975 resultados para Range Expansion


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The Japanese oyster drill or rock snail Pteropurpura (Ocinebrellus) inornata (Récluz, 1851), a marine mollusc, belonging to the family Muricidae, is reported from Portugal for the first time. This non-indigenous species, most likely introduced accidentally from French oyster rearing areas into mainland Portugal, has been regularly sampled in shellfish-culture and nearby environments in Sagres, Algarve, Southwest Portugal since 2005–2008. Detailed studies are urgently needed in order to assess whether or not it has become an invasive species due to a range expansion beyond its point of initial introduction. Outputs should provide information to decision-makers to predict and limit further spread which might result in biodiversity loss and negative economical consequences in locally species-rich areas.

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This thesis presents research into the space use of a specialist reedbed Passerine, the Bearded Reedling, or Bearded Tit, Panurus biarmicus, with a view to inform the conservation of this species and reedbeds as a whole. How a species uses space, and how space use changes between individuals or over time, can influence: the ability to forage and hunt effectively, breeding success, susceptibility to predation, genetic health, disease spread, robustness against environmental change and ultimately, colonisation or extinction. Thus, understanding the space use of animals can provide critical insight into ecological systems. Birds offer interesting models when studying animal space use, as, by being intrinsically mobile, many bird species can occupy multiple spatial scales. As a consequence of being completely dependent on patchy and ephemeral reedbed habitats, the Bearded Reedling, has a clustered, inhomogeneous distribution throughout its range. This drives the existence of distinct spatial scales upon which space use studies should be characterised. Distribution and movement within a single reedbed can be considered local-scale, while spatial processes between reedbeds can be considered wide-scale. Temporal processes may act upon both of these scales. For example, changing interactions with predators may influence nest positioning at a local-scale, while seasonal changes in resource requirements might drive processes such as migration at a wide-scale. The Bearded Reedling has a wide temperate breeding range, extending over much of Eurasia. On the IUCN’s red list, it is listed as ‘of least concern’, with an estimated European population between 240,000-480,000 breeding pairs. Despite its relatively favourable conservation status, its dependence on reedbed habitats drives a fragmented distribution, with populations being concentrated in small, isolated, stands. Over the last century reedbed wetlands have suffered rapid declines caused by drainage schemes undertaken to improve land for development or agriculture. Additionally, many remaining reed stands are subject to extensive commercial management to produce thatch or biofuel. Conversely, in other areas, management is driven by conservation motives which recognise the present threats to reedbeds, and aim to encourage the diversity of species associated with these habitats. As the Bearded Reedling is fundamentally linked to the quality and structure of a reed stand, understanding the space use of this species will offer information for the direct conservation of this specialist species, and for the effects of reedbed management as a whole. This thesis first presents studies of space use at a local-scale. All local-scale research is conducted at the Tay Reedbeds in eastern Scotland. Mist netting and bird ringing data are used within capture recapture models, which include an explicit spatial component, to gain insight into the abundance of the Bearded Reedling on the Tay. This abundance estimation approach suggests the Tay reedbeds are a stronghold for this species on the British Isles, and that, as a high latitude site, the Tay may have importance for range expansion. A combination of transect surveys and radio-tracking data are then used to establish the local-scale space use of this species during the breeding and autumnal seasons. These data are related to changes in the structure of reed caused by local management in the form of mosaic winter reed cutting. Results suggest that birds exploit young and cut patches of reed as foraging resources when they are available, and that old, unmanaged reed is critical for nesting and winter foraging. Further local-scale studies concern the spatial patterns in the nesting habits of this species. Mosaic reed cutting creates clear edges in a reedbed. Artificial nests placed in the Tay Reedbeds demonstrate increased nest predation rates closer to the edges of cut patches. Additionally, high predation rates become reduced as the cut reed re-grows, suggesting that reed cutting may increase accessibility of the stand to predators. As Bearded Reedling nests are uncommon and difficult to locate, the timing, site selection and structure of a sample of real nests from the Tay is then detailed. These demonstrate an early, and relatively rigid breeding onset in this species, the importance of dense, compacted reeds as nesting sites and a degree of flexibility in nest structure. Conservation efforts will also benefit from studies into wide-scale spatial processes. These may be important when establishing how colonisation events occur and when predicting the effects of climatic change. The Bearded Reedling has been traditionally considered a resident species which only occasionally undertakes wide-scale, between-reedbed, movements. Indeed, the ecology of this species suggests strict year round local residency to reedbeds, with distinct seasonal changes in diet allowing occupation of these habitats year round. The European ringing recoveries of this species, since the 1970s are investigated to better characterise the wider movements of specialist resident. These suggest residency in southern populations, but higher instances of movement than expected in more northerly regions. In these regions wide-scale movement patterns resemble those of partial regular migratory species. An understanding of local and wide-scale spatial processes can offer a strong foundation on which to build conservation strategies. This thesis aims to use studies of space use to provide this foundation for the Bearded Reedling and offer further insight into the ecology of reedbed habitats as a whole. The thesis concludes by proposing an effective strategy for the conservation management of reedbeds that will especially benefit the Bearded Reedling.

