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The coast is subject to increasing pressure from a multitude of often competing users. Coastal managers are faced with the challenge of balancing the distribution and activities of users. They must take into account user conflicts, environmental impacts, socioeconomic benefits, and the voices of the coastal community. On another stream. Geographic Information Systems (GIS) are being heralded as decision support tools. These tools range from inventory warehouses to dedicated Spatial Decision Support Systems (SDSS) to impending Collaborative Spatial Decision Making Systems (CSDMS) for decision-making groups. This research investigated the marriage of these two fields, coastal management and GIS, through the development and pilot implementation of a Coastal SDSS for multiple-use management. The investigation was pursued by exploring the component parts of a Coastal SDSS: (1) the decision makers and process within which they function; (2) the analysis upon which decisions are made; and (3) the data which are analysed and in themselves contribute to an understanding of the decision problem and solution. Information and observations for each of these components were gathered and woven together from five sources: (1) literature survey; (2) a two-phase questionnaire of coastal decision makers; (3) interviews of participants of a resource management multi-stakeholder process; (4) non-participant observation of an ongoing coastal management process; and (5) two workshops involving the pilot implementation of a Coastal SDSS to evaluate its effectiveness for group-based coastal management. The workshops, involving members from eight stakeholder groups, formed part of a current coastal management initiative in Barkley Sound, Vancouver Island. The pilot Coastal SDSS was programmed in Arclnfo™. It included the development of position analysis and multi-criteria analysis models accessed from a customised interface. The results from the workshops were assimilated with previous findings into design and implementation specifications of a Coastal SDSS. Twenty-one specifications are made for the development and implemention of a Coastal SDSS under categories of: 1) format; 2) decision making; 3) analysis; and 4) data. A chauffeur-driven system is advocated as the preferred format of implementation directed by a GIS facilitator and GIS analyst. Of critical importance to the successful implementation of a Coastal SDSS is adequate preparation of technical accessibility for participants. The decision making approach of a Coastal SDSS should lie in the generation and evaluation of alternatives with an emphasis on graphic communication and dynamic decision making. The analytical component of a Coastal SDSS must balance quantitative analysis with qualitative, and deterministic with interactive. Analytical specifications recommended include capability analysis, spatial coincidence, multi-criteria analysis, consensus evaluation, alternative evaluation, environmental modelling and generic GIS functionality. The points of emphasis for the data component include a taxonomy of coastal inventory with particular reference to coastal use and administrative framework, representation of the coast as a continuous transition zone between marine and terrestrial environments, cartographic communication geared towards decision making, and a metadata strategy for managing data quality. This research concludes that Coastal SDSS can fill a void in and enhance coastal management particularly with respect to supporting communication and objective spatial analytical methods. However, decision makers were cautious in embracing a central role for Coastal SDSS. Their concerns can be addressed by involving the full range of coastal decision makers in the design and development of Coastal SDSS particularly through experimental research design and by incorporating GIS into coastal management curricula. / Graduate

This thesis introduces three new model-free tests for isotropy, equal distribution and random superposition in non-rectangular windows respectively. For isotropy, a bootstrap-type test is proposed. The corresponding test statistic assesses the discrepancy between the uniform distribution and the empirical normalised reduced second-order moment measure of a sector of fixed radius with increasing central angle. The null distribution of the discrepancy is then estimated by stochastic reconstruction, which generates bootstrap-type samples of point patterns that resemble the spatial structure of the given pattern. The new test is applicable for small sample sizes and is shown to have more robust powers to different choices of user-chosen parameter when compared with the asymptotic chi-squared test by Guan et al. (2006) in our simulation. For equal distribution, a model-free asymptotic test is introduced. The proposed test statistic compares the discrepancy between the empirical second-order product densities of the observed point patterns at some pre-chosen lag vectors. Under certain mild moment conditions and a weak dependence assumption, the limiting null distribution of the test statistic is the chi-squared distribution. Simulation results show that the new test is more powerful than the permutation test by Hahn (2012) for comparing point patterns with similar structures but different distributions. The new test for random superposition is a modification of the toroidal shift test by Lotwick and Silverman (1982). The idea is to extrapolate the pattern observed in a non-rectangular window to a larger rectangular region by the stochastic reconstruction so that the toroidal shift test can be applied. Simulation results show that the powers of the test applied to patterns with extrapolated points are remarkably higher than those of the test applied to the largest inscribed rectangular windows, with only slightly increased type I error rates. Real data sets are used to illustrate the advantages of the tests developed in this thesis over the existing tests in the literature.

