Résumé: Pelagic sharks are an important bycatch in pelagic fisheries, especially for drifting longlines targeting swordfish. In the Cabo Verde Archipelago (tropical NE Atlantic), pelagic shark catches can reach a significant proportion of the total catches. Due to the increased concern on the status of pelagic shark species, this study was developed to enhance the current knowledge of those sharks in the Cabo Verde region in comparison to the adjacent areas, especially associated with European Union (EU) pelagic longline fishing activity. Stock status indicators for the two main species, blue shark (Prionace glauca) and shortfin mako (Isurus oxyrinchus), were developed, based on fisheries data from logbooks and onboard scientific observers, including analysis of size frequency distributions and standardized catch-per-unit-of-effort (CPUE) indexes over time. The standardized CPUEs have been stable or increasing for both species in the past 10 years, indicating no signs of local depletion. In terms of sizes, the blue shark catch is composed mainly of adults, which can be a sign of a stable population. On the contrary, the catch of shortfin mako is composed mainly of juveniles, which in conjunction of a decrease of mean size might be a cause of concern, highlighting possible overfishing on the species in the region. Thirty satellite tags, 25 archival miniPATs and 5 SPOT GPS, were deployed in the Cabo Verde Exclusive Economic Zone (EEZ), showing that those species are highly mobile. The biomass and size distributions were modeled with spatial and seasonal models (GAMs) identifying locations where juveniles are predominantly concentrated and that should be prioritized for conservation. This work presents new information on the status of pelagic sharks in the Cabo Verde region in the context of those highly migratory species, and can now be used to promote more sustainable fisheries in the region.

Résumé: Effective ocean management and the conservation of highly migratory species depend on resolving the overlap between animal movements and distributions, and fishing effort. However, this information is lacking at a global scale. Here we show, using a big-data approach that combines satellite-tracked movements of pelagic sharks and global fishing fleets, that 24% of the mean monthly space used by sharks falls under the footprint of pelagic longline fisheries. Space-use hotspots of commercially valuable sharks and of internationally protected species had the highest overlap with longlines (up to 76% and 64%, respectively), and were also associated with significant increases in fishing effort. We conclude that pelagic sharks have limited spatial refuge from current levels of fishing effort in marine areas beyond national jurisdictions (the high seas). Our results demonstrate an urgent need for conservation and management measures at high-seas hotspots of shark space use, and highlight the potential of simultaneous satellite surveillance of megafauna and fishers as a tool for near-real-time, dynamic management.

Résumé: Depredation in marine ecosystems is defined as the damage or removal of fish or bait from fishing gear by predators. Depredation raises concerns about the conservation of species involved, fisheries yield and profitability, and reference points based on stock assessment of depredated species. Therefore, the development of accurate indicators to assess the impact of depredation is needed. Both the Reunion Island and the Seychelles archipelago pelagic longline fisheries targeting swordfish (Xiphias gladius) and tuna (Thunnus spp.) are affected by depredation from toothed whales and pelagic sharks. In this study, we used fishery data collected between 2004 and 2015 to propose depredation indicators and to assess depredation levels in both fisheries. For both fisheries, the interaction rate (depredation occurrence) was significantly higher for shark compared to toothed whale depredation. However, when depredation occurred, toothed whale depredation impact was significantly higher than shark depredation impact, with higher depredation per unit effort (number of fish depredated per 1000 hooks) and damage rate (proportion of fish depredated per depredated set). The gross depredation rate in the Seychelles was 18.3%. A slight increase of the gross depredation rate was observed for the Reunion Island longline fleet from 2011 (4.1% in 2007–2010 and 4.4% in 2011–2015). Economic losses due to depredation were estimated by using these indicators and published official statistics. A loss of 0.09 EUR/hook due to depredation was estimated for the Reunion Island longline fleet, and 0.86 EUR/hook for the Seychelles. These results suggest a southward decreasing toothed whale and shark depredation gradient in the southwest Indian Ocean. Seychelles depredation levels are among the highest observed in the world revealing this area as a “hotspot” of interaction between pelagic longline fisheries and toothed whales. This study also highlights the need for a set of depredation indicators to allow for a global comparison of depredation rates among various fishing grounds worldwide.

