Knowledge of a species habitat-use patterns, as well as an understanding of the distribution and spatial arrangement of preferred habitat, is essential for developing comprehensive management or conservation plans. This information is absent for many species, especially so for those living or breeding in remote areas. Habitat-use models can assist in delineating specific habitat requirements or preferences of a species. When coupled with geographic information system (GIS) technology, such models are now frequently used to identify important habitats and to better define species distributions.<p> Recent and persistent warming, widespread contaminant accumulation, and intensifying land use in the arctic heighten the urgent need for better information about spatial distributions and key habitats for northern wildlife. Here, I used aerial survey and corresponding digital land cover data to investigate breeding-ground distributions and landscape-level habitat associations of greater white-fronted geese (Anser albifrons frontalis), small Canada geese (Branta canadensis hutchinsii), tundra swans (Cygnus columbianus), king eiders (Somateria spectabilis), and long-tailed ducks (Clangula hyemalis) in the Queen Maud Gulf Migratory Bird Sanctuary and the Rasmussen Lowlands, Nunavut, Canada.<p> First, I addressed the sensitivity of inferences about predicting waterfowl presence on the basis of the amounts and configurations of arctic habitat sampled at four scales. Detection and direction of relationships of focal species with land cover covariates often varied when land cover data were analysed at different scales. For instance, patterns of habitat use for a given species at one spatial scale may not necessarily be predicted from patterns arising from measurements taken at other scales. Thus, inference based on species-habitat patterns from some scales may lead to inaccurate depictions of how habitat influences species. Potential variation in species-environment relationships relative to spatial scale needs to be acknowledged by wildlife managers to avoid inappropriate management decisions.<p> Second, I used bird presence determined during aerial surveys and classified satellite imagery to develop species-habitat models for describing breeding-ground distributions and habitat associations of each focal species. Logistic regression models identified lowland land cover types to be particularly important for the species considered. I used the Receiver Operating Characteristic (ROC) technique and the area under the curve (AUC) metric to evaluate the precision of models, where the AUC is equal to the probability that two randomly selected encounter and non-encounter survey segments will be discriminated as such by the model. In the Queen Maud Gulf, AUC values indicated reasonable model discrimination for white-fronted geese, Canada geese, and tundra swans (i.e, AUC > 0.7). Precision of species-habitat models for king eiders and long-tailed ducks was lower than other species considered, but predict encounters and non-encounters significantly better than the null model. For all species, precision of species-habitat models was lower in the Rasmussen Lowlands than in the Queen Maud Gulf, although discrimination ability remained significantly better than the null model for three of five species (king eider and long-tailed duck models performed no better than the null model here).<p> Finally, I simulated anticipated environmental change (i.e., climate warming) in the arctic by applying species-habitat models to manipulated land cover data, and then predicted distributional responses of focal species. All species considered in this research exhibited some association to lowland cover types; white-fronted geese, Canada geese, and tundra swans in particular demonstrated strong affinity toward these habitats. Others authors predict lowland cover types to be most affected by warming. Reductions of wet sedge, hummock, and tussock graminoid cover predicted in this simulation, predominantly along the coast of the Queen Maud Gulf study area and in central areas of the Rasmussen Lowlands, suggest that distributions of species dependant on these lowland habitats will be significantly reduced, if predictions about warming and habitat loss prove to be correct. Research presented here provides evidence that modeling of species distributions using landscape-level habitat data is a tractable method to identify habitat associations, to determine key habitats and regions, and to forecast species responses to environmental changes.

