91 resultados para variance effective population size
Resumo:
Theory predicts that in small isolated populations random genetic drift can lead to phenotypic divergence; however this prediction has rarely been tested quantitatively in natural populations. Here we utilize natural repeated island colonization events by members of the avian species complex, Zosterops lateralis, to assess whether or not genetic drift alone is an adequate explanation for the observed patterns of microevolutionary divergence in morphology. Morphological and molecular genetic characteristics of island and mainland populations are compared to test three predictions of drift theory: (1) that the pattern of morphological change is idiosyncratic to each island; (2) that there is concordance between morphological and neutral genetic shifts across island populations; and (3) for populations whose time of colonization is known, that the rate of morphological change is sufficiently slow to be accounted for solely by genetic drift. Our results are not consistent with these predictions. First, the direction of size shifts was consistently towards larger size, suggesting the action of a nonrandom process. Second, patterns of morphological divergence among recently colonized populations showed little concordance with divergence in neutral genetic characters. Third, rate tests of morphological change showed that effective population sizes were not small enough for random processes alone to account for the magnitude of microevolutionary change. Altogether, these three lines of evidence suggest that drift alone is not an adequate explanation of morphological differentiation in recently colonized island Zosterops and therefore we suggest that the observed microevolutionary changes are largely a result of directional natural selection.
Resumo:
The duration of movements made to intercept moving targets decreases and movement speed increases when interception requires greater temporal precision. Changes in target size and target speed can have the same effect on required temporal precision, but the response to these changes differs: changes in target speed elicit larger changes in response speed. A possible explanation is that people attempt to strike the target in a central zone that does not vary much with variation in physical target size: the effective size of the target is relatively constant over changes in physical size. Three experiments are reported that test this idea. Participants performed two tasks: (1) strike a moving target with a bat moved perpendicular to the path of the target; (2) press on a force transducer when the target was in a location where it could be struck by the bat. Target speed was varied and target size held constant in experiment 1. Target speed and size were co-varied in experiment 2, keeping the required temporal precision constant. Target size was varied and target speed held constant in experiment 3 to give the same temporal precision as experiment 1. Duration of hitting movements decreased and maximum movement speed increased with increases in target speed and/or temporal precision requirements in all experiments. The effects were largest in experiment 1 and smallest in experiment 3. Analysis of a measure of effective target size (standard deviation of strike locations on the target) failed to support the hypothesis that performance differences could be explained in terms of effective size rather than actual physical size. In the pressing task, participants produced greater peak forces and shorter force pulses when the temporal precision required was greater, showing that the response to increasing temporal precision generalizes to different responses. It is concluded that target size and target speed have independent effects on performance.
Resumo:
In wildlife management, the program of monitoring will depend on the management objective. If the objective is damage mitigation, then ideally it is damage that should be monitored. Alternatively, population size (N) can be used as a surrogate for damage, but the relationship between N and damage obviously needs to be known. If the management objective is a sustainable harvest, then the system of monitoring will depend on the harvesting strategy. In general, the harvest strategy in all states has been to offer a quota that is a constant proportion of population size. This strategy has a number of advantages over alternative strategies, including a low risk of over- or underharvest in a stochastic environment, simplicity, robustness to bias in population estimates and allowing harvest policy to be proactive rather than reactive. However, the strategy requires an estimate of absolute population size that needs to be made regularly for a fluctuating population. Trends in population size and in various harvest statistics, while of interest, are secondary. This explains the large research effort in further developing accurate estimation methods for kangaroo populations. Direct monitoring on a large scale is costly. Aerial surveys are conducted annually at best, and precision of population estimates declines with the area over which estimates are made. Management at a fine scale (temporal or spatial) therefore requires other monitoring tools. Indirect monitoring through harvest statistics and habitat models, that include rainfall or a greenness index from satellite imagery, may prove useful.
