Life-history consequences of divergent selection on egg size in Drosophila melanogaster

Life histories are generally assumed to evolve via antagonistic pleiotropy (negative genetic correlations) among traits, and trade-offs between life-history traits are typically studied using either phenotypic manipulations or selection experiments. We investigated the trade-off between egg size and fecundity in Drosophila melanogaster by examining both the phenotypic and genetic relationships between these traits after artificial selection for large and small eggs, relative to female body size. Egg size responded strongly to selection in both directions, increasing in the large-egg selected lines and decreasing in the small-egg selected lines. Phenotypic correlations between egg size and fecundity in the large-egg selected lines were negative, but no relationship between these traits occurred in either the control or small-egg selected lines. There was no negative genetic correlation between egg size and fecundity. Total reproductive allocation decreased in the small-egg selected lines but did not increase in the large-egg lines. Our results have three implications. First, our selection procedure may have forced females selected for large eggs into a physiological trade-off not reflected in a negative genetic correlation between these traits. Second, the lack of a negative genetic correlation between egg size and number suggests that the phenotypic trade-off frequently observed between egg size and number in other organisms may not evolve over the short term via a direct genetic trade-off whereby increases in egg size are automatically accompanied by decreased fecundity. Finally, total reproductive allocation may not evolve independently of egg size as commonly assumed.

Pursuing the popular in Australian history

No abstract

Absolute risk of breast cancer for Australian women with a family history

Background: The purpose of the present paper was to estimate the absolute risk of breast cancer over the remainder of a lifetime in Australian women with different categories of family history. Methods: Age-specific breast cancer incidence rates were adjusted for screening effects, and rates in those with no family history were estimated using the attributable fraction (AF). Relative risks from a published meta-analysis were applied to obtain incidence rates for different categories of family history, and age-specific incidence was converted to cumulative risk of breast cancer. The risk estimates were based upon Australian population statistics and published relative risks. Breast cancer incidence was from New South Wales women for 1996. The AF was calculated using prevalence of a family history of breast cancer from data on Queensland women. The cumulative absolute risk of breast cancer was calculated from decade and mid-decade ages to age 79 years, not adjusted for competing causes of death. Results: Lifetime risk is approximately 8.6% (1 in 12) for the general population and 7.8% (1 in 13) for those without a family history. Women with one relative affected have lifetime risks of 1 in 6-8 and those with two relatives affected have lifetime risks of 1 in 4-6. The cumulative residual lifetime risk decreases with advancing age; by age 60 years all groups with only one relative affected have well above a 90% probability of not developing breast cancer to age 79 years. Conclusions: These Australian risk statistics are useful for public information and in the clinical setting. Risks given here apply to women with average breast cancer risk from other risk factors.

Variation in mortality rates in Australia: correlation with Indigenous status, remoteness and socio-economic deprivation

Background The aim of this study was to study ecological correlations between age-adjusted all-cause mortality rates in Australian statistical divisions and (1) the proportion of residents that self-identify as Indigenous, (2) remoteness, and (3) socio-economic deprivation. Methods All-cause mortality rates for 57 statistical divisions were calculated and directly standardized to the 1997 Australian population in 5-year age groups using Australian Bureau of Statistics (ABS) data. The proportion of residents who self-identified as Indigenous was obtained from the 1996 Census. Remoteness was measured using ARIA (Accessibility and Remoteness Index for Australia) values. Socioeconomic deprivation was measured using SEIFA (Socio-Economic index for Australia) values from the ABS. Results Age-standardized all-cause mortality varies twofold from 5.7 to 11.3 per 1000 across Australian statistical divisions. Strongest correlation was between Indigenous status and mortality (r = 0.69, p < 0.001). correlation between remoteness and mortality was modest (r = 0.39, p = 0.002) as was correlation between socio-economic deprivation and mortality (r = -0.42, p = 0.001). Excluding the three divisions with the highest mortality, a multiple regression model using the logarithm of the adjusted mortality rate as the dependent variable showed that the partial correlation (and hence proportion of the variance explained) for Indigenous status was 0.03 (9 per cent; p = 0.03), for SEIFA score was -0.17 (3 per cent; p = 0.22); and for remoteness was -0.22 (5 per cent; p = 0.13). Collectively, the three variables studied explain 13 per cent of the variability in mortality. Conclusions Ecological correlation exists between all-cause mortality, Indigenous status, remoteness and disadvantage across Australia. The strongest correlation is with indigenous status, and correlation with all three characteristics is weak when the three statistical divisions with the highest mortality rates are excluded. intervention targeted at these three statistical divisions could reduce much of the variability in mortality in Australia.

