948 resultados para habitat condition
Resumo:
Aim: To quantify the consequences of major threats to biodiversity, such as climate and land-use change, it is important to use explicit measures of species persistence, such as extinction risk. The extinction risk of metapopulations can be approximated through simple models, providing a regional snapshot of the extinction probability of a species. We evaluated the extinction risk of three species under different climate change scenarios in three different regions of the Mexican cloud forest, a highly fragmented habitat that is particularly vulnerable to climate change. Location: Cloud forests in Mexico. Methods: Using Maxent, we estimated the potential distribution of cloud forest for three different time horizons (2030, 2050 and 2080) and their overlap with protected areas. Then, we calculated the extinction risk of three contrasting vertebrate species for two scenarios: (1) climate change only (all suitable areas of cloud forest through time) and (2) climate and land-use change (only suitable areas within a currently protected area), using an explicit patch-occupancy approximation model and calculating the joint probability of all populations becoming extinct when the number of remaining patches was less than five. Results: Our results show that the extent of environmentally suitable areas for cloud forest in Mexico will sharply decline in the next 70 years. We discovered that if all habitat outside protected areas is transformed, then only species with small area requirements are likely to persist. With habitat loss through climate change only, high dispersal rates are sufficient for persistence, but this requires protection of all remaining cloud forest areas. Main conclusions: Even if high dispersal rates mitigate the extinction risk of species due to climate change, the synergistic impacts of changing climate and land use further threaten the persistence of species with higher area requirements. Our approach for assessing the impacts of threats on biodiversity is particularly useful when there is little time or data for detailed population viability analyses. © 2013 John Wiley & Sons Ltd.
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Object detection is a fundamental task in many computer vision applications, therefore the importance of evaluating the quality of object detection is well acknowledged in this domain. This process gives insight into the capabilities of methods in handling environmental changes. In this paper, a new method for object detection is introduced that combines the Selective Search and EdgeBoxes. We tested these three methods under environmental variations. Our experiments demonstrate the outperformance of the combination method under illumination and view point variations.
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Place recognition has long been an incompletely solved problem in that all approaches involve significant compromises. Current methods address many but never all of the critical challenges of place recognition – viewpoint-invariance, condition-invariance and minimizing training requirements. Here we present an approach that adapts state-of-the-art object proposal techniques to identify potential landmarks within an image for place recognition. We use the astonishing power of convolutional neural network features to identify matching landmark proposals between images to perform place recognition over extreme appearance and viewpoint variations. Our system does not require any form of training, all components are generic enough to be used off-the-shelf. We present a range of challenging experiments in varied viewpoint and environmental conditions. We demonstrate superior performance to current state-of-the- art techniques. Furthermore, by building on existing and widely used recognition frameworks, this approach provides a highly compatible place recognition system with the potential for easy integration of other techniques such as object detection and semantic scene interpretation.
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Traditional perceptions of the human-animal relationship in the urban context typically see the spatial rejection of wildlife from the built environment and limiting of biodiversity conservation programs to areas of natural reserve. As urban growth places further spatial demands on natural habitat and contributes to continued global biodiversity loss, the recently introduced conservation approach of reconciliation ecology makes a call promoting ecological stewardship through embedding wildlife habitat within human dominated areas. Coinciding with this, the architectural sphere has seen a recent trend of design investigation addressing artificial animal habitat as features of the built environment. Although these precedents are currently a niche and scattered trend they show potential to address the human-animal dualism challenging the framework of reconciliation ecology. This research explores the role design plays in influencing perceptions of urban wildlife habitat, particularly considering the need to create and communicate value around wildlife biodiversity as a component of urban cultural place-making and ecological literacy. The study purpose sets out to establish a set of approaches and cultural preferences with which to direct further classification and development of this architectural trend. Brisbane is utilised as a case study city, as a locale containing proximities of relatively high wildlife and human populations in an urban setting and an established legislative biodiversity heritage and ethic. Through use of a qualitative and quantitative questionnaire targeting Brisbane residents, the research methodology established that although respondents perceptions generally aligned with traditional prejudice against wildlife around human buildings, artificial habitat intervention would be supported within the CBD provided it allowed for adequate distancing of humans from wildlife and conformed with contextual surroundings, or otherwise addressed habitat through redevelopment at an urban scale. As such further research directions for artificial habitat should focus on integration of artificial habitat as a component of façade design or green infrastructure programs.
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To effectively address the high rate of failure of Insulated Rail Joints (IRJs) in the heavy haul lines, a research plan was designed and implemented with particular attention to understand their mechanical behaviour and deterioration process. In this paper, part of this ongoing research is described. During the past decades many studies have tried to improve the service life of IRJs by introducing a new structural design or material for IRJ components. This paper looks into this problem from a different perspective highlighting the significance of localised condition of track to the loads and responses of the IRJs. Results from a series of field measurements conducted in a rail track within the Australian Rail Track Corporation (ARTC) network are discussed. The interactive effects of IRJ responses and localised track condition are further investigated using the results obtained from numerical simulations. The field measurements and the simulation results provide valuable insight on the influence of track condition to the behaviour of IRJs.