The expected rise in aviation demand requires the reduction of the environmental impacts that impede this desired growth, such as fuel burn, emissions, and airport noise. A number of current technology programs attempt to identify, evaluate, and select the environmental technology solutions for the coming decades. Fleet-level evaluation will be essential to deciding between various technology options because it provides a system-level assessment that clarifies the effect of operational and policy variables. Fleet-level modeling in general, introduces various complexities, and detailed fleet-level models require significant time and computing resources to execute. With a large number of potential technology options available for assessment, a full detailed analysis of the technology space is infeasible. Therefore, a simplified fleet-level environmental evaluation methodology is required to select scenarios to carry forward for detailed modeling. Capabilities such as the Global and Regional Environmental Aviation Tradeoff (GREAT) tool, have achieved rapid simplified fleet-level analysis for fuel burn and emissions, but currently lack a satisfactory generic framework to evaluate fleet-level noise. The primary objective of this research is to formulate and implement a generic fleet-level noise methodology that allows decision makers to analyze the fleet-level impact of many technology scenarios on the quantity of noise, and also its distribution about certain airport types. This information can be leveraged to provide screening assessments of technology impacts earlier in the decision-making process, reserving more sophisticated modeling techniques for the most promising scenarios. The capability gaps identified are addressed by the development of a rapid generic fleet-level noise model that captures basic airport noise contour shape and contour area, a categorization of airports with respect to their operational and infrastructure characteristics, and the development of shape metrics that enable rapid classification and comparison of contour shapes. Once the capability gaps were addressed, the resultant System-Wide Assessment of Noise (SWAN) methodology was implemented via use cases to demonstrate the application of the methodology, examining the introduction of a set of possible near-term (N+1) future technologies into the forecast. While these examples are simplified and notional, they demonstrate the types of analyses and investigations that can be performed with the SWAN methodology, providing answers regarding the impact of technologies on contour shapes. The development, verification, validation, and demonstration of these capabilities complete a framework for evaluating fleet-level noise at the screening-level that retains the ability to capture and effectively discuss shape information beyond the capability of current screening-level noise evaluation techniques. By developing a rapid generic fleet-level noise model, a set of Generic Airports, and metrics that objectively quantify and describe shape, decision-makers can access greater levels of information, including the critical facet of contour shape in fleet-level airport noise.

Knowledge of a species habitat-use patterns, as well as an understanding of the distribution and spatial arrangement of preferred habitat, is essential for developing comprehensive management or conservation plans. This information is absent for many species, especially so for those living or breeding in remote areas. Habitat-use models can assist in delineating specific habitat requirements or preferences of a species. When coupled with geographic information system (GIS) technology, such models are now frequently used to identify important habitats and to better define species distributions.<p> Recent and persistent warming, widespread contaminant accumulation, and intensifying land use in the arctic heighten the urgent need for better information about spatial distributions and key habitats for northern wildlife. Here, I used aerial survey and corresponding digital land cover data to investigate breeding-ground distributions and landscape-level habitat associations of greater white-fronted geese (Anser albifrons frontalis), small Canada geese (Branta canadensis hutchinsii), tundra swans (Cygnus columbianus), king eiders (Somateria spectabilis), and long-tailed ducks (Clangula hyemalis) in the Queen Maud Gulf Migratory Bird Sanctuary and the Rasmussen Lowlands, Nunavut, Canada.<p> First, I addressed the sensitivity of inferences about predicting waterfowl presence on the basis of the amounts and configurations of arctic habitat sampled at four scales. Detection and direction of relationships of focal species with land cover covariates often varied when land cover data were analysed at different scales. For instance, patterns of habitat use for a given species at one spatial scale may not necessarily be predicted from patterns arising from measurements taken at other scales. Thus, inference based on species-habitat patterns from some scales may lead to inaccurate depictions of how habitat influences species. Potential variation in species-environment relationships relative to spatial scale needs to be acknowledged by wildlife managers to avoid inappropriate management decisions.<p> Second, I used bird presence determined during aerial surveys and classified satellite imagery to develop species-habitat models for describing breeding-ground distributions and habitat associations of each focal species. Logistic regression models identified lowland land cover types to be particularly important for the species considered. I used the Receiver Operating Characteristic (ROC) technique and the area under the curve (AUC) metric to evaluate the precision of models, where the AUC is equal to the probability that two randomly selected encounter and non-encounter survey segments will be discriminated as such by the model. In the Queen Maud Gulf, AUC values indicated reasonable model discrimination for white-fronted geese, Canada geese, and tundra swans (i.e, AUC > 0.7). Precision of species-habitat models for king eiders and long-tailed ducks was lower than other species considered, but predict encounters and non-encounters significantly better than the null model. For all species, precision of species-habitat models was lower in the Rasmussen Lowlands than in the Queen Maud Gulf, although discrimination ability remained significantly better than the null model for three of five species (king eider and long-tailed duck models performed no better than the null model here).<p> Finally, I simulated anticipated environmental change (i.e., climate warming) in the arctic by applying species-habitat models to manipulated land cover data, and then predicted distributional responses of focal species. All species considered in this research exhibited some association to lowland cover types; white-fronted geese, Canada geese, and tundra swans in particular demonstrated strong affinity toward these habitats. Others authors predict lowland cover types to be most affected by warming. Reductions of wet sedge, hummock, and tussock graminoid cover predicted in this simulation, predominantly along the coast of the Queen Maud Gulf study area and in central areas of the Rasmussen Lowlands, suggest that distributions of species dependant on these lowland habitats will be significantly reduced, if predictions about warming and habitat loss prove to be correct. Research presented here provides evidence that modeling of species distributions using landscape-level habitat data is a tractable method to identify habitat associations, to determine key habitats and regions, and to forecast species responses to environmental changes.

