A majority of the arid grasslands in the western U.S. have been dramatically altered by anthropogenic influences resulting in degradation and desertification. Within the arid grasslands of North America a guild of burrowing herbivorous rodents that includes kangaroo rats (Dipodomys spp.) and prairie dogs (Cynomys spp.) is often considered integral to arid grassland maintenance. As part of the larger guild of burrowing herbivorous rodents, kangaroo rats are considered to be an important keystone guild whose role as ecosystem engineers and habitat modifiers complements that of prairie dogs. Together these species organize and structure arid grassland ecosystems and the biodiversity therein, by providing a mosaic of microhabitat patches, thus increasing overall heterogeneity. In an area where black-tailed prairie dogs (C. ludovicianus) were reintroduced, I used Giving-up Density (GUD) to assess the indirect effects black-tailed prairie dogs might have on the foraging patterns of resident kangaroo rats (D. spectabilis and D. merriamii). My objective was to compare and contrast kangaroo rat foraging GUD within and along the boundary of a on a recently established black-tailed prairie dog colony with that in the surrounding unmodified native habitat. This enabled assessment of whether black-tailed prairie dogs had an influence on the perceived quality of the habitat by kangaroo rats. Kangaroo rats visited off-colony feeding trays more frequently, and collected a greater mean mass of seed per tray as well. This indicates that the kangaroo rats perceived the area off the prairie dog colony as having a lower foraging cost than on the colony or along the colony edge. I conclude that from the perspective of the seed-eating kangaroo rat, the colony is not viewed as high quality habitat. What impact the reintroduction and management of one keystone species might have on another keystone species deserves additional consideration as we attempt to restore arid grassland ecosystems.

Social perspectives on natural resources management have become an increasingly valuable part of natural resources management decision making, especially at the policy or governance level. However, due to the range of social contexts that can exist around management questions, not every technique for incorporating stakeholders into management is suited for every management problem. My research examines the social landscape around chronic wasting disease (CWD) management on the Canadian prairies in order to identify a way forward for stakeholder involvement in CWD management. CWD is a prion disease that results in neurodegeneration and death in cervids. CWD has the potential for broad social impact because it infects elk and deer, species which are both hunted and ranched. Furthermore, management and monitoring efforts in free-ranging cervids frequently incorporate hunting activity. Q methodology was used to survey stakeholders in Saskatchewan and Manitoba and synthesize perspectives about stakeholder understanding of CWD as a problem and preferences for potential solutions. The perspectives that emerged emphasized the importance of increasing knowledge about CWD and a generalized trust in government management, coupled with a desire for stakeholder consultation under the auspices of government leadership. I found that CWD management may not be ready for stakeholder spearheaded management activity due to ambivalence and uncertainty among stakeholders, but stakeholder involvement in CWD management can still offer valuable insight for managers. This is especially notable in light of the recent loss of Saskatchewan’s CWD monitoring program.

No description available.

A fundamental problem in ecology is determining what factors affect the distribution of organisms across a landscape. Landscapes are by their nature heterogeneous and different habitat types confer different fitness benefits and costs to organisms that inhabit them. Ecologists are now aware of the importance of examining multiple spatial scales when designing studies quantifying animal resource selection. Scale of analysis has been shown to be important, since ecological pressures relating to the establishment of a home range differ from those relating to the use of resources within the home range. Most studies that examine multiple spatial scales examine the effect of modifying extent. Here, I examine the role of grain, an underappreciated component of scale, on our interpretation of habitat selection patterns and functional response. The goal of this thesis was to examine how grain size affects the interpretation of animal resource selection and functional response across multiple habitats. The perceptual range of an individual is known to change with habitat, therefore I hypothesized that resource selection and functional response would be both grain- and habitat-dependent, and that resource selection functions computed using different grains for different resources would be more predictive than models computed using only a single grain. I used GPS-collared white-tailed deer (Odocoileus virginianus) to quantify resource selection functions at various grains and used generalized linear mixed effects modelling and multi-model inference techniques to examine how resource selection patterns changed with spatial scale across habitat types. I used selection ratios to examine functional response across grains. Model coefficients changed with grain and the strength of selection varied by habitat type. Multi-grain resource selection functions had lower AIC values and better cross-validation scores than single grain models. Functional response varied with scale and habitat type, displaying a unique relationship for each habitat. My results suggest that spatial memory and habitat-dependent perceptual range play an important role in resource selection. I conclude that the examination of multiple grains in the study of animal habitat selection and functional response represents a step forward in our ability to understand what drives the distribution and abundance of organisms.