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Background Understanding how different socioeconomic indicators are associated with transport modes provide insight into which interventions might contribute to reducing socioeconomic inequalities in health. The purpose of this study was to examine associations between neighbourhood-level socioeconomic disadvantage, individual-level socioeconomic position (SEP) and usual transport mode. Methods This investigation included 11,036 residents from 200 neighbourhoods in Brisbane, Australia. Respondents self-reported their usual transport mode (car or motorbike, public transport, walking or cycling). Indicators for individual-level SEP were education, occupation, and household income; and neighbourhood disadvantage was measured using a census-derived index. Data were analysed using multilevel multinomial logistic regression. High SEP respondents and residents of the most advantaged neighbourhoods who used a private motor vehicle as their usual form of transport was the reference category. Results Compared with driving a motor vehicle, the odds of using public transport were higher for white collar employees (OR1.68, 95%CrI 1.41-2.01), members of lower income households (OR 1.71 95%CrI 1.25-2.30), and residents of more disadvantaged neighbourhoods (OR 1.93, 95%CrI 1.46-2.54); and lower for respondents with a certificate-level education (OR 0.60, 95%CrI 0.49-0.74) and blue collar workers (OR 0.63, 95%CrI 0.50-0.81). The odds of walking for transport were higher for the least educated (OR 1.58, 95%CrI 1.18-2.11), those not in the labour force (OR 1.94, 95%CrI 1.38-2.72), members of lower income households (OR 2.10, 95%CrI 1.23-3.64), and residents of more disadvantaged neighbourhoods (OR 2.73, 95%CrI 1.46-5.24). The odds of cycling were lower among less educated groups (OR 0.31, 95% CrI 0.19-0.48). Conclusion The relationships between socioeconomic characteristics and transport modes are complex, and provide challenges for those attempting to encourage active forms of transportation. Further work is required exploring the individual- and neighbourhood-level mechanisms behind transport mode choice, and what factors might influence individuals from different socioeconomic backgrounds to change to more active transport modes.
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This paper presents the results of a research project aimed at examining the capabilities and challenges of two distinct but not mutually exclusive approaches to in-service bridge assessment: visual inspection and installed monitoring systems. In this study, the intended functionality of both approaches was evaluated on its ability to identify potential structural damage and to provide decision-making support. Inspection and monitoring are compared in terms of their functional performance, cost, and barriers (real and perceived) to implementation. Both methods have strengths and weaknesses across the metrics analyzed, and it is likely that a hybrid evaluation technique that adopts both approaches will optimize efficiency of condition assessment and ultimately lead to better decision making.
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Aerosol deposition in cylindrical tubes is a subject of interest to researchers and engineers in many applications of aerosol physics and metrology. Investigation of nano-particles in different aspects such as lungs, upper airways, batteries and vehicle exhaust gases is vital due the smaller size, adverse health effect and higher trouble for trapping than the micro-particles. The Lagrangian particle tracking provides an effective method for simulating the deposition of nano-particles as well as micro-particles as it accounts for the particle inertia effect as well as the Brownian excitation. However, using the Lagrangian approach for simulating ultrafine particles has been limited due to computational cost and numerical difficulties. In this paper, the deposition of nano-particles in cylindrical tubes under laminar condition is studied using the Lagrangian particle tracking method. The commercial Fluent software is used to simulate the fluid flow in the pipes and to study the deposition and dispersion of nano-particles. Different particle diameters as well as different flow rates are examined. The point analysis in a uniform flow is performed for validating the Brownian motion. The results show good agreement between the calculated deposition efficiency and the analytic correlations in the literature. Furthermore, for the nano-particles with the diameter more than 40 nm, the calculated deposition efficiency by the Lagrangian method is less than the analytic correlations based on Eulerian method due to statistical error or the inertia effect.
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The safety and performance of bridges could be monitored and evaluated by Structural Health Monitoring (SHM) systems. These systems try to identify and locate the damages in a structure and estimate their severities. Current SHM systems are applied to a single bridge, and they have not been used to monitor the structural condition of a network of bridges. This paper propose a new method which will be used in Synthetic Rating Procedures (SRP) developed by the authors of this paper and utilizes SHM systems for monitoring and evaluating the condition of a network of bridges. Synthetic rating procedures are used to assess the condition of a network of bridges and identify their ratings. As an additional part of the SRP, the method proposed in this paper can continuously monitor the behaviour of a network of bridges and therefore it can assist to prevent the sudden collapses of bridges or the disruptions to their serviceability. The method could be an important part of a bridge management system (BMS) for managers and engineers who work on condition assessment of a network of bridges.
