Inclusion of prey data improves prediction of bluefin tuna (Thunnus thynnus) distribution

We examined the distribution of Atlantic bluefin tuna ( Thunnus thynnus ) in the Gulf of Maine, Northwest Atlantic Ocean, from 17 to 23 August 1995, in relation to physical and biological parameters. Specifically, we fit a binomial GLM to the bluefin tuna presence–absence data and predictor variables that include: sea surface temperature (SST), ocean depth, distance to an SST front, time-lagged density of SST fronts, and an interpolated surface of Atlantic herring ( Clupea harengus ) density. In addition, we use simple and partial Mantel tests to examine whether bluefin tuna presence–absence data are significantly associated with these predictors, once spatial autocorrelation is accounted for. Results suggest that the distribution of bluefin tuna significantly correlated with herring density ( z  =   3.525, P  =   0.000424), and that inclusion of biological variables results in a more parsimonious model. Mantel tests results indicate that bluefin tuna abundance is significantly correlated with herring density after the effect of spatial structure is removed (Mantel r  =   0.043, P  <   0.019).     

Predicting the occurrence of Atlantic bluefin tuna (Thunnus thynnus) larvae in the northern Gulf of Mexico: building a classification model from archival data

Although bluefin tuna are found throughout the Atlantic Ocean, spawning in the western Atlantic has been recorded predominantly in the Gulf of Mexico (GOM) in spring. Larval bluefin tuna abundances from the northern GOM are formulated into an index used to tune the adult stock assessment, and the variability of this index is currently high. This study investigated whether some of the variability in larval bluefin tuna abundances was related to environmental conditions, by defining associations between larval bluefin tuna catch locations, and a suite of environmental variables. We hypothesized that certain habitat types, as defined by environmental variables, would be more likely to contain bluefin tuna larvae. Favorable habitat for bluefin tuna larvae was defined using a classification tree approach. Habitat within the Loop Current was generally less favorable, as were warm‐core rings, and cooler waters on the continental shelf. The location and size of favorable habitat was highly variable among years, which was reflected in the locations of larval bluefin tuna catches. The model successfully placed bluefin tuna larvae in favorable habitat with nearly 90% accuracy, but many negative stations were also located within theoretically favorable habitat. The probability of collecting larval bluefin tuna in favorable habitat was nearly twice the probability of collecting bluefin tuna larvae across all habitats (35.5 versus 21.0%). This model is a useful addition to knowledge of larval bluefin tuna distributions; however, the incorporation of variables describing finer‐scale features, such as thermal fronts, may significantly improve the model’s predictive power.     

Variability of preferred environmental conditions for Atlantic bluefin tuna (Thunnus thynnus) larvae in the Gulf of Mexico during 1993–2011

The Gulf of Mexico (GOM) is the primary spawning ground for western Atlantic bluefin tuna (Thunnus thynnus). In this work, information reported by previous studies about the preferred environmental conditions for the occurrence of bluefin tuna larvae in the GOM is integrated into a dimensionless index, the BFT_Index. This index is used to evaluate the spatial and temporal variability of areas with favorable environmental conditions for larvae within the GOM during 1993–2011. The main findings of this work are that: (i) the proposed index successfully captures the spatial and temporal variability in the in situ occurrence of bluefin tuna larvae; (ii) areas with favorable environmental conditions for larvae in the GOM exhibit year‐to‐year spatial and temporal variability linked with mesoscale ocean features and sea surface temperature; and (iii) comparison of the BFT_Index‐derived variability with recruitment of age‐0 fish estimated from recent stock assessment indicates that changes in environmental conditions may drive a relevant component (~58%) of the recruitment variability. The comparison with the recruitment dataset further revealed the existence of key regions linked with recruitment in the central/northern GOM, and that the Loop Current may function as a trap for larvae, possibly leading to low survival rates. Above (below) average conditions for occurrence of larvae in the GOM during spring were observed in 2000, 2001, 2002, 2006–2008, and 2011 (1994, 1996, 1998, 1999, 2003 and 2010). Results reported here have potential applications to assessment of bluefin tuna.     