Dans le premier chapitre, on démontre divers résultats sur le plus grand quotient du groupe fondamental étale premier aux caractéristiques, parmi lesquels la formule de Künneth et l'invariance par changement de corps séparablement clos pour les schémas de type fini sur un corps. Ces énoncés sont déduits de faits généraux sur les images directes de champs, une fois spécialisés au cas des torseurs sous un groupe constant fini d'ordre inversible sur la base. Des résultats analogues<br />pour le groupe fondamental modéré sont également discutés.<br /><br />Au deuxième chapitre, on déduit de la formule du conducteur, conjecturée par S. Bloch, celle de P. Deligne exprimant, dans le cas d'une singularité isolée, la dimension totale des cycles évanescents en fonction du nombre de Milnor.<br />En particulier, la formule de Deligne est établie en dimension relative un.<br /><br />Dans le troisième chapitre, on compare les 1-isomotifs de P. Deligne sur un corps avec la théorie de V. Voevodsky en dimension inférieure à 1.

Dans cette thèse, on étude le complexe des cycles proches d'un faisceau l-adique sur un schéma au-dessus d'un trait en utilisant la théorie de ramification d'Abbes et Saito. La première partie est consacrée à une nouvelle preuve d'une formule de Deligne et Kato qui calcule la dimension du complexe des cycles proches d'un faisceau l-adique sur une courbe relative lisse au-dessus d'un trait strictement local. Deligne a considéré le cas où le faisceau n'a pas de ramification verticale, et Kato a traité le cas général. Notre approche est basée sur une notion locale de cycle caractéristiquedéfinie grâce au conducteur de Swan raffiné d'Abbes et Saito. Dans la deuxième partie, on démontre une formule qui calcule le conducteur de Swan de la cohomologie du complexe des cycles proches d'un faisceau l-adique sur une variété lisse au-dessus d'un trait d'égale caractéristique, vérifiant une certaine condition de ramification. Tsushima a introduit la classe caractéristique raffinée du faisceau et il a démontré qu'elle calcule le conducteur de Swan de la cohomologie du complexe de ses cycles proches par une formule du type Lefschetz-Verdier. On calcule la classe caractéristique raffinée comme un produit d'intersection sur le fibré cotangent logarithmique de la variété faisant apparaître le cycle caractéristique du faisceau défini par Abbes et Saito et la section nulle.

River mouths are very active coastal regions. Continuous sediment supply by the river and the movement by wave action cause the shoreline to change in time and space. Modeling of shoreline changes is an essential step before the design of any coastal engineering project. This research aimed to develop a system of numerical models to present the shoreline changes around a river mouth. The system of numerical models has three components: 1) modeling of nearshore wave characteristics, 2) modeling of longshore sand transport rates using the results of the first component, 3) modeling of shoreline changes using the estimated sand transport rates. Thus, firstly, deep water wave characteristics including the annual wave rose affecting Manavgat River mouth have been obtained from the database of NATO TU-WAVES Project. Then REF/DIF1 and SWAN nearshore wave models have been used to find out nearshore wave conditions. Since the results obtained from REF/DIF1 wave model have been found to be more reasonable compared to SWAN&rsquo / s output, REF/DIF1 wave model has been used in preparing a time series nearshore reference wave file with three hours time interval. This reference file has been used to run GENESIS. Last step of the numerical shoreline change modelling of Manavgat River mouth was the calibration procedure in which the &ldquo / transport parameters&rdquo / k1 and k2 have been determined. As there is lack of measurements of shoreline positions that can be used in calibrating shoreline change model, k1 and k2 has been approximately found to be k1=0.516 and k2=0.9 by using an empirical sediment transport formula. As a future study, it is recommended that when the protection structure controlling the river mouth is finished, the measurements of shoreline position behind the structure should be used in verification of shoreline change model in order to get more accurate results.