No description available.

This investigation was designed to test a hypothesis formulated by Julia Sherman (1967) concerning the development of spatial visualization and mathematic skills. The intention of the study was to examine the influence of early physical training on spatial visualization and mathematic skills, to determine whether intensive training in spatial relations would have a differential impact on male/female spatial performance and to gather information concerning the relationship between spatial visualization and mathematic performance. The investigation was divided into three studies and used 166 college students as subjects. Study one examined the impact of long term physical training, gymnastics, on spatial visualization and mathematic scores of two matched-groups selected from 99 subjects. The two groups, gymnast and control, each consisted of 28 subjects (14 males and 14 females) and were matched on IQ score, age, ethnic group, socioeconomic status, parental and sex-role identification, achievement motivation and years of training in other sports. Gymnasts averaged 5.5 years of gymnastic training: the control group had none. Study two examined spatial visualization scores obtained by 67 architectural students (49 males and 18 females) before and after a semester's training in spatial relations. Study three compared scores obtained by all 166 subjects on the Shepard Metzler Mental Rotation Test and a mathematic test derived from the Otis Test of Mental Abilities. The test of the hypothesis relating to the influence of early physical training on spatial and mathematic performance was not successful as the training of the gymnasts did not extend to early childhood. While significant sex-related differences favoring males were found in spatial performance, the amount of variance in spatial scores accounted for by sex was small, only 8%. No significant sex-related differences in mathematic performance were found. In study two, both males and females significantly improved spatial performance following training, but females did not demonstrate a significantly greater rate of improvement as predicted. The results of the third study indicated a moderate positive relationship between spatial and mathematic performance, however, no evidence was found to support a direct causal relationship between spatial skill and mathematic performance.

