A program in population genetics and demography.
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Explore the source record for details and available documents.
Explore the source record for details and available documents.
Explore the source record for details and available documents.
Explore the source record for details and available documents.
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In population studies on aging, the data on genetic markers are often collected for individuals from different age groups. The purpose of such studies is to identify, by comparison of the frequencies of selected genotypes, "longevity" or "frailty" genes in the oldest and in younger groups of individuals. To address questions about more-complicated aspects of genetic influence on longevity, additional information must be used. In this article, we show that the use of demographic information, together with data on genetic markers, allows us to calculate hazard rates, relative risks, and survival functions for respective genes or genotypes. New methods of combining genetic and demographic information are discussed. These methods are tested on simulated data and then are applied to the analysis of data on genetic markers for two haplogroups of human mtDNA. The approaches suggested in this article provide a powerful tool for analyzing the influence of candidate genes on longevity and survival. We also show how factors such as changes in the initial frequencies of candidate genes in subsequent cohorts, or secular trends in cohort mortality, may influence the results of an analysis.
Accurate measures of age-dependent mortality are critical to life-history analysis and measures of fitness, yet these measures are difficult to obtain in natural populations. Age-dependent mortality patterns can be obscured not only by seasonal variation in environmental conditions and reproduction but also by changes in the heterogeneity among individuals in the population over time due to selection. This study of Plantago lanceolata uses longitudinal data from a field study with a large number of individuals to develop a model to estimate the shape of the baseline hazard function that represents the age-dependent risk of mortality. The model developed here uses both constant (genetics, spatial location) and time-varying (temperature, rainfall, reproduction, size) covariates not only to estimate the underlying mortality pattern but also to demonstrate that the risk of mortality associated with fitness components can change with time/age. Moreover, this analysis suggests that increasing size after reproductive maturity may allow this plant species to escape from demographic senescence.
Understanding physiological and behavioral mechanisms underlying the diversity of observed life-history strategies is challenging because of difficulties in obtaining long-term measures of fitness and in relating fitness to these mechanisms. We evaluated effects of experimentally elevated testosterone on male fitness in a population of dark-eyed juncos studied over nine breeding seasons using a demographic modeling approach. Elevated levels of testosterone decreased survival rates but increased success of producing extra-pair offspring. Higher overall fitness for testosterone-treated males was unexpected and led us to consider indirect effects of testosterone on offspring and females. Nest success was similar for testosterone-treated and control males, but testosterone-treated males produced smaller offspring, and smaller offspring had lower postfledging survival. Older, more experienced females preferred to mate with older males and realized higher reproductive success when they did so. Treatment of young males increased their ability to attract older females yet resulted in poor reproductive performance. The higher fitness of testosterone-treated males in the absence of a comparable natural phenotype suggests that the natural phenotype may be constrained. If this phenotype were to arise, the negative social effects on offspring and mates suggest that these effects might prevent high-testosterone phenotypes from spreading in the population.
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The rapid spread of HIV in the 1980s and 1990s in the non-industrialised world is now leading to an AIDS epidemic. This in turn is having a demographic and economic impact on these societies. This article assesses the most recent evidence for these impacts. It concludes that, while there is already a real and measurable impact, there is far worse to come. The demographic consequences will be particularly serious. Economic impact is rather more uncertain, and the article looks at the macro-economic impact as well as that on firms. In addition, it is postulated that economics may not be the most appropriate discipline to assess the true effects of the disease.
Microsatellites have been widely used as tools for population studies. However, inference about population processes relies on the specification of mutation parameters that are largely unknown and likely to differ across loci. Here, we use data on somatic mutations to investigate the mutation process at 14 tetranucleotide repeats and carry out an advanced multilocus analysis of different demographic scenarios on worldwide population samples. We use a method based on less restrictive assumptions about the mutation process, which is more powerful to detect departures from the null hypothesis of constant population size than other methods previously applied to similar data sets. We detect a signal of population expansion in all samples examined, except for one African sample. As part of this analysis, we identify an "anomalous" locus whose extreme pattern of variation cannot be explained by variability in mutation size. Exaggerated mutation rate is proposed as a possible cause for its unusual variation pattern. We evaluate the effect of using it to infer population histories and show that inferences about demographic histories are markedly affected by its inclusion. In fact, exclusion of the anomalous locus reduces interlocus variability of statistics summarizing population variation and strengthens the evidence in favor of demographic growth.