58 resultados para Population density
Resumo:
The primary purpose of this paper is to overview a selection of advanced water treatment technology systems that are suited for application in towns and settlements in remote and very remote regions of Australia and vulnerable and lagging rural regions in Sri Lanka. This recognises that sanitation and water treatment are inextricably linked and both are needed to reduce risks to environment and population health from contaminated water sources. For both Australia and Sri Lanka only a small fraction of the settlements in rural and remote regions are connected to water treatment facilities and town water supplies. In Australia’s remote/very remote regions raw water is drawn from underground sources and rainwater capture. Most settlements in rural Sri Lanka rely on rivers, reservoirs, wells, springs or carted water. Furthermore, Sri Lanka has more than 25,000 hand pumped tube wells which saved the communities during recent droughts. Decentralised water supply systems offer the opportunity to provide safe drinking water to these remote/very remote and rural regions where centralised systems are not feasible due to socio-cultural, economic, political, technological reasons. These systems reduce health risks from contaminated water supplies. In remote areas centralized systems fail due to low population density and less affordability. Globally, a new generation of advanced water treatment technologies are positioned to make a major impact on the provision of safe potable water in remote/very remote regions in Australia and rural regions in Sri Lanka. Some of these systems were developed for higher income countries. However, with careful selection and further research they can be tailored to match local socio-economic conditions and technical capacity. As such, they can equally be used to provide decentralised water supply in communities in developed and developing countries such as Australia and Sri Lanka.
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Threatened species often exist in a small number of isolated subpopulations. Given limitations on conservation spending, managers must choose from strategies that range from managing just one subpopulation and risking all other subpopulations to managing all subpopulations equally and poorly, thereby risking the loss of all subpopulations. We took an economic approach to this problem in an effort to discover a simple rule of thumb for optimally allocating conservation effort among subpopulations. This rule was derived by maximizing the expected number of extant subpopulations remaining given n subpopulations are actually managed. We also derived a spatiotemporally optimized strategy through stochastic dynamic programming. The rule of thumb suggested that more subpopulations should be managed if the budget increases or if the cost of reducing local extinction probabilities decreases. The rule performed well against the exact optimal strategy that was the result of the stochastic dynamic program and much better than other simple strategies (e.g., always manage one extant subpopulation or half of the remaining subpopulation). We applied our approach to the allocation of funds in 2 contrasting case studies: reduction of poaching of Sumatran tigers (Panthera tigris sumatrae) and habitat acquisition for San Joaquin kit foxes (Vulpes macrotis mutica). For our estimated annual budget for Sumatran tiger management, the mean time to extinction was about 32 years. For our estimated annual management budget for kit foxes in the San Joaquin Valley, the mean time to extinction was approximately 24 years. Our framework allows managers to deal with the important question of how to allocate scarce conservation resources among subpopulations of any threatened species. © 2008 Society for Conservation Biology.
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Japanese encephalitis (JE) is the most common cause of viral encephalitis and an important public health concern in the Asia-Pacific region, particularly in China where 50% of global cases are notified. To explore the association between environmental factors and human JE cases and identify the high risk areas for JE transmission in China, we used annual notified data on JE cases at the center of administrative township and environmental variables with a pixel resolution of 1 km×1 km from 2005 to 2011 to construct models using ecological niche modeling (ENM) approaches based on maximum entropy. These models were then validated by overlaying reported human JE case localities from 2006 to 2012 onto each prediction map. ENMs had good discriminatory ability with the area under the curve (AUC) of the receiver operating curve (ROC) of 0.82-0.91, and low extrinsic omission rate of 5.44-7.42%. Resulting maps showed JE being presented extensively throughout southwestern and central China, with local spatial variations in probability influenced by minimum temperatures, human population density, mean temperatures, and elevation, with contribution of 17.94%-38.37%, 15.47%-21.82%, 3.86%-21.22%, and 12.05%-16.02%, respectively. Approximately 60% of JE cases occurred in predicted high risk areas, which covered less than 6% of areas in mainland China. Our findings will help inform optimal geographical allocation of the limited resources available for JE prevention and control in China, find hidden high-risk areas, and increase the effectiveness of public health interventions against JE transmission.
