Trayectoria a largo plazo de algunas especies de Elasmobranquios en los mares de Toscana (Mediterráneo noroccidental) a través de 50 años de datos de captura

The time series of elasmobranch catch rates off the Tuscany coasts (NW Mediterranean) were investigated by means of min/max auto-correlation factor analysis in order to estimate variations in population abundance and evaluate the influence of environmental and anthropogenic factors. The analyses highlighted a general decreasing trend in the catch rates of sharks and skates from 1961 to the mid-1990s, mainly influenced by the increase in fishing effort. Since the 1990s, the EU Common Fishery Policy for the Mediterranean has promoted the reduction of fishing fleets through incentives to vessel demolition. The Porto S. Stefano trawl fleet has decreased by about 50%, leading to a decrease in fishing effort which seemed to be the most relevant factor affecting the increasing trend shown by the catch rates of Galeus melastomus, Scyliorhinus canicula and skates from 1991 to 2009. The elasmobranch assemblage did not undergo major shifts but the weighted frequency of occurrence shows that elasmobranchs were more frequent in the past. Particular caution should be paid in interpreting the recent rebound of some species as an early sign of recovery: trawl survey data and landing data show that over the last 50 years elasmobranch fauna have undergone a drastic decline and that recent rebounds are still far from a recovery to historical levels.Se investigaron las series históricas de datos de captura de algunas especies de Elasmobranquios en los mares de Toscana (Mediterráneo noroccidental), por medio del análisis de auto-correlación factorial MAFA, con el fin de evaluar las variaciones en la abundancia de poblaciones y la influencia de factores ambientales y antropogénicos. Los análisis permitieron poner en relieve una tendencia a la disminución, a partir de 1961 hasta la mitad de los años 1990, de las tasas de captura de las especies de tiburones y rayas demersales. Esta disminución parece ser debida principalmente al aumento del esfuerzo pesquero. Sin embargo, desde 1990 capacidad y actividad pesquera mostraron una tendencia a la disminución, como resultado de la Política Pesquera Común de la UE para el Mediterráneo. La flota de arrastre de Porto Santo Stefano disminuyó en un 50%; esta reducción parece ser el factor más importante que produjo un aumento en los indices de abundancia relativa de Galeus melastomus, Scyliorhinus canicula y de las rayas, desde 1991 a 2009. Sin embargo la composición en especies de los Elasmobranquios no ha mostrado evidentes cambios en el tiempo, a pesar de muchas especies que han sufrido una disminución en la frecuencia de occurrencia. Por lo tanto, la interpretación de estos resultados como señal de recuperación de las poblaciones de elasmobranquios, necesita de una precaución especial. De hecho durante los últimos 50 años la fauna de elasmobranquios en el Mediterráneo ha sufrido una drástica reducción y todavía no se está observando ninguna considerable señal de recuperación

Model based CFP indicators, F/Fmsy and SSB Mediterranean region case study

This work presents the application to Mediterranean stocks of a set of model-based indicators, being developed for monitoring the implementation of the Common Fisheries Policy (CFP). The work constitutes an application of the methodology, as such the results should not be used as representative of the CFP implementation in the Mediterranean. This document is mainly constituted of R code, showing how the indicators can be computed and presenting a set of diagnostics and stability tests. The models tested were a linear model, a linear mixed effects model with random intercept by stock, a GAMM with random intercept by stock and a GAMM with random intercept by Mediterranean GSA and species. The stability tests were designed to evaluate the estimates of recent (2003-2013) time series of trends in SSB and annual mean values of F/Fmsy. The results were presented to the STECF's 2015 winter plenary (STECF-PLEN-15-03).JRC.G.3-Maritime affair

Bioeconomic Modelling Applied to Fisheries with R/FLR/FLBEIA

The main objectives of the study presented in this report were to test the FLBEIA API, condition an operating model for the North Sea mixed fisheries and provide feedback on bioeconomic modelling limitations. Additionally, Fishrent and Fcube were also tested. FLR, FLBEIA, Fishrent and Fcube are software packages implemented by the scientific community studying fisheries to run bioeconomic models. A large test was carried out on FLBEIA by both running existing examples and trying to implement a bioeconomic model for the North Sea. In general the group felt FLBEIA is on the correct path to provide a bioeconomic modeling framework, although some work is still required. FLBEIA is not ready yet for production. A list of bugs and improvements was assembled. Conditioning a bioeconomic operating model for the North Sea showed the difficulties of merging economic and biological information. Inconsistencies on the effort definition seem to create additional problems when relating both sources of information. This subject must be further explored. The exercise was successful but data problems prevented the performance of a full economic analysis, although trend analysis on economic indicators for each scenario tested was possible. Nevertheless, these results must be taken carefully.JRC.G.4-Maritime affair

DEVELOPING NEW APPROACHES TO GLOBAL STOCK STATUS ASSESSMENT AND FISHERY PRODUCTION POTENTIAL OF THE SEAS

Stock status is a key parameter for evaluating the sustainability of fishery resources and developing corresponding management plans. However, the majority of stocks are not assessed, often as a result of insufficient data and a lack of resources needed to execute formal stock assessments. The working group involved in this publication focused on two approaches to estimating fisheries status: one based on single-stock status, and the other based on ecosystem production.JRC.G.4-Maritime affair