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The analysis of investment in the electric power has been the subject of intensive research for many years. The efficient generation and distribution of electrical energy is a difficult task involving the operation of a complex network of facilities, often located over very large geographical regions. Electric power utilities have made use of an enormous range of mathematical models. Some models address time spans which last for a fraction of a second, such as those that deal with lightning strikes on transmission lines while at the other end of the scale there are models which address time horizons consisting of ten or twenty years; these usually involve long range planning issues. This thesis addresses the optimal long term capacity expansion of an interconnected power system. The aim of this study has been to derive a new, long term planning model which recognises the regional differences which exist for energy demand and which are present in the construction and operation of power plant and transmission line equipment. Perhaps the most innovative feature of the new model is the direct inclusion of regional energy demand curves in the nonlinear form. This results in a nonlinear capacity expansion model. After review of the relevant literature, the thesis first develops a model for the optimal operation of a power grid. This model directly incorporates regional demand curves. The model is a nonlinear programming problem containing both integer and continuous variables. A solution algorithm is developed which is based upon a resource decomposition scheme that separates the integer variables from the continuous ones. The decompostion of the operating problem leads to an interactive scheme which employs a mixed integer programming problem, known as the master, to generate trial operating configurations. The optimum operating conditions of each trial configuration is found using a smooth nonlinear programming model. The dual vector recovered from this model is subsequently used by the master to generate the next trial configuration. The solution algorithm progresses until lower and upper bounds converge. A range of numerical experiments are conducted and these experiments are included in the discussion. Using the operating model as a basis, a regional capacity expansion model is then developed. It determines the type, location and capacity of additional power plants and transmission lines, which are required to meet predicted electicity demands. A generalised resource decompostion scheme, similar to that used to solve the operating problem, is employed. The solution algorithm is used to solve a range of test problems and the results of these numerical experiments are reported. Finally, the expansion problem is applied to the Queensland electricity grid in Australia.

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The analysis of investment in the electric power has been the subject of intensive research for many years. The efficient generation and distribution of electrical energy is a difficult task involving the operation of a complex network of facilities, often located over very large geographical regions. Electric power utilities have made use of an enormous range of mathematical models. Some models address time spans which last for a fraction of a second, such as those that deal with lightning strikes on transmission lines while at the other end of the scale there are models which address time horizons consisting of ten or twenty years; these usually involve long range planning issues. This thesis addresses the optimal long term capacity expansion of an interconnected power system. The aim of this study has been to derive a new, long term planning model which recognises the regional differences which exist for energy demand and which are present in the construction and operation of power plant and transmission line equipment. Perhaps the most innovative feature of the new model is the direct inclusion of regional energy demand curves in the nonlinear form. This results in a nonlinear capacity expansion model. After review of the relevant literature, the thesis first develops a model for the optimal operation of a power grid. This model directly incorporates regional demand curves. The model is a nonlinear programming problem containing both integer and continuous variables. A solution algorithm is developed which is based upon a resource decomposition scheme that separates the integer variables from the continuous ones. The decompostion of the operating problem leads to an interactive scheme which employs a mixed integer programming problem, known as the master, to generate trial operating configurations. The optimum operating conditions of each trial configuration is found using a smooth nonlinear programming model. The dual vector recovered from this model is subsequently used by the master to generate the next trial configuration. The solution algorithm progresses until lower and upper bounds converge. A range of numerical experiments are conducted and these experiments are included in the discussion. Using the operating model as a basis, a regional capacity expansion model is then developed. It determines the type, location and capacity of additional power plants and transmission lines, which are required to meet predicted electicity demands. A generalised resource decompostion scheme, similar to that used to solve the operating problem, is employed. The solution algorithm is used to solve a range of test problems and the results of these numerical experiments are reported. Finally, the expansion problem is applied to the Queensland electricity grid in Australia