Bias, precision and heritability of self-reported and clinically measured height in Australian twins
Resumo:
Many studies of quantitative and disease traits in human genetics rely upon self-reported measures. Such measures are based on questionnaires or interviews and are often cheaper and more readily available than alternatives. However, the precision and potential bias cannot usually be assessed. Here we report a detailed quantitative genetic analysis of stature. We characterise the degree of measurement error by utilising a large sample of Australian twin pairs (857 MZ, 815 DZ) with both clinical and self-reported measures of height. Self-report height measurements are shown to be more variable than clinical measures. This has led to lowered estimates of heritability in many previous studies of stature. In our twin sample the heritability estimate for clinical height exceeded 90%. Repeated measures analysis shows that 2-3 times as many self-report measures are required to recover heritability estimates similar to those obtained from clinical measures. Bivariate genetic repeated measures analysis of self-report and clinical height measures showed an additive genetic correlation > 0.98. We show that the accuracy of self-report height is upwardly biased in older individuals and in individuals of short stature. By comparing clinical and self-report measures we also showed that there was a genetic component to females systematically reporting their height incorrectly; this phenomenon appeared to not be present in males. The results from the measurement error analysis were subsequently used to assess the effects of error on the power to detect linkage in a genome scan. Moderate reduction in error (through the use of accurate clinical or multiple self-report measures) increased the effective sample size by 22%; elimination of measurement error led to increases in effective sample size of 41%.
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Patterns of population subdivision and the relationship between gene flow and geographical distance in the tropical estuarine fish Lares calcarifer (Centropomidae) were investigated using mtDNA control region sequences. Sixty-three putative haplotypes were resolved from a total of 270 individuals from nine localities within three geographical regions spanning the north Australian coastline. Despite a continuous estuarine distribution throughout the sampled range, no haplotypes were shared among regions. However, within regions, common haplotypes were often shared among localities. Both sequence-based (average Phi(ST)=0.328) and haplotype-based (average Phi(ST)=0.182) population subdivision analyses indicated strong geographical structuring. Depending on the method of calculation, geographical distance explained either 79 per cent (sequence-based) or 23 per cent (haplotype-based) of the variation in mitochondrial gene flow. Such relationships suggest that genetic differentiation of L. calcarifer has been generated via isolation-by-distance, possibly in a stepping-stone fashion. This pattern of genetic structure is concordant with expectations based on the life history of L. calcarifer and direct studies of its dispersal patterns. Mitochondrial DNA variation, although generally in agreement with patterns of allozyme variation, detected population subdivision at smaller spatial scales. Our analysis of mtDNA variation in L. calcarifer confirms that population genetic models can detect population structure of not only evolutionary significance but also of demographic significance. Further, it demonstrates the power of inferring such structure from hypervariable markers, which correspond to small effective population sizes.
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We use a spatially explicit population model to explore the population consequences of different habitat selection mechanisms on landscapes with fractal variation in habitat quality. We consider dispersal strategies ranging from random walks to perfect habitat selectors for two species of arboreal marsupial, the greater glider (Petauroides volans) and the mountain brushtail possum (Trichosurus caninus). In this model increasing habitat selection means individuals obtain higher quality territories, but experience increased mortality during dispersal. The net effect is that population sizes are smaller when individuals actively select habitat. We find positive relationships between habitat quality and population size can occur when individuals do not use information about the entire landscape when habitat quality is spatially autocorrelated. We also find that individual behaviour can mitigate the negative effects of spatial variation on population average survival and fecundity. (C) 1998 Elsevier Science Ltd. All rights reserved.
Resumo:
Objective: From Census data, to document the distribution of general practitioners in Australia and to estimate the number of general practitioners needed to achieve an equitable distribution accounting for community health need. Methods: Data on location of general practitioners, population size and crude mortality by statistical division (SD) were obtained from the Australian Bureau of Statistics. The number of patients per general practitioner by SD was calculated and plotted. Using crude mortality to estimate community health need, a ratio of the number of general practitioners per person:mortality was calculated for all Australia and for each SD (the Robin Hood Index). From this, the number of general practitioners needed to achieve equity was calculated. Results: In all, 26,290 general practitioners were identified in 57 SDs. The mean number of people per general practitioner is 707, ranging from 551 to 1887. Capital city SDs have most favourable ratios. The Robin Hood Index for Australia is 1, and ranges from 0.32 (relatively under-served) to 2.46 (relatively over-served). Twelve SDs (21%) including all capital cities and 65% of all Australians, have a Robin Hood Index > 1. To achieve equity per capita 2489 more general practitioners (10% of the current workforce) are needed. To achieve equity by the Robin Hood Index 3351 (13% of the current workforce) are needed. Conclusions: The distribution of general practitioners in Australia is skewed. Nonmetropolitan areas are relatively underserved. Census data and the Robin Hood Index could provide a simple means of identifying areas of need in Australia.
