Age and growth of the bigeye thresher shark, Alopias superciliosus, from the pelagic longline fisheries in the tropical northeastern Atlantic Ocean, determined by vertebral band counts

The bigeye thresher, Alopias supercilious, is commonly caught as bycatch in pelagic longline fisheries targeting swordfish. Little information is yet available on the biology of this species, however. As part of an ongoing study, observers sent aboard fishing vessels have been collecting set of information that includes samples of vertebrae, with the aim of investigating age and growth of A. supercilious. A total of 117 specimens were sampled between September 2008 and October 2009 in the tropical northeastern Atlantic, with specimens ranging from 101 to 242 cm fork length (FL) (176 to 407 cm total length). The A. supercilious vertebrae were generally difficult to read, mainly because they were poorly calcified, which is typical of Lamniformes sharks. Preliminary trials were carried out to determine the most efficient band enhancement technique for this species, in which crystal violet section staining was found to be the best methodology. Estimated ages in this sample ranged from 2 to 22 years for females and 1 to 17 years for males. A version of the von Bertalanffy growth model (VBGF) re-parameterised to estimate L(0), and a modified VBGF using a fixed L(0) were fitted to the data. The Akaike information criterion (AIC) was used to compare these models. The VBGF produced the best results, with the following parameters: L(inf) = 293 cm FL, k = 0.06 y(-1) and L(0) = 111 cm FL for females; L(inf) = 206 cm FL, k = 0.18 y(-1) and L(0) = 93 cm FL for males. The estimated growth coefficients confirm that A. supercilious is a slow-growing species, highlighting its vulnerability to fishing pressure. It is therefore urgent to carry out more biological research to inform fishery managers more adequately and address conservation issues.

Trends in NE Atlantic landings (southern Portugal): identifying the relative importance of fisheries and environmental variables

Time series of commercial landings from the Algarve (southern Portugal) from 1982 to 1999 were analyzed using min/max autocorrelation factor analysis (MAFA) and dynamic factor analysis (DFA). These techniques were used to identify trends and explore the relationships between the response variables (annual landings of 12 species) and explanatory variables [sea surface temperature, rainfall, an upwelling index, Guadiana river (south-east Portugal) flow, the North Atlantic oscillation, the number of licensed fishing vessels and the number of commercial fishermen]. Landings were more highly correlated with non-lagged environmental variables and in particular with Guadiana river flow. Both techniques gave coherent results, with the most important trend being a steady decline over time. A DFA model with two explanatory variables (Guadiana river flow and number of fishermen) and three common trends (smoothing functions over time) gave good fits to 10 of the 12 species. Results of other models indicated that river flow is the more important explanatory variable in this model. Changes in the mean flow and discharge regime of the Guadiana river resulting from the construction of the Alqueva dam, completed in 2002, are therefore likely to have a significant and deleterious impact on Algarve fisheries landings.

A multi-model approach to evaluate the role of environmental variability and fishing pressure in sardine fisheries

Understanding the fluctuations in population abundance is a central question in fisheries. Sardine fisheries is of great importance to Portugal and is data-rich and of primary concern to fisheries managers. In Portugal, sub-stocks of Sardina pilchardus (sardine) are found in different regions: the Northwest (IXaCN), Southwest (IXaCS) and the South coast (IXaS-Algarve). Each of these sardine sub-stocks is affected differently by a unique set of climate and ocean conditions, mainly during larval development and recruitment, which will consequently affect sardine fisheries in the short term. Taking this hypothesis into consideration we examined the effects of hydrographic (river discharge), sea surface temperature, wind driven phenomena, upwelling, climatic (North Atlantic Oscillation) and fisheries variables (fishing effort) on S. pilchardus catch rates (landings per unit effort, LPUE, as a proxy for sardine biomass). A 20-year time series (1989-2009) was used, for the different subdivisions of the Portuguese coast (sardine sub-stocks). For the purpose of this analysis a multi-model approach was used, applying different time series models for data fitting (Dynamic Factor Analysis, Generalised Least Squares), forecasting (Autoregressive Integrated Moving Average), as well as Surplus Production stock assessment models. The different models were evaluated, compared and the most important variables explaining changes in LPUE were identified. The type of relationship between catch rates of sardine and environmental variables varied across regional scales due to region-specific recruitment responses. Seasonality plays an important role in sardine variability within the three study regions. In IXaCN autumn (season with minimum spawning activity, larvae and egg concentrations) SST, northerly wind and wind magnitude were negatively related with LPUE. In IXaCS none of the explanatory variables tested was clearly related with LPUE. In IXaS-Algarve (South Portugal) both spring (period when large abundances of larvae are found) northerly wind and wind magnitude were negatively related with LPUE, revealing that environmental effects match with the regional peak in spawning time. Overall, results suggest that management of small, short-lived pelagic species, such as sardine quotas/sustainable yields, should be adapted to a regional scale because of regional environmental variability.