Comparative Influence of Ocean Conditions on Yellowfin and Atlantic Bluefin Tuna Catch from Longlines in the Gulf of Mexico

Directed fishing effort for Atlantic bluefin tuna in the Gulf of Mexico (GOM), their primary spawning grounds in the western Atlantic, has been prohibited since the 1980s due to a precipitous decline of the spawning stock biomass. However, pelagic longlines targeted at other species, primarily yellowfin tuna and swordfish, continue to catch Atlantic bluefin tuna in the GOM as bycatch. Spatial and temporal management measures minimizing bluefin tuna bycatch in the GOM will likely become important in rebuilding the western Atlantic bluefin stock. In order to help inform management policy and understand the relative distribution of target and bycatch species in the GOM, we compared the spatiotemporal variability and environmental influences on the catch per unit effort (CPUE) of yellowfin (target) and bluefin tuna (bycatch). Catch and effort data from pelagic longline fisheries observers (1993–2005) and scientific tagging cruises (1998–2002) were coupled with environmental and biological data. Negative binomial models were used to fit the data for both species and Akaike's Information Criterion (corrected for small sample size) was used to determine the best model. Our results indicate that bluefin CPUE had higher spatiotemporal variability as compared to yellowfin CPUE. Bluefin CPUE increased substantially during the breeding months (March-June) and peaked in April and May, while yellowfin CPUE remained relatively high throughout the year. In addition, bluefin CPUE was significantly higher in areas with negative sea surface height anomalies and cooler sea surface temperatures, which are characteristic of mesoscale cyclonic eddies. In contrast, yellowfin CPUE was less sensitive to environmental variability. These differences in seasonal variability and sensitivity to environmental influences suggest that bluefin tuna bycatch in the GOM can be reduced substantially by managing the spatial and temporal distribution of the pelagic longline effort without substantially impacting yellowfin tuna catches

Reproductive Schedules in Southern Bluefin Tuna: Are Current Assumptions Appropriate?

Southern bluefin tuna (SBT) appear to comprise a single stock that is assumed to be both mixed across its distribution and having reproductive adults that are obligate, annual spawners. The putative annual migration cycle of mature SBT consists of dispersed foraging at temperate latitudes with migration to a single spawning ground in the tropical eastern Indian Ocean. Spawning migrations have been assumed to target two peaks in spawning activity; one in September-October and a second in February-March. SBT of sizes comparable to that of individuals observed on the spawning ground were satellite tagged in the Tasman Sea region (2003–2008) and demonstrated both migrations to the spawning grounds and residency in the Tasman Sea region throughout the whole year. All individuals undertaking apparent spawning migrations timed their movements to coincide with the second recognised spawning peak or even later. These observations suggest that SBT may demonstrate substantial flexibility in the scheduling of reproductive events and may even not spawn annually as currently assumed. Further, the population on the spawning grounds may be temporally structured in association with foraging regions. These findings provide new perspectives on bluefin population and spatial dynamics and warrant further investigation and consideration of reproductive schedules in this species

Spawning Behaviour and Post-spawning Migration Patterns of Atlantic Bluefin Tuna (Thunnus thynnus) Ascertained from Satellite Archival Tags

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Long-Term GPS Tracking of Ocean Sunfish Mola mola Offers a New Direction in Fish Monitoring

