927 resultados para parcel-scale spatial analysis


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1. Although population viability analysis (PVA) is widely employed, forecasts from PVA models are rarely tested. This study in a fragmented forest in southern Australia contrasted field data on patch occupancy and abundance for the arboreal marsupial greater glider Petauroides volans with predictions from a generic spatially explicit PVA model. This work represents one of the first landscape-scale tests of its type. 2. Initially we contrasted field data from a set of eucalypt forest patches totalling 437 ha with a naive null model in which forecasts of patch occupancy were made, assuming no fragmentation effects and based simply on remnant area and measured densities derived from nearby unfragmented forest. The naive null model predicted an average total of approximately 170 greater gliders, considerably greater than the true count (n = 81). 3. Congruence was examined between field data and predictions from PVA under several metapopulation modelling scenarios. The metapopulation models performed better than the naive null model. Logistic regression showed highly significant positive relationships between predicted and actual patch occupancy for the four scenarios (P = 0.001-0.006). When the model-derived probability of patch occupancy was high (0.50-0.75, 0.75-1.00), there was greater congruence between actual patch occupancy and the predicted probability of occupancy. 4. For many patches, probability distribution functions indicated that model predictions for animal abundance in a given patch were not outside those expected by chance. However, for some patches the model either substantially over-predicted or under-predicted actual abundance. Some important processes, such as inter-patch dispersal, that influence the distribution and abundance of the greater glider may not have been adequately modelled. 5. Additional landscape-scale tests of PVA models, on a wider range of species, are required to assess further predictions made using these tools. This will help determine those taxa for which predictions are and are not accurate and give insights for improving models for applied conservation management.

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With the advent of functional neuroimaging techniques, in particular functional magnetic resonance imaging (fMRI), we have gained greater insight into the neural correlates of visuospatial function. However, it may not always be easy to identify the cerebral regions most specifically associated with performance on a given task. One approach is to examine the quantitative relationships between regional activation and behavioral performance measures. In the present study, we investigated the functional neuroanatomy of two different visuospatial processing tasks, judgement of line orientation and mental rotation. Twenty-four normal participants were scanned with fMRI using blocked periodic designs for experimental task presentation. Accuracy and reaction time (RT) to each trial of both activation and baseline conditions in each experiment was recorded. Both experiments activated dorsal and ventral visual cortical areas as well as dorsolateral prefrontal cortex. More regionally specific associations with task performance were identified by estimating the association between (sinusoidal) power of functional response and mean RT to the activation condition; a permutation test based on spatial statistics was used for inference. There was significant behavioral-physiological association in right ventral extrastriate cortex for the line orientation task and in bilateral (predominantly right) superior parietal lobule for the mental rotation task. Comparable associations were not found between power of response and RT to the baseline conditions of the tasks. These data suggest that one region in a neurocognitive network may be most strongly associated with behavioral performance and this may be regarded as the computationally least efficient or rate-limiting node of the network.

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In this study we report the results of two experiments on visual attention conducted with patients with early-onset schizophrenia. These experiments investigated the effect of irrelevant spatial-scale information upon the processing of relevant spatial-scale information, and the ability to shift the spatial scale of attention, across consecutive trials, between different levels of the hierarchical stimulus. Twelve patients with early-onset schizophrenia and matched controls performed local-global tasks under: (1) directed attention conditions with a consistency manipulation and (2) divided-attention conditions. In the directed-attention paradigm, the early-onset patients exhibited the normal patterns of global advantage and interference, and were not unduly affected by the consistency manipulation. Under divided-attention conditions, however, the early-onset patients exhibited a local-processing deficit. The source of this local processing deficit lay in the prolonged reaction time to local targets, when these had been preceded by a global target, but not when preceded by a local target. These findings suggest an impaired ability to shift the spatial scale of attention from a global to a local spatial scale in early-onset schizophrenia. (C) 2003 Elsevier Science (USA). All rights reserved.