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In this work, the thermal expansion properties of carbon nanotube (CNT)-reinforced nanocomposites with CNT content ranging from 1 to 15 wt% were evaluated using a multi-scale numerical approach, in which the effects of two parameters, i.e., temperature and CNT content, were investigated extensively. For all CNT contents, the obtained results clearly revealed that within a wide low-temperature range (30°C ~ 62°C), thermal contraction is observed, while thermal expansion occurs in a high-temperature range (62°C ~ 120°C). It was found that at any specified CNT content, the thermal expansion properties vary with temperature - as temperature increases, the thermal expansion rate increases linearly. However, at a specified temperature, the absolute value of the thermal expansion rate decreases nonlinearly as the CNT content increases. Moreover, the results provided by the present multi-scale numerical model were in good agreement with those obtained from the corresponding theoretical analyses and experimental measurements in this work, which indicates that this multi-scale numerical approach provides a powerful tool to evaluate the thermal expansion properties of any type of CNT/polymer nanocomposites and therefore promotes the understanding on the thermal behaviors of CNT/polymer nanocomposites for their applications in temperature sensors, nanoelectronics devices, etc.

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Background The expansion of cell colonies is driven by a delicate balance of several mechanisms including cell motility, cell-to-cell adhesion and cell proliferation. New approaches that can be used to independently identify and quantify the role of each mechanism will help us understand how each mechanism contributes to the expansion process. Standard mathematical modelling approaches to describe such cell colony expansion typically neglect cell-to-cell adhesion, despite the fact that cell-to-cell adhesion is thought to play an important role. Results We use a combined experimental and mathematical modelling approach to determine the cell diffusivity, D, cell-to-cell adhesion strength, q, and cell proliferation rate, ?, in an expanding colony of MM127 melanoma cells. Using a circular barrier assay, we extract several types of experimental data and use a mathematical model to independently estimate D, q and ?. In our first set of experiments, we suppress cell proliferation and analyse three different types of data to estimate D and q. We find that standard types of data, such as the area enclosed by the leading edge of the expanding colony and more detailed cell density profiles throughout the expanding colony, does not provide sufficient information to uniquely identify D and q. We find that additional data relating to the degree of cell-to-cell clustering is required to provide independent estimates of q, and in turn D. In our second set of experiments, where proliferation is not suppressed, we use data describing temporal changes in cell density to determine the cell proliferation rate. In summary, we find that our experiments are best described using the range D = 161 - 243 ?m2 hour-1, q = 0.3 - 0.5 (low to moderate strength) and ? = 0.0305 - 0.0398 hour-1, and with these parameters we can accurately predict the temporal variations in the spatial extent and cell density profile throughout the expanding melanoma cell colony. Conclusions Our systematic approach to identify the cell diffusivity, cell-to-cell adhesion strength and cell proliferation rate highlights the importance of integrating multiple types of data to accurately quantify the factors influencing the spatial expansion of melanoma cell colonies.

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The axial coefficients of thermal expansion (CTE) of various carbon nanotubes (CNTs), i.e., single-wall carbon nanotubes (SWCNTs), and some multi-wall carbon nanotubes (MWCNTs), were predicted using molecular dynamics (MDs) simulations. The effects of two parameters, i.e., temperature and the CNT diameter, on CTE were investigated extensively. For all SWCNTs and MWCNTs, the obtained results clearly revealed that within a wide low temperature range, their axial CTEs are negative. As the diameter of CNTs decreases, this temperature range for negative axial CTEs becomes narrow, and positive axial CTEs appear in high temperature range. It was found that the axial CTEs vary nonlinearly with the temperature, however, they decrease linearly as the CNT diameter increases. Moreover, within a wide temperature range, a set of empirical formulations was proposed for evaluating the axial CTEs of armchair and zigzag SWCNTs using the above two parameters. Finally, it was found that the absolute value of the negative axial CTE of any MWCNT is much smaller than those of its constituent SWCNTs, and the average value of the CTEs of its constituent SWCNTs. The present fundamental study is very important for understanding the thermal behaviors of CNTs in such as nanocomposite temperature sensors, or nanoelectronics devices using CNTs.