Resumo:
Regional and national surveys provide a broadscale description of the koala's present distribution in Australia. A detailed understanding of its distribution is precluded, however, by past and continuing land clearing across large parts of the koala's range. Koala population density increased in some regions during the late 1800s and then declined dramatically in the early 1900s. The decline was associated with habitat loss, hunting, disease, fire, and drought. Declines are continuing in Queensland and New South Wales. In contrast, dense koala populations in habitat isolates in Victoria and South Australia are managed to reduce population size and browse damage. Current understanding of koala distribution and abundance suggests that the species does not meet Australian criteria as endangered or vulnerable fauna. Its conservation status needs to be reviewed, however, in light of the extensive land clearing in New South Wales and Queensland since the last (1980s) broadscale surveys. Consequently, we recommend that broadacre clearing by curtailed in New South Wales and Queensland and that regular, comprehensive, standardized, national koala surveys be undertaken. Given the fragmentation of koala habitat and regional differences in the status of the koala, we recommended that studies on regional variation in the koala be intensified and that koala ecology in fragmented and naturally restricted habitats be developed. More generally, the National Koala Conservation Strategy should be implemented.
Resumo:
Objective: To document trends in the distribution of general practitioners (GPs) in Australia between 1986 and 1996, adjusted for community need. Methods: Data on the location of GPs, population size and crude mortality in statistical divisions (SD) were obtained from the Australian Bureau of Statistics Census of Population and Housing in 1986 and 1996. From these data, we calculated measures of distribution equality (number of people sharing each GP in each SD) and distribution equity (number of people sharing each GP divided by the crude mortality rate; the Robin Hood Index), and analysed temporal changes in the distribution of GPs. Results: Nationally the number of people sharing each GP fell 11% from 1,038 in 1986 to 921 in 1996. However, in 41 of 57 SDs (72%, p=0.01) the number of people sharing a GP actually increased over this time, and the average Robin Hood Index across SDs fell from 0.943 to 0.783 (p=0.004), indicating increasingly inequitable distribution. Comparing the Robin Hood index values of all SDs ranked in pairs, the value fell in 53 of 57 (93%, p<0.001) paired SDs over the decade. These patterns demonstrate increasing inequity over the decade. The number of people sharing each GP was consistently and substantially lower in the capital city SDs and the Robin Hood Index values were consistently and substantially higher (overserved) compared with country SDs. Conclusions: Despite there being more GPs per capita in Australia, their distribution became increasingly unequal and inequitable between 1986 and 1996, such that rural and remote areas became increasingly poorly served.
Resumo:
We shall examine a model, first studied by Brockwell et al. [Adv Appl Probab 14 (1982) 709.], which can be used to describe the longterm behaviour of populations that are subject to catastrophic mortality or emigration events. Populations can suffer dramatic declines when disease, such as an introduced virus, affects the population, or when food shortages occur, due to overgrazing or fluctuations in rainfall. However, perhaps surprisingly, such populations can survive for long periods and, although they may eventually become extinct, they can exhibit an apparently stationary regime. It is useful to be able to model this behaviour. This is particularly true of the ecological examples that motivated the present study, since, in order to properly manage these populations, it is necessary to be able to predict persistence times and to estimate the conditional probability distribution of population size. We shall see that although our model predicts eventual extinction, the time till extinction can be long and the stationary exhibited by these populations over any reasonable time scale can be explained using a quasistationary distribution. (C) 2001 Elsevier Science Ltd. All rights reserved.
Resumo:
This study conducted in 1999/2000 was designed to evaluate the efficacy of praziquantel against Schistosoma japonicum in an area with repeated chemotherapy (Area A) compared with a newly identified endemic focus (Area B) in Hunan Province, China. The population size was 2015 and 2180 in Areas A and B, respectively, of which 1129 and 1298 subjects received stool examination. A total of 230 subjects were identified by the Kato-Katz technique (4 smears per person) as being infected with S. japonicum, 124 in Area A (prevalence 11 %) and 106 in Area B (prevalence 8.2%). They were treated with a single oral dose of praziquantel (40 mg/kg) in the non-transmission season. A follow-up stool examination was made 50 days after treatment. Among the 220 cases followed, 22 were found stool-egg-positive, with an overall cure rate of 90 %, and 99 % reduction of infection intensity (eggs per gram stool). No significant difference was found in cure rates between the 2 areas (89.7% vs 90.3%). The efficacy of the drug in the area with repeated chemotherapy was not significantly different from that in the newly identified endemic focus. This study, therefore, suggests that the efficacy of praziquantel against S. japonicum has not changed in the Dongting Lake region after more than 14 years of mass chemotherapy, and there is no evidence of tolerance or resistance of S. japonicum against praziquantel.