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An assessment of the changes in the distribution and extent of mangroves within Moreton Bay, southeast Queensland, Australia, was carried out. Two assessment methods were evaluated: spatial and temporal pattern metrics analysis, and change detection analysis. Currently, about 15,000 ha of mangroves are present in Moreton Bay. These mangroves are important ecosystems, but are subject to disturbance from a number of sources. Over the past 25 years, there has been a loss of more than 3800 ha, as a result of natural losses and mangrove clearing (e.g. for urban and industrial development, agriculture and aquaculture). However, areas of new mangroves have become established over the same time period, offsetting these losses to create a net loss of about 200 ha. These new mangroves have mainly appeared in the southern bay region and the bay islands, particularly on the landward edge of existing mangroves. In addition, spatial patterns and species composition of mangrove patches have changed. The pattern metrics analysis provided an overview of mangrove distribution and change in the form of single metric values, while the change detection analysis gave a more detailed and spatially explicit description of change. An analysis of the effects of spatial scales on the pattern metrics indicated that they were relatively insensitive to scale at spatial resolutions less than 50 m, but that most metrics became sensitive at coarser resolutions, a finding which has implications for mapping of mangroves based on remotely sensed data. (C) 2003 Elsevier Science B.V. All rights reserved.

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This paper analyzes the geography of regional competitiveness in manufacturing in Brazil. The authors estimate stochastic frontiers to calculate regional efficiency of representative firms in 137 regions in the period 2000-2006, in four sectors defined by technological intensity. The efficiency results are analyzed using Markov Spatial Transition Matrices to provide insights into the transition of regions between efficiency levels, considering their local spatial context. The results indicate that geography plays an important role in manufacturing competitiveness. In particular, regions with more competitive neighbors are more likely to improve their relative efficiency (pull effect) over time, and regions with less competitive neighbors are more likely to lose relative efficiency (drag effect). The authors find that the pull effect is stronger than the drag effect.

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This paper offers some preliminary steps in the marriage of some of the theoretical foundations of new economic geography with spatial computable general equilibrium models. Modelling the spatial economy of Colombia using the traditional assumptions of computable general equilibrium (CGE) models makes little sense when one territorial unit, Bogota, accounts for over one quarter of GDP and where transportation costs are high and accessibility low compared to European or North American standards. Hence, handling market imperfections becomes imperative as does the need to address internal spatial issues from the perspective of Colombia`s increasing involvement with external markets. The paper builds on the Centro de Estudios de Economia Regional (CEER) model, a spatial CGE model of the Colombian economy; non-constant returns and non-iceberg transportation costs are introduced and some simulation exercises carried out. The results confirm the asymmetric impacts that trade liberalization has on a spatial economy in which one region, Bogota, is able to more fully exploit scale economies vis--vis the rest of Colombia. The analysis also reveals the importance of different hypotheses on factor mobility and the role of price effects to better understand the consequences of trade opening in a developing economy.

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The spatial pattern of outbreaks of pink wax scale, Ceroplastes rubens Maskell, within and among umbrella trees, Schefflera actinophylla (Endl.), in southeastern Queensland was investigated. Pink wax scale was common on S. actinophylla, with approximately 84% of trees positive for scale and 14% of bees recording outbreak densities exceeding 0.4 adults per leaflet. Highly aggregated distributions of C. rubens occur within and among umbrella trees. Clumped distributions within trees appear to result from variable birth and death rates and limited movement of first instar crawlers. The patchy distribution of pink wax scale among trees is probably a consequence of variation in dispersal success of scale, host and environmental suitability for establishment and rates of biological control. Pink wax scale was more prevalent on trees in roadside positions and in exposed situations, indicating that such trees are more suitable and/or susceptible to scale colonisation.