Satellite tracking of large pelagic fish provides insights on free-ranging behaviour, distributions and population structuring. Up to now, such fish have been tracked remotely using two principal methods: direct positioning of transmitters by Argos polar-orbiting satellites, and satellite relay of tag-derived light-level data for post hoc track reconstruction. Error fields associated with positions determined by these methods range from hundreds of metres to hundreds of kilometres. However, low spatial accuracy of tracks masks important details, such as foraging patterns. Here we use a fast-acquisition global positioning system (Fastloc GPS) tag with remote data retrieval to track long-term movements, in near real time and position accuracy of <70 m, of the world's largest bony fish, the ocean sunfish Mola mola. Search-like movements occurred over at least three distinct spatial scales. At fine scales, sunfish spent longer in highly localised areas with faster, straighter excursions between them. These ‘stopovers’ during long-distance movement appear consistent with finding and exploiting food patches. This demonstrates the feasibility of GPS tagging to provide tracks of unparalleled accuracy for monitoring movements of large pelagic fish, and with nearly four times as many locations obtained by the GPS tag than by a conventional Argos transmitter. The results signal the potential of GPS-tagged pelagic fish that surface regularly to be detectors of resource ‘hotspots’ in the blue ocean and provides a new capability for understanding large pelagic fish behaviour and habitat use that is relevant to ocean management and species conservation

A Parsimonious Approach to Modeling Animal Movement Data

Animal tracking is a growing field in ecology and previous work has shown that simple speed filtering of tracking data is not sufficient and that improvement of tracking location estimates are possible. To date, this has required methods that are complicated and often time-consuming (state-space models), resulting in limited application of this technique and the potential for analysis errors due to poor understanding of the fundamental framework behind the approach. We describe and test an alternative and intuitive approach consisting of bootstrapping random walks biased by forward particles. The model uses recorded data accuracy estimates, and can assimilate other sources of data such as sea-surface temperature, bathymetry and/or physical boundaries. We tested our model using ARGOS and geolocation tracks of elephant seals that also carried GPS tags in addition to PTTs, enabling true validation. Among pinnipeds, elephant seals are extreme divers that spend little time at the surface, which considerably impact the quality of both ARGOS and light-based geolocation tracks. Despite such low overall quality tracks, our model provided location estimates within 4.0, 5.5 and 12.0 km of true location 50% of the time, and within 9, 10.5 and 20.0 km 90% of the time, for above, equal or below average elephant seal ARGOS track qualities, respectively. With geolocation data, 50% of errors were less than 104.8 km (<0.94°), and 90% were less than 199.8 km (<1.80°). Larger errors were due to lack of sea-surface temperature gradients. In addition we show that our model is flexible enough to solve the obstacle avoidance problem by assimilating high resolution coastline data. This reduced the number of invalid on-land location by almost an order of magnitude. The method is intuitive, flexible and efficient, promising extensive utilization in future research

Bayesian Estimation of Animal Movement from Archival and Satellite Tags

The reliable estimation of animal location, and its associated error is fundamental to animal ecology. There are many existing techniques for handling location error, but these are often ad hoc or are used in isolation from each other. In this study we present a Bayesian framework for determining location that uses all the data available, is flexible to all tagging techniques, and provides location estimates with built-in measures of uncertainty. Bayesian methods allow the contributions of multiple data sources to be decomposed into manageable components. We illustrate with two examples for two different location methods: satellite tracking and light level geo-location. We show that many of the problems with uncertainty involved are reduced and quantified by our approach. This approach can use any available information, such as existing knowledge of the animal's potential range, light levels or direct location estimates, auxiliary data, and movement models. The approach provides a substantial contribution to the handling uncertainty in archival tag and satellite tracking data using readily available tools

Investigating Behaviour and Population Dynamics of Striped Marlin (Kajikia audax) from the Southwest Pacific Ocean with Satellite Tags