Modelling life history strategies with capture-recapture data: Evolutionary demography of the water skink Eulamprus tympanum

Matrix population models, elasticity analysis and loop analysis can potentially provide powerful techniques for the analysis of life histories. Data from a capture-recapture study on a population of southern highland water skinks (Eulamprus tympanum) were used to construct a matrix population model. Errors in elasticities were calculated by using the parametric bootstrap technique. Elasticity and loop analyses were then conducted to identify the life history stages most important to fitness. The same techniques were used to investigate the relative importance of fast versus slow growth, and rapid versus delayed reproduction. Mature water skinks were long-lived, but there was high immature mortality. The most sensitive life history stage was the subadult stage. It is suggested that life history evolution in E. tympanum may be strongly affected by predation, particularly by birds. Because our population declined over the study, slow growth and delayed reproduction were the optimal life history strategies over this period. Although the techniques of evolutionary demography provide a powerful approach for the analysis of life histories, there are formidable logistical obstacles in gathering enough high-quality data for robust estimates of the critical parameters.

Variation in cervical cancer screening by region, socio-economic, migrant and Indigenous status in women in New South Wales

The purpose of this study was to estimate the extent of association of cervical screening in NSW women with socio-economic status (SES), rurality, and proportions of non-English speaking background (NESB) and Indigenous status. Data on women who had at least one Pap test over two years (January 1998-December 1999) were obtained from the NSW Pap test Register. Each local government area (LGA) was allocated to categories of population proportions of NESB and Indigenous status, a rurality classification based on population density and remoteness, and to an SES quintile. The odds ratios (OR) of having a Pap test were estimated and confounding adjusted by multiple logistic regression analysis. Implied Pap test rates in urban NESB and in rural Indigenous women were estimated from the modelled estimates. The adjusted OR for a Pap test in large rural centres (1.14) was significantly higher than those for metropolitan or capital city residents (0.9 and 1.0 respectively). Adjusted OR for a Pap test in other rural centres (0.73) and other remote areas (0.64) were significantly lower than those for metropolitan or capital city residents. In urban populations the lowest OR were in areas with both low SES and high proportion of NESB. The lowest OR for Pap screening in rural populations occurred in the most remote areas with the highest proportion of Indigenous women. For urban NESB women the biennial Pap test rate was estimated as 50%, and for rural Indigenous women 29%, compared with the NSW average of 59%.

Causes and consequences of long-term climatic variability on the Australian continent

1. Ice-volume forced glacial-interglacial cyclicity is the major cause of global climate variation within the late Quaternary period. Within the Australian region, this variation is expressed predominantly as oscillations in moisture availability. Glacial periods were substantially drier than today with restricted distribution of mesic plant communities, shallow or ephemeral water bodies and extensive aeolian dune activity. 2. Superimposed on this cyclicity in Australia is a trend towards drier and/or more variable climates within the last 350 000 years. This trend may have been initiated by changes in atmospheric and ocean circulation resulting from Australia's continued movement into the Southeast Asian region and involving the onset or intensification of the El Nino-Southern Oscillation system and a reduction in summer monsoon activity. 3. Increased biomass burning, stemming originally from increased climatic variability and later enhanced by activities of indigenous people, resulted in a more open and sclerophyllous vegetation, increased salinity and a further reduction in water availability. 4. Past records combined with recent observations suggest that the degree of environmental variability will increase and the drying trend will be enhanced in the foreseeable future, regardless of the extent or nature of human intervention.

History of vegetation and habitat change in the Austral-Asian region

Over 1000 marine and terrestrial pollen diagrams and Some hundreds of vertebrate faunal sequences have been studied in the Austral-Asian region bisected by the PEPII transect, from the Russian arctic extending south through east Asia, Indochina, southern Asia, insular Southeast Asia (Sunda), Melanesia, Australasia (Sahul) and the western south Pacific. The majority of these records are Holocene but sufficient data exist to allow the reconstruction of the changing biomes over at least the past 200,000 years. The PEPII transect is free of the effects of large northern ice caps yet exhibits vegetational change in glacial cycles of a similar scale to North America. Major processes that can be discerned are the response of tropical forests in both lowlands and uplands to glacial cycles, the expansion of humid vegetation at the Pleistocene-Holocene transition and the change in faunal and vegetational controls as humans occupy the region. There is evidence for major changes in the intensity of monsoon and El Nino-Southern oscillation variability both on glacial-interglacial and longer time scales with much of the region experiencing a long-term trend towards more variable and/or drier climatic conditions. Temperature variation is most marked in high latitudes and high altitudes with precipitation providing the major climate control in lower latitude, lowland areas. At least some boundary shifts may be the response of vegetation to changing CO2 levels in the atmosphere. Numerous questions of detail remain, however, and current resolution is too coarse to examine the degree of synchroneity of millennial scale change along the transect. (C) 2003 Elsevier Ltd and INQUA. All rights reserved.