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A class of growth models incorporating time-dependent factors and stochastic perturbations are introduced. The proposed model includes the existing growth models used in fisheries as special cases. Particular attention is given to growth of a population (in average weight or length) from which observations are taken randomly each time and the analysis of tag-recapture data. Two real data sets are used for illustration: (a) to estimate the seasonal effect and population density effect on growth of farmed prawn (Penaeus monodon) from weight data and (b) to assess the effect of tagging on growth of barramundi (Lates calcarifer)
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We consider the motion of a diffusive population on a growing domain, 0 < x < L(t ), which is motivated by various applications in developmental biology. Individuals in the diffusing population, which could represent molecules or cells in a developmental scenario, undergo two different kinds of motion: (i) undirected movement, characterized by a diffusion coefficient, D, and (ii) directed movement, associated with the underlying domain growth. For a general class of problems with a reflecting boundary at x = 0, and an absorbing boundary at x = L(t ), we provide an exact solution to the partial differential equation describing the evolution of the population density function, C(x,t ). Using this solution, we derive an exact expression for the survival probability, S(t ), and an accurate approximation for the long-time limit, S = limt→∞ S(t ). Unlike traditional analyses on a nongrowing domain, where S ≡ 0, we show that domain growth leads to a very different situation where S can be positive. The theoretical tools developed and validated in this study allow us to distinguish between situations where the diffusive population reaches the moving boundary at x = L(t ) from other situations where the diffusive population never reaches the moving boundary at x = L(t ). Making this distinction is relevant to certain applications in developmental biology, such as the development of the enteric nervous system (ENS). All theoretical predictions are verified by implementing a discrete stochastic model.
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Much of our understanding and management of ecological processes requires knowledge of the distribution and abundance of species. Reliable abundance or density estimates are essential for managing both threatened and invasive populations, yet are often challenging to obtain. Recent and emerging technological advances, particularly in unmanned aerial vehicles (UAVs), provide exciting opportunities to overcome these challenges in ecological surveillance. UAVs can provide automated, cost-effective surveillance and offer repeat surveys for pest incursions at an invasion front. They can capitalise on manoeuvrability and advanced imagery options to detect species that are cryptic due to behaviour, life-history or inaccessible habitat. UAVs may also cause less disturbance, in magnitude and duration, for sensitive fauna than other survey methods such as transect counting by humans or sniffer dogs. The surveillance approach depends upon the particular ecological context and the objective. For example, animal, plant and microbial target species differ in their movement, spread and observability. Lag-times may exist between a pest species presence at a site and its detectability, prompting a need for repeat surveys. Operationally, however, the frequency and coverage of UAV surveys may be limited by financial and other constraints, leading to errors in estimating species occurrence or density. We use simulation modelling to investigate how movement ecology should influence fine-scale decisions regarding ecological surveillance using UAVs. Movement and dispersal parameter choices allow contrasts between locally mobile but slow-dispersing populations, and species that are locally more static but invasive at the landscape scale. We find that low and slow UAV flights may offer the best monitoring strategy to predict local population densities in transects, but that the consequent reduction in overall area sampled may sacrifice the ability to reliably predict regional population density. Alternative flight plans may perform better, but this is also dependent on movement ecology and the magnitude of relative detection errors for different flight choices. Simulated investigations such as this will become increasingly useful to reveal how spatio-temporal extent and resolution of UAV monitoring should be adjusted to reduce observation errors and thus provide better population estimates, maximising the efficacy and efficiency of unmanned aerial surveys.
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We introduce a framework for population analysis of white matter tracts based on diffusion-weighted images of the brain. The framework enables extraction of fibers from high angular resolution diffusion images (HARDI); clustering of the fibers based partly on prior knowledge from an atlas; representation of the fiber bundles compactly using a path following points of highest density (maximum density path; MDP); and registration of these paths together using geodesic curve matching to find local correspondences across a population. We demonstrate our method on 4-Tesla HARDI scans from 565 young adults to compute localized statistics across 50 white matter tracts based on fractional anisotropy (FA). Experimental results show increased sensitivity in the determination of genetic influences on principal fiber tracts compared to the tract-based spatial statistics (TBSS) method. Our results show that the MDP representation reveals important parts of the white matter structure and considerably reduces the dimensionality over comparable fiber matching approaches.