Resumo:
Understanding the genetic architecture of quantitative traits can greatly assist the design of strategies for their manipulation in plant-breeding programs. For a number of traits, genetic variation can be the result of segregation of a few major genes and many polygenes (minor genes). The joint segregation analysis (JSA) is a maximum-likelihood approach for fitting segregation models through the simultaneous use of phenotypic information from multiple generations. Our objective in this paper was to use computer simulation to quantify the power of the JSA method for testing the mixed-inheritance model for quantitative traits when it was applied to the six basic generations: both parents (P-1 and P-2), F-1, F-2, and both backcross generations (B-1 and B-2) derived from crossing the F-1 to each parent. A total of 1968 genetic model-experiment scenarios were considered in the simulation study to quantify the power of the method. Factors that interacted to influence the power of the JSA method to correctly detect genetic models were: (1) whether there were one or two major genes in combination with polygenes, (2) the heritability of the major genes and polygenes, (3) the level of dispersion of the major genes and polygenes between the two parents, and (4) the number of individuals examined in each generation (population size). The greatest levels of power were observed for the genetic models defined with simple inheritance; e.g., the power was greater than 90% for the one major gene model, regardless of the population size and major-gene heritability. Lower levels of power were observed for the genetic models with complex inheritance (major genes and polygenes), low heritability, small population sizes and a large dispersion of favourable genes among the two parents; e.g., the power was less than 5% for the two major-gene model with a heritability value of 0.3 and population sizes of 100 individuals. The JSA methodology was then applied to a previously studied sorghum data-set to investigate the genetic control of the putative drought resistance-trait osmotic adjustment in three crosses. The previous study concluded that there were two major genes segregating for osmotic adjustment in the three crosses. Application of the JSA method resulted in a change in the proposed genetic model. The presence of the two major genes was confirmed with the addition of an unspecified number of polygenes.
Resumo:
Several small isolates of rainforest situated on the central eastern coast of Australia are home to a rich herpetofauna, including four endemic species of leaftail geckos (Phyllurus spp.) and two skinks (Eulamprus spp.). To examine the extent and geographic pattern of historical subdivision among isolates, we assayed mtDNA variation in two species endemic to rainforests of this region (Phyllurus ossa and Eulamprus amplus) and, for comparison, a more widespread and less specialised lizard, Carlia rhomboidalis. There is a clear genetic signature of historical changes in population size and distribution in P. ossa that is consistent with Pleistocene (or earlier) rainforest contraction and subsequent expansion. Although more pronounced in the gecko, phylogeographic structure was congruent between E. amplus and P. ossa. In contrast to the saxicolous, rainforest-restricted P. ossa and E. amplus, the rainforest-generalist species, C. rhomboidalis, does not display strong geographic population structure. The differences in genetic population structure exhibited by the three species are consistent with species-specific differences in ecology.
Resumo:
The suitability of spotlight counts to index red fox abundance was assessed in an arid environment through a comparison with a scat deposition index (active attractant). In most cases there was a high degree of correlation between the two indices, suggesting that the spotlight counts were accurately documenting fluctuations in population size. However, the precision of the spotlight index was often low (c.v. = 0.07-0.46), suggesting that the technique may not allow the statistical detection of small changes in abundance. During periods when there was an influx of new individuals into the population, the seasonal scat index displayed a three-month time lag in documenting abundance while foxes accustomed themselves to the presence of the regular food supply. The level of precision of the scat index was also found to be relatively low (c.v. = 0.21-0.48). Nevertheless, further refinements of this technique may produce a suitable measure of fox abundance.
Resumo:
Objective: To outline the major methodological issues appropriate to the use of the population impact number (PIN) and the disease impact number (DIN) in health policy decision making. Design: Review of literature and calculation of PIN and DIN statistics in different settings. Setting: Previously proposed extensions to the number needed to treat (NNT): the DIN and the PIN, which give a population perspective to this measure. Main results: The PIN and DIN allow us to compare the population impact of different interventions either within the same disease or in different diseases or conditions. The primary studies used for relative risk estimates should have outcomes, time periods and comparison groups that are congruent and relevant to the local setting. These need to be combined with local data on disease rates and population size. Depending on the particular problem, the target may be disease incidence or prevalence and the effects of interest may be either the incremental impact or the total impact of each intervention. For practical application, it will be important to use sensitivity analyses to determine plausible intervals for the impact numbers. Conclusions: Attention to various methodological issues will permit the DIN and PIN to be used to assist health policy makers assign a population perspective to measures of risk.