Bayesian ranking and selection of fishing boat efficiencies

The steadily accumulating literature on technical efficiency in fisheries attests to the importance of efficiency as an indicator of fleet condition and as an object of management concern. In this paper, we extend previous work by presenting a Bayesian hierarchical approach that yields both efficiency estimates and, as a byproduct of the estimation algorithm, probabilistic rankings of the relative technical efficiencies of fishing boats. The estimation algorithm is based on recent advances in Markov Chain Monte Carlo (MCMC) methods—Gibbs sampling, in particular—which have not been widely used in fisheries economics. We apply the method to a sample of 10,865 boat trips in the US Pacific hake (or whiting) fishery during 1987–2003. We uncover systematic differences between efficiency rankings based on sample mean efficiency estimates and those that exploit the full posterior distributions of boat efficiencies to estimate the probability that a given boat has the highest true mean efficiency.

Fine root biomass and turnover in southern taiga estimated by root inclusion nets

Fine roots play an important part in forest carbon, nutrient and water cycles. The turnover of fine roots constitutes a major carbon input to soils. Estimation of fine root turnover is difficult, labour intensive and is often compounded by artefacts created by soil disturbance. In this work, an alternative approach of using inclusion nets installed in an undisturbed soil profile was used to measure fine root production and was compared to the in-growth core method. There was no difference between fine root production estimated by the two methods in three southern taiga sites with contrasting soil conditions and tree species composition in the Central Forest State Biosphere Reserve, Russia. Expressed as annual production over standing biomass, Norway spruce fine root turnover was in the region of 0.10 to 0.24 y-1. The inclusion net technique is suitable for field based assessment of fine root production. There are several advantages over the in-growth core method, due to non-disturbance of the soil profile and its potential for very high rate of replication.

Weightless neural nets for face recognition: a comparison

This paper considers the application of weightless neural networks (WNNs) to the problem of face recognition and compares the results with those provided using a more complicated multiple neural network approach. WNNs have significant advantages over the more common forms of neural networks, in particular in term of speed of operation and learning. A major difficulty when applying neural networks to face recognition problems is the high degree of variability in expression, pose and facial details: the generalisation properties of a WNN can be crucial. In the light of this problem a software simulator of a WNN has been built and the results of some initial tests are presented and compared with other techniques

Pattern separation in digital learning nets

Pattern separation is a new technique in digital learning networks which can be used to detect state conflicts. This letter describes pattern separation in a simple single-layer network, and an application of the technique in networks with feedback.

A continuum model of a fishing net

A working report for the Department of Agriculture and Fisheries, Scotland, Marine Laboratory Aberdeen

Perceptions of informal safety nets: a case study from a South African informal settlement

The relevance and importance of informal safety nets that buffer poor households from livelihood hardships have been given little attention in South Africa’s development programmes to date. This article contributes to the understanding of informal safety nets by investigating local perceptions in a South African informal settlement. The main findings of the study are that families perform an important safety net function, but that these sources of assistance can be susceptible to social isolation. Immediate neighbours and friends also play an important safety net role, but these reciprocal-based sources of assistance may be difficult to secure. Community-wide threats can have a severe impact on people’s ability to engage in safety net transfers. Many of these difficulties stem from South Africa’s structural unemployment crisis. This factor is the greatest danger to the future of the informal safety net system in the informal settlement.

Estimating regional benefits of reducing targeted pollutants: An application to agricultural effects on water quality and the value of recreational fishing

The general focus of this paper is the regional estimation of marginal benefits of targeted water pollution abatement to instream uses. Benefit estimates are derived from actual consumer choices of recreational fishing activities and the implied expenditures for various levels of water quality. The methodology is applied to measuring the benefits accruing to recreational anglers in Indiana from the abatement of pollutants that are by-products of agricultural crop production.

Bayesian ranking and slection of fishing boat efficiencies

The steadily accumulating literature on technical efficiency in fisheries attests to the importance of efficiency as an indicator of fleet condition and as an object of management concern. In this paper, we extend previous work by presenting a Bayesian hierarchical approach that yields both efficiency estimates and, as a byproduct of the estimation algorithm, probabilistic rankings of the relative technical efficiencies of fishing boats. The estimation algorithm is based on recent advances in Markov Chain Monte Carlo (MCMC) methods— Gibbs sampling, in particular—which have not been widely used in fisheries economics. We apply the method to a sample of 10,865 boat trips in the US Pacific hake (or whiting) fishery during 1987–2003. We uncover systematic differences between efficiency rankings based on sample mean efficiency estimates and those that exploit the full posterior distributions of boat efficiencies to estimate the probability that a given boat has the highest true mean efficiency.