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。     

西北印度洋大眼金枪鱼渔场预报模型建立与模块开发

根据1990—2003年印度洋大眼金枪鱼延绳钓渔业数据和美国国家海洋和大气管理局提供的海表温度、叶绿素-a历史环境数据,应用环境因子叠加方法,构建了西印度洋大眼金枪鱼渔场预报模型,用于金枪鱼渔场预报。分析得出各月适宜海表温度、叶绿素-a浓度范围和历史高产区空间位置;导入实时海表温度、叶绿素-a等遥感栅格数据,分别提取适宜海表温度、适宜叶绿素-a浓度和历史高产区的空间栅格数据集,最后在空间上对3种栅格数据进行空间叠加并取交集。交集所指空间区域即为大眼金枪鱼潜在渔场位置。通过精度检验,表明该模型渔场预报精度为60.5%。并以VC++6.0工具为开发平台,对此模型进行了设计开发,实现了模块预报西北印度洋大眼金枪鱼渔场。     

Climatic oscillations and tuna catch rates in the Indian Ocean: a wavelet approach to time series analysis

We analysed the influence of climatic oscillations [based on the Indian Oscillation Index (IOI)] on monthly catch rates of two tropical tuna species in the equatorial Indian Ocean. We carried out wavelet analysis, an efficient method of time series analysis to study non‐stationary data. Catch per unit of effort (CPUE) of bigeye tuna was computed from Japanese longline statistics from 1955 to 2002 in the equatorial Indian Ocean and CPUE of yellowfin tuna was derived from industrial purse seine statistics from 1984 to 2003 in the Western Indian Ocean. Wavelet analyses allowed us to quantify both the pattern of variability in the time series and non‐stationary associations between tuna and climatic signals. Phase analyses were carried out to investigate dependency between the two signals. We reported strong associations between tuna and climate series for the 4‐ and 5‐yr periodic modes, i.e. the periodic band of the El Niño Southern Oscillation signal propagation in the Indian Ocean. These associations were non‐stationary, evidenced from 1970 to 1990 for bigeye, and from 1984 to 1991 and then from 1993 to 2001 for yellowfin. Warm episodes (low negative IOI values) matched increases of longline catch rates of bigeye during the 1970–1990 time frame, whereas the strong 1997–1998 warm event matched a decrease of purse seine catch rates of yellowfin. We discussed these results in terms of changes in catchability for purse seine and longline.     

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.     

热带大西洋金枪鱼延绳钓兼捕鲨鱼种类组成和渔获率及其与表温的关系

根据2007年12月~2008年3月采集的热带大西洋(05°37′~12°01′N、29°00′~36°51′W)金枪鱼延绳钓渔获物数据,分析了金枪鱼延绳钓兼捕鲨鱼的种类组成、渔获量、渔获率及其与表温的关系。本次调查共捕获鲨鱼8种,隶属3目7科7属,总渔获尾数为633 ind,总渔获量达26 837.4 kg,其中大青鲨为主要兼捕种类。各种鲨鱼渔获率平均值在0.003~1.524 ind/1 000 hooks之间,其中大青鲨最高,其值为1.524 ind/1 000 hooks,大眼砂锥齿鲨最低,其值为0.003 ind/1 000 hooks。各种鲨鱼渔获率月变化不明显(ANOVA,P=0.901)。鲨鱼总渔获率和大青鲨渔获率与表温都呈显著性负相关。大青鲨主要出现渔场的表温范围为24.6~25.8℃。     

Do habitat models accurately predict the depth distribution of pelagic fishes?

Habitat models are used to correct estimates of fish abundance derived from pelagic longline fishing gear. They combine information on hook depth with the species’ preferences for ambient environmental conditions to adjust the gear's catchability. We compare depth distributions of bigeye tuna (Thunnus obesus) catch predicted by a habitat model with distributions derived from data collected by observers on longliners in the tropical Pacific Ocean. Our analyses show that the habitat model does not accurately predict the depth distribution of bigeye tuna; its predictions are worse than those from models that assume no effect of depth on catches. Statistical models provided superior fits to the observed depth distribution. The poor performance of the habitat model is probably due to (1) problems in estimating hook depth, (2) fine‐scale variations in environmental conditions, (3) incomplete knowledge of habitat preferences and (4) differences between the distribution of bigeye tuna and their vulnerability to longline gear.     