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Foot plantar fascia is an important foot tissue in stabilizing the longitudinal arch of human foot. Direct measurement to monitor the mechanical situation of plantar fascia at human locomotion is difficult. The purpose of this study was to construct a three-dimensional finite element model of the foot to calculate the internal stress/strain value of plantar fascia during different stage of gait. The simulated stress distribution of plantar fascia was the lowest at heel-strike, which concentrated on the medial side of calcaneal tubercle. The peak stress of plantar fascia was appeared at push-off, and the value is more than 5 times of the heel-strike position. Current FE model was able to explore the plantar fascia tension trend at the main sub-phases of foot. More detailed fascia model and intrinsic muscle forces could be developed in the further study.
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This thesis evaluates a chronic condition self-management program for Aboriginal and Torres Strait Islander people in urban south-east Queensland who have or are at risk of cardiovascular disease. Outcomes showed short-term improvements for some anthropometry measures which could be a trend for improvement in other anthropometry indicators over the longer term. The program was of particular benefit for participants who had several social and emotional wellbeing conditions. The use of an Aboriginal and Torres Strait Islander conceptual framework was critical in undertaking culturally competent quantitative research in this project.
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Positive nitrogenase activities ranging from 0.18 to 0.78 nmol of C2H4 cm−2 h−1 were detected on the leaf surfaces of different varieties of cotton (Gossypium hirsutum L. and G. herbaceum L.) plants. Beijerinckia sp. was observed to be the predominant nitrogen-fixing microorganism in the phyllosphere of these varieties. A higher level of phyllosphere nitrogen-fixing activity was recorded in the variety Varalaxmi despite a low C/N ratio in the leaf leachates. Leaf surfaces of the above variety possessed the largest number of hairy outgrowths (trichomes) which entrapped a majority of microbes. Immersion of plant roots in nutrient medium containing 32Pi led to the accumulation of label in the trichome-borne microorganisms, thereby indicating a possible transfer of nutrients from leaf to microbes via trichomes. Extrapolation of acetylene reduction values suggested that 1.6 to 3.2 kg of N ha−1 might be contributed by diazotrophs in the phyllosphere of the variety Varalaxmi during the entire growth period.
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he Dirac generator formalism for relativistic Hamiltonian dynamics is reviewed along with its extension to constraint formalism. In these theories evolution is with respect to a dynamically defined parameter, and thus time evolution involves an eleventh generator. These formulations evade the No-Interaction Theorem. But the incorporation of separability reopens the question, and together with the World Line Condition leads to a second no-interaction theorem for systems of three or more particles. Proofs are omitted, but the results of recent research in this area is highlighted.
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Seagrass meadows across north-eastern Australia, survive a range of environmental conditions in coastal bays, reefs, estuarine and deepwater habitats through adaptation of a range of structural, morphological and physiological features. The aim of this study was to investigate the influence of spatial features (habitat type, site and depth) and photon flux on the photosynthetic performance of 11 tropical seagrass species. Pulse amplitude modulated (PAM) fluorometry was used to generate rapid light curves from which measures of maximal electron transport rate (ETRmax), photosynthetic efficiency (?), saturating irradiance (Ek) and effective quantum yield (?F/Fm?) were derived. The amount of light absorbed by leaves (absorption factor) was also determined for each population. In intertidal habitats many seagrass species exhibited typical sun-type responses with a close coupling of both ETRmax and Ek with photon flux. Photosynthetic performance ranged from minima in Thalassodendron ciliatum to maxima in Syringodium isoetifolium. The absence of a coupling between photosynthetic performance and photon flux in subtidal populations was most likely due to highly variable light climates and possible light attenuation, and hence the photo-biology of estuarine and deepwater seagrasses exhibited photosynthetic responses indicative of light limitation. In contrast seagrass species from shallow reef and coastal habitats for the most part exhibited light saturation characteristics. Of all the variables examined ETRmax, Ek and ?F/Fm? were most responsive to changing light climates and provide reliable physiological indicators of real-time photosynthetic performance of tropical seagrasses under different light conditions.
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This paper describes a vision-only system for place recognition in environments that are tra- versed at different times of day, when chang- ing conditions drastically affect visual appear- ance, and at different speeds, where places aren’t visited at a consistent linear rate. The ma- jor contribution is the removal of wheel-based odometry from the previously presented algo- rithm (SMART), allowing the technique to op- erate on any camera-based device; in our case a mobile phone. While we show that the di- rect application of visual odometry to our night- time datasets does not achieve a level of perfor- mance typically needed, the VO requirements of SMART are orthogonal to typical usage: firstly only the magnitude of the velocity is required, and secondly the calculated velocity signal only needs to be repeatable in any one part of the environment over day and night cycles, but not necessarily globally consistent. Our results show that the smoothing effect of motion constraints is highly beneficial for achieving a locally consis- tent, lighting-independent velocity estimate. We also show that the advantage of our patch-based technique used previously for frame recogni- tion, surprisingly, does not transfer to VO, where SIFT demonstrates equally good performance. Nevertheless, we present the SMART system us- ing only vision, which performs sequence-base place recognition in extreme low-light condi- tions where standard 6-DOF VO fails and that improves place recognition performance over odometry-less benchmarks, approaching that of wheel odometry.