Relatively little published information on cyanoprokaryote (blue-green algal) blooms in the freshwater wetlands in Western Australia is available. There has been little research on the urban lakes and rivers, examining the relationship between environmental conditions and toxin-producing blooms. In this project the ecology, morphology and toxicity of cyanoprokaryota blooms in 27 metropolitan lakes and sumplands, as well as three major rivers, from 2000 to 2003, on the Swan Coastal Plain (SCP) in the southwest of Western Australia were investigated. / A total of 24 species were identified and described, of which nine species had not been previously documented in the area. This included the potentially toxic species Cylindrospermopsis raciborskii, Aphanizomenon ovalisporum and Anabaena bergii var. limnetica. An illustrated guide to the common bloom-forming species was generated using conventional taxonomic criteria. / Microcystis flos-aquae and Microcystis aeruginosa were the dominant bloom-forming cyanoprokaryotes, widespread in their distribution. Anabaena circinalis, A. bergii var. limnetica and Anabaenopsis elenkinii were the common filamentous species. Anabaena circinalis was common to certain freshwater sites, while A. bergii var. limnetica and A. elenkinii occurred in salinity ranging from fresh (< 1ppt) to hyposaline (3-10 ppt). Sites with similar species assemblages were identified using two-way indicator species analysis and clustering analysis. From this, a distinct distribution pattern emerged, which was defined by the main genera observed in the lakes – Microcystis, Anabaena, Aphanizomenon and Anabaenopsis. / The spatial and temporal distribution of the common bloom-forming cyanoprokaryote species was examined in conjunction with spring-summer physico-chemical data using principal component analysis. It was found that pH, water temperature and electrical conductivity/salinity accounted for variations among the lakes, with electrical conductivity the variable explaining the greatest variation. Lakes located on the coast, or further inland at the base of the Darling Scarp, were more hyposaline to saline, and the remaining lakes were fresh. Although the SCP lakes form consanguineous groups based on geochemistry and hydrology, no similarities among them were found in terms of water quality. / The relationship between nitrogen (N) and phosphorus (P) concentrations (total and dissolved inorganic) and cyanoprokaryote community structure (N-fixing versus non-N-fixing species) was investigated in five selected lakes; Yangebup Lake, Bibra Lake, Blue Gum Lake, Tomato Lake and Emu Lake. The lakes ranged from mesotrophic to eutrophic and supported spring-summer blooms containing multiple species. Overall an inverse relationship between cyanoprokaryote abundance and total ambient nutrient concentrations at the time of the blooms was evident. No transition in dominance in the community was observed in Yangebup Lake, Emu Lake and Bibra Lake, as they were dominated by non-heterocytic species (M. aeruginosa and M. flos-aquae) throughout spring and summer. For Yangebup Lake and Bibra Lake, the abundance of non-heterocytic species decreased concomitantly with decreasing dissolved inorganic N. In contrast, heterocytic species (A. circinalis) dominated the spring community in Tomato Lake, and summer community in Blue Gum Lake, when N and P concentrations were at their highest. / The presence of microcystins in Microcystis dominated blooms was examined using high performance chromatography. A total of 32 natural bloom samples, representing 13 lakes, were analysed for microcystin variants; -LR, -RR and -YR. Twenty-eight samples proved to be toxic with the highest total microcystin concentration from 1645 to 8428.6 µg L[superscript]-1, the lowest concentrations were less than 10 µg L[superscript]-1 with some below the detection limit. Microcystis aeruginosa and M. flos-aquae were associated with these microcystin-containing blooms, although M. flos-aquae appear to be less toxic. The presence of Nodularia spumigena in the Lake Yangebup was associated with high concentrations of nodularin (1664 µg L[superscript]-1). / Employing enzyme-linked immunosorbent assay for microcystins and the brine shrimp (Artemia) bioassays allowed a greater number of lake samples to be analysed and provided a rapid assessment of toxicity. The three methods for cyanotoxin detection verified Yangebup Lake, Herdsman Lake, Hyde Park, Jackadder Lake and Emu Lake as highly toxic sites. Low toxicity was demonstrated in samples from Lake Goollelal, Lake Joondalup, Lake Claremont, Blue Gum Lake and North Lake. These results provided