Total marine fisheries catches within the exclusive economic zone of the Canary Islands, Spain, were reconstructed to include catches from the various small-scale artisanal fleets and their discards, as well as subsistence, recreational and other unreported catch. Total reconstructed catch was estimated at 38600 t in 1950, increasing to 81200 t in 1985, declining to approximately 43700 t year–1 in the early 2000s, and finally spiking to about 65300 t year–1 by the late 2000s. These catches coincide with a severe depletion of fish stocks, especially those of demersal species, due in part to fishing overcapacity in the artisanal sector, despite attempts to limit effort by the government. Spain only started to report catches to the FAO in 2006, and from 2006 to 2010 reconstructed catch was seven times the reported catch. Nearly 70% of this catch was from the recreational fishing sector, due in part to technological advancements and increased investments in the construction and improvement of secondary ports.

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A secure and high-quality operation of power grids requires frequency to be managed to keep it stable around a reference value. The deviation of the frequency from this reference value is caused by the imbalance between the active power produced and consumed. In the Smart Grid paradigm, the balance can be achieved by adjusting the demand to the production constraints, instead of the other way round. In this paper, an swarm intelligence-based approach for frequency management is proposed. It is grounded on the idea that a swarm is composed of decentralised individual agents (particles) and that each of them interacts with other ones via a shared environment. Three swarm intelligence-based policies ensure a decentralised frequency management in the smart power grid, where agents of swarm are making decisions and acting on the demand side. Policies differ in behaviour function of agents. Finally, these policies are evaluated and compared using indicators that point out their advantages.

In several cities, bus rapid transit (BRT) systems have begun to experience problems of capacity. Various solutions have been proposed to address these problems, from simple operational modifications to improvements that require modification of the existing infrastructure. Decisions about modification are a challenging undertaking for policy makers; proposals need to be evaluated on the basis of costs (monetary and qualitative or unconventional) and expected returns. For this paper, seven scenarios for Line 1 of the BRT system in Mexico City, Mexico, were structured and modeled to evaluate how operational and level of service improve as a result of (a) operational modifications, (b) investments in infrastructure, and (c) technology acquisitions. Scenarios were modeled by using the simulation tool EMBARQ SimBRT and were ranked by the relative complexity of their execution. Three criteria were used for determining the level of complexity: the cost of implementation, the required time, and the administrative process. Results of the scenarios show positive impacts on operation and level-of-service indicators. The paper also reveals that better results are obtained for implementations requiring infrastructure investment than for those involving operational modifications. However, the impact of the proposed implementation is limited; few implementations show progress on the analyzed indicators in a range of 10% variation, giving evidence of the difficulties of improving service. Finally, the paper provides important insights in the decision-making process for transport upgrading, as it describes a methodology to select a proposed improvement on the basis of tradeoff between expected benefits and required administrative process and financial costs.