Résumé: Productivity and Susceptibility Analysis (PSA) is a methodology for evaluating the vulnerability of a stock based on its biological productivity and susceptibility to fishing. In this study, we evaluated the vulnerability of 60 stocks of tuna, billfishes and other teleosts caught by the tuna longline fleets operating in the South Atlantic and Indian Ocean using a semi-quantitative PSA. We (a) evaluated the vulnerability of the species in the study areas; (b) compared the vulnerability of target and non-target species and oceans; (c) analyzed the sensitivity of data entry; and (d) compared the results of the PSA to other fully quantitative assessment methods. Istiophoridae exhibited the highest scores for vulnerability. The top 10 species at risk were: Atlantic Istiophorus albicans; Indian Ocean Istiompax indica; Atlantic Makaira nigricans and Thunnus alalunga; Indian Ocean Xiphias gladius; Atlantic T. albacares, Gempylus serpens, Ranzania laevis and X. gladius; and Indian Ocean T. alalunga. All species considered at high risk were targeted or were commercialized bycatch, except for the Atlantic G. serpens and R. laevis which.were discarded, and may be considered as a false positive. Those species and others at high risk should be prioritized for further assessment and/or data collection. Most species at moderate risk were bycatch species kept for sale. Conversely, species classified at low risk were mostly discarded. Overall, species at high risk were overfished and/or subjected to overfishing. Moreover, all species considered to be within extinction risk (Critically Endangered, Endangered and Vulnerable) were in the high risk category. The good concordance between approaches corroborates the results of our analysis. PSA is not a replacement for traditional stock assessments, where a stock is assessed at regular intervals to provide management advice. It is of importance, however, where there is uncertainty about catches and life history parameters, since it can identify species at risk, and where management action and data collection is required, e.g. for many species at high and most at moderate risk in the South Atlantic and Indian oceans.

Résumé: The identification and mitigation of adverse effects of the bycatch of tuna longline fishery have been mainly developed and implemented for seabirds, sharks and turtles and, the knowledge on teleost bycatch for this fishery, remains very poor. This paper contributes to a comprehensive assessment of life history traits and fishery attributes of target and bycatch species caught by the tuna longline fishery in the South Atlantic and Indian Oceans. Data was compiled on seven life history traits and three fishery attributes for 33 and 27 teleost stocks caught by longliners in South Atlantic and Indian Oceans, respectively. In addition, each species was assigned into four categories describing the fate of the catch: target species for commercial use, bycatch species kept for consumption, bycatch species kept for commercial use and discarded bycatch. Life history traits and fishery attributes did not differ between oceans. However, non-target but commercialized species were smaller in the Atlantic Ocean. Teleosts caught by the tuna longline fishery was segregated into three main groups: (1) the fast growing species represented mainly by dolphinfishes (Coryphaena hippurus and C. equisellis), skipjack tuna (Katsuwonus pelamis), kawakawa (Euthynnus affinis), bullet tuna (Auxis rochei), snoek (Thyrsites atun) and blackfin tuna (Thunnus atlanticus); (2) target tunas and most other bycatch species which were part of an intermediate group and (3) billfishes including swordfish representing the large and slow growing species with moderate to high market values and unknown or highly uncertain stock status. Investment in some key life history traits (such as growth coefficient) and the development of quantitative or semi-quantitative approaches (stock assessment and Ecological Risk Assessment) should be priorized as precautionary management measures for these species.

Résumé: A combination of fisheries dependent and independent data was used to assess the vulnerability of the oceanic whitetip shark to pelagic longline fisheries. The Brazilian tuna longline fleet, operating in the equatorial and southwestern Atlantic, is used as a case study. Fisheries dependent data include information from logbooks (from 1999 to 2011) and on-board observers (2004 to 2010), totaling 65,277 pelagic longline sets. Fisheries independent data were obtained from 8 oceanic whitetip sharks tagged with pop-up satellite archival tags in the area where longline fleet operated. Deployment periods varied from 60 to 178 days between 2010 and 2012. Tagging and pop-up sites were relatively close to each other, although individuals tended to travel long distances before returning to the tagging area. Some degree of site fidelity was observed. High utilization hotspots of tagged sharks fell inside the area under strongest fishing pressure. Despite the small sample size, a positive correlation between tag recorded information and catch data was detected. All sharks exhibited a strong preference for the warm and shallow waters of the mixed layer, spending on average more than 70% of the time above the thermocline and 95% above 120 m. Results indicate that the removal of shallow hooks on longline gear might be an efficient mitigation measure to reduce the bycatch of this pelagic shark species. The work also highlights the potential of tagging experiments to provide essential information for the development of spatio-temporal management measures.