Horizontal and vertical movements of juvenile bluefin tuna (Thunnus orientalis) in relation to seasons and oceanographic conditions in the eastern Pacific Ocean

Electronically tagged juvenile Pacific bluefin, Thunnus orientalis, were released off Baja California in the summer of 2002. Time‐series data were analyzed for 18 fish that provided a record of 380 ± 120 days (mean ± SD) of ambient water and peritoneal cavity temperatures at 120 s intervals. Geolocations of tagged fish were estimated based on light‐based longitude and sea surface temperature‐based latitude algorithms. The horizontal and vertical movement patterns of Pacific bluefin were examined in relation to oceanographic conditions and the occurrence of feeding events inferred from thermal fluctuations in the peritoneal cavity. In summer, fish were located primarily in the Southern California Bight and over the continental shelf of Baja California, where juvenile Pacific bluefin use the top of the water column, undertaking occasional, brief forays to depths below the thermocline. In autumn, bluefin migrated north to the waters off the Central California coast when thermal fronts form as the result of weakened equatorward wind stress. An examination of ambient and peritoneal temperatures revealed that bluefin tuna fed during this period along the frontal boundaries. In mid‐winter, the bluefin returned to the Southern California Bight possibly because of strong downwelling and depletion of prey species off the Central California waters. The elevation of the mean peritoneal cavity temperature above the mean ambient water temperature increased as ambient water temperature decreased. The ability of juvenile bluefin tuna to maintain a thermal excess of 10°C occurred at ambient temperatures of 11–14°C when the fish were off the Central California coast. This suggests that the bluefin maintain peritoneal temperature by increasing heat conservation and possibly by increasing internal heat production when in cooler waters. For all of the Pacific bluefin tuna, there was a significant correlation between their mean nighttime depth and the visible disk area of the moon.     

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.     

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.     

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.     

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.     

Schooling and migration of large pelagic fishes relative to environmental cues

A kinesis model driven by high-resolution sea surface temperature maps is used to simulate Atlantic bluefin tuna movements in the Gulf of Maine during summer months. Simulations showed that individuals concentrated in areas of thermal preference. Results are compared to empirical distribution maps of bluefin tuna schools determined from aerial overflights of the stock during the same time periods. Simulations and empirical observations showed similar bluefin tuna distributions along fronts, although interannual variations in temperature ranges occupied suggest that additional foraging factors are involved. Performance of the model is further tested by simulating the relatively large-scale annual north–south migrations of bluefin tuna that followed a preferred thermal regime. Despite the model's relatively simple structure, results suggest that kinesis is an effective mechanism for describing movements of large pelagic fish in the expansive ocean environment.     

Evaluating spatio‐temporal variability in the habitat quality of Atlantic cod (Gadus morhua) in the Gulf of Maine

Reduced abundance and contracted spatial distribution of Atlantic cod, Gadus morhua, in the Gulf of Maine (GOM) may indicate large spatio‐temporal variation in their habitat quality. Season‐specific Habitat Suitability Index (HSI) models were developed to quantify such variation in the offshore GOM management area. Data used were non‐zero cod catch rates with calibrations from the Northeast Fisheries Science Center (NEFSC) spring and fall bottom trawl surveys over the period 1982–2013 and key physical environmental variables including depth, bottom temperature, bottom salinity and sediment types. Significant declines were found in the average HSI across the study area in the springs of early 2000s and 2010s. These low average HSI values coincide with reduced age‐1 recruitment of GOM cod stock after the mid‐1990s. Moreover, the western coastal areas of the GOM generally exhibited higher average HSI values than the eastern coastal areas, whereas the offshore areas always had the lowest average HSI. Relatively higher cod survey catch rates in the western GOM may imply positive influences of environmental controls on the distribution of GOM cod.     

Environmental effects on swordfish and blue shark catch rates in the US North Pacific longline fishery

