971 resultados para Population Connectivity
Resumo:
The Giant Long-Armed Prawn, Macrobrachium lar is a freshwater species native to the Indo-Pacific. M. lar has a long-lived, passive, pelagic marine larval stage where larvae need to colonise freshwater within three months to complete their development. Dispersal is likely to be influenced by the extensive distances larvae must transit between small oceanic islands to find suitable freshwater habitat, and by prevailing east to west wind and ocean currents in the southern Pacific Ocean. Thus, both intrinsic and extrinsic factors are likely to influence wild population structure in this species. The present study sought to define the contemporary broad and fine-scale population genetic structure of Macrobrachium lar in the south-western Pacific Ocean. Three polymorphic microsatellite loci were used to assess patterns of genetic variation within and among 19 wild adult sample sites. Statistical procedures that partition variation implied that at both spatial scales, essentially all variation was present within sample sites and differentiation among sites was low. Any differentiation observed also was not correlated with geographical distance. Statistical approaches that measure genetic distance, at the broad-scale, showed that all south-western Pacific Islands were essentially homogeneous, with the exception of a well supported divergent Cook Islands group. These findings are likely the result of some combination of factors that may include the potential for allelic homoplasy, through to the effects of sampling regime. Based on the findings, there is most likely a divergent M. lar Cook Islands clade in the south-western Pacific Ocean, resulting from prevailing ocean currents. Confirmation of this pattern will require a more detailed analysis of nDNA variation using a larger number of loci and, where possible, use of larger population sizes.
Resumo:
Almost all metapopulation modelling assumes that connectivity between patches is only a function of distance, and is therefore symmetric. However, connectivity will not depend only on the distance between the patches, as some paths are easy to traverse, while others are difficult. When colonising organisms interact with the heterogeneous landscape between patches, connectivity patterns will invariably be asymmetric. There have been few attempts to theoretically assess the effects of asymmetric connectivity patterns on the dynamics of metapopulations. In this paper, we use the framework of complex networks to investigate whether metapopulation dynamics can be determined by directly analysing the asymmetric connectivity patterns that link the patches. Our analyses focus on “patch occupancy” metapopulation models, which only consider whether a patch is occupied or not. We propose three easily calculated network metrics: the “asymmetry” and “average path strength” of the connectivity pattern, and the “centrality” of each patch. Together, these metrics can be used to predict the length of time a metapopulation is expected to persist, and the relative contribution of each patch to a metapopulation’s viability. Our results clearly demonstrate the negative effect that asymmetry has on metapopulation persistence. Complex network analyses represent a useful new tool for understanding the dynamics of species existing in fragmented landscapes, particularly those existing in large metapopulations.
Resumo:
While purporting to enhance Australia’s sustainability, the federal government’s Population Strategy rejects the assessment of the limiting factors to future population growth, thus avoiding urgent threshold issues such as resource depletion and environmental destruction. A more forward-thinking and whole-system perspective would assess and incorporate critical biophysical limits into governance processes with suitable prioritisation. It would encourage communities to examine their individual and collective responsibilities in the context of these limits in order to most equitably optimise outcomes; and it would employ both a resource-based examination of minimum population requirements, and an impact-based assessment of maximum thresholds. This carrying capacity approach to planning could help guide society towards a more sustainable future.
Resumo:
Here we present a sequential Monte Carlo approach that can be used to find optimal designs. Our focus is on the design of phase III clinical trials where the derivation of sampling windows is required, along with the optimal sampling schedule. The search is conducted via a particle filter which traverses a sequence of target distributions artificially constructed via an annealed utility. The algorithm derives a catalogue of highly efficient designs which, not only contain the optimal, but can also be used to derive sampling windows. We demonstrate our approach by designing a hypothetical phase III clinical trial.
