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.
© 2008 Elsevier B.V. All rights reserved..

Résumé: Mercury (Hg) is a global threat for marine ecosystems, especially within the Mediterranean Sea. The concern is higher for deep-sea organisms, as the Hg concentration in their tissues is commonly high. To assess the influence of food supply at two trophic levels, total Hg concentrations and carbon and nitrogen stable isotope ratios were determined in 7 species (4 teleosts, 2 sharks, and 1 crustacean) sampled on the upper part of the continental slope of the Gulf of Lions (Northwestern Mediterranean Sea), at depths between 284 and 816 m. Mean Hg concentrations ranged from 1.30 ± 0.61 to 7.13 ± 7.09 μg g− 1 dry mass, with maximum values observed for small-spotted catshark Scyliorhinus canicula. For all species except blue whiting Micromesistius poutassou, Hg concentrations were above the health safety limits for human consumption defined by the European Commission, with a variable proportion of the individuals exceeding limits (from 23% for the Norway lobster Nephrops norvegicus to 82% for the blackbelly rosefish Helicolenus dactylopterus). Measured concentrations increased with increasing trophic levels. Carbon isotopic ratios measured for these organisms demonstrated that settling phytoplanktonic organic matter is not only the main source fueling trophic webs but also the carrier of Hg to this habitat. Inter- and intraspecific variations of Hg concentrations revealed the importance of feeding patterns in Hg bioaccumulation. In addition, biological parameters, such as growth rate or bathymetric range explain the observed contamination trends.

Résumé: Thanks to the availability of the MEDITS survey data, a standardized picture of the occurrence and abundance of demersal Chondrichthyes in the northern Mediterranean has been obtained. During the spring-summer period between 2012 and 2015, 41 Chondrichthyes, including 18 sharks (5 orders and 11 families). 22 batoids (3 orders and 4 families) and 1 chimaera, were detected from several geographical sub-areas (GSAs) established by the General Fisheries Commission for the Mediterranean. Batoids had a preferential distribution on the continental shelf (10-200 m depth). while shark species were more frequent on the slope (200-800 m depth). Only three species, the Carcharhiniformes Galeus melastomus and Scyliorhinus canicida and the Torpediniformes Torpedo matmorata were caught in all GSAs studied. On the continental shelf, the Rajidae family was the most abundant, being represented in primis by Raja clavaia and then by R. miraleius, R. polystigma and R. asterias. The slope was characterized by the prevalence of G. melastomus in all GSAs, followed by S. canictda, E. spinax and Squalus blainville. Areas under higher fishing pressure, such as the Adriatic Sea and the Spanish coast (with the exception of the Balearic Islands), show a low abundance of chondrichthyans, but other areas with a high level of fishing pressure, such as southwestern Sicily, show a high abundance, suggesting that other environmental drivers work together with fishing pressure to shape their distribution. Results of generalized additive models highlighted that depth is one of the most important environmental drivers influencing the distribution of both batoid and shark species, although temperature also showed a significant influence on their distribution. The approach explored in this work shows the possibility of producing maps modelling the distribution of demersal chondrichthyans in the Mediterranean that are useful for the management and conservation of these species at a regional scale. However, because of the vulnerability of these species to fishing exploitation, fishing pressure should be further incorporated in these models in addition to these environmental drivers.