A dissertation submitted in fulfilment of the academic requirements for the degree of Master of Science in the School of Animal, Plant and Environmental Sciences, University of the Witwatersrand, Johannesburg. June 2016 / The African baobab (Adansonia digitata) is a charismatic and iconic tree. This keystone species has highly specific moisture requirements for recruitment, a very slow life history, low dispersal capabilities, and is exposed to heavy, often destructive utilization by baboons, elephants and humans. These characteristics result in the reduced ability for baobabs to accommodate and respond to changing environmental conditions. During periods of unfavourable conditions, baobabs rely on the persistence of established individuals for the survival of the population. The Kruger National Park (KNP), South Africa falls within the southern-most distribution of the baobab. A perceived lack of recruitment together with high numbers of dead large baobabs recorded in aerial surveys prompted concern over local population decline in the early 1990s. Long-term monitoring is necessary in order to quantify changes occurring within the KNP baobab population. For this reason Dr Ian Whyte sampled 424 baobab trees in northern KNP in 1995/1996 to describe population size-class distributions and elephant damage. Nearly all of these baobabs, with the addition of 486 individuals were resampled in 2001 by Michele Hofmeyr. This study resampled the majority of these 910 baobabs plus 126 individuals within 50m of those previously sampled, culminated in a data set spanning 18 years and most of the dominant vegetation and climatic zones within the baobab’s KNP range. Photographs taken in 1995/6 and repeated in 2013 allowed for simultaneous direct visual comparisons of elephant damage to baobab stems. This study aimed to record the temporal and spatial changes in the demographics of, and damage to, this sample of 1036 baobabs in order to define and evaluate the factors threatening KNP baobab persistence. The overall population stem diameter structure of baobabs in the KNP showed a healthy inverse J-shaped distribution, with a high proportion of smaller trees and a decreasing proportion of larger trees at each sampling snapshot. However no seedling recruitment was observed during intensive searches within 50m of sampled trees, accumulating in a total area of 4km2. Growth was only noticeable in sub-adult trees >0.15m and <1m in stem diameter. Annualised mortality increased three-fold between the periods 1995/6-2001 (0.25%) and 2001-2013 (0.79%). It is speculated that this increase in mortality is due to the cumulative effect of increased elephant damage, together with below average rainfall years of 2002 to 2013. Trees that had previously sustained severe and very severe damage contributed the highest proportion (32%) of mortality. When comparing sizeclasses, the majority of mortality (61%) was recorded within the <1m stem diameter size-class. However, a high proportion of very large trees (21% of the 4- 4.5m and 29% of the 5-5.5m stem-diameter baobabs sampled) had died from unknown causes. With no recruitment of seedlings evident and little recruitment between size classes, mortality alone was not enough to significantly change the baobab population structure between 1995/6, 2001 and 2013. This might change should more very large (>4m stem-diameter) trees die, as these size classes make up less than 2% of the population. At a spatial scale, maximum fire return interval, level of elephant damage and mean annual temperature all had significant impacts on the size-class distribution of baobabs. Longer (>30 years) maximum fire return intervals and higher mean annual temperatures (23°C) supported an inverse J-shaped baobab population structure whilst shorter (<30 years) maximum fire return intervals and lower mean annual temperatures (21-22°C) supported a bell-shaped population structure. Increases in bark damage over time correlated with increased elephant density (primarily attributed to mature male elephant density). Smaller baobabs – those less than <1m in stem diameter, generally escaped elephant utilization altogether, or suffered very severe damage by elephants. Despite a 3-fold increase in mortality and no recruitment over the 18 year study period, the KNP baobab population has maintained its inverse J-shaped population structure. The high proportion of mortality in the >4m stem diameter is however concerning as the persistence of these large baobabs is essential for the survival of the population during unfavourable conditions for recruitment.

This thesis develops methodologies for continuous estimation of hydrological variables which infill missing daily rainfall data and the forecast of weekly streamflows from a watershed. Several mathematical programming formulations were developed and used to estimate missing historical rainfall data. Functional relationships were created between radar precipitation and known rain gauge data then are used to estimate the missing data. Streamflow predictions models require highly non-linear mathematical models to capture the complex physical characteristics of a watershed. An artificial neural network model was developed for streamflow prediction. There are no set methods of creating a neural network and the selection of architecture and inputs to a neural network affects the performance. This thesis addresses this issue with automated input and network architecture selection through optimization. MATLABª scripts are developed and used to test many combinations and select a model through optimization. / by Ricardo Eric Brown. / Thesis (M.S.C.S.)--Florida Atlantic University, 2012. / Includes bibliography. / Electronic reproduction. Boca Raton, Fla., 2012. Mode of access: World Wide Web.

The focus of this thesis is extremal dependence among spatial observations. In particular, this research extends the notion of the extremogram to the spatial process setting. Proposed by Davis and Mikosch (2009), the extremogram measures extremal dependence for a stationary time series. The versatility and flexibility of the concept made it well suited for many time series applications including from finance and environmental science. After defining the spatial extremogram, we investigate the asymptotic properties of the empirical estimator of the spatial extremogram. To this end, two sampling scenarios are considered: 1) observations are taken on the lattice and 2) observations are taken on a continuous region in a continuous space, in which the locations are points of a homogeneous Poisson point process. For both cases, we establish the central limit theorem for the empirical spatial extremogram under general mixing and dependence conditions. A high level overview is as follows. When observations are observed on a lattice, the asymptotic results generalize those obtained in Davis and Mikosch (2009). For non-lattice cases, we define a kernel estimator of the empirical spatial extremogram and establish the central limit theorem provided the bandwidth of the kernel gets smaller and the sampling region grows at proper speeds. We illustrate the performance of the empirical spatial extremogram using simulation examples, and then demonstrate the practical use of our results with a data set of rainfall in Florida and ground-level ozone data in the eastern United States. The second part of the thesis is devoted to bootstrapping and variance estimation with a view towards constructing asymptotically correct confidence intervals. Even though the empirical spatial extremogram is asymptotically normal, the limiting variance is intractable. We consider three approaches: for lattice data, we use the circular bootstrap adapted to spatial observations, jackknife variance estimation, and subsampling variance estimation. For data sampled according to a Poisson process, we use subsampling methods to estimate the variance of the empirical spatial extremogram. We establish the (conditional) asymptotic normality for the circular block bootstrap estimator for the spatial extremogram and show L2 consistency of the variance estimated by jackknife and subsampling. Then, we propose a portmanteau style test to check the existence of extremal dependences at multiple lags. The validity of confidence intervals produced from these approaches and a portmanteau style test are demonstrated through simulation examples. Finally, we illustrate this methodology to two data sets. The first is the amount of rainfall over a grid of locations in northern Florida. The second is ground-level ozone in the eastern United States, which are recorded on an irregularly spaced set of stations.