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Identifying railway capacity is an important task that can identify "in principal" whether the network can handle an intended traffic flow, and whether there is any free capacity left for additional train services. Capacity determination techniques can also be used to identify how best to improve an existing network, and at least cost. In this article an optimization approach has been applied to a case study of the Iran national railway, in order to identify its current capacity and to optimally expand it given a variety of technical conditions. This railway is very important in Iran and will be upgraded extensively in the coming years. Hence the conclusions in this article may help in that endeavor. A sensitivity analysis is recommended to evaluate a wider range of possible scenarios. Hence more useful lower and upper bounds can be provided for the performance of the system

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High temperature expansion is an effective tool for studying second order phase transitions. With this in mind, we have looked at a high momentum expansion for homogeneous isotropic turbulence. Combining our results with those of the inertial range, we give another view of extended self-similarity (ESS).

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Background Aneurysm expansion rate is an important indicator of the potential risk of abdominal aortic aneurysm (AAA) rupture. Stress within the AAA wall is also thought to be a trigger for its rupture. However, the association between aneurysm wall stresses and expansion of AAA is unclear. Methods and Results Forty-four patients with AAAs were included in this longitudinal follow-up study. They were assessed by serial abdominal ultrasonography and computed tomography scans if a critical size was reached or a rapid expansion occurred. Patient-specific 3-dimensional AAA geometries were reconstructed from the follow-up computed tomography images. Structural analysis was performed to calculate the wall stresses of the AAA models at both baseline and final visit. A nonlinear large-strain finite element method was used to compute the wall-stress distribution. The relationship between wall stresses and expansion rate was investigated. Slowly and rapidly expanding aneurysms had comparable baseline maximum diameters (median, 4.35 cm [interquartile range, 4.12 to 5.0 cm] versus 4.6 cm [interquartile range, 4.2 to 5.0 cm]; P=0.32). Rapidly expanding AAAs had significantly higher shoulder stresses than slowly expanding AAAs (median, 300 kPa [interquartile range, 280 to 320 kPa] versus 225 kPa [interquartile range, 211 to 249 kPa]; P=0.0001). A good correlation between shoulder stress at baseline and expansion rate was found (r=0.71; P=0.0001). Conclusion A higher shoulder stress was found to have an association with a rapidly expanding AAA. Therefore, it may be useful for estimating the expansion of AAAs and improve risk stratification of patients with AAAs.

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Background:Quantifying genetic diversity and metapopulation structure provides insights into the evolutionary history of a species and helps develop appropriate management strategies. We provide the first assessment of genetic structure in spinner sharks (Carcharhinus brevipinna), a large cosmopolitan carcharhinid, sampled from eastern and northern Australia and South Africa. Methods and Findings:Sequencing of the mitochondrial DNA NADH dehydrogenase subunit 4 gene for 430 individuals revealed 37 haplotypes and moderately high haplotype diversity (h = 0.6770 ±0.025). While two metrics of genetic divergence (ΦST and FST) revealed somewhat different results, subdivision was detected between South Africa and all Australian locations (pairwise ΦST, range 0.02717–0.03508, p values ≤ 0.0013; pairwise FST South Africa vs New South Wales = 0.04056, p = 0.0008). Evidence for fine-scale genetic structuring was also detected along Australia’s east coast (pairwise ΦST = 0.01328, p < 0.015), and between south-eastern and northern locations (pairwise ΦST = 0.00669, p < 0.04).Conclusions: The Indian Ocean represents a robust barrier to contemporary gene flow in C. brevipinna between Australia and South Africa. Gene flow also appears restricted along a continuous continental margin in this species, with data tentatively suggesting the delineation of two management units within Australian waters. Further sampling, however, is required for a more robust evaluation of the latter finding. Evidence indicates that all sampled populations were shaped by a substantial demographic expansion event, with the resultant high genetic diversity being cause for optimism when considering conservation of this commercially-targeted species in the southern Indo-Pacific.