the first evidence of cyanotoxin producing blooms in urban lakes of the SCP. / A comparative study on cyanoprokaryota blooms in Swan River estuary, upper Canning River and upper Serpentine River found that these sites, although hyposaline to saline, contained species that were common in the freshwater lakes. Sampling the river systems showed M. aeruginosa, M. flos-aquae, A. circinalis, A. elenkinii and Planktothrix planctonica to be cosmopolitan in distribution, present in SCP wetlands of varied salinity. Similarities between the upper Canning River and lakes in environmental conditions and species assemblage were demonstrated using multivariate analyses. / Toxin analysis of bloom samples from the Swan River and upper Canning River revealed microcystin concentrations were less than that of the surrounding lakes (1.05-124.16 µg L[superscript]-1). Similarly, nodularin concentrations were higher in Yangebup Lake than the upper Serpentine River. However, the dominance of Anabaena in Canning River samples, and the highly toxic result from the Artemia bioassay suggests microcystin is not the predominant cyanotoxin in this wetland. / This study has produced an overview of the distribution and morphology of cyanotoxin-producing cyanoprokaryotes in the SCP wetlands. The data presented provide the basis for further cyanoprokaryote research in Western Australia, in particular the molecular characterisation of bloom-forming toxic species.

Wave energy has a great potential in many coastal areas thanks to a number of advantages: the abundant resource, the highest energy density of all renewables, the greater availability factors than e.g. wind or solar energy; and the low environmental and particularly visual impact. In addition, a novel advantage will be investigated in this work: the possibility of a synergetic use for carbon-free energy production and coastal protection. In this context, wave energy can contribute not only to decarbonising the energy supply and reducing greenhouse emissions, but also to mitigating coastal erosion. In effect, wave farms will be deployed nearshore to generate electricity from wave energy, and therefore the leeward coast will be exposed to a milder wave climate, which can potentially mitigate coastal erosion. This thesis aims to determine the effectiveness of wave farms for combating coastal erosion by means of a suite of state-of-the-art process-based numerical models that are applied in several case studies (Perranporth Beach,UK; and Xago Beach, Spain) and at different time scales (from the short-term to the long-term). A wave propagation model, SWAN, is used to establish the effects of the wave farm on the wave conditions. The outcomes of SWAN will be coupled to XBeach, a costal processes model that is applied to analyse the effects of the milder wave conditions on the coast. In addition to these models, empirical classifications and analytical solutions are used as well to characterise the alteration of the beach morphology due to the presence of a wave farm. The analysis of the wave farm impacts on the wave conditions and the beach morphology will be carried out through a set of ad hoc impact indicators. Parameters such as the reduction in the significant wave height, the performance of the wave farm, the effects on the seabed level and the erosion in the beach face area are defined to characterise these impacts. Moreover, the role played by the key design parameters of wave farms, e.g. farm-to-coast distance or layout, is also examined. The results from this analysis demonstrate that wave farms, in addition to their main purpose of generating carbon-free energy, are capable of reducing erosion at the coast. Storm-induced erosion is significantly reduced due to the presence of wave farms in the areas most at risk from this phenomenon. However, the effects of wave farms on the coast do not lend themselves to general statements, for they will depend on the wave farm design (WEC type, layout and farm-to-coast distance) and the characteristics of the area in question, as shown in this document for Perranporth and Xago. In summary, this synergy will improve the economic viability of wave farm projects through savings in conventional coastal defence measures, thereby fostering the development of this nascent renewable, reducing greenhouse gas emission and converging towards a more sustainable energy model. Thus, wave energy contributes to mitigating climate change by two means, one acting on the cause, the other on the effect: (i) by bringing down carbon emissions (cause) through its production of renewable energy, and (ii) by reducing coastal erosion (effect).