Behaviour and distribution of striped marlin within the southwest Pacific Ocean were investigated using electronic tagging data collected from 2005–2008. A continuous-time correlated random-walk Kalman filter was used to integrate double-tagging data exhibiting variable error structures into movement trajectories composed of regular time-steps. This state-space trajectory integration approach improved longitude and latitude error distributions by 38.5 km and 22.2 km respectively. Using these trajectories as inputs, a behavioural classification model was developed to infer when, and where, ‘transiting’ and ‘area-restricted’ (ARB) pseudo-behavioural states occurred. ARB tended to occur at shallower depths (108±49 m) than did transiting behaviours (127±57 m). A 16 day post-release period of diminished ARB activity suggests that patterns of behaviour were affected by the capture and/or tagging events, implying that tagged animals may exhibit atypical behaviour upon release. The striped marlin in this study dove deeper and spent greater time at ≥200 m depth than those in the central and eastern Pacific Ocean. As marlin reached tropical latitudes (20–21°S) they consistently reversed directions, increased swimming speed and shifted to transiting behaviour. Reversals in the tropics also coincided with increases in swimming depth, including increased time ≥250 m. Our research provides enhanced understanding of the behavioural ecology of striped marlin. This has implications for the effectiveness of spatially explicit population models and we demonstrate the need to consider geographic variation when standardizing CPUE by depth, and provide data to inform natural and recreational fishing mortality parameters

Genetic Structure of Bluefin Tuna in the Mediterranean Sea Correlates with Environmental Variables

Abstract Background Atlantic Bluefin Tuna (ABFT) shows complex demography and ecological variation in the Mediterranean Sea. Genetic surveys have detected significant, although weak, signals of population structuring; catch series analyses and tagging programs identified complex ABFT spatial dynamics and migration patterns. Here, we tested the hypothesis that the genetic structure of the ABFT in the Mediterranean is correlated with mean surface temperature and salinity. Methodology We used six samples collected from Western and Central Mediterranean integrated with a new sample collected from the recently identified easternmost reproductive area of Levantine Sea. To assess population structure in the Mediterranean we used a multidisciplinary framework combining classical population genetics, spatial and Bayesian clustering methods and a multivariate approach based on factor analysis. Conclusions FST analysis and Bayesian clustering methods detected several subpopulations in the Mediterranean, a result also supported by multivariate analyses. In addition, we identified significant correlations of genetic diversity with mean salinity and surface temperature values revealing that ABFT is genetically structured along two environmental gradients. These results suggest that a preference for some spawning habitat conditions could contribute to shape ABFT genetic structuring in the Mediterranean. However, further studies should be performed to assess to what extent ABFT spawning behaviour in the Mediterranean Sea can be affected by environmental variation.(undefined

Distribution and Habitat Associations of Billfish and Swordfish Larvae across Mesoscale Features in the Gulf of Mexico

Ichthyoplankton surveys were conducted in surface waters of the northern Gulf of Mexico (NGoM) over a three-year period (2006–2008) to determine the relative value of this region as early life habitat of sailfish (Istiophorus platypterus), blue marlin (Makaira nigricans), white marlin (Kajikia albida), and swordfish (Xiphias gladius). Sailfish were the dominant billfish collected in summer surveys, and larvae were present at 37.5% of the stations sampled. Blue marlin and white marlin larvae were present at 25.0% and 4.6% of the stations sampled, respectively, while swordfish occurred at 17.2% of the stations. Areas of peak production were detected and maximum density estimates for sailfish (22.09 larvae 1000 m−2) were significantly higher than the three other species: blue marlin (9.62 larvae 1000 m−2), white marlin (5.44 larvae 1000 m−2), and swordfish (4.67 larvae 1000 m−2). The distribution and abundance of billfish and swordfish larvae varied spatially and temporally, and several environmental variables (sea surface temperature, salinity, sea surface height, distance to the Loop Current, current velocity, water depth, and Sargassum biomass) were deemed to be influential variables in generalized additive models (GAMs). Mesoscale features in the NGoM affected the distribution and abundance of billfish and swordfish larvae, with densities typically higher in frontal zones or areas proximal to the Loop Current. Habitat suitability of all four species was strongly linked to physicochemical attributes of the water masses they inhabited, and observed abundance was higher in slope waters with lower sea surface temperature and higher salinity. Our results highlight the value of the NGoM as early life habitat of billfishes and swordfish, and represent valuable baseline data for evaluating anthropogenic effects (i.e., Deepwater Horizon oil spill) on the Atlantic billfish and swordfish populations