Resumo:
The Australian Government is about to release Australia’s first sustainable population policy. Sustainable population growth, among other things, implies sustainable energy demand. Current modelling of future energy demand both in Australia and by agencies such as the International Energy Agency sees population growth as one of the key drivers of energy demand. Simply increasing the demand for energy in response to population policy is sustainable only if there is a radical restructuring of the energy system away from energy sources associated with environmental degradation towards one more reliant on renewable fuels and less reliant on fossil fuels. Energy policy can also address the present nexus between energy consumption per person and population growth through an aggressive energy efficiency policy. The paper considers the link between population policies and energy policies and considers how the overall goal of sustainability can be achieved. The methods applied in this analysis draw on the literature of sustainable development to develop elements of an energy planning framework to support a sustainable population policy. Rather than simply accept that energy demand is a function of population increase moderated by an assumed rate of energy efficiency improvement, the focus is on considering what rate of energy efficiency improvement is necessary to significantly reduce the standard connections between population growth and growth in energy demand and what policies are necessary to achieve this situation. Energy efficiency policies can only moderate unsustainable aspects of energy demand and other policies are essential to restructure existing energy systems into on-going sustainable forms. Policies to achieve these objectives are considered. This analysis shows that energy policy, population policy and sustainable development policies are closely integrated. Present policy and planning agencies do not reflect this integration and energy and population policies in Australia have largely developed independently and whether the outcome is sustainable is largely a matter of chance. A genuinely sustainable population policy recognises the inter-dependence between population and energy policies and it is essential that this is reflected in integrated policy and planning agencies
Resumo:
The Australian Government is about to release Australia’s first sustainable population policy. Sustainable population growth, among other things, implies sustainable energy demand. Current modelling of future energy demand both in Australia and by agencies such as the International Energy Agency sees population growth as one of the key drivers of energy demand. Simply increasing the demand for energy in response to population policy is sustainable only if there is a radical restructuring of the energy system away from energy sources associated with environmental degradation towards one more reliant on renewable fuels and less reliant on fossil fuels. Energy policy can also address the present nexus between energy consumption per person and population growth through an aggressive energy efficiency policy. The paper considers the link between population policies and energy policies and considers how the overall goal of sustainability can be achieved. The methods applied in this analysis draw on the literature of sustainable development to develop elements of an energy planning framework to support a sustainable population policy. Rather than simply accept that energy demand is a function of population increase moderated by an assumed rate of energy efficiency improvement, the focus is on considering what rate of energy efficiency improvement is necessary to significantly reduce the standard connections between population growth and growth in energy demand and what policies are necessary to achieve this situation. Energy efficiency policies can only moderate unsustainable aspects of energy demand and other policies are essential to restructure existing energy systems into on-going sustainable forms. Policies to achieve these objectives are considered. This analysis shows that energy policy, population policy and sustainable development policies are closely integrated. Present policy and planning agencies do not reflect this integration and energy and population policies in Australia have largely developed independently and whether the outcome is sustainable is largely a matter of chance. A genuinely sustainable population policy recognises the inter-dependence between population and energy policies and it is essential that this is reflected in integrated policy and planning agencies
Resumo:
Obesity has been widely regarded as a public health concern because of its adverse impact on individuals’ health. Systematic reviews have been published in examining the effect of obesity on depression, but with major emphasis on general obesity as measured by the body mass index. Despite a stronger effect of abdominal obesity on individuals’ physical health outcomes, to our best knowledge, no systematic review was undertaken with regard to the relationship between abdominal obesity and depression. This paper reports the results of a systematic review and meta-analysis of cross-sectional studies examining the relationship between abdominal obesity and depression in a general population. Multiple electronic databases were searched until the end of September 2009. 15 articles were systematically reviewed and meta-analyzed. The analysis showed that the odds ratio of having depression for individuals with abdominal obesity was 1.38 (95% CI, 1.22–1.57) as compared to those who are not obese. Furthermore, it was found that this relationship did not vary with potential confounders including gender, age, measurement of depression and abdominal obesity, and study quality.