Habitat analysis of the commercial tuna of the Eastern Tropical Pacific Ocean

We have extracted information on the habitats of bigeye (Thunnus obesus), skipjack (Katsuwonus pelamis) and yellowfin (Thunnus albacares) in the Eastern Tropical Pacific Ocean by matching the spatial‐temporal distribution of catch and effort of purse seine and longline fleets collected by the Inter‐American Tropical Tuna Commission with oceanographic conditions and subjecting the matched data to Quotient Analysis and General Additive Models (GAMs). These analyses yielded the following results. The habitats defined by the GAM analysis of young fish differ significantly between two periods, one before and one after the introduction of fish aggregation devices (FADs). This was not true for the older fish caught by longline. We speculate that these changes were caused by the extensive use of FADs. Younger bigeye and yellowfin caught by the purse seine fleet have a different preference of environmental variables compared to older fish caught by longline. This is to be expected since tuna of different age groups have different sizes, metabolic capabilities and swimming skills. Moreover, as revealed by GAMs, the habitats of young fish differ between species to a much larger degree than those of older fish. Our results indicate the fundamental differences between fishing methods, targeted species, and operating region of the two fisheries. Specifically, young bigeye occupy equatorial waters farther from the coast and where the hypoxic layer is deeper, young skipjack occupy more productive waters associated with equatorial and coastal upwelling, and young yellowfin occupy broad areas where waters are underlain by a shallow hypoxic layer.     

Modeling environmental influence on Atlantic bluefin tuna bycatch by Mexican longliners in the Gulf of Mexico

Atlantic bluefin tuna (ABFT) stocks have been considered overfished over the last decades, especially the western stock, whose main spawning grounds are in the Gulf of Mexico (GoM). Despite the current measures implemented, spawner bycatch by the longline fleet targeting yellowfin tuna (YFT) may explain the lack of recovery of local stocks. This situation demands the implementation of appropriate spatiotemporal management strategies to minimize bluefin bycatch in the GoM, which involves knowledge in depth of its distribution and environmental forcing. Using catch and effort data from the Mexican commercial longline fleet with 100% scientific observer coverage from 1999 to 2012 and satellite derived environmental data, this study investigated the influence of environmental conditions on catch per unit effort (CPUE) of ABFT and YFT. General additive models (GAMs) were fitted using a negative binomial distribution and applying Akaike information criterion (AIC) to select the best model. Bluefin CPUE exhibited a marked seasonality, reaching higher values in February and March while YFT catches occurred throughout the year. Two main locations were identified with higher ABFT bycatch rates, Campeche Bay and the western‐central area of the GoM. Higher ABFT CPUE was significantly associated with areas with negative sea level anomalies and low sea surface temperatures, characteristic of cyclonic eddies. Instead, YFT CPUE showed a lesser environmental influence in its distribution. To our knowledge, the patterns shown in this study provide the first in‐depth approach to understand ABFT bycatch in Mexican waters, which will help in further development of adequate management strategies.     

A comparison of circle hook and J hook performance in a western equatorial Atlantic Ocean pelagic longline fishery

Catch composition, catch rates, hooking location, and status at release at haulback were monitored during 81 experimental sets (launches and hauling fishing per day) in a commercial pelagic longline fishery targeting tuna in the equatorial South Atlantic Ocean. Circle hooks (size 18/0, 0° offset) and J-style hooks (size 9/0, 10° offset) with squid baits were deployed in an alternating fashion. The catch composition was not significantly different for most species between the two types of hooks, except for bigeye tuna, which showed a significantly higher proportion of catches on the circle hook (p ? 0.001) and for sailfish, pelagic stingray, and leatherback sea turtle, which had higher catch rates on the J-style hook (p = 0.018, p ? 0.001, and p = 0.044, respectively). Bigeye and yellowfin tuna showed significantly higher rates of survival at the time of gear retrieval with circle hooks, and circle hooks hooked bigeye tuna, yellowfin tuna, swordfish, and sailfish significantly more often externally than internally. Our results suggest that the use of size 18/0, 0° offset circle hooks in the equatorial pelagic longline fishery may increase the survival of bycatch species at the time of gear retrieval with minimal effects on the catches of target species.     

El Niño effects in the Palmyra Atoll region: oceanographic changes and bigeye tuna (Thunnus obesus) catch rate variability

A generalized additive model (GAM) was constructed to separate and quantify the effects of fishery‐based (operational) and oceanographic parameters on the bigeye tuna (Thunnus obesus) catch rates at Palmyra Atoll in the central Tropical Pacific. Bigeye catch, the number of hooks per set, and set location from 4884 longline sets spanning January 1994 to December 2003 were used with a temporally corresponding El Niño‐Southern Oscillation (ENSO) indicator built from sea surface height (SSH) data. Observations of environmental data combined with the results from the GAM indicated that there is an increase in bigeye catch rates corresponding to an increase in eastward advection during the winter months of El Niño events. A seasonal pattern with higher bigeye catch rates from December to April and a spatial pattern with higher rates to the northeast and northwest of the atoll were observed during this study period. It is hypothesized that the combination of the eastward advection of the warm pool coupled with vertical changes in temperature during the winter months of El Niño events increases the availability of bigeye tuna in this region. This increase in availability may be due to a change in exploitable population size, location, or both.     

