Orchardgrass (<i>Dactylis glomerata</i> L.) and western wheatgrass (<i>Pascopyrum smithii </i>(Rydb.) L.) seeds have different degrees of dormancy that result in non-uniform seedling emergence in the field. Seed dormancy of the two species, in part, causes disagreement between germination tests in the laboratory and seedling emergence in the field. Experiments were conducted over two years in the laboratory and in the field to determine the effects of alternating temperatures on changes in seed dormancy and germination of orchardgrass and western wheatgrass. The two western wheatgrass cultivars (Walsh and LC9078a) had deeper dormancy than the two orchardgrass cultivars (Arctic and Lineta). Dormancy of both species was broken by temperatures with 10oC amplitude; this temperature variation was similar to that which occurred at a 1 cm depth in the soil. Optimal temperatures for germination of orchardgrass (10-25oC) were broader than those for western wheatgrass (15-20oC). Seedling emergence of orchardgrass was less sensitive to seeding date in the spring than western wheatgrass; seedling emergence of western wheatgrass increased as seeding date was delayed from early to late May if soil water was not limiting. The rate of seedling emergence increased with increasing temperature in both species, therefore, faster and more uniform seedling emergence can be expected from late spring seeding dates. Seeds were often exposed to light during germination tests in the laboratory while planting seeds in the soil usually prevented exposure of seeds to light. Seedling emergence of orchardgrass in the field was usually less than the germination percentage obtained in the laboratory because of light exposure during germination tests could break dormancy in orchardgrass seeds and the small seeds of orchardgrass had limited energy reserves for pre-emergence seedling growth. On the other hand, germination of western wheatgrass seeds was reduced by exposure to light during germination and seeds were larger than those of orchardgrass. Therefore, seedling emergence of western wheatgrass in the field was usually greater than germination tests would predict. The use of thermal time models to study seed dormancy changes and germination revealed the dual effects of temperature on these processes. The modified thermal time model takes the difference between germination and seedling emergence into account and can accurately predict seedling emergence in the field (R2=0.88 to 0.99). Thermal time models for predicting seedling emergence in the field can also be developed for other forages, however, cultivar- and species-specific parameters must be developed for the models.

White spruce (<i>Picea glauca</i> (Moench) Voss), black spruce (<i>P. mariana</i> (Mill.) BSP), and jack pine (<i>Pinus banksiana</i> Lamb.) are dominant conifer trees within the boreal forest. Rising CO2 concentrations may create hotter and drier conditions in the Southern Boreal Forest of Canada, and have negative impacts on germination and regeneration of conifers. Conifers vary in their germination requirements and may have different responses to climate change. Experiments were conducted to access the germination potential, variability among collections, and to predict the ability of these conifers to germinate under future climatic conditions. Twelve collections of white spruce and black spruce and ten collections of jack pine seeds were collected from the Boreal Plain Ecozone of Saskatchewan. Seeds of all collections varied in their dormancy characteristics and dormancy breaking requirements because no single stratification or light treatment stimulated germination in all three species. Seed dormancy was greatest in white spruce and least in black spruce. Germination tests at 5, 10, 12.5, 15, 17.5, 20, 25, 30, and 35°C were used to develop thermal time models. Each species had unique temperatures for optimal germination ranging from 20°C in white spruce, 20-25°C in black spruce, and 25-30°C in jack pine. The speed of germination under similar temperature regimes was fastest for jack pine, intermediate for black spruce, and slowest for white spruce. The base temperature for white spruce decreased (r=0.63, P=0.03) with increasing June precipitation while that of jack pine tended to increase with latitude (r=0.60, P=0.07) and April precipitation (r=0.58, P=0.08). No environmental variables correlated with germination of black spruce. The Canadian Global Climate Model, version 2, with emission scenarios predicted future temperature and precipitation at the sites where seeds were collected. Using the base temperature for germination as a guideline, temperatures suitable for germination in the spring are predicted to advance by a few weeks to a month and a half earlier with increased concentrations of CO2. Moisture availability may, however, control seed germination at these sites. Overall, jack pine and black spruce might better adapt to increasing temperature because of their high germination temperatures (>30°C). Variation in most germination parameters existed among collections, suggesting this variability can be used to select seed sources for reforestation or assisted migration in a changing climate.

