Multi-species and multi-interest management: An ecosystem approach to market squid (Loligo opalescens) harvest in California

Market squid (Loligo opalescens) plays a vital role in the California ecosystem and serves as a major link in the food chain as both a predator and prey species. For over a century, market squid has also been harvested off the California coast from Monterey to San Pedro. Expanding global markets, coupled with a decline in squid product from other parts of the world, in recent years has fueled rapid expansion of the virtually unregulated California fishery. Lack of regulatory management, in combination with dramatic increases in fishing effort and landings, has raised numerous concerns from the scientific, fishing, and regulatory communities. In an effort to address these concerns, the National Oceanic and Atmospheric Administration’s (NOAA) Channel Islands National Marine Sanctuary (CINMS) hosted a panel discussion at the October 1997 California Cooperative Oceanic and Fisheries Investigations (CalCOFI) Conference; it focused on ecosystem management implications for the burgeoning market squid fishery. Both panel and audience members addressed issues such as: the direct and indirect effects of commercial harvesting upon squid biomass; the effects of harvest and the role of squid in the broader marine community; the effects of environmental variation on squid population dynamics; the sustainability of the fishery from the point of view of both scientists and the fishers themselves; and the conservation management options for what is currently an open access and unregulated fishery. Herein are the key points of the ecosystem management panel discussion in the form of a preface, an executive summary, and transcript. (PDF contains 33 pages.

Fisheries production systems, climate change and climate variability in West Africa: an annotated bibliography

This bibliography is intended for people who are involved in fisheries, aquaculture, climate change, disaster management and policy development in West Africa or interested in one or more of these issues. The literature in this bibliography includes peer-reviewed journals, books and book chapters, grey reports and institutional technical papers, but is restricted to literature in English. They were gathered through an extensive web search using fisheries, fish, coastal, inland, aquaculture and/or in combination with climate change and impacts, climate variability, specific country names, West Africa and Gulf of Guinea as the main keywords.Fisheries, Climatic change, Aquaculture, Inland fisheries, Bibliographies, Disasters, Africa, West,

What Is the Storage Effect, Why Should It Occur in Cancers, and How Can It Inform Cancer Therapy?

Intratumor heterogeneity is a feature of cancer that is associated with progression, treatment resistance, and recurrence. However, the mechanisms that allow diverse cancer cell lineages to coexist remain poorly understood. The storage effect is a coexistence mechanism that has been proposed to explain the diversity of a variety of ecological communities, including coral reef fish, plankton, and desert annual plants. Three ingredients are required for there to be a storage effect: (1) temporal variability in the environment, (2) buffered population growth, and (3) species-specific environmental responses. In this article, we argue that these conditions are observed in cancers and that it is likely that the storage effect contributes to intratumor diversity. Data that show the temporal variation within the tumor microenvironment are needed to quantify how cancer cells respond to fluctuations in the tumor microenvironment and what impact this has on interactions among cancer cell types. The presence of a storage effect within a patient’s tumors could have a substantial impact on how we understand and treat cancer

Path planning and collision avoidance for autonomous surface vehicles I: a review

Autonomous surface vehicles are gaining increasing attention worldwide due to the potential benefits of improving safety and efficiency. This has raised the interest in developing methods for path planning that can reduce the risk of collisions, groundings, and stranding accidents at sea, as well as costs and time expenditure. In this paper, we review guidance, and more specifically, path planning algorithms of autonomous surface vehicles and their classification. In particular, we highlight vessel autonomy, regulatory framework, guidance, navigation and control components, advances in the industry, and previous reviews in the field. In addition, we analyse the terminology used in the literature and attempt to clarify ambiguities in commonly used terms related to path planning. Finally, we summarise and discuss our findings and highlight the potential need for new regulations for autonomous surface vehicles

Effects of fishing during the spawning period: implications for management

Avoidance of fishing during the spawning season has been proposed as a contribution to achieving sustainable exploitation. Here we review the biological effects of fishing during the spawning period and explore their implication on sustainable management. A distinction will be made between direct mortality and indirect effects. The latter will review how fishery disturbance will affect the physiology and behaviour. Based on the results, a classification scheme is presented of the vulnerability for fisheries during the spawning period. Finally the implications for the population dynamics and fisheries management are discussed