Application of a habitat-based model to estimate effective longline fishing effort and relative abundance of Pacific bigeye tuna (Thunnus obesus)

A new habitat‐based model is developed to improve estimates of relative abundance of Pacific bigeye tuna (Thunnus obesus). The model provides estimates of `effective' longline effort and therefore better estimates of catch‐per‐unit‐of‐effort (CPUE) by incorporating information on the variation in longline fishing depth and depth of bigeye tuna preferred habitat. The essential elements in the model are: (1) estimation of the depth distribution of the longline gear, using information on gear configuration and ocean currents; (2) estimation of the depth distribution of bigeye tuna, based on habitat preference and oceanographic data; (3) estimation of effective longline effort, using fine‐scale Japanese longline fishery data; and (4) aggregation of catch and effective effort over appropriate spatial zones to produce revised time series of CPUE. Model results indicate that effective effort has increased in both the western and central Pacific Ocean (WCPO) and eastern Pacific Ocean (EPO). In the WCPO, effective effort increased by 43% from the late 1960s to the late 1980s due primarily to the increased effectiveness of effort (deeper longline sets) rather than to increased nominal effort. Over the same period, effective effort increased 250% in the EPO due primarily to increased nominal effort. Nominal and standardized CPUE indices in the EPO show similar trends – a decline during the 1960s, a period of stability in the 1970s, high values during 1985–1986 and a decline thereafter. In the WCPO, nominal CPUE is stable over the time‐series; however, standardized CPUE has declined by ～50%. If estimates of standardized CPUE accurately reflect relative abundance, then we have documented substantial reductions of bigeye tuna abundance for some regions in the Pacific Ocean. A decline in standardized CPUE in the subtropical gyres concurrent with stability in equatorial areas may represent a contraction in the range of the population resulting from a decline in population abundance. The sensitivity of the results to the habitat (temperature and oxygen) assumptions was tested using Monte Carlo simulations.     

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.     

基于GAM模型分析水温垂直结构对热带大西洋大眼金枪鱼渔获率的影响

通过模型分析环境变量对延绳钓大眼金枪鱼渔获率的影响,评估适宜垂直活动空间对大西洋大眼金枪鱼延绳钓渔获率的作用。首先采用回归分析检验环境变量对延绳钓渔获率(由单位捕捞努力渔获量(catch per unit fishing effort,CPUE)表示)的影响显著性,结合时空变量,采用GAM(generalized additive model)模型分析各变量对大眼金枪鱼CPUE非线性作用。模型结果表明,环境因子和时空变量对热带大西洋延绳钓大眼金枪鱼渔获率空间分布影响明显。大西洋大眼金枪鱼延绳钓的高渔获率月份出现在夏季和冬季,空间上在赤道以北和30?~50?W。12℃等温线深度对大眼金枪鱼延绳钓渔获率的影响表现为抛物线形状,高渔获率出现在深度较浅的250 m水层,随着12℃等温线深度的增加,大眼金枪鱼延绳钓渔获率降低。温跃层下界深度和深度差对大眼金枪鱼延绳钓渔获率的影响都是穹顶状。随着温跃层下界深度值和深度差由小变大至200 m,延绳钓渔获率递增;温跃层下界深度和深度差超过200 m后,延绳钓渔获率变小。温跃层下界深度和深度差对大眼金枪鱼延绳钓渔获率影响显著的水层分别是200 m和50 m。研究结果显示,12℃等温线深度和温跃层对热带大西洋延绳钓大眼金枪鱼渔获率影响是交叉的,在大眼金枪鱼适宜垂直活动水层受限到和延绳钓作业深度相同时,延绳钓渔获率最高;在适宜垂直活动空间过深或者过浅时,延绳钓渔获率都变小,但可以通过改变作业方式提高渔获率。采用延绳钓CPUE进行渔场和资源评估要考虑金枪鱼适宜垂直活动空间。     

大西洋南部金枪鱼渔场的生产调查报告

根据随船调查材料，对大西洋南部金枪鱼延绳钓渔业从捕捞技术，渔场环境因素，渔获物情况、初加工、销售等方面做出了总结。本文着重分析了各个作业渔场的渔获情况，判断出八个中心渔场的位置，并就大眼金枪鱼在这几个中心渔场的生物学特征做了统计分析，从而为用地理信息技术预报渔场提供了实施依据。     

Alternative error distribution models for standardization of catch rates of non-target species from a pelagic longline fishery: billfish species in the Venezuelan tuna longline fishery