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Functional magnetic resonance imaging (fMRI) based on BOLD signal has been used to indirectly measure the local neural activity induced by cognitive tasks or stimulation. Most fMRI data analysis is carried out using the general linear model (GLM), a statistical approach which predicts the changes in the observed BOLD response based on an expected hemodynamic response function (HRF). In cases when the task is cognitively complex or in cases of diseases, variations in shape and/or delay may reduce the reliability of results. A novel exploratory method using fMRI data, which attempts to discriminate between neurophysiological signals induced by the stimulation protocol from artifacts or other confounding factors, is introduced in this paper. This new method is based on the fusion between correlation analysis and the discrete wavelet transform, to identify similarities in the time course of the BOLD signal in a group of volunteers. We illustrate the usefulness of this approach by analyzing fMRI data from normal subjects presented with standardized human face pictures expressing different degrees of sadness. The results show that the proposed wavelet correlation analysis has greater statistical power than conventional GLM or time domain intersubject correlation analysis. (C) 2010 Elsevier B.V. All rights reserved.

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Study design: Single-blind randomized, controlled clinical study. Objectives: To evaluate, using kinematic gait analysis, the results obtained from gait training on a treadmill with body weight support versus those obtained with conventional gait training and physiotherapy. Setting: Thirty patients with sequelae from traumatic incomplete spinal cord injuries at least 12 months earlier; patients were able to walk and were classified according to motor function as ASIA (American Spinal Injury Association) impairment scale C or D. Methods: Patients were divided randomly into two groups of 15 patients by the drawing of opaque envelopes: group A (weight support) and group B (conventional). After an initial assessment, both groups underwent 30 sessions of gait training. Sessions occurred twice a week, lasted for 30min each and continued for four months. All of the patients were evaluated by a single blinded examiner using movement analysis to measure angular and linear kinematic gait parameters. Six patients (three from group A and three from group B) were excluded because they attended fewer than 85% of the training sessions. Results: There were no statistically significant differences in intra-group comparisons among the spatial-temporal variables in group B. In group A, the following significant differences in the studied spatial-temporal variables were observed: increases in velocity, distance, cadence, step length, swing phase and gait cycle duration, in addition to a reduction in stance phase. There were also no significant differences in intra-group comparisons among the angular variables in group B. However, group A achieved significant improvements in maximum hip extension and plantar flexion during stance. Conclusion: Gait training with body weight support was more effective than conventional physiotherapy for improving the spatial-temporal and kinematic gait parameters among patients with incomplete spinal cord injuries. Spinal Cord (2011) 49, 1001-1007; doi:10.1038/sc.2011.37; published online 3 May 2011

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The collection of spatial information to quantify changes to the state and condition of the environment is a fundamental component of conservation or sustainable utilization of tropical and subtropical forests, Age is an important structural attribute of old-growth forests influencing biological diversity in Australia eucalypt forests. Aerial photograph interpretation has traditionally been used for mapping the age and structure of forest stands. However this method is subjective and is not able to accurately capture fine to landscape scale variation necessary for ecological studies. Identification and mapping of fine to landscape scale vegetative structural attributes will allow the compilation of information associated with Montreal Process indicators lb and ld, which seek to determine linkages between age structure and the diversity and abundance of forest fauna populations. This project integrated measurements of structural attributes derived from a canopy-height elevation model with results from a geometrical-optical/spectral mixture analysis model to map forest age structure at a landscape scale. The availability of multiple-scale data allows the transfer of high-resolution attributes to landscape scale monitoring. Multispectral image data were obtained from a DMSV (Digital Multi-Spectral Video) sensor over St Mary's State Forest in Southeast Queensland, Australia. Local scene variance levels for different forest tapes calculated from the DMSV data were used to optimize the tree density and canopy size output in a geometric-optical model applied to a Landsat Thematic Mapper (TU) data set. Airborne laser scanner data obtained over the project area were used to calibrate a digital filter to extract tree heights from a digital elevation model that was derived from scanned colour stereopairs. The modelled estimates of tree height, crown size, and tree density were used to produce a decision-tree classification of forest successional stage at a landscape scale. The results obtained (72% accuracy), were limited in validation, but demonstrate potential for using the multi-scale methodology to provide spatial information for forestry policy objectives (ie., monitoring forest age structure).