One of the three largest systems of black-tailed prairie dog (BTPD) colonies is located in northwestern Chihuahua, Mexico. During the last two decades, the area occupied by these colonies has been highly reduced and fragmented. Previous studies suggested that agriculture, poisoning, cattle overgrazing and shrub encroachment could be the factors responsible for such declines. However, the severe drought occurring in the region between 1994 and 2004 has not been considered in this equation. Because these populations occur in arid regions at the southern edge of the species range, they could be especially sensitive to changes in plant productivity. Furthermore, fragmentation of colonies may accelerate population declines due to size and isolation effects. In this study, I analyzed species-habitat relationships at different spatial and temporal scales to understand the causes of recent declines of BTPDs in northwestern Chihuahua. The most severe loss of colony area and most local extinctions occurred between 1988 and 2000, but most likely before 1997. Extinction of colonies before 2000 mostly occurred at small and isolated colonies in low-productivity areas. The coincidence of greatest area decline with the occurrence of most intense drought suggests a prominent role of drought in the population collapse. Overall, patterns of BTPD occurrence and abundance in Chihuahua are greatly influenced by spatial and temporal variation in forage cover. Although BTPDs were more likely to occur in open areas with short vegetation, increased forage cover positively predicted occurrence. High levels of forage cover during the dry season were positively related with BTPD density, juvenile production and population rate of change, but forage cover during the preceding rainy season was a negative predictor of demographic indices. High plant productivity during humid periods seems to have negative impacts on BTPD populations, presumably because the rapid plant growth reduces visibility and predator detection by BTPDs. The most influential landscape variable was the effective isolation of colonies. Although increased isolation may reduce the probability of occurrence at a given site, highly isolated locations may support high population densities. Contrary to my original predictions, I did not detect significant impacts of human-related factors on BTPD distribution and abundance. / Ecology

Stochastic volatility (SV) models provide a means of tracking and forecasting the variance of financial asset returns. While SV models have a number of theoretical advantages over competing variance modelling procedures they are notoriously difficult to estimate. The distinguishing feature of the SV estimation literature is that those algorithms that provide accurate parameter estimates are conceptually demanding and require a significant amount of computational resources to implement. Furthermore, although a significant number of distinct SV specifications exist, little attention has been paid to how one would choose the appropriate specification for a given data series. Motivated by these facts, a likelihood based joint estimation and specification testing procedure for SV models is introduced that significantly overcomes the operational issues surrounding existing estimators. The estimation and specification testing procedures in this thesis are made possible by the introduction of a discrete nonlinear filtering (DNF) algorithm. This procedure uses the nonlinear filtering set of equations to provide maximum likelihood estimates for the general class of nonlinear latent variable problems which includes the SV model class. The DNF algorithm provides a fast and accurate implementation of the nonlinear filtering equations by treating the continuously valued state-variable as if it were a discrete Markov variable with a large number of states. When the DNF procedure is applied to the standard SV model, very accurate parameter estimates are obtained. Since the accuracy of the DNF is comparable to other procedures, its advantages are seen as ease and speed of implementation and the provision of online filtering (prediction) of variance. Additionally, the DNF procedure is very flexible and can be used for any dynamic latent variable problem with closed form likelihood and transition functions. Likelihood based specification testing for non-nested SV specifications is undertaken by formulating and estimating an encompassing model that nests two competing SV models. Likelihood ratio statistics are then used to make judgements regarding the optimal SV specification. The proposed framework is applied to SV models that incorporate either extreme returns or asymmetries.

abstract: Once considered an abundant species in the eastern United States, local populations of red-shouldered hawks, Buteo lineatus, have declined due to habitat destruction. This destruction has created suitable habitat for red-tailed hawks, Buteo jamaicensis, and therefore increased competition between these two raptor species. Since suitable habitat is the main limiting factor for raptors, a computer model was created to simulate the effect of habitat loss in central Maryland and the impact of increased competition between the more aggressive red-tailed hawk. These simulations showed urban growth contributed to over a 30% increase in red-tailed hawk habitat as red-shouldered hawk habitat decreased 62.5-70.1% without competition and 71.8-76.3% with competition. However there was no significant difference seen between the rate of available habitat decline for current and predicted development growth. / Dissertation/Thesis / M.S. Applied Biological Sciences 2011

