Thesis (M.S.)--Oregon State University, 2007. / Printout. Includes bibliographical references (leaves 101-107). Also available on the World Wide Web.

Thesis (Ph. D.)--Ohio State University, 2007. / Title from first page of PDF file. Includes bibliographical references (p. 155-167).

This thesis seeks to understand the coexistence that occurs between people and snow leopards on the roof of the world. Within a political ecology framework, it aims to show how various social and economic factors can influence this coexistence and promote the conservation of Himalayan species and ecosystems. In particular, the thesis addresses the twin assumptions that access to assets, via more diverse livelihoods, and access to influence, via decentralised conservation governance, will improve coexistence. The study opens with an assessment of household livelihoods and then compares them between two iconic but contrasting Protected Areas. The thesis then assesses: (i) knowledge of and attitudes to snow leopards; (ii) attitudes to their conservation; (iii) household livestock losses to snow leopards; and (iv) conflicts between people and snow leopard conservation. Additionally, perceptions of several proposed mitigation methods are also examined. The political ecology framework employs access theory, the Sustainable Livelihoods model and a mixed-methods approach. Using systematic sampling, a quantitative questionnaire was administered to 705 households at two sites in the Nepal Himalayas: Sagarmatha National Park, with a centralised governance model, and Annapurna Conservation Area, with a decentralised one. Seventy qualitative interviews were also collected for cross-methods triangulation. Multiple and logistic regression models were the main form of statistical analyses. Access to tourism income, and larger household size, best explained livelihoods scores. Attitudes to snow leopards were best explained by attitudes to their conservation and numbers of livestock owned per household. Attitudes to snow leopard conservation depended on perceptions of snow leopards and household livelihoods. Perceptions of conflict with snow leopards and their conservation was related to the number of livestock lost by any source of mortality. A number of variables explained attitudes to the proposed mitigation measures, including gender, livelihood strategies, livestock numbers and support for snow leopard conservation. In conclusion, access to assets and access to influence do shape human coexistence with snow leopards and their conservation, albeit in more nuanced ways than anticipated.

The aim of this work was to visualise heterogeneous deformation in snow under controlled laboratory conditions. Heterogeneous deformation was observed for both homogenous and heterogeneous loading conditions. Understanding deformation of snow is important in many scientific fields including vehicle traction, avalanche forecasting, and winter sports. This thesis investigates the deformation behaviour of snow on the centimetre scale under moderate strain rates (0.005 to 0.1 s-1) when subject to one-dimensional compression or to indentation. In order to allow controlled and repeatable snow deformation experiments, a new type of artificial snow was developed. This snow type was examined by low temperature scanning electron microscopy and by traditional avalanche observer’s methodology. Penetrometer experiments were conducted on the artificial snow and on natural seasonal snow in Scotland. The two snow types were found to be similar: results obtained on artificial snow are thus applicable to natural snow. A reproducible technique of manufacture and a thorough characterisation of the artificial snow are presented. One-dimensional compression experiments were conducted on the artificial snow. The experiments were in confined compression in a specially constructed apparatus, designed to provide for back-lit photography. Images were taken at 0.25 second intervals and analysed using digital image correlation, thus providing 2D strain fields. With careful control of photographic parameters, it is demonstrated that process of applying tracer substances to the snow is not necessary, thus allowing an unprecedented resolution. Spontaneously-forming strain localisations were observed for the first time, indicating strain softening behaviour. Damage was observed to propagate through the specimen as a moving front, resembling a wave. The force required to propagate the front remained nearly constant until the whole specimen was compacted, at which point a new front formed and the process repeated. The experimental method was extended to 2D indention experiments with a range of sizes and shapes of indenter. Complex deformation fields were observed, extending up to 6 times the width of the indenter on each side. Observed deformation included tensile tearing as well as compression and shear. The maximum local strain achieved in the indentation experiments was similar to that achieved by the first compaction front in one-dimensional compression. The work here presented has implications for snow deformation generally: strain localisation introduces a characteristic length, which may prevent scaling of models or results. The indentation results are particularly relevant to snow penetrometry, where indentation experiments are used to try and extract microstructural information from buried snow layers for the purpose of avalanche prediction. The common assumption that the penetrometer interacts only with snow very close to its tip may need to be reconsidered.