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Osteoporosis is a disease characterized by low bone mineral density (BMD) and poor bone quality. Peak bone density is achieved by the third decade of life, after which bone is maintained by a balanced cycle of bone resorption and synthesis. Age-related bone loss occurs as the bone resorption phase outweighs the bone synthesis phase of bone metabolism. Heritability accounts for up to 90% of the variability in BMD. Chromosomal loci including 1p36, 2p22-25, 11q12-13, parathyroid hormone receptor type 1 (PTHR1), interleukin-6 (IL-6), interleukin 1 alpha (IL-1α) and type II collagen A1/vitamin D receptor (COL11A1/VDR) have been linked or shown suggestive linkage with BMD in other populations. To determine whether these loci predispose to low BMD in the Irish population, we investigated 24 microsatellite markers at 7 chromosomal loci by linkage studies in 175 Irish families of probands with primary low BMD (T-score ≤ -1.5). Nonparametric analysis was performed using the maximum likelihood variance estimation and traditional Haseman-Elston tests on the Mapmaker/Sibs program. Suggestive evidence of linkage was observed with lumbar spine BMD at 2p22-25 (maximum LOD score 2.76) and 11q12-13 (MLS 2.55). One region, 1p36, approached suggestive linkage with femoral neck BMD (MLS 2.17). In addition, seven markers achieved LOD scores > 1.0, D2S149, D11S1313, D11S987, D11S1314 including those encompassing the PTHR1 (D3S3559, D3S1289) for lumbar spine BMD and D2S149 for femoral neck BMD. Our data suggest that genes within a these chromosomal regions are contributing to a predisposition to low BMD in the Irish population.
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Adolescent Idiopathic Scoliosis (AIS) is the most common deformity of the spine, affecting 2-4% of the population. Previous studies have shown that the vertebrae in scoliotic spines undergo abnormal shape changes, however there has been little exploration of how AIS affects bone density distribution within the vertebrae. Existing pre-operative CT scans of 53 female idiopathic scoliosis patients with right-sided main thoracic curves were used to measure the lateral (right to left) bone density profile at mid-height through each vertebral body. This study demonstrated that AIS patients have a marked convex/concave asymmetry in bone density for vertebral levels at or near the apex of the scoliotic curve. To the best of our knowledge, the only previous studies of bone density distribution in AIS are those of Périé et al [1,2], who reported a coronal plane ‘mechanical migration’ of 0.54mm toward the concavity of the scoliotic curve in the lumbar apical vertebrae of 11 scoliosis patients. This is comparable to the value of 0.8mm (4%) in our study, especially since our patients had more severe scoliotic curves. From a bone adaptation perspective, these results suggest that the axial loading on the scoliotic spine is strongly asymmetric.
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Habitat fragmentation can have an impact on a wide variety of biological processes including abundance, life history strategies, mating system, inbreeding and genetic diversity levels of individual species. Although fragmented populations have received much attention, ecological and genetic responses of species to fragmentation have still not been fully resolved. The current study investigated the ecological factors that may influence the demographic and genetic structure of the giant white-tailed rat (Uromys caudimaculatus) within fragmented tropical rainforests. It is the first study to examine relationships between food resources, vegetation attributes and Uromys demography in a quantitative manner. Giant white-tailed rat densities were strongly correlated with specific suites of food resources rather than forest structure or other factors linked to fragmentation (i.e. fragment size). Several demographic parameters including the density of resident adults and juvenile recruitment showed similar patterns. Although data were limited, high quality food resources appear to initiate breeding in female Uromys. Where data were sufficient, influx of juveniles was significantly related to the density of high quality food resources that had fallen in the previous three months. Thus, availability of high quality food resources appear to be more important than either vegetation structure or fragment size in influencing giant white-tailed rat demography. These results support the suggestion that a species’ response to fragmentation can be related to their specific habitat requirements and can vary in response to local ecological conditions. In contrast to demographic data, genetic data revealed a significant negative effect of habitat fragmentation on genetic diversity and effective population size in U. caudimaculatus. All three fragments showed lower levels of allelic richness, number of private alleles and expected heterozygosity compared with the unfragmented continuous rainforest site. Populations at all sites were significantly differentiated, suggesting restricted among population gene flow. The combined effects of reduced genetic diversity, lower effective population size and restricted gene flow suggest that long-term viability of small fragmented populations may be at risk, unless effective management is employed in the future. A diverse range of genetic reproductive behaviours and sex-biased dispersal patterns were evident within U. caudimaculatus populations. Genetic paternity analyses revealed that the major mating system in U. caudimaculatus appeared to be polygyny at sites P1, P3 and C1. Evidence of genetic monogamy, however, was also