The relationship between ballet and fairy tale is by no means a new or unique discovery—to either dance history or literary studies. However, aside from relatively brief mentions of ballets as examples of fairy-tale adaptation, ballet's relevance to fairy-tale studies has been somewhat undervalued. While scholars often relegate ballet to a smaller part in fairy tale's influence through the performing arts, fairy-tale ballet deserves to have its own, independent academic conversation because ballet contributes uniquely to both fairy-tale history and canon. Ballet can be credited with both giving new life to an old tale and creating a brand new one through an amalgamation of formalistic fairy-tale motifs and figures—particularly when it comes to female figures. Through an analysis of nineteenth-century Romanticism, fairy-tale form, and the narratives created by three of the most famous fairy bride ballets--La Sylphide, Giselle, and Swan Lake--we can distinguish how Romantic ballet affects fairy-tale studies because of the special conditions this "feminized" art placed on narrative and character. The pervasion of the fairy bride character and motif in ballet indicates a potentially unique tale type, and these three fairy brides together reveal a different dimension to our view of female fairy-tale characters by actively shaping their own stories according to Romantic values that place them outside of traditional fairy-tale roles. Thus, fairy-tale ballets significantly substantiate Romantic imagination beyond the bounds of literary form, and therefore both emphasize and nuance the fairy-tale female paradigm by making unique contributions to the fairy-tale canon.

Hurricane hazards result from the combined processes of wind, waves, storm surge, and overwash (Lennon et al., 1996). Predicting the severity of these hazards requires immense effort to quantify the processes and then predict how different coastal regions respond to them. A somewhat simpler, but no less daunting task is to begin to predict the hazards due to potential erosion of barrier islands. A four-part scale has been developed by Sallenger (2000) to provide a framework for understanding how barrier islands might respond during extreme storm events. These four regimes describe how beach and dune elevations interact with surge and wave runup. This study will produce estimates of potential hazards through combining lidar surveys of dune elevation with modeled elevations of storm water levels. Direct measurements of maximum wave heights during hurricanes are rare. We evaluated three simple equations proposed by Kjerfve (1986), Young (1988), and Hsu (1998) to forecast the maximum wave height (Hmax) generated by three 1999 hurricanes. Model results were compared to wave data recorded by the National Oceanic and Atmospheric Administration (NOAA) wave rider buoys. The radius of maximum winds, wind speed, forward velocity, distance from buoy to the storm's eye-wall (r), and buoy's position relative to the quadrant of the storm (Q) were found to have significant and direct roles in evaluating recorded hurricane induced wave heights (H) and thus, were individually examined for each comparison. The implications of the r and Q on H were assessed when determining the overall effectiveness of the modelers' equations. Linear regression analyses tested the accuracy of each modeled prediction of the Hmax, comparing it to the observed wave heights. Three statistical criteria were used to quantify model performance. Hsu's model was the most reliable and useful forecasting technique. Despite the predictive skill of Hsu's model, direct observations of the maximum wave conditions, when available and appropriate, are preferred as inputs for SWAN, a 3rd generation shoaling wave model. Outputs from SWAN are used to calculate the empirical relationships for wave runup. For our test case, pre and post-storm topographies were surveyed as part of a joint USGS-NASA program using lidar technology. These data sets were used to calculate changes in the elevation and location of the dune crest (Dhigh) and dune base (Dlow) for the North Carolina Outer Banks. We hindcast potential coastal hazards (erosional hot spots) using the pre-storm morphology and modeled wave runup and compare those estimates to the measured results from the post-storm survey. Links among the existing topography and spatial variations in wave runup were found to be 95% correlated for the north-south and east-west facing barrier islands. Application of Sallenger's (2000) four-part Storm Impact Scale to the pre-storm Dhigh elevation survey and wave runup extremes (Rhigh and Rlow) were found to accurately predict zones of overwash and showed potential to forecast the inundation regime.