This dissertation collects two papers regarding the econometric and economic theory and testing of the predictability of asset returns. It is widely accepted that stock returns are not only predictable but highly so. This belief is due to an abundance of existing empirical literature fi nding often overwhelming evidence in favor of predictability. The common regressors used to test predictability (e.g., the dividend-price ratio for stock returns) are very persistent and their innovations are highly correlated with returns. Persistence when combined with a correlation between innovations in the regressor and asset returns can cause substantial over-rejection of a true null hypothesis. This result is both well documented and well known. On the other hand, stochastic volatility is both broadly accepted as a part of return time series and largely ignored by the existing econometric literature on the predictability of returns. The severe e ffect that stochastic volatility can have on standard tests are demonstrated here. These deleterious e ffects render standard tests invalid. However, this problem can be easily corrected using a simple change of chronometer. When a return time series is read in the usual way, at regular intervals of time (e.g., daily observations), then the distribution of returns is highly non-normal and displays marked time heterogeneity. If the return time series is, instead, read according to a clock based on regular intervals of volatility, then returns will be independent and identically normally distributed. This powerful result is utilized in a unique way in each chapter of this dissertation. This time-deformation technique is combined with the Cauchy t-test and the newly introduced martingale estimation technique. This dissertation nds no evidence of predictability in stock returns. Moreover, using martingale estimation, the cause of the Forward Premium Anomaly may be more easily discerned.

A credit derivative is a financial instrument whose value depends on the credit risk of an underlying asset or assets. Credit risk is the possibility that the obligor fails to honor any payment obligation. This thesis proposes four new computational methods for the valuation of credit derivatives. Compared with synthetic collateralized debt obligations (CDOs) or basket default swaps (BDS), the value of which depends on the defaults of a prescribed underlying portfolio, a forward-starting CDO or BDS has a random underlying portfolio, as some ``names'' may default before the CDO or BDS starts. We develop an approach to convert a forward product to an equivalent standard one. Therefore, we avoid having to consider the default combinations in the period between the start of the forward contract and the start of the associated CDO or BDS. In addition, we propose a hybrid method combining Monte Carlo simulation with an analytical method to obtain an effective method for pricing forward-starting BDS. Current factor copula models are static and fail to calibrate consistently against market quotes. To overcome this deficiency, we develop a novel chaining technique to build a multi-period factor copula model from several one-period factor copula models. This allows the default correlations to be time-dependent, thereby allowing the model to fit market quotes consistently. Previously developed multi-period factor copula models require multi-dimensional integration, usually computed by Monte Carlo simulation, which makes the calibration extremely time consuming. Our chaining method, on the other hand, possesses the Markov property. This allows us to compute the portfolio loss distribution of a completely homogeneous pool analytically. The multi-period factor copula is a discrete-time dynamic model. As a first step towards developing a continuous-time dynamic model, we model the default of an underlying by the first hitting time of a Wiener process, which starts from a random initial state. We find an explicit relation between the default distribution and the initial state distribution of the Wiener process. Furthermore, conditions on the existence of such a relation are discussed. This approach allows us to match market quotes consistently.

A credit derivative is a financial instrument whose value depends on the credit risk of an underlying asset or assets. Credit risk is the possibility that the obligor fails to honor any payment obligation. This thesis proposes four new computational methods for the valuation of credit derivatives. Compared with synthetic collateralized debt obligations (CDOs) or basket default swaps (BDS), the value of which depends on the defaults of a prescribed underlying portfolio, a forward-starting CDO or BDS has a random underlying portfolio, as some ``names'' may default before the CDO or BDS starts. We develop an approach to convert a forward product to an equivalent standard one. Therefore, we avoid having to consider the default combinations in the period between the start of the forward contract and the start of the associated CDO or BDS. In addition, we propose a hybrid method combining Monte Carlo simulation with an analytical method to obtain an effective method for pricing forward-starting BDS. Current factor copula models are static and fail to calibrate consistently against market quotes. To overcome this deficiency, we develop a novel chaining technique to build a multi-period factor copula model from several one-period factor copula models. This allows the default correlations to be time-dependent, thereby allowing the model to fit market quotes consistently. Previously developed multi-period factor copula models require multi-dimensional integration, usually computed by Monte Carlo simulation, which makes the calibration extremely time consuming. Our chaining method, on the other hand, possesses the Markov property. This allows us to compute the portfolio loss distribution of a completely homogeneous pool analytically. The multi-period factor copula is a discrete-time dynamic model. As a first step towards developing a continuous-time dynamic model, we model the default of an underlying by the first hitting time of a Wiener process, which starts from a random initial state. We find an explicit relation between the default distribution and the initial state distribution of the Wiener process. Furthermore, conditions on the existence of such a relation are discussed. This approach allows us to match market quotes consistently.