found in the three fragmented sites, and was the dominant mating system in the remaining low density, small fragment (P2). High variability in reproductive skew and reproductive success was also found but was less pronounced when only resident Uromys were considered. Male body condition predicted which males sired offspring, however, neither body condition nor heterozygosity levels were accurate predictors of the number of offspring assigned to individual males or females. Genetic spatial autocorrelation analyses provided evidence for increased philopatry among females at site P1, but increased philopatry among males at site P3. This suggests that male-biased dispersal occurs at site P1 and female-biased dispersal at site P3, implying that in addition to mating systems, Uromys may also be able to adjust their dispersal behaviour to suit local ecological conditions. This study highlights the importance of examining the mechanisms that underlie population-level responses to habitat fragmentation using a combined ecological and genetic approach. The ecological data suggested that habitat quality (i.e. high quality food resources) rather than habitat quantity (i.e. fragment size) was relatively more important in influencing giant white-tailed rat demographics, at least for the populations studied here . Conversely, genetic data showed strong evidence that Uromys populations were affected adversely by habitat fragmentation and that management of isolated populations may be required for long-term viability of populations within isolated rainforest fragments.
Resumo:
Adolescent Idiopathic Scoliosis (AIS) is the most common deformity of the spine, affecting 2-4% of the population. Previous studies have shown that the vertebrae in scoliotic spines undergo abnormal shape changes, however there has been little exploration of how scoliosis affects bone density distribution within the vertebrae. In this study, existing CT scans of 53 female idiopathic scoliosis patients with right-sided main thoracic curves were used to measure the lateral (right to left) bone density profile at mid-height through each vertebral body. Five key bone density profile measures were identified from each normalised bone density distribution, and multiple regression analysis was performed to explore the relationship between bone density distribution and patient demographics (age, height, weight, body mass index (BMI), skeletal maturity, time since Menarche, vertebral level, and scoliosis curve severity). Results showed a marked convex/concave asymmetry in bone density for vertebral levels at or near the apex of the scoliotic curve. At the apical vertebra, mean bone density at the left side (concave) cortical shell was 23.5% higher than for the right (convex) cortical shell, and cancellous bone density along the central 60% of the lateral path from convex to concave increased by 13.8%. The centre of mass of the bone density profile at the thoracic curve apex was located 53.8% of the distance along the lateral path, indicating a shift of nearly 4% toward the concavity of the deformity. These lateral bone density gradients tapered off when moving away from the apical vertebra. Multi-linear regressions showed that the right cortical shell peak bone density is significantly correlated with skeletal maturity, with each Risser increment corresponding to an increase in mineral equivalent bone density of 4-5%. There were also statistically significant relationships between patient height, weight and BMI, and the gradient of cancellous bone density along the central 60% of the lateral path. Bone density gradient is positively correlated with weight, and negatively correlated with height and BMI, such that at the apical vertebra, a unit decrease in BMI corresponds to an almost 100% increase in bone density gradient.
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1. A diverse array of patterns has been reported regarding the spatial extent of population genetic structure and effective dispersal in freshwater macroinvertebrates. In river systems, the movements of many taxa can be restricted to varying degrees by the natural stream channel hierarchy. 2. In this study, we sampled populations of the non-biting freshwater midge Echinocladius martini in the Paluma bioregion of tropical northeast Queensland to investigate fine scale patterns of within- and among-stream dispersal and gene flow within a purported historical refuge. We amplified a 639 bp fragment of mitochondrial COI and analysed genetic structure using pairwise ΦST, hierarchical AMOVA, Mantel tests and a parsimony network. Genetic variation was partitioned among stream sections using Streamtree to investigate the effect of potential instream dispersal barriers. 3. The data revealed strong natal site fidelity and significant differentiation among neighbouring, geographically proximate streams. We found evidence for only episodic adult flight among sites on separate stream reaches. Overall, however, our data suggested that both larval and adult dispersal was largely limited to within a stream channel. 4. This may arise from a combination of the high density of riparian vegetation physically restricting dispersal and from the joint effects of habitat stability and large population sizes. Together these may mitigate the requirement for movement among streams to avoid inbreeding and local extinction due to habitat change and may thus enable persistence of upstream populations in the absence of regular compensatory upstream flight. Taken together, these data suggest that dispersal of E. martini is highly restricted, to the scale of only a few kilometres, and hence occurs predominantly within the natal stream.