Résumé: We investigated the diversity and distribution of two communities, micronekton organisms and large predatory fishes, sampled in mesoscale features of the Mozambique Channel from 2003 to 2009, by combining mid-water trawls, stomach contents of fish predators and instrumented longline fishing surveys. The highest species richness for assemblages was found in divergences and fronts rather than in the core of eddies. Despite an unbalanced scheme, diversity indices did not differ significantly between cyclonic and anticyclonic eddies, divergences and fronts. We found that eddies and associated physical cues did not substantially affect the distribution of micronektonic species which are mainly driven by the diel vertical migration pattern. Top predators exhibited a more complex response. Swordfish (Xiphias gladius) associated better with mesoscale features than tunas, with a clear preference for divergences which is consistent with the diel vertical migrations and occurrence of its main prey, the flying squids Sthenoteuthis oualaniensis (Ommastrephidae). On the other hand, the probability of presence of yellowfin tuna was not tied to any specific eddy structure. However, the highest values of positive yellowfin CPUEs were associated with low horizontal gradients of sea-level anomalies. We also showed a non-linear response of positive yellowfin CPUEs with respect to the depth of the minimal oxygen content. The larger the distance between the hooks and the minimal oxygen layer, towards the surface or at greater depths, the higher the CPUE, highlighting that yellowfin congregated in well-oxygenated waters. Micronekton sampled by mid-water trawls and stomach contents exhibited different species composition. The highly mobile organisms were not caught by trawling whereas they remain accessible to predators. The combination of stomach contents and mid-water trawls undoubtedly improved our understanding of the micronekton assemblage distribution. Our results provide some evidence that mesoscale features in the Mozambique Channel do not strongly affect the distribution of the mid-trophic level organisms such as micronekton and most of the large predatory fishes, and hypotheses are proposed to support this result.

Résumé: ABSTRACT: In the Indian Ocean, the blue shark Prionace glauca and the silky shark Carcharhinus falciformis represent the 2 main shark bycatch species in pelagic longline and purse seine fisheries, respectively. With the increasing market demand for fins, catches may increase in the future, with potential effects on ecosystem trophic functioning through top-down cascading effects. Knowledge of the species’ trophic ecology is therefore crucial but is limited by the lack of data from the Indian Ocean. Stable isotope analysis was therefore performed on muscle tissues (δ15N and δ13C) of these 2 shark species from the western Indian Ocean. Our study showed that body length, season, and zone effects were relatively small for the 2 species. However, significant δ13C differences between the 2 species suggest niche partitioning, with silky sharks having a more inshore foraging habitat than blue sharks. Finally, lower muscle δ15N values were observed in juvenile silky sharks caught by purse seiners around fish aggregating devices (FADs) compared to juveniles caught by longliners. One hypothesis is that FADs could act as an ecological trap for juvenile silky sharks, leading to a position at lowest trophic level for these individuals. However, different foraging habitats could also explain the observed patterns between juveniles. Although preliminary, our results provide a basis for the implementation of species-specific protection and management strategies.

Résumé: Historical longline catch per unit effort (CPUE) constitutes the major time series used in tuna stock assessment to followthe trend in abundance since the beginning of the large-scale tuna fisheries. The efficiency and species composition of a longline fishing operations essentially depends on the overlap in the vertical and spatial distribution between hooks and species habitat. Longline catchability depends on the vertical distribution of hooks and the aim of our paper was to analyse principal factors affecting the deviation of observed longline hook depths from predicted values. Since observed hook depth is usually shallower than predicted, this deviation is called longline shoaling.We evaluate the accuracy of hook depth distribution estimated from a theoretical catenary model commonly used in longline CPUE standardizations. Temperature-depth recorders (TDRs) were deployed on baskets of a monitored longline. Mainline shapes and maximum fishing depths were similar to gear configurations commonly used to target both yellowfin and bigeye tuna by commercial longliners in the central part of the South Pacific Ocean. Our working hypothesis assumes that the maximum fishing depth reached by the mainline depends on the gear configuration (sag ratio, mainline length per basket), the fishing tactics (bearing of the setting) and environmental variables characterizing water mass dynamics (wind stress, current velocity and shear). Based on generalized additive models (GAMs) simple transformations are proposed to account for the non-linearity between the shoaling and explanatory variables. Then, generalized linear models (GLMs) were fit to model the effects of explanatory variables on the longline shoaling. Results indicated that the shoaling (absolute aswell as relative) was significantly influenced by (1) the shape of the mainline (i.e., the tangential angle), which is the strongest predictor, and (2) the current shear and the direction of setting. Geometric forcing (i.e. transverse versus in-line) between the environment and the longline set is shown for the first time from in situ experimental fishing data. Results suggest that a catenary model that does not take these factors into consideration provides a biased estimate of the vertical distribution of hooks and must be used with caution in CPUEs standardization methods. Since catchability varies in time and space we discuss how suitable data could be routinely collected onboard commercial fishing vessels in order to estimate longline catchability for stock assessments.
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