The concept of ecosystem services is getting more used in planning. One important type of cultural ecosystem services is recreation, which has to be consumed where it is provided in contrast to services that can be transported to the beneficiaries. This creates a demand for users to move to the site of the service, making accessibility an important characteristic of the service. In a sustainable region the access to different services, including recreation, has to be considered in planning. With general transit feed specification data available, storing spatial information and time tables for public transport, the possibility to create time table dependent travel time models emerge. This study utilizes a prototype tool for a geographic information system software to create a network model using time tables to calculate travel times between different origins and water related, cultural ecosystem services via the public transport network in Stockholm County, Sweden. This allows for mapping of spatial variation of access within a region, and by combining this with current census data and population forecasts potential visitors to different recreational sites now and in the future can be estimated. By consulting regional planners in the design of the study the results were made useful for the study area Stockholm County as planning support system.

京都大学 / 0048 / 新制・課程博士 / 博士(工学) / 甲第18311号 / 工博第3903号 / 新制||工||1599(附属図書館) / 31169 / 京都大学大学院工学研究科化学工学専攻 / (主査)教授 長谷部 伸治, 教授 大嶋 正裕, 教授 宮原 稔 / 学位規則第4条第1項該当 / Doctor of Philosophy (Engineering) / Kyoto University / DFAM

京都大学 / 0048 / 新制・課程博士 / 博士(情報学) / 甲第19340号 / 情博第592号 / 新制||情||103(附属図書館) / 32342 / 京都大学大学院情報学研究科社会情報学専攻 / (主査)教授 多々納 裕一, 教授 矢守 克也, 教授 守屋 和幸 / 学位規則第4条第1項該当 / Doctor of Informatics / Kyoto University / DGAM

Transit travel time and operating speed influence service attractiveness, operating cost, system efficiency and sustainability. The Tri-County Metropolitan Transportation District of Oregon (TriMet) provides public transportation service in the tri-county Portland metropolitan area. TriMet was one of the first transit agencies to implement a Bus Dispatch System (BDS) as a part of its overall service control and management system. TriMet has had the foresight to fully archive the BDS automatic vehicle location and automatic passenger count data for all bus trips at the stop level since 1997. More recently, the BDS system was upgraded to provide stop-level data plus 5-second resolution bus positions between stops. Rather than relying on prediction tools to determine bus trajectories (including stops and delays) between stops, the higher resolution data presents actual bus positions along each trip. Bus travel speeds and intersection signal/queuing delays may be determined using this newer information. This thesis examines the potential applications of higher resolution transit operations data for a bus route in Portland, Oregon, TriMet Route 14. BDS and 5-second resolution data from all trips during the month of October 2014 are used to determine the impacts and evaluate candidate trip time models. Comparisons are drawn between models and some conclusions are drawn regarding the utility of the higher resolution transit data. In previous research inter-stop models were developed based on the use of average or maximum speed between stops. We know that this does not represent realistic conditions of stopping at a signal/crosswalk or traffic congestion along the link. A new inter-stop trip time model is developed using the 5-second resolution data to determine the number of signals encountered by the bus along the route. The variability in inter-stop time is likely due to the effect of the delay superimposed by signals encountered. This newly developed model resulted in statistically significant results. This type of information is important to transit agencies looking to improve bus running times and reliability. These results, the benefits of archiving higher resolution data to understand bus movement between stops, and future research opportunities are also discussed.

Yes / Aquatic vegetation can significantly affect flow structure, sediment transport, bed scour and water quality in rivers, lakes, reservoirs and open channels. In this study, the lattice Boltzmann method is applied for performing the two dimensional numerical simulation of the flow structure in a flume with rigid vegetation. A multi-relaxation time model is applied to improve the stability of the numerical scheme for flow with high Reynolds number. The vegetation induced drag force is added in lattice Boltzmann equation model with the algorithm of multi-relaxation time in order to improve the simulation accuracy,. Numerical simulations are performed for a wide range of flow and vegetation conditions and are validated by comparing with the laboratory experiments. Analysis of the simulated and experimentally measured flow field shows that the numerical simulation can satisfactorily reproduce the laboratory experiments, indicating that the proposed lattice Boltzmann model has high accuracy for simulating flow-vegetation interaction in open channel. / National Natural Science Foundation of China (grant number: 11861003 and 11761005)