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Accurate knowledge of water content in seasonal snow can be helpful for water resource management. In this study, a distributed temperature index snow model based on temperature and precipitation as forcing data, is used to estimate snow storage in the Jollie catchment approximately 20km east of the main divide of the central Southern Alps, New Zealand. The main objective is to apply a frequently used assimilation method, the ensemble Kalman square root filter, to assimilate remotely sensed snow covered area into the model and evaluate the impacts of this approach on simulations of snow water equivalent. A 250m resolution remotely sensed data from Moderate Resolution Imaging Spectroradiometer (MODIS), specifically tuned to the study location was used. Temperature and precipitation were given on a 0.055 latitude/longitude grid. Precipitation was perturbed as input into the model, generating 100 ensemble members, which represented model error. Only observations of snow covered area that had less that 25% cloud cover classification were used in the assimilation precess. The error in the snow covered area observations was assumed to be 0.1 and grow linearly with cloud cover fraction up to 1 for a totally cloud covered pixel. As the model was not calibrated, two withholding experiments were conducted, in which observations withheld from the assimilation process were compared to the results. Two model states were updated in the assimilation, the total snow accumulation state variable and the total snow melt state variable. The results of this study indicate that the model underestimates snow storage at the end of winter and/or does not detect snow fall events during the ablation period. The assimilation method only affected simulated snow covered area and snow storage during the ablation period. That corresponded to higher correlation between modelled snow cover area and the updated state variables. Withholding experiments show good agreement between observations and simulated snow covered area. This study successfully applied the ensemble Kalman square root filter and showed its applicability for New Zealand conditions.

The snow cover plays an important role not only for the whole climate system but also for tourism and economy in the Lapland winter (e.g. dog sledding, snow mobile, etc). Snow constitutes a shelter for animals and plants during the winter due to thermal isolation, but, on the range of this investigation, it can make grazing difficult for reindeers, if the conditions are not favorable. Different approaches to the study have been made; the first and most important part of the investigation was a campaign in Järämä, in Swedish Lapland. During 3 days (between the 3rd and 5th of March 2009), a series of snow pits were done, recording snow grain size, snow layers depth, snow hardness/compactness, density and temperature. The hardness in the snow was evaluated through ram penetration tests. It was additionally studied the correspondence between the snow layers found in situ and the Sámi terminology. Another approach of the study consisted of satellite observations during the winter season 2008/2009 with day light in the region. The type of imagery used was MODIS (The Moderate Resolution Imaging Spectroradiometer) daily snow albedo and 8-day surface reflectance products. Measurements of temperature, precipitation, snow depth were used to cover the polar night time when satellite images were missing. According to these weather observations some snow metamorphisms were also studied, and their influence on the snowpack conditions. Through the comparison between all these forms of data it was found that in the winter season 2008/2009 the conditions for reindeers grazing were not good due to the formation of ice encapsulating the lichens and grass. Additionally several hard snow layers have been found in the snowpack which increase the difficulty to dig in the snow and may cause problems to the reindeers’ digestion. Snow hardness measurements with a ram penetrometer, manual tests and visual grain size observation proved these discovers. Several periods of positive temperature may cause melting/refreezing cycles contributing to the formation of hard snow layers. These conclusions are supported by the snow albedo and surface reflectance satellite imagery. In these images is visible a period with snow albedo decreasing a lot in the beginning of autumn, after the first lasting snowfall. The weather conditions in early fall, when the first durable snow occurs, are of extreme importance for the reindeers’ grazing, and in the case of the studied winter season, the conditions were not favorable.

Accurate knowledge of water content in seasonal snow can be helpful for water resource management. In this study, a distributed temperature index snow model based on temperature and precipitation as forcing data, is used to estimate snow storage in the Jollie catchment approximately 20km east of the main divide of the central Southern Alps, New Zealand. The main objective is to apply a frequently used assimilation method, the ensemble Kalman square root filter, to assimilate remotely sensed snow covered area into the model and evaluate the impacts of this approach on simulations of snow water equivalent. A 250m resolution remotely sensed data from Moderate Resolution Imaging Spectroradiometer (MODIS), specifically tuned to the study location was used. Temperature and precipitation were given on a 0.055 latitude/longitude grid. Precipitation was perturbed as input into the model, generating 100 ensemble members, which represented model error. Only observations of snow covered area that had less that 25% cloud cover classification were used in the assimilation precess. The error in the snow covered area observations was assumed to be 0.1 and grow linearly with cloud cover fraction up to 1 for a totally cloud covered pixel. As the model was not calibrated, two withholding experiments were conducted, in which observations withheld from the assimilation process were compared to the results. Two model states were updated in the assimilation, the total snow accumulation state variable and the total snow melt state variable. The results of this study indicate that the model underestimates snow storage at the end of winter and/or does not detect snow fall events during the ablation period. The assimilation method only affected simulated snow covered area and snow storage during the ablation period. That corresponded to higher correlation between modelled snow cover area and the updated state variables. Withholding experiments show good agreement between observations and simulated snow covered area. This study successfully applied the ensemble Kalman square root filter and showed its applicability for New Zealand conditions.