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Performance indicators in the public sector have often been criticised for being inadequate and not conducive to analysing efficiency. The main objective of this study is to use data envelopment analysis (DEA) to examine the relative efficiency of Australian universities. Three performance models are developed, namely, overall performance, performance on delivery of educational services, and performance on fee-paying enrolments. The findings based on 1995 data show that the university sector was performing well on technical and scale efficiency but there was room for improving performance on fee-paying enrolments. There were also small slacks in input utilisation. More universities were operating at decreasing returns to scale, indicating a potential to downsize. DEA helps in identifying the reference sets for inefficient institutions and objectively determines productivity improvements. As such, it can be a valuable benchmarking tool for educational administrators and assist in more efficient allocation of scarce resources. In the absence of market mechanisms to price educational outputs, which renders traditional production or cost functions inappropriate, universities are particularly obliged to seek alternative efficiency analysis methods such as DEA.

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A laboratory scale sequencing batch reactor (SBR) operating for enhanced biological phosphorus removal (EBPR) and fed with a mixture of volatile fatty acids (VFAs) showed stable and efficient EBPR capacity over a four-year-period. Phosphorus (P), poly-beta-hydroxyalkanoate (PHA) and glycogen cycling consistent with classical anaerobic/aerobic EBPR were demonstrated with the order of anaerobic VFA uptake being propionate, acetate then butyrate. The SBR was operated without pH control and 63.67+/-13.86 mg P l(-1) was released anaerobically. The P% of the sludge fluctuated between 6% and 10% over the operating period (average of 8.04+/-1.31%). Four main morphological types of floc-forming bacteria were observed in the sludge during one year of in-tensive microscopic observation. Two of them were mainly responsible for anaerobic/aerobic P and PHA transformations. Fluorescence in situ hybridization (FISH) and post-FISH chemical staining for intracellular polyphosphate and PHA were used to determine that 'Candidatus Accumulibacter phosphatis' was the most abundant polyphosphate accumulating organism (PAO), forming large clusters of coccobacilli (1.0-1.5 mum) and comprising 53% of the sludge bacteria. Also by these methods, large coccobacillus-shaped gammaproteobacteria (2.5-3.5 mum) from a recently described novel cluster were glycogen-accumulating organisms (GAOs) comprising 13% of the bacteria. Tetrad-forming organisms (TFOs) consistent with the 'G bacterium' morphotype were alphaproteobacteria , but not Amaricoccus spp., and comprised 25% of all bacteria. According to chemical staining, TFOs were occasionally able to store PHA anaerobically and utilize it aerobically.

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The majority of the world's population now resides in urban environments and information on the internal composition and dynamics of these environments is essential to enable preservation of certain standards of living. Remotely sensed data, especially the global coverage of moderate spatial resolution satellites such as Landsat, Indian Resource Satellite and Systeme Pour I'Observation de la Terre (SPOT), offer a highly useful data source for mapping the composition of these cities and examining their changes over time. The utility and range of applications for remotely sensed data in urban environments could be improved with a more appropriate conceptual model relating urban environments to the sampling resolutions of imaging sensors and processing routines. Hence, the aim of this work was to take the Vegetation-Impervious surface-Soil (VIS) model of urban composition and match it with the most appropriate image processing methodology to deliver information on VIS composition for urban environments. Several approaches were evaluated for mapping the urban composition of Brisbane city (south-cast Queensland, Australia) using Landsat 5 Thematic Mapper data and 1:5000 aerial photographs. The methods evaluated were: image classification; interpretation of aerial photographs; and constrained linear mixture analysis. Over 900 reference sample points on four transects were extracted from the aerial photographs and used as a basis to check output of the classification and mixture analysis. Distinctive zonations of VIS related to urban composition were found in the per-pixel classification and aggregated air-photo interpretation; however, significant spectral confusion also resulted between classes. In contrast, the VIS fraction images produced from the mixture analysis enabled distinctive densities of commercial, industrial and residential zones within the city to be clearly defined, based on their relative amount of vegetation cover. The soil fraction image served as an index for areas being (re)developed. The logical match of a low (L)-resolution, spectral mixture analysis approach with the moderate spatial resolution image data, ensured the processing model matched the spectrally heterogeneous nature of the urban environments at the scale of Landsat Thematic Mapper data.