Advanced lightweight structural materials like composites are being increasingly utilized in various engineering applications due to high specific strength and stiffness with tailorable properties. Even though composites have the advantage of modulating a large number of design parameters to achieve various application-specific requirements, this concurrently brings the challenge of dealing with inevitable uncertainties during manufacturing and service-life conditions. This dissertation focuses on practically relevant modelling of random spatial variability coupled with the influence of damage to quantify the effect of source-uncertainties following an efficient surrogate based framework. Layer-wise random variable based approach and the random field based approaches of uncertainty modelling are investigated to quantify the stochastic dynamics and stability characteristics of in a probabilistic multi-scale framework. A novel concept of stochastic representative volume element is proposed to consider the spatially varying structural attributes effectively. A physically relevant random field based modelling approach with correlated material properties is adopted based on the Karhunen-Loève expansion. To understand the relative influences, sensitivity of the stochastic input parameters are analyzed for the global structural responses of composite laminates considering micro and macro mechanical properties separately. Besides the conventional sources of uncertainty in material and structural properties, another source of uncertainty is considered in the form of noise. Besides probabilistic analysis, this dissertation proposes a fuzzy representative volume element based approach for modelling spatial variability in non-probabilistic analysis for the cases where statistical distributions of the stochastic input parameters are not available. The results reveal that stochasticity affects the system performance significantly. A notable difference in the global stochastic behaviour is identified depending upon the adopted uncertainty modeling approach. Thus, it is imperative to appropriately model the sourceuncertainties during the analysis and design process. The dissertation provides comprehensive insights on the effect of source-uncertainties on composites following an efficient, yet practically relevant modelling approach.

Harbour porpoise (Phocoena phocoena) are the most abundant cetacean in UK waters, and are likely to be affected by a variety of marine industries and activities. This research uses data collected by acoustic recorders (C-PODs) and aerial video surveys to investigate patterns in porpoise detection. The findings can be split into five key themes, and are used to support the development of spatial management and survey recommendations. 1. Porpoise detection changes based on time of day in different habitats, indicating possible differences in diel habitat use and highlighting potential issues with visual or video data collection methods for assessing distribution. 2. Porpoise exhibit seasonal shifts in detection, yet year-round data are often lacking, therefore seasonal changes in distribution are often unknown. 3. The highest proportions of buzzes (associated with foraging) are not detected in areas with the highest relative density of porpoise. I propose that porpoise use different foraging strategies in different habitats which are not equally detectable by acoustic recorders. 4. Porpoise distribution may be influenced by the distribution of perceived risk from predator / competitor species (dolphins). Temporal partitioning of sites may arise either from porpoise actively avoiding times when bottlenose dolphins are expected to be present, or from porpoise and bottlenose preferences for different environmental conditions. 5. The choice of spatial modelling method can influence the fine-scale predictions of areas with the highest density. Improving our understanding of top and mesopredator ecology is informative for management strategies. Each of the points raised above should be considered when determining management strategies to minimise the impact from fisheries, offshore developments and other industrial activities on harbour porpoise.