Effective fisheries management instrumental in improving fish stock status

Marine fish stocks are an important part of the world food system and are particularly important for many of the poorest people of the world. Most existing analyses suggest overfishing is increasing, and there is widespread concern that fish stocks are decreasing throughout most of the world. We assembled trends in abundance and harvest rate of stocks that are scientifically assessed, constituting half of the reported globalmarine fish catch. For these stocks, on average, abundance is increasing and is at proposed target levels. Compared with regions that are intensively managed, regions with less-developed fisheries management have, on average, 3-fold greater harvest rates and half the abundance as assessed stocks. Available evidence suggests that the regions without assessments of abundance have little fisheries management, and stocks are in poor shape. Increased application of area-appropriate fisheries science recommendations and management tools are still needed for sustaining fisheries in places where they are lacking.Fil: Hilborn, Ray. University of Washington; Estados UnidosFil: Amoroso, Ricardo Oscar. University of Washington; Estados UnidosFil: Anderson, Christopher M.. University of Washington; Estados UnidosFil: Baum, Julia K.. University of Victoria; CanadáFil: Branch, Trevor A.. University of Washington; Estados UnidosFil: Costello, Christopher. University of California at Santa Barbara; Estados UnidosFil: de Moor, Carryn L.. University of Cape Town; SudáfricaFil: Faraj, Abdelmalek. Einstitut National de Recherche Halieutique; MarruecosFil: Hively, Daniel. University of Washington; Estados UnidosFil: Jensen, Olaf P.. Rutgers University; Estados UnidosFil: Kurota, Hiroyuki. Japan Fisheries Research and Education Agency; JapónFil: Little, L. Richard. Csiro Oceans and Atmosphere; AustraliaFil: Mace, Pamela. Ministry for Primary Industries; Nueva ZelandaFil: McClanahan, Tim. Wildlife Conservation Society; Estados UnidosFil: Melnychuk, Michael C.. University of Washington; Estados UnidosFil: Minto, Cóilín. Galway-Mayo Institute of Technology; IrlandaFil: Osio, Giacomo Chato. Joint Research Centre (JRC); Italia. DG Maritime Affairs and Fisheries, European Commission; BélgicaFil: Pons, Maite. University of Washington; Estados UnidosFil: Parma, Ana María. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Centro Nacional Patagónico. Centro para el Estudio de Sistemas Marinos; ArgentinaFil: Segurado, Susana. Sustainable Fisheries Partnership; Estados UnidosFil: Szuwalski, Cody S.. University of California at Santa Barbara; Estados UnidosFil: Wilson, Jono R.. University of California at Santa Barbara; Estados Unidos. The Nature Conservancy; Estados UnidosFil: Ye, Yimin. Food and Agriculture Organization of the United Nations; Itali

Improving estimates of population status and trend with superensemble models

Fishery managers must often reconcile conflicting estimates of population status and trend. Superensemble models, commonly used in climate and weather forecasting, may provide an effective solution. This approach uses predictions from multiple models as covariates in an additional "superensemble" model fitted to known data. We evaluated the potential for ensemble averages and superensemble models (ensemble methods) to improve estimates of population status and trend for fisheries. We fit four widely applicable data-limited models that estimate stock biomass relative to equilibrium biomass at maximum sustainable yield (B/BMSY). We combined these estimates of recent fishery status and trends in B/BMSY with four ensemble methods: an ensemble average and three superensembles (a linear model, a random forest and a boosted regression tree). We trained our superensembles on 5,760 simulated stocks and tested them with cross-validation and against a global database of 249 stock assessments. Ensemble methods substantially improved estimates of population status and trend. Random forest and boosted regression trees performed the best at estimating population status: inaccuracy (median absolute proportional error) decreased from 0.42 -0.56 to 0.32 -0.33, rank-order correlation between predicted and true status improved from 0.02 - 0.32 to 0.44 - 0.48 and bias (median proportional error) declined from - 0.22 - 0.31 to - 0.12 - 0.03. We found similar improvements when predicting trend and when applying the simulation-trained superensembles to catch data for global fish stocks. Superensembles can optimally leverage multiple model predictions; however, they must be tested, formed from a diverse set of accurate models and built on a data set representative of the populations to which they are applied

Assessment for All initiative(a4a) - Workshop on development of MSE algorithms with R/FLR/a4a

The a4a approach to Management Strategies Evaluation ( MSE ) is to develop a set of common methods and procedures to build a minimal standard MSE algorithm. This has the most common elements of both uncertainty and management options. Such a tool set should allow for the development of MSE simulations for many fisheries in an operational time frame. Between the 30th of January and the 3rd of February, in Ispra, Italy, the JRC organized a workshop on development of MSE algorithms with R/FLR/a4a. The workshop was a mix of hands-on coding and discussion/implementation of concepts associated with MSEs. The participants used the most recent version of the a4a MSE code, modularized the most important processes and developed their own version of several processes so that the MSE could model and test alternative management procedures to the one initially coded.JRC.D.2-Water and Marine Resource

Mapping EU fishing activities using ship tracking data

<p>Information and understanding of fishing activities at sea are fundamental components of marine knowledge and maritime situational awareness. Such information is important to fisheries science, public authorities and policy-makers. In this paper we introduce a first map at European scale of EU fishing activities extracted using Automatic Identification System ship tracking data. The resulting map is a density of points that identify fishing activities. A measure of the reliability of such information is also presented as a map of coverage reception capabilities.</p