An adaptive autopilot design for an uninhabited surface vehicle

An adaptive autopilot design for an uninhabited surface vehicle Andy SK Annamalai The work described herein concerns the development of an innovative approach to the design of autopilot for uninhabited surface vehicles. In order to fulfil the requirements of autonomous missions, uninhabited surface vehicles must be able to operate with a minimum of external intervention. Existing strategies are limited by their dependence on a fixed model of the vessel. Thus, any change in plant dynamics has a non-trivial, deleterious effect on performance. This thesis presents an approach based on an adaptive model predictive control that is capable of retaining full functionality even in the face of sudden changes in dynamics. In the first part of this work recent developments in the field of uninhabited surface vehicles and trends in marine control are discussed. Historical developments and different strategies for model predictive control as applicable to surface vehicles are also explored. This thesis also presents innovative work done to improve the hardware on existing Springer uninhabited surface vehicle to serve as an effective test and research platform. Advanced controllers such as a model predictive controller are reliant on the accuracy of the model to accomplish the missions successfully. Hence, different techniques to obtain the model of Springer are investigated. Data obtained from experiments at Roadford Reservoir, United Kingdom are utilised to derive a generalised model of Springer by employing an innovative hybrid modelling technique that incorporates the different forward speeds and variable payload on-board the vehicle. Waypoint line of sight guidance provides the reference trajectory essential to complete missions successfully. The performances of traditional autopilots such as proportional integral and derivative controllers when applied to Springer are analysed. Autopilots based on modern controllers such as linear quadratic Gaussian and its innovative variants are integrated with the navigation and guidance systems on-board Springer. The modified linear quadratic Gaussian is obtained by combining various state estimators based on the Interval Kalman filter and the weighted Interval Kalman filter. Change in system dynamics is a challenge faced by uninhabited surface vehicles that result in erroneous autopilot behaviour. To overcome this challenge different adaptive algorithms are analysed and an innovative, adaptive autopilot based on model predictive control is designed. The acronym ‘aMPC’ is coined to refer to adaptive model predictive control that is obtained by combining the advances made to weighted least squares during this research and is used in conjunction with model predictive control. Successful experimentation is undertaken to validate the performance and autonomous mission capabilities of the adaptive autopilot despite change in system dynamics.EPSRC (Engineering and Physical Sciences Research Council

A novel methodology for the assessment or wave energy opions at early stages

276 p.El aumento de la proporción de generación de electricidad a partir de fuentes renovables es clave para garantizar un sistema energético totalmente descarbonizado y luchar contra el cambio climático. La energía undimotriz es un recurso abundante pero, al mismo tiempo, es la menos desarrollada de todas las tecnologías renovables. El marco de evaluación común desarrollado en la tesis se basa en principios sólidos de ingeniería de sistemas y abarca el contexto externo, los requisitos del sistema y los criterios de evaluación. Se puede aplicar a diferentes niveles de madurez tecnológica y capta los aspectos cualitativos relacionados con las expectativas de las partes interesadas. El enfoque novedoso guía las decisiones de diseño a lo largo del proceso de desarrollo para la gestión adecuada del riesgo y la incertidumbre, y facilita la selección y evaluación comparativa de la tecnología undimotriz a diferentes niveles de madurez de manera controlada. Los métodos propuestos en esta investigación brindan información valiosa para enfocar los esfuerzos de innovación en aquellas áreas que tienen la mayor influencia en el desempeño de la tecnología. La incorporación de estrategias de innovación eficaces en el desarrollo de la energía undimotriz ayuda a gestionar la complejidad del sistema y canalizar la innovación hacia mejoras útiles.Tecnali

Robust Path Following on Rivers Using Bootstrapped Reinforcement Learning

This paper develops a Deep Reinforcement Learning (DRL)-agent for navigation and control of autonomous surface vessels (ASV) on inland waterways. Spatial restrictions due to waterway geometry and the resulting challenges, such as high flow velocities or shallow banks, require controlled and precise movement of the ASV. A state-of-the-art bootstrapped Q-learning algorithm in combination with a versatile training environment generator leads to a robust and accurate rudder controller. To validate our results, we compare the path-following capabilities of the proposed approach to a vessel-specific PID controller on real-world river data from the lower- and middle Rhine, indicating that the DRL algorithm could effectively prove generalizability even in never-seen scenarios while simultaneously attaining high navigational accuracy