Generalized additive models (GAMs) were applied to examine the relative influence of various factors on fishery performance, defined as nominal catch- per-unit-effort (CPUE) of swordfish (Xiphias gladius) and blue shark (Prionace glauca) in the Hawaii-based swordfish fishery. Commercial fisheries data for the analysis consisted of a 5 year (1991–1995) time series of 27 901 longline sets. Mesoscale relationships were analysed for seven physical variables (latitude, longitude, SST, SST frontal energy, temporal changes in SST (ΔSST), SST frontal energy (ΔSST frontal energy) and bathymetry), all of which may affect the availability of swordfish and blue shark to the fishery, and three variables (number of lightsticks per hook, lunar index, and wind velocity) which may relate to the effectiveness of the fishing gear. Longline CPUE data were analysed in relation to SST data on three spatiotemporal scales (18 km weekly, 1°-weekly, 1°-monthly). Depending on the scale of SST data, GAM analysis accounted for 39–42% and 44–45% of the variance in nominal CPUE for swordfish and blue shark, respectively. Stepwise GAM building revealed the relative importance of the variables in explaining the variance in CPUE. For swordfish, by decreasing importance, the variables ranked: (1) latitude, (2) time, (3) longitude, (4) lunar index, (5) lightsticks per hook, (6) SST, (7) ΔSST frontal energy, (8) wind velocity, (9) SST frontal energy, (10) bathymetry, and (11) ΔSST. For blue shark, the variables ranked: (1) latitude, (2) longitude, (3) time, (4) SST, (5) lightsticks per hook, (6) ΔSST, (7) ΔSST frontal energy, (8) SST frontal energy, (9) wind velocity, (10) lunar index, and (11) bathymetry. Swordfish CPUE increased with latitude to peak at 35–40°N and increased in the vicinity of temperature fronts and during the full moon. Shark CPUE also increased with latitude up to 40°N, and increased westward, but declined abruptly at SSTs colder than 16°C. As a comparison with modelling fishery performance in relation to specific environmental and fishery operational effects, fishery performance was also modelled as a function of categorical time (month) and area (2° squares) variables using a generalized linear model (GLM) approach. The variance accounted for by the GLMs was ≈ 1–3% lower than the variance explained by the GAMs. Time series of swordfish and blue shark CPUE standardized for the environmental and operational variables quantified in the GAM and for the time-area effects in the GLM are presented. For swordfish, both nominal and standardized time series indicate a decline in CPUE, whereas the opposite trend was seen for blue shark.     

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。     

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.     

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.     

Brown shrimp (Farfantepenaeus aztecus) density distribution in the Northern Gulf of Mexico: an approach using boosted regression trees

The estuarine‐dependent brown shrimp, Farfantepenaeus aztecus, is a significant commercial fishery and important species in the Gulf of Mexico (GOM) ecosystem as well as being a key component in energy transfer between benthic and pelagic food web systems. Because of the economical and ecological importance of brown shrimp, we developed a spatial population model to identify places of high shrimp density under a set of spatial, environmental and temporal variables in the Northern Gulf of Mexico (NGOM). We used fisheries‐independent data collected by the Southeast Area Monitoring and Assessment Program (SEAMAP) from 1992 to 2007 (summer and fall seasons). The relationship between the predictor variables and shrimp density was modeled using Boosted Regression Trees (BRT). Within the environmental variables included in the model, bottom type and depth of the water column were the most important predictors of shrimp density in the NGOM. Spatial predictions performed using the trained BRT model for summer and fall seasons showed a spatial segregation of shrimp density. During the summer, higher densities were predicted near the Texas and Louisiana coast and during the fall, higher densities were predicted further offshore. The model performed well and allowed successful prediction of brown shrimp hot spots in the NGOM. Model results allow fisheries managers to evaluate the potential impact from fisheries on the resource and to develop future fisheries management strategies, understand the biology of brown shrimp as well as assess the potential impacts of oil spills or climate change.     

Long‐term changes in recruitment of age‐0 Pacific bluefin tuna (Thunnus orientalis) and environmental conditions around Japan

Recruitment of age‐0 Pacific bluefin tuna (Thunnus orientalis) from 1952 to 2014 was examined by a sequential regime shift detection method. The regime shifts in recruitment were detected in 1957, 1972, 1980, 1994 and 2009. The durations of regime shift ranged from 8–15 years and averaged 13.0 years. In both the total (1952–2014) and data rich (1980–2014) periods, negative relationships were found between recruitment and the Pacific Decadal Oscillation in autumn, and positive relationships were found between recruitment and sea surface temperature (SST) anomalies in the northern part of the East China Sea, in the southwestern part of the Sea of Japan, and in the waters off Shikoku and Tokai in summer and autumn. The 1994 and 2009 regime shifts in recruitment occurred in the same years as shifts in SST anomalies in the northern part of the East China Sea in summer. These results suggest that the ocean conditions in the northern part of the East China Sea are closely related to recruitment of Pacific bluefin tuna, and that the warmer conditions result in higher recruitment of the species.     