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Background Seasonal changes in cardiovascular disease (CVD) risk factors may be due to exposure to seasonal environmental variables like temperature and acute infections or seasonal behavioural patterns in physical activity and diet. Investigating the seasonal pattern of risk factors should help determine the causes of the seasonal pattern in CVD. Few studies have investigated the seasonal variation in risk factors using repeated measurements from the same individual, which is important as individual and population seasonal patterns may differ. Methods The authors investigated the seasonal pattern in systolic and diastolic blood pressure, heart rate, body weight, total cholesterol, triglycerides, high-density lipoprotein cholesterol, C reactive protein and fibrinogen. Measurements came from 38 037 participants in the population-based cohort, the Tromsø Study, examined up to eight times from 1979 to 2008. Individual and population seasonal patterns were estimated using a cosinor in a mixed model. Results All risk factors had a highly statistically significant seasonal pattern with a peak time in winter, except for triglycerides (peak in autumn), C reactive protein and fibrinogen (peak in spring). The sizes of the seasonal variations were clinically modest. Conclusions Although the authors found highly statistically significant individual seasonal patterns for all risk factors, the sizes of the changes were modest, probably because this subarctic population is well adapted to a harsh climate. Better protection against seasonal risk factors like cold weather could help reduce the winter excess in CVD observed in milder climates.
Bodyweight and other correlates of symptom detected breast cancers in a population offered screening
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Objective: To determine factors associated with symptom detected breast cancers in a population offered screening. Methods We interviewed 1,459 Australian women aged 40–69, 946 with symptom detected and 513 with mammogram detected invasive breast cancers ≥1.1 cm in diameter, about their personal, mammogram and breast histories before diagnosis and reviewed medical records for tumour characteristics and mammogram dates, calculating ORs and 95% confidence intervals (CIs) for symptom- vs mammogram-detected cancers in logistic regression models. Results: Lack of regular mammograms (<2 mammograms in the 4.5 years before diagnosis) was the strongest correlate of symptom detected breast cancer (OR=3.04 for irregular or no mammograms). In women who had regular mammograms (≥2 mammograms in the 4.5 years before diagnosis), the independent correlates of symptom detected cancers were low BMI (OR <25kg/m2 vs ≥30kg/m2=2.18, 95% CI 1.23-3.84; p=0.008), increased breast density (available in 498 women) (OR highest quarter vs lowest =3.50, 95% CI 1.76-6.97; ptrend=0.004), high grade cancer and a larger cancer (each p<0.01). In women who did not have regular mammograms, the independent correlates were age <50 years, a first cancer and a ≥2cm cancer. Smoking appeared to modify the association of symptom detected cancer with low BMI (higher ORs for low BMI in current smokers) and estrogen receptor (ER) status (higher ORs for low BMI in ER− cancers). Conclusion: Women with low BMI may benefit from a tailored approach to breast cancer detection, particularly if they smoke.
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To understand the underlying genetic architecture of cardiovascular disease (CVD) risk traits, we undertook a genome-wide linkage scan to identify CVD quantitative trait loci (QTLs) in 377 individuals from the Norfolk Island population. The central aim of this research focused on the utilization of a genetically and geographically isolated population of individuals from Norfolk Island for the purposes of variance component linkage analysis to identify QTLs involved in CVD risk traits. Substantial evidence supports the involvement of traits such as systolic and diastolic blood pressures, high-density lipoprotein-cholesterol, low-density lipoprotein-cholesterol, body mass index and triglycerides as important risk factors for CVD pathogenesis. In addition to the environmental inXuences of poor diet, reduced physical activity, increasing age, cigarette smoking and alcohol consumption, many studies have illustrated a strong involvement of genetic components in the CVD phenotype through family and twin studies. We undertook a genome scan using 400 markers spaced approximately 10 cM in 600 individuals from Norfolk Island. Genotype data was analyzed using the variance components methods of SOLAR. Our results gave a peak LOD score of 2.01 localizing to chromosome 1p36 for systolic blood pressure and replicated previously implicated loci for other CVD relevant QTLs.