The income requirements of marine protected areas

Given the growing impact of human activities on the sea, managers are increasingly turning to marine protected areas (MPAs) to protect marine habitats and species. Many MPAs have been unsuccessful, however, and lack of income has been identified as a primary reason for failure. In this study, data from a global survey of 79 MPAs in 36 countries were analysed and attempts made to construct predictive models to determine the income requirements of any given MPA. Statistical tests were used to uncover possible patterns and relationships in the data, with two basic approaches. In the first of these, an attempt was made to build an explanatory "bottom-up" model of the cost structures that might be required to pursue various management activities. This proved difficult in practice owing to the very broad range of applicable data, spanning many orders of magnitude. In the second approach, a "top-down" regression model was constructed using logarithms of the base data, in order to address the breadth of the data ranges. This approach suggested that MPA size and visitor numbers together explained 46% of the minimum income requirements (P < 0.001), with area being the slightly more influential factor. The significance of area to income requirements was of little surprise, given its profile in the literature. However, the relationship between visitors and income requirements might go some way to explaining why northern hemisphere MPAs with apparently high incomes still claim to be under-funded. The relationship between running costs and visitor numbers has important implications not only in determining a realistic level of funding for MPAs, but also in assessing from where funding might be obtained. Since a substantial proportion of the income of many MPAs appears to be utilized for amenity purposes, a case may be made for funds to be provided from the typically better resourced government social and educational budgets as well as environmental budgets. Similarly visitor fees, already an important source of funding for some MPAs, might have a broader role to play in how MPAs are financed in the future. (C) 2007 Elsevier Ltd. All rights reserved.

The development of convergence and accommodation

Aim: To review current literature on the development of convergence and accommodation. The accommodation and vergence systems provide the foundation upon which bifoveal binocular single vision develops. Deviations from their normal development not only are implicated in the aetiology of convergence anomalies, accommodative anomalies and strabismus, but may also be implicated in failure of the emmetropisation process. Method: This review considers the problems of researching the development of accommodation and vergence in infants and how infant research has had to differ from adult methods. It then reviews and discusses the implications of current research into the development of both systems and their linkages. Results: Vergence and accommodation develop rapidly in the first months of life, with accommodation changing from relatively fixed myopic focus in the neonatal period to adult-like responses by 4 months of age. Vergence develops gradually and becomes more accurate after 4 months of age, but has been demonstrated in infants well before the age that binocular disparity detection mechanisms are thought to develop. Hypotheses for this early vergence mechanism are discussed. The relationship between accommodation and vergence shows much more variability in infants than adult literature has found, but this apparent adult/infant difference may be partly attributed to methodological differences rather than maturational change alone. Conclusions: Variability and flexibility characterise infant responses. This variability may enable infants to develop a flexible and robust binocular system for later life. Studies of infant visual cue use may give clues to the aetiology of strabismus and refractive error.

Minimum stable convergence criteria for stochastic diffusion search

An analysis of Stochastic Diffusion Search (SDS), a novel and efficient optimisation and search algorithm, is presented, resulting in a derivation of the minimum acceptable match resulting in a stable convergence within a noisy search space. The applicability of SDS can therefore be assessed for a given problem.

An information approach to the dynamics in farm income: implications for farmland markets

The valuation of farmland is a perennial issue for agricultural policy, given its importance in the farm investment portfolio. Despite the significance of farmland values to farmer wealth, prediction remains a difficult task. This study develops a dynamic information measure to examine the informational content of farmland values and farm income in explaining the distribution of farmland values over time.

Convergence analysis of stochastic diffusion search

In this paper we present a connectionist searching technique - the Stochastic Diffusion Search (SDS), capable of rapidly locating a specified pattern in a noisy search space. In operation SDS finds the position of the pre-specified pattern or if it does not exist - its best instantiation in the search space. This is achieved via parallel exploration of the whole search space by an ensemble of agents searching in a competitive cooperative manner. We prove mathematically the convergence of stochastic diffusion search. SDS converges to a statistical equilibrium when it locates the best instantiation of the object in the search space. Experiments presented in this paper indicate the high robustness of SDS and show good scalability with problem size. The convergence characteristic of SDS makes it a fully adaptive algorithm and suggests applications in dynamically changing environments.