Measuring departures from Hardy-Weinberg: a Markov chain Monte Carlo method for estimating the inbreeding coefficient

Many well-established statistical methods in genetics were developed in a climate of severe constraints on computational power. Recent advances in simulation methodology now bring modern, flexible statistical methods within the reach of scientists having access to a desktop workstation. We illustrate the potential advantages now available by considering the problem of assessing departures from Hardy-Weinberg (HW) equilibrium. Several hypothesis tests of HW have been established, as well as a variety of point estimation methods for the parameter which measures departures from HW under the inbreeding model. We propose a computational, Bayesian method for assessing departures from HW, which has a number of important advantages over existing approaches. The method incorporates the effects-of uncertainty about the nuisance parameters--the allele frequencies--as well as the boundary constraints on f (which are functions of the nuisance parameters). Results are naturally presented visually, exploiting the graphics capabilities of modern computer environments to allow straightforward interpretation. Perhaps most importantly, the method is founded on a flexible, likelihood-based modelling framework, which can incorporate the inbreeding model if appropriate, but also allows the assumptions of the model to he investigated and, if necessary, relaxed. Under appropriate conditions, information can be shared across loci and, possibly, across populations, leading to more precise estimation. The advantages of the method are illustrated by application both to simulated data and to data analysed by alternative methods in the recent literature.

The joint effects of larval density and C-14-cypermethrin on the life history and population growth rate of the midge Chironomus riparius

1. Chemical effects on organisms are typically assessed using individual-level endpoints or sometimes population growth rate (PGR), but such measurements are generally made at low population densities. In contrast most natural populations are subject to density dependence and fluctuate around the environmental carrying capacity as a result of individual competition for resources. As ecotoxicology aims to make reliable population projections of chemical impacts in the field, an understanding of how high-density or resource-limited populations respond to environmental chemicals is essential. 2. Our objective was to determine the joint effects of population density and chemical stress on the life history and PGR of an important ecotoxicological indicator species, Chironomus riparius, under controlled laboratory conditions. Populations were fed the same ration but initiated at different densities and exposed to a solvent control and three concentrations of C-14-cypermethrin in a sediment-water test system for 67 days at 20 +/- 1 degreesC. 3. Density had a negative effect on all the measured life-history traits, and PGR declined with increasing density in the controls. Exposure to C-14-cypermethrin had a direct negative effect on juvenile survival, presumably within the first 24 h because the chemical rapidly dissipated from the water column. Reductions in the initial larval densities resulted in an increase in the available resources for the survivors. Subsequently, exposed populations emerged sooner and started producing offspring earlier than the controls. C-14-cypermethrin had no effect on estimated fecundity and adult body weight but interacted with density to reduce the time to first emergence and first reproduction. As a result, PGR increased with cypermethrin concentration when populations were initiated at high densities. 4. Synthesis and applications. The results showed that the effects of C-14-cypermethrin were buffered at high density, so that the joint effects of density and chemical stress on PGR were less than additive. Low levels of chemical stressors may increase carrying capacity by reducing juvenile competition for resources. More and perhaps fitter adults may be produced, similar to the effects of predators and culling; however, toxicant exposure may result in survivors that are less tolerant to changing conditions. If less than additive effects are typical in the field, standard regulatory tests carried out at low density may overestimate the effects of environmental chemicals. Further studies over a wide range of chemical stressors and organisms with contrasting life histories are needed to make general recommendations.

Hypothesis management in situation assessment

A situation assessment uses reports from sensors to produce hypotheses about a situation at a level of aggregation that is of direct interest to a military commander. A low level of aggregation could mean forming tracks from reports, which is well documented in the tracking literature as track initiation and data association. In this paper there is also discussion on higher level aggregation; assessing the membership of tracks to larger groups. Ideas used in joint tracking and identification are extended, using multi-entity Bayesian networks to model a number of static variables, of which the identity of a target is one. For higher level aggregation a scheme for hypothesis management is required. It is shown how an offline clustering of vehicles can be reduced to an assignment problem.

Reviewing the sustainability/stationarity of current account imbalances with tests for bounded integration

We investigate for 26 OECD economies whether their current account imbalances to GDP are driven by stochastic trends. Regarding bounded stationarity as the more natural counterpart of sustainability, results from Phillips–Perron tests for unit root and bounded unit root processes are contrasted. While the former hint at stationarity of current account imbalances for 12 economies, the latter indicate bounded stationarity for only six economies. Through panel-based test statistics, current account imbalances are diagnosed as bounded non-stationary. Thus, (spurious) rejections of the unit root hypothesis might be due to the existence of bounds reflecting hidden policy controls or financial crises.