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Circulating tumor cells (CTCs) are the seeds for cancer metastases development, which is responsible for >90% of cancer-related deaths. Accurate quantification of CTCs in human fluids could be an invaluable tool for understanding cancer prognosis, delivering personalized medicine to prevent metastasis and finding cancer therapy effectiveness. Although CTCs were first discovered more than 200 years ago, until now it has been a nightmare for clinical practitioners to capture and diagnose CTCs in clinical settings. Our society needs rapid, sensitive, and reliable assays to identify the CTCs from blood in order to help save millions of lives. Due to the phenotypic EMT transition, CTCs are undetected for more than one-third of metastatic breast cancer patients in clinics. To tackle the above challenges, the first volume in “Circulating Tumor Cells (CTCs): Detection Methods, Health Impact and Emerging Clinical Challenges discusses recent developments of different technologies, which have the capability to target and elucidate the phenotype heterogenity of CTCS. It contains seven chapters written by world leaders in this area, covering basic science to possible device design which can have beneficial applications in society. This book is unique in its design and content, providing an in-depth analysis to elucidate biological mechanisms of cancer disease progression, CTC detection challenges, possible health effects and the latest research on evolving technologies which have the capability to tackle the above challenges. It describes the broad range of coverage on understanding CTCs biology from early predictors of the metastatic spread of cancer, new promising technology for CTC separation and detection in clinical environment and monitoring therapy efficacy via finding the heterogeneous nature of CTCs. (Imprint: Nova Biomedical)

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Modeling the distributions of species, especially of invasive species in non-native ranges, involves multiple challenges. Here, we developed some novel approaches to species distribution modeling aimed at reducing the influences of such challenges and improving the realism of projections. We estimated species-environment relationships with four modeling methods run with multiple scenarios of (1) sources of occurrences and geographically isolated background ranges for absences, (2) approaches to drawing background (absence) points, and (3) alternate sets of predictor variables. We further tested various quantitative metrics of model evaluation against biological insight. Model projections were very sensitive to the choice of training dataset. Model accuracy was much improved by using a global dataset for model training, rather than restricting data input to the species’ native range. AUC score was a poor metric for model evaluation and, if used alone, was not a useful criterion for assessing model performance. Projections away from the sampled space (i.e. into areas of potential future invasion) were very different depending on the modeling methods used, raising questions about the reliability of ensemble projections. Generalized linear models gave very unrealistic projections far away from the training region. Models that efficiently fit the dominant pattern, but exclude highly local patterns in the dataset and capture interactions as they appear in data (e.g. boosted regression trees), improved generalization of the models. Biological knowledge of the species and its distribution was important in refining choices about the best set of projections. A post-hoc test conducted on a new Partenium dataset from Nepal validated excellent predictive performance of our “best” model. We showed that vast stretches of currently uninvaded geographic areas on multiple continents harbor highly suitable habitats for Parthenium hysterophorus L. (Asteraceae; parthenium). However, discrepancies between model predictions and parthenium invasion in Australia indicate successful management for this globally significant weed. This article is protected by copyright. All rights reserved.

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Modeling the distributions of species, especially of invasive species in non-native ranges, involves multiple challenges. Here, we developed some novel approaches to species distribution modeling aimed at reducing the influences of such challenges and improving the realism of projections. We estimated species-environment relationships with four modeling methods run with multiple scenarios of (1) sources of occurrences and geographically isolated background ranges for absences, (2) approaches to drawing background (absence) points, and (3) alternate sets of predictor variables. We further tested various quantitative metrics of model evaluation against biological insight. Model projections were very sensitive to the choice of training dataset. Model accuracy was much improved by using a global dataset for model training, rather than restricting data input to the species’ native range. AUC score was a poor metric for model evaluation and, if used alone, was not a useful criterion for assessing model performance. Projections away from the sampled space (i.e. into areas of potential future invasion) were very different depending on the modeling methods used, raising questions about the reliability of ensemble projections. Generalized linear models gave very unrealistic projections far away from the training region. Models that efficiently fit the dominant pattern, but exclude highly local patterns in the dataset and capture interactions as they appear in data (e.g. boosted regression trees), improved generalization of the models. Biological knowledge of the species and its distribution was important in refining choices about the best set of projections. A post-hoc test conducted on a new Partenium dataset from Nepal validated excellent predictive performance of our “best” model. We showed that vast stretches of currently uninvaded geographic areas on multiple continents harbor highly suitable habitats for Parthenium hysterophorus L. (Asteraceae; parthenium). However, discrepancies between model predictions and parthenium invasion in Australia indicate successful management for this globally significant weed. This article is protected by copyright. All rights reserved.