Marine protected areas and small-scale fisheries in South Africa: promoting governance, participation, equity and benefit sharing

This monograph studies the progress achieved by conservation partners in South Africa on the implementation of the Convention on Biological Diversity (CBD) Programme Element Two components of governance, participation, equity and benefit sharing, from the perspective of small-scale fishing communities. It explores the strategies and mechanisms used by different authorities to create the conditions whereby local communities can benefit from marine protected areas (MPAs), of which South Africa has gazetted 24, highlighting examples of best practice. The monograph will be useful for researchers, scientists, fishworker organizations, environmentalists and anyone interested in the protection of marine biodiversity and the promotion of sustainable fisheries management.

Online multiple classifier boosting for object tracking

This paper presents a new online multi-classifier boosting algorithm for learning object appearance models. In many cases the appearance model is multi-modal, which we capture by training and updating multiple strong classifiers. The proposed algorithm jointly learns the classifiers and a soft partitioning of the input space, defining an area of expertise for each classifier. We show how this formulation improves the specificity of the strong classifiers, allowing simultaneous location and pose estimation in a tracking task. The proposed online scheme iteratively adapts the classifiers during tracking. Experiments show that the algorithm successfully learns multi-modal appearance models during a short initial training phase, subsequently updating them for tracking an object under rapid appearance changes. © 2010 IEEE.

A study on rural women's empowerment through participation in aquaculture

The study was undertaken to understand the rural women's (i) extent of participation in some selected aquaculture practices and (ii) extent of empowerment through participation in aquaculture program. Data were collected from 200 selected rural women of two districts - Sherpur and Kishoreganj. Each of the families where the selected rural women who were involved in aquaculture under the supervision of two partner NGOs of DSAP, namely- Foundation for Human Development (FHD) and Center for Rural and Environmental Development (CRED). Both conventional and participatory methods of data collection were employed where structured questionnaire and Focus Group Discussion (FGD) were used as the tools. The data collection procedure took five-months spanning from September 2004 to January 2005. Appropriate scales were developed and used in order to determine the focus variables of the study, while most analyses regarding women empowerment were done using 'before' and 'after' method. Empowerment of women was measured by five dimensions such as decision making ability, spending ability, social participation, cosmopoliteness, access to assets and resources. The ten selected aquaculture practices were: fish feeding, eradication of aquatic vegetation from fish pond, disease detection, application of fertilizer, liming, harvesting of fry and fish, fish stock management, pond excavation, use of insecticides, and sale of fry and fish. The study also aimed at determining some selected characteristics of rural women and determining relationship between their extent of empowerment and the selected characteristics. The characteristics of rural women included: age, personal education, average family education, family size, family farm size, area under aquaculture, extension media exposure, training exposure, knowledge in aquaculture, and family income. The findings revealed an overall low level of participation by rural women in aquaculture activities. However, significant level of improvement was identified regarding overall status of empowerment during the course of participation in aquaculture program under DSAP.

Enhancement of fish production in a reservoir after partitioning by dikes through community participation

A reservoir of 70 acres was portioned by dikes into four manageable big ponds to get more production of fishes at Basurhat, Noakhali, Bangladesh under the supervision of local community through a society of 40 people ownership. Pangus (Pangasius hypophthalmus) @ 20,000/acre, and then fry and fingerlings of different types of fishes such as catla (Catla catla), rohu (Labeo rohita), mrigal (Cirrhina mrigala), grass carp (Ctenophmyngodon idella), bighead (Aristichthys nobili), silver carp (Hypophthalmichthys molitrix), common carp (Cyprinus cmpio) and rajpunti (Puntius gonionatus) @ 500/acre were stocked. Feed containing 25% protein was used two times daily and feed was adjusted fortnightly. After 8 months, all the fishes were weighed 0.80-2.10 kg except rajpunti (150-200 g) and tilapia (150-220 g), and a total of 25 ton of fish was harvested which was five times higher than the previous production under signal ownership. The production of fishes were increased after partitioning the lake with dikes due to proper management and control.

Report of the MPA Atlas and the interactive online database portal of the Bay of Bengal Large Marine Ecosystem

This report describes the process and details of developing an interactive online database portal for the BOBLME region.The MPA (Marine Protected Area) Atlas website, created by WorldFish was designed to provide public access to the latest information relevant to marine scientists, managers and conservationists. The main features include; BOBLME MPA database;interactive geospatial maps;and information about important habitats such as coral reefs,BOBLME boundaries and bathymetry.

An Online Expectation-Maximization Algorithm for Changepoint Models

Changepoint models are widely used to model the heterogeneity of sequential data. We present a novel sequential Monte Carlo (SMC) online Expectation-Maximization (EM) algorithm for estimating the static parameters of such models. The SMC online EM algorithm has a cost per time which is linear in the number of particles and could be particularly important when the data is representable as a long sequence of observations, since it drastically reduces the computational requirements for implementation. We present an asymptotic analysis for the stability of the SMC estimates used in the online EM algorithm and demonstrate the performance of this scheme using both simulated and real data originating from DNA analysis.

An Online Expectation-Maximization Algorithm for Changepoint Models

Changepoint models are widely used to model the heterogeneity of sequential data. We present a novel sequential Monte Carlo (SMC) online Expectation-Maximization (EM) algorithm for estimating the static parameters of such models. The SMC online EM algorithm has a cost per time which is linear in the number of particles and could be particularly important when the data is representable as a long sequence of observations, since it drastically reduces the computational requirements for implementation. We present an asymptotic analysis for the stability of the SMC estimates used in the online EM algorithm and demonstrate the performance of this scheme using both simulated and real data originating from DNA analysis.

Forecasting high-frequency futures returns using online langevin dynamics

Forecasting the returns of assets at high frequency is the key challenge for high-frequency algorithmic trading strategies. In this paper, we propose a jump-diffusion model for asset price movements that models price and its trend and allows a momentum strategy to be developed. Conditional on jump times, we derive closed-form transition densities for this model. We show how this allows us to extract a trend from high-frequency finance data by using a Rao-Blackwellized variable rate particle filter to filter incoming price data. Our results show that even in the presence of transaction costs our algorithm can achieve a Sharpe ratio above 1 when applied across a portfolio of 75 futures contracts at high frequency. © 2011 IEEE.