Alternative error distributions were evaluated for calculating indices of relative abundance for non-target species using catch and effort data from commercial fisheries. A general procedure is presented for testing the underlying assumptions of different error distributions. Catch rates, from an observer program, of billfish caught mainly as bycatch in a pelagic tuna longline fishery in the Western Central Atlantic were standardized. Although catches of billfishes are not common in pelagic tuna longline fisheries, these fisheries are one of the main sources of fishing mortality for these stocks in the central Atlantic due to the magnitude and spatial extent of longline fishing effort. Billfish CPUE data are highly skewed with a large proportion of zero observations. Delta distribution models can accommodate this type of data, and involve modeling the probability of a non-zero observation and the catch rate given that the catch is non-zero separately. Three different Delta models were compared against other error distributions, including the lognormal, log-gamma, and Poisson. Diagnostic checks and deviance table analyses were performed to identify the best error distribution and the set of factors and interactions that most adequately explained the observed variability. The results indicated that the Delta-lognormal model (a binomial error distribution for the probability of a non-zero catch and lognormal error for the positive catch rates) complied best with the underlying characteristics of the data set. Analyses of catch rates for blue marlin, white marlin and sailfish confirmed the spatio-temporal nature of their distribution in the central Atlantic and Caribbean Sea. Also, the analyses indicated that catch rates of billfish differed among fishing vessel types; larger vessels had a higher probability of catching blue marlin, the more oceanic-oriented species, and lower probabilities of catching the more coastal-oriented species white marlin and sailfish. Standardized catch rates indicated in general a lower relative abundance for blue and white marlin in the most recent years, although estimated confidence intervals overlap through the years especially for white marlin.     

Environmental and spatial effects on the distribution of blue marlin (Makaira nigricans) as inferred from data for longline fisheries in the Pacific Ocean

Blue marlin is distributed throughout tropical and temperate waters in the Pacific Ocean. However, the preference of this species for particular habitats may impact its vulnerability to being caught. The relationship between spatio‐temporal patterns of blue marlin abundance and environmental factors is examined using generalized additive models fitted to catch and effort data from longline fisheries. The presence of blue marlin, and the catch rate given presence, are modeled separately. Latitude, longitude, and sea‐surface temperature explain the greatest proportion of the deviance. Spatial distributions of relative density of blue marlin, based on combining the probability of presence and relative density given presence, indicate that there is seasonal variation in the distribution of blue marlin, and that the highest densities occur in the tropics. Seasonal patterns in the relative density of blue marlin appear to be related to shifts in SST. The distribution and relative abundance of blue marlin are sufficiently heterogeneous in space and time that the results of analyses of catch and effort data to identify ‘hotspots’ could be used as the basis for time‐area management to reduce the amount of blue marlin bycaught in longline fisheries.     

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。     

应用贝叶斯状态空间剩余产量模型框架评估印度洋大眼金枪鱼的资源状况

根据1950―2016年的渔获量数据及1955―2016年的单位捕捞努力量(Catch Per Unit Effort,CPUE)数据,采用贝叶斯状态空间剩余产量模型框架JABBA(Just Another Bayesian Biomass Assessment)对印度洋大眼金枪鱼(Thunnus obesus)的资源状况进行评估,分析了渔船效应、CPUE数据尺度对评估结果的影响。结果表明,模型拟合效果对于不同时间跨度下CPUE数据的选择比较敏感。当选用时间跨度为1979―2016年的CPUE数据且考虑渔船效应时,模型拟合效果最好。2016年大眼金枪鱼的资源量为812 kt,最大可持续产量(Maximum Sustainable Yield,MSY)为163 kt,远高于同年渔获量86.81 kt,其资源量具有82.50%的概率处于"健康"状态。当总允许可捕量为69.45～104.17 kt时(2016年渔获量的80%～120%),未来10年大眼金枪鱼的资源量仍高于B_(MSY)(达到MSY所需的生物量)。回顾性分析结果表明,该资源评估结果存在一定程度的回顾性问题,捕捞死亡率和资源量分别存在被低估和高估的现象。将来需要在模型结构设定、CPUE数据选择及模型参数的先验分布设置等方面进一步优化。     

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.     

中西太平洋鲣鱼丰度的时空分布及其与表温的关系

中西太平洋是全球金枪鱼围网的主要海域,鲣鱼(Katsuwonus pelamis)是金枪鱼围网的主要作业对象。本研究利用1983～2007年中西太平洋金枪鱼围网渔获物数据,结合海洋表层温度(SST)数据,分析中西太平洋鲣鱼资源丰度在时间序列和空间位置上的分布规律。研究表明,1983～2002年,各年平均CPUE在时间序列上呈一定的上升趋势,1983～2002年,平均SST在一定范围内上下波动,平均CPUE和平均SST无显著相关性;2003～2007年,平均CPUE和平均SST均呈较大幅度上升,两者呈显著相关。从空间位置分析,鲣鱼资源量集中出现在SST为28～30℃之间的海域,在5°N和10°S附近海域CPUE反映的总体资源量较高,而在0°和5°S的资源量较低。鲣鱼资源量较大区域分布在冷暖水团交汇处。