Fish demand and supply projections

It has been predicted that the global demand for fish for human consumption will increase by more than 50% over the next 15 years. The FAO has projected that the increase in supply will originate primarily from marine fisheries, aquaculture and to a lesser extent from inland fisheries, but with a commensurate price increase. However, there are constraints to increased production in both marine and inland fisheries, such as overfishing, overexploitation limited potential increase and environmental degradation due to industrialization. The author sees aquaculture as having the greatest potential for future expansion. Aquaculture practices vary depending on culture, environment, society amd sources of fish. Inputs are generally low-cost, ecologically efficient and the majority of aquaculture ventures are small-scale and family operated. In the future, advances in technology, genetic improvement of cultured species, improvement in nutrition, disease management, reproduction control and environmental management are expected along with opportunities for complimentary activities with agriculture, industrial and wastewater linkages. The main constraints to aquaculture are from reduced access to suitable land and good quality water due to pollution and habitat degradation. Aquaculture itself carries minimal potential for aquatic pollution. State participation in fisheries production has not proven to be the best way to promote the fisheries sector. The role of governments is increasingly seen as creating an environment for economic sectors to make an optimum contribution, through support in areas such as infrastructure, research, training and extension and a legal framework. The author feels that a holistic approach integrating the natural and social sciences is called for when fisheries policy is being examined.

Differences in Dolphin Mortality Rates in Night and Day Sets for the U.S. Eastern Tropical Pacific Tuna Purse Seine Fishery

Because dolphins sometimes travel with yellowfin tuna, Thunnus albacares, in the eastern tropical Pacific (ETP), purse seiners use the dolphins to locate and capture tuna schools. During the process of setting the purse seine nets, dolphins often become entangled and drown before they can be released. Data for the U.S. purse seine fleet in the ETP during 1979-88 show that dolphin mortality rates in sets made during the night are higher than mortality rates in sets made during the day. Even with efforts to reduce nightset mortality rates through the use of high intensity floodlights, night set mortality rates remain higher. The data are also used to simulate a regulation on the fishery aimed at eliminating night sets and show that dolphin mortality rates would decrease.

Building social and ecological resilience to climate change in Roviana, Solomon Islands: PASAP country activity for Solomon Islands: Brief review: climate change trends and projections for Solomon Islands

As part of the Australian Government’s International Climate Change Adaptation Initiative (ICCAI), the Pacific Adaptation Strategy Assistance Program (PASAP) aims to enhance the capacity of partner countries to assess key vulnerabilities and risks, formulate adaptation strategies and plans, mainstream adaptation into decision-making, and inform robust longterm national planning and decision-making in partner countries. The Department of Climate Change and Energy Efficiency contracted University of Queensland (UQ) and University of California, Santa Barbara (UCSB) to lead the project: “Building social and ecological resilience to climate change in Roviana, Solomon Islands” (2010-2012). Under this project The WorldFish Center was subcontracted to undertake outputs 5 and 6 of Objective three: (5) Review of climate change evidence and projections for the study area and (6) Vulnerability and adaptation assessment for the study area. This report addresses the first of these and comprises a desktop review of climate change evidence and projections for the study area.

Otimização global topográfica aplicada a problemas de otimização com restrições de igualdade e desigualdade

Os métodos de otimização que adotam condições de otimalidade de primeira e/ou segunda ordem são eficientes e normalmente esses métodos iterativos são desenvolvidos e analisados através da análise matemática do espaço euclidiano n-dimensional, o qual tem caráter local. Esses métodos levam a algoritmos iterativos que são usados para o cálculo de minimizadores globais de uma função não linear, principalmente não-convexas e multimodais, dependendo da posição dos pontos de partida. Método de Otimização Global Topográfico é um algoritmo de agrupamento, o qual é fundamentado nos conceitos elementares da teoria dos grafos, com a finalidade de gerar bons pontos de partida para os métodos de busca local, com base nos pontos distribuídos de modo uniforme no interior da região viável. Este trabalho tem como objetivo a aplicação do método de Otimização Global Topográfica junto com um método robusto e eficaz de direções viáveis por pontos-interiores a problemas de otimização que tem restrições de igualdade e/ou desigualdade lineares e/ou não lineares, que constituem conjuntos viáveis com interiores não vazios. Para cada um destes problemas, é representado também um hiper-retângulo compreendendo cada conjunto viável, onde os pontos amostrais são gerados.

On-line learning of mutually orthogonal subspaces for face recognition by image sets.

We address the problem of face recognition by matching image sets. Each set of face images is represented by a subspace (or linear manifold) and recognition is carried out by subspace-to-subspace matching. In this paper, 1) a new discriminative method that maximises orthogonality between subspaces is proposed. The method improves the discrimination power of the subspace angle based face recognition method by maximizing the angles between different classes. 2) We propose a method for on-line updating the discriminative subspaces as a mechanism for continuously improving recognition accuracy. 3) A further enhancement called locally orthogonal subspace method is presented to maximise the orthogonality between competing classes. Experiments using 700 face image sets have shown that the proposed method outperforms relevant prior art and effectively boosts its accuracy by online learning. It is shown that the method for online learning delivers the same solution as the batch computation at far lower computational cost and the locally orthogonal method exhibits improved accuracy. We also demonstrate the merit of the proposed face recognition method on portal scenarios of multiple biometric grand challenge.