Human footprint - in which land is converted for human use - is a leading contributor to global habitat and biodiversity loss. The accelerated rate of human landscape change to meet our growing needs has led to the direct loss of critical habitat and shifts in species distributions, interactions, and behaviour. These altered conditions affect species’ ability to adapt to environmental stressors, while some species thrive and others decline. In North America, one ungulate has successfully invaded new habitat in conjunction with human land use – the white-tailed deer. Across the continent, the invasion of white-tailed deer has led to increased competition with other ungulate species including mule deer, moose, and woodland caribou. In regions with abundant apex predators, they have become a source of primary prey as their populations increase. The mechanisms by which deer occupy landscapes in the northern extents of their geographic range are not well studied outside of the winter months, or how deer respond behaviourally to various types of human disturbance in a predator-rich environment. To address these knowledge gaps, I examined population scale resource selection across seasons and individual movement behaviour in white-tailed deer in northeastern Alberta’s intensively developed oil and gas landscape. I used previously developed models of predator frequency to spatially extrapolate wolf and black bear occurrence across my study region as indicators of indirect predation risk. I used two approaches to habitat modeling to examine deer responses to various modes of human landscape change, including roads, seismic lines, and cut blocks in addition to predators and natural habitat. Deer were best described by cumulative effects – or the combination of all of these factors – across all seasons with proximity to linear features explaining the most variation among the parameters tested. Most prominently in winter, deer strongly selected for habitat features expected to contain abundant natural sources of forage, and linear features, despite a potential increased risk of predation by wolves – suggesting that deer make energetic trade-offs between forage availability and predation risk. At the individual level, deer significantly increased their rate of movement when occupying habitat associated with predation risk. I suggest that deer make greater energetic trade-offs during winter when mobility is limited to evade predators and energetic costs are higher. The continued use of anthropogenic features post-winter, increased rate of movement and spread of landscape occupancy by deer may allude to the importance of human disturbance in maintaining deer in northern climates. Linear corridors may be an important mechanism by which deer are able to successfully colonize new areas at the northern extents of their range. My results shed light on the drivers of deer distributions in human altered landscapes for managing populations where the invasion of deer is complicit in the decline of other ungulate species such as woodland caribou in Alberta’s boreal forest. / Graduate

Master of Science / Horticulture, Forestry, and Recreation Resources / Peg McBee / Three wildlife seed mixes were tested, Perfect Plot (BioLogic), Rack Force (Evolved Harvest), and Bird and Buck Whitetail and Gamebird mix (Star Seed). Two methods of research were conducted, (1) a food plot monitoring field study, and (2) a seed germination laboratory test. Food plots were planted in northwest (Jennings) and northeast (Manhattan) Kansas. Single season occupancy models from Program MARK were used to determine plot usage and preference of the seed mixes. Feeding patterns were analyzed from two locations targeting white-tailed deer (Odocoileus virginianus). Camera trap data were also analyzed for raccoon (Procyon lotor), wild turkey (Melagris gallopavo), and coyote (Canis latrans). During the summer 2014, the Bird and Buck mix retained the greatest amount of desirable vegetation, compared to the Rack Force and Perfect Plot mixes, which exhibited intermediate and relatively poor stand condition, respectively. White-tailed deer were documented at 100% occupancy using all (i.e., 100%) plots of all three mixes in Manhattan and Jennings, Kansas. In Manhattan, a significant increase in feeding events was observed for the months of July (45% of days) and August (50% of days) compared to the month of June (34% of days; p < 0.02). In contrast, deer feeding events in Jennings declined from 67% and 55% of days in June and July, respectively, to only 18% of days in August (p < 0.001). After initially having establishment issues among all three mixes, a laboratory study was initiated comparing the germination rates of each seed mix. Ten 1-gram random samples of each seed mix were tested in complete darkness at a constant 25-30°C for 25 days. When comparing daily germination rates of the seeds in the mixes, peak germination for all mixes (p < 0.0001) occurred on days 5-10 and 12-14. A single expected germination rate of similar plant types (i.e. alfalfa, clover, chicory, grasses) was computed from the seed tag, and then compared to the observed proportion of total seeds sampled that germinated. Bird and Buck recorded the highest germination, 79%, only 0.5% less than the expected overall germination. Perfect Plot and Rack Force recorded germination rates of 49% and 52%, which respectively, were 7% and 11% less than was expected.

Este trabalho tem como objetivo calcular intervalos de confiança para altos quantis oriundos de distribuições de caudas pesadas. Para isso, utilizamos os métodos da aproximação pela distribuição normal, razão de verossimilhanças, {\\it data tilting} e gama generalizada. Obtivemos, através de simulações, que os intervalos calculados a partir do método da gama generalizada apresentam probabilidades de cobertura bem próximas do nível de confiança, com amplitudes médias menores do que os outros três métodos, para dados gerados da distribuição Weibull. Todavia, para dados gerados da distribuição Fréchet, o método da razão de verossimilhanças fornece os melhores intervalos. Aplicamos os métodos utilizados neste trabalho a um conjunto de dados reais, referentes aos pagamentos de indenizações, em reais, de seguros de incêndio, de um determinado grupo de seguradoras no Brasil, no ano de 2003 / In this work, confidence intervals for high quantiles from heavy-tailed distributions were computed. More specifically, four methods, namely, normal approximation method, likelihood ratio method, data tilting method and generalised gamma method are used. A simulation study with data generated from Weibull distribution has shown that the generalised gamma method has better coverage probabilities with the smallest average length intervals. However, from data generated from Fréchet distribution, the likelihood ratio method gives the better intervals. Moreover, the methods used in this work are applied on a real data set from 1758 Brazilian fire claims