Commuting in small towns in rural areas: the case of St Andrews.

Since many rural commuters depend on the private car due to lack of convenient public transport, car reduction policies designed for large cities with ample public transport may be unsuitable for smaller towns. In particular, pricing policies designed to encourage public transport use may be less effective, as commuters with no convenient substitute to driving will be unable to switch. This paper develops multinomial and mixed logit models of commuters’ mode choice using data from a survey of commuters in the University of St Andrews. We find that the direct elasticities of the car mode are comparable to estimates reported in studies of commuting in larger urban areas, while the demand for public transport is considerably more elastic. The value of in-vehicle time is found to be about half of the UK average, reflecting that the roads in the St Andrews area are relatively uncongested.Mode choice, Rural commuting, Discrete choice models

Discrete Choice Experiments: A Guide to Model Specification, Estimation and Software

We provide a user guide on the analysis of data (including best–worst and best–best data) generated from discrete-choice experiments (DCEs), comprising a theoretical review of the main choice models followed by practical advice on estimation and post-estimation. We also provide a review of standard software. In providing this guide, we endeavour to not only provide guidance on choice modelling but to do so in a way that provides a ‘way in’ for researchers to the practicalities of data analysis. We argue that choice of modelling approach depends on the research questions, study design and constraints in terms of quality/quantity of data and that decisions made in relation to analysis of choice data are often interdependent rather than sequential. Given the core theory and estimation of choice models is common across settings, we expect the theoretical and practical content of this paper to be useful to researchers not only within but also beyond health economics

What patients want from a primary care consultation. A discrete choice experiment to identify patients' priorities

Once imágenes de astroblastos y astrocitos.Eleven pictures of astroblasts and astrocytes

The early marine distribution of Atlantic salmon in the North-east Atlantic : A genetically informed stock-specific synthesis

The survival of Atlantic salmon (Salmo salar), an increasingly rare anadromous species, has declined dramatically during its marine phase, with disproportionate impacts on the poorly understood early post-smolt period. Logistical constraints on collecting oceanic data to inform this issue pose a formidable obstacle. To advance understanding of post-smolt distributional ecology in the North-east Atlantic, a comprehensive analysis of existing information was undertaken. Data were synthesized from 385 marine cruises, 10,202 individual trawls, and 9,269 captured post-smolts, spanning three decades and similar to 4.75 million km(2) of ocean, with 3,423 individuals genetically assigned to regional phylogeographic origin. The findings confirm major migrational post-smolt aggregations on the continental shelf-edge off Ireland, Scotland and Norway, and an important marine foraging area in the Norwegian Sea. Genetic analysis shows that aggregational stock composition does not simply reflect distance to natal rivers, with northern phylogeographic stock groups significantly under-represented in sampled high-seas aggregations. It identifies a key foraging habitat for southern European post-smolts located in international waters immediately west of the Voring Plateau escarpment, potentially exposing them to a high by-catch mortality from extra-territorial pelagic fisheries. Evidence of the differential distribution of regional stocks points to fundamental differences in their migration behaviours and may lead to inter-stock variation in responses to environmental change and marine survival. The study shows that understanding of post-smolt marine ecology, as regards to stock-specific variations in habitat utilization, biological performance and exposure to mortality factors, can be significantly advanced by data integration across studies and exploiting genetic approaches.Peer reviewe