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

Ten lessons on the resilience of the EU common fisheries policy towards climate change and fuel efficiency - A call for adaptive, flexible and well-informed fisheries management

To effectively future-proof the management of the European Union fishing fleets we have explored a suite of case studies encompassing the northeast and tropical Atlantic, the Mediterranean, Baltic and Black Seas. This study shows that European Union (EU) fisheries are likely resilient to climate-driven short-term stresses, but may be negatively impacted by long-term trends in climate change. However, fisheries' long-term stock resilience can be improved (and therefore be more resilient to increasing changes in climate) by adopting robust and adaptive fisheries management, provided such measures are based on sound scientific advice which includes uncertainty. Such management requires regular updates of biological reference points. Such updates will delineate safe biological limits for exploitation, providing both high long-term yields with reduced risk of stock collapse when affected by short-term stresses, and enhanced compliance with advice to avoid higher than intended fishing mortality. However, high resilience of the exploited ecosystem does not necessarily lead to the resilience of the economy of EU fisheries from suffering shocks associated with reduced yields, neither to a reduced carbon footprint if fuel use increases from lower stock abundances. Fuel consumption is impacted by stock development, but also by changes in vessel and gear technologies, as well as fishing techniques. In this respect, energy-efficient fishing technologies already exist within the EU, though implementing them would require improving the uptake of innovations and demonstrating to stakeholders the potential for both reduced fuel costs and increased catch rates. A transition towards reducing fuel consumption and costs would need to be supported by the setup of EU regulatory instruments. Overall, to effectively manage EU fisheries within a changing climate, flexible, adaptive, well-informed and well-enforced management is needed, with incentives provided for innovations and ocean literacy to cope with the changing conditions, while also reducing the dependency of the capture fishing industry on fossil fuels. To support such management, we provide 10 lessons to characterize 'win-win' fishing strategies for the European Union, which develop leverages in which fishing effort deployed corresponds to Maximum Sustainable Yield targets and Common Fisheries Policy minimal effects objectives. In these strategies, higher catch is obtained in the long run, less fuel is spent to attain the catch, and the fisheries have a higher resistance and resilience to shock and long-term factors to face climate-induced stresses

Experimental study of differentially rotating supersonic plasma flows produced by aluminium wire array Z-pinches

A novel approach to cylindrical wire array z-pinches has been developed in order to create a rotating plasma flow analogous to astrophysical accretion discs. The method involves subjecting the wire array to a cusp magnetic field (B_r) to create converging off axis ablation streams to form a rotating flow. The rotation is sustained by the ram pressure of the ablation streams in a quasi-equilibrium state for approximately 150 ns. This corresponds to one full rotation of the plasma about the axis. The rotating plasma is supersonic with Mach number ~2 and a radially constant rotation velocity between 60 and 75 km/s; the angular velocity therefore has an r^-1 dependence and the flow is differential. A Thomson scattering diagnostic is used to measure the electron and ion temperatures as Te ~30 eV and Ti >55 eV and the ionisation of the plasma (Z) between 6 and 8. These parameters are used to calculate the Reynolds number (10^5 to 10^6) and magnetic Reynolds numbers (20 to 100) which are large enough for viscous and resistive effects to be negligible on the large scale of the flow. These are of sufficient magnitude for the experiment to be scalable to astrophysical accretion discs. Further more the Reynolds number for the experiment is large enough for shear instabilities to manifest in the plasma. Some evidence for this can be seen in XUV images and Thomson spectra which indicate the development of perturbations and vorticity within the flow. Predictions for the growth rate of the Kelvin Helmholtz instability, 12 to 40 ns, agree reasonably well with the observed perturbation growth of ~30 ns. It is also possible that shear instabilities are driving hydrodynamic turbulence. Turbulent heating of the plasma could explain the approximately 500 eV increase in the ion temperature observed from some Thomson spectra. Further work is required however to prove the existence of shear flows and turbulence within the experiments.Open Acces

A stochastic programming model for the tertiary control of microgrids

In this thesis a scenario-based two-stage stochastic programming model is proposed to solve a microgrid's tertiary control optimization problem taking into account some renewable energy resource s uncertainty as well uncertain energy deviation prices in the electricity market. Scenario generation methods for wind speed realizations are also studied. Results show that the introduction of stochastic programming represents an improvement over a deterministic model

A stochastic programming model for the tertiary control of microgrids

In this thesis a scenario-based two-stage stochastic programming model is proposed to solve a microgrid's tertiary control optimization problem taking into account some renewable energy resource s uncertainty as well uncertain energy deviation prices in the electricity market. Scenario generation methods for wind speed realizations are also studied. Results show that the introduction of stochastic programming represents an improvement over a deterministic model

A stochastic programming model for the tertiary control of microgrids

In this thesis a scenario-based two-stage stochastic programming model is proposed to solve a microgrid's tertiary control optimization problem taking into account some renewable energy resource s uncertainty as well uncertain energy deviation prices in the electricity market. Scenario generation methods for wind speed realizations are also studied. Results show that the introduction of stochastic programming represents an improvement over a deterministic model

Uncertainty estimation and model selection in stock assessment models with non-parametric effects on fishing mortality

Uncertainty coming from assessment models leads to risk in decision making and ignoring or misestimating it can result in an erroneous management action. Some parameters, such as selectivity or survey catchabilities, can present a wide range of shapes and the introduction of smooth functions, which up to now have not been widely used in assessment models, allows for more flexibility to capture underlying nonlinear structures. In this work a simulation study emulating a sardine population is carried out to compare 3 different methods for uncertainty estimation: multivariate normal distribution, bootstrap (without and with bias correction) and Markov chain Monte Carlo (MCMC). In order to study their performance depending on the model complexity, five different scenarios are defined depending on the shape of the smooth function of the fishing mortality. From 100 simulated data sets, performance is measured in terms of point estimation, coefficients of variation, bias, skewness, coverage probabilities and correlation. In all approaches model fitting is carried out using the a4a framework. All three methods result in very similar performance. The main differences are found for observation variance parameters where the bootstrap and the multivariate normal approach result in underestimation of these parameters. In general MCMC is considered to have better performance, being able to detect skewness in posterior distributions, showing small bias and reaching expected coverage probabilities. It is also more efficient in terms of time consumption in comparison with bootstrapping.JRC.D.2-Water and Marine Resource

A stochastic programming model for the tertiary control of microgrids

In this work a scenario-based two-stage stochastic programming model is proposed to solve a microgrid’s tertiary control optimization problem taking into account some renewable energy resource’s uncertainty as well as uncertain energy deviation prices in the electricity market. Scenario generation methods for wind speed realizations are also studied. Results show that the introduction of stochastic programming represents a significant improvement over a deterministic model.Peer ReviewedPostprint (published version

A stochastic programming model for the tertiary control of microgrids

In this work a scenario-based two-stage stochastic programming model is proposed to solve a microgrid’s tertiary control optimization problem taking into account some renewable energy resource’s uncertainty as well as uncertain energy deviation prices in the electricity market. Scenario generation methods for wind speed realizations are also studied. Results show that the introduction of stochastic programming represents a significant improvement over a deterministic model.Peer Reviewe