变量对 CPUE 影响权重的前 3 位分别为海表温度梯度、海表温度和混合层深度, 其中, 在秋季 9—11 月海表温度梯度的权重值均为最高;(3) HSI 模型的检验和评价总体准确率分别为 82.0%和 73.2%, 秋季可达 87.7%和 77.9%, 在盛渔期 10 月, 预测准确率达 89.4%;(4) HSI 高值区与秋刀鱼实际渔场在空间分布基本一致。研究表明该模型适用于秋刀鱼的渔情预报, 并在每天的速报中具有明显优势。