Environmental modeling of occurrence of dolphinfish (Coryphaena spp.) in the Pacific Ocean off Mexico reveals seasonality in abundance,hot spots and migration patterns

Dolphinfish are little known migratory fish targeted by sport, artisanal and commercial fleets. In this study, we analyzed a 10 year database of incidental catches of the tuna purse seine fleet in the Pacific Ocean off Mexico with the aim to understand the environmental determinants of the spatial distribution and seasonal migration patterns of dolphinfish. We modeled the probability of occurrence of dolphinfish as a function of spatial (geographical coordinates), temporal (month/year) and environmental variables (sea surface temperature [SST], chlorophyll [CHL] and sea surface height [SSH], inferred from satellites) using logistic Generalized Additive Models. Dolphinfish preferred waters with SST values from 23 to 28°C, low (<0.2 mg/m³) CHL values, and primarily positive SSH values. Two dolphinfish hot spots were found in the study area: one in an oceanic zone (10°–15°N, 120°–125°W), which was more defined during spring, and one on the Pacific side of the Baja California Peninsula, which became important during summer. Models suggested that dolphinfish migrated through the study area following a “corridor” that ran from the Gulf of Tehuantepec along the Equatorial Upwelling zone to the oceanic hot spot zone, which in turn connected with the hot spot off the BCP. This “migratory corridor” went around the Eastern Pacific Warm Pool, which suggested that dolphinfish avoided this high temperature‐low production zone. Dolphinfish occupied zones close to certain oceanic features, such as eddies and thermal fronts. Results suggested that the primary cause of the biological hot spots was wind‐driven upwelling, because the hot spots became more important 3–4 months after the peak in upwelling activity.     

Improving the Color Shelf Life of Farmed Southern Bluefin Tuna (Thunnus maccoyii) Flesh with Dietary Supplements of Vitamins E and C and Selenium

ABSTRACT

The use of dietary antioxidants to increase the shelf life of farmed southern bluefin tuna (SBT) flesh was examined over a 10-week period using either a standard pellet (Control) or high-vitamin pellet (HV) fortified with vitamin E, vitamin C, and selenium. Following harvest, muscle samples were taken and assessed for antioxidant content. Flesh color shelf life was assessed in muscle stored at 4°C for 8 days. Muscle vitamin levels were significantly higher in the HV group than the Control group for vitamin E (20.4 ± 1.74 vs 9.7 ± 0.89 mg/kg) and vitamin C (29.1 ± 4.36 vs 4.3 ± 0.41 mg.kg^–1), but selenium levels were not higher. Muscle samples from the HV group had a slower rate of browning than did those from the Control group, particularly over days 4 to 7 of storage. Results indicated that feeding a diet approximately 10 times higher in dietary antioxidants raised levels of vitamin E and vitamin C, but not selenium, in tuna flesh and increased the shelf life of tuna.     

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.     

A dynamic optimisation model for the behaviour of tunas at ocean fronts

We present a model that simulates the foraging behaviour of tunas in the vicinity of ocean fronts. Stochastic dynamic programming is used to determine optimal habitat choice and swimming speed in relation to environmental variables (water temperature and clarity) and prey characteristics (abundance and energy density). By incorporating submodels for obligate physiological processes (gastric evacuation, standard and active metabolic costs) and sensory systems (visual feeding efficiency), we have integrated into a single fitness-based model many of the factors that might explain the aggregation of tunas at ocean fronts. The modelling technique describes fitness landscapes for all combinations of states, and makes explicit, testable predictions about time- and state-dependent behaviour. Enhanced levels of searching activity when hungry and towards the end of the day are an important feature of the optimal behaviour predicted. We consider the model to be particularly representative of the behaviour of the warm-water tunas or Neothunnus (e.g. skipjack, Katsuwonus pelamis , and yellowfin, Thunnus albacares ) and for surface-dwelling temperate tunas (e.g. young albacore, Thunnus alalunga ), which are often observed to aggregate near fronts. For the bluefin group (i.e. older albacore; northern and southern bluefin, Thunnus thynnus and Thunnus maccoyii ), for which extended vertical migrations are a significant and as yet unexplained component of behaviour, the model is able to reproduce observed behaviour by adopting the lower optimal temperature and standard metabolic rate of albacore. The model cannot explain why physiological differences exist between and within the different tuna species, but it does show how differences in susceptibility to thermal stress will permit different behaviour.