PubMed Health⌕ Search

Biomedical subjects

B J T Morgan

Publications and source records attributed to B J T Morgan.

7 recordsLinked to original sources

Factors influencing soay sheep survival: a Bayesian analysis.

This article presents a Bayesian analysis of mark-recapture-recovery data on Soay sheep. A reversible jump Markov chain Monte Carlo technique is used to determine age classes of common survival, and to model the survival probabilities in those classes using logistic regression. This involves environmental and individual covariates, as well as random effects. Auxiliary variables are used to impute missing covariates measured on individual sheep. The Bayesian approach suggests different models from those previously obtained using classical statistical methods. Following model averaging, features that were not previously detected, and which are of ecological importance, are identified.

Animals↗

Semiparametric regression in capture-recapture modeling.

Capture-recapture models were developed to estimate survival using data arising from marking and monitoring wild animals over time. Variation in survival may be explained by incorporating relevant covariates. We propose nonparametric and semiparametric regression methods for estimating survival in capture-recapture models. A fully Bayesian approach using Markov chain Monte Carlo simulations was employed to estimate the model parameters. The work is illustrated by a study of Snow petrels, in which survival probabilities are expressed as nonlinear functions of a climate covariate, using data from a 40-year study on marked individuals, nesting at Petrels Island, Terre Adélie.

Animals↗

New approximations to the Malthusian parameter.

Approximations to the Malthusian parameter of an age-dependent branching process are obtained in terms of the moments of the lifetime distribution, by exploiting a link with renewal theory. In several examples, the new approximations are more accurate than those currently in use, even when based on only the first two moments. The new approximations are extended to include a form of asymmetric cell division that occurs in some species of yeast. When used for inference, the new approximations are shown to have high efficiency.

Biometry↗

Estimating the number of prions in yeast cells.

Certain yeast cells contain proteins that behave like the mammalian prion PrP and are called yeast prions. The yeast prion protein Sup35p can exist in one of two stable forms, giving rise to phenotypes [PSI(+)] and [psi(-)]. If the chemical guanidine hydrochloride (GdnHCl) is added to a culture of growing [PSI(+)] cells, the proportion of [PSI(+)] cells decreases over time. This process is called curing and is due to a failure to propagate the prion form of Sup35p. We describe how curing can be modelled, and improve upon previous models for the underlying processes of cell division and prion segregation; the new model allows for asymmetric cell division and unequal prion segregation. We conclude by outlining plans for future experimentation and modelling.

Cell Division↗

The analysis of ring-recovery data using random effects.

We show how random terms, describing both yearly variation and overdispersion, can easily be incorporated into models for mark-recovery data, through the use of Bayesian methods. For recovery data on lapwings, we show that the incorporation of the random terms greatly improves the goodness of fit. Omitting the random terms can lead to overestimation of the significance of weather on survival, and overoptimistic prediction intervals in simulations of future population behavior. Random effects models provide a natural way of modeling overdispersion-which is more satisfactory than the standard classical approach of scaling up all standard errors by a uniform inflation factor. We compare models by means of Bayesian p-values and the deviance information criterion (DIC).

Animals↗

Models for yeast prions.

The cytoplasmic heritable determinant [PSI+] of the yeast Saccharomyces cerevisiae exhibits prion-like properties. The properties of yeast prions are studied in the hope that this will enhance the understanding of mammalian prions, which cause mad-cow, Creutzfeldt-Jakob, and related neurodegenerative diseases. When host cells divide, the yeast prions distribute themselves without loss over the daughter cells. Experimental data provide information on how the proportion of cells with prions decreases over time when priori replication is inhibited. One feature of scientific interest is the unknown mean number, n0, of prions assumed to be present in the cells at the start of the experiment. We develop several stochastic models and by fitting them to the data, we obtain substantially larger estimates of n0 compared with a previous analysis. An interesting feature of a model with constant cell generation times is that the predicted proportion of cells with prions varies over time as a sequence of linked hyperbolic curves. Avenues for future research are outlined, which relax simplifying assumptions made in the models. We make several recommendations for the design of future experiments.

Biometry↗

Integrating mark-recapture-recovery and census data to estimate animal abundance and demographic parameters.

In studies of wild animals, one frequently encounters both census and mark-recapture-recovery data. We show how a state-space model for census data in combination with the usual multinomial-based models for ring-recovery data provide estimates of productivity not available from either type of data alone. The approach is illustrated on two British bird species. For the lapwing, we calibrate how its recent decline could be due to a decrease in productivity. For the heron, there is no evidence for a decline in productivity, and the combined analysis increases significantly the strength of logistic regressions of survival on winter severity.

Animals↗