No description available.

abstract: An understanding of diet habits is crucial in implementing proper management strategies for wildlife. Diet analysis, however, remains a challenge for ruminant species. Microhistological analysis, the method most often employed in herbivore diet studies, is tedious and time consuming. In addition, it requires considerable training and an extensive reference plant collection. The development of DNA barcoding (species identification using a standardized DNA sequence) and the availability of recent DNA sequencing techniques offer new possibilities in diet analysis for ungulates. Using fecal material collected from controlled feeding trials on pygmy goats, (Capra hicus), novel DNA barcoding technology using the P6-loop of the chloroplast trnL (UAA) intron was compared with the traditional microhistological technique. At its current stage of technological development, this study demonstrated that DNA barcoding did not enhance the ability to detect plant species in herbivore diets. A higher mean species composition was reported with microhistological analysis (79%) as compared to DNA barcoding (50%). Microhistological analysis consistently reported a higher species presence by forage class. For affect positive species identification, microhistology estimated an average of 89% correct detection in control diets, while DNA barcoding estimated 50% correct detection of species. It was hypothesized that a number of factors, including variation in chloroplast content in feed species and the effect of rumen bacteria on degradation of DNA, influenced the ability to detect plant species in herbivore diets and concluded that while DNA barcoding opens up new possibilities in the study of plant-herbivore interactions, further studies are needed to standardize techniques and for DNA bar-coding in this context. / Dissertation/Thesis / M.S. Applied Biological Sciences 2012

Translocation of wildlife has become common practice for wildlife managers charged with management of animals on increasingly modified landscapes. Translocation can be used to reduce population density in the source area, supplement existing populations, reestablish extirpated populations, and establish new populations. Mule deer (Odocoileus hemionus) are a species of great interest to the public in western North America. Although translocations have been used to manage mule deer, very little has been done to document the outcomes of this management practice. The purpose of this research was to evaluate movement, site fidelity, space use, and survival of translocated mule deer in relation to the timing of release (early versus late winter) and to provide managers with information useful in judging the relative value of translocation as a management strategy for this species. We captured 102 mule deer in January and March 2013 and translocated them from winter range near Parowan, UT, to winter range along the Pahvant Mountain Range near Holden, UT (approximately 144 km north of the capture location). Each deer was fitted with a radio transmitter (21 GPS collars, 81 VHF collars) prior to release to document outcomes. In January 2013 and 2014 we also captured and marked a total of 70 resident deer (non-translocated deer; 9 GPS collars, 61 VHF collars) to serve as a reference group within our study area. Following release, we monitored deer weekly through March 2015. We found that translocated deer had lower annual survival rates than resident deer during the first year following release, but similar annual survival rates to resident deer during the second year following release. Additionally, we found that age strongly influenced the survival of translocated deer; young deer (e.g., 2.5 year olds) were more than twice as likely to survive the initial year following translocation than old deer (e.g., 7.5 year olds). We also found that translocated deer had larger home ranges compared to resident deer during the first and second years following release. However, the average size of translocated deer home ranges decreased from year 1 to year 2 following release. Despite these large home ranges and extended movements during the summer months, most surviving deer (96 %) returned (within < 30 km) to winter range where they were released. We found no difference in movement, site fidelity, or survival for transplanted deer released in January and March. Based on our findings, wildlife managers that elect to translocate mule deer should not expect a difference in survival between early and late winter releases, but will likely see high site fidelity, higher survival rates during the second year following translocation (compared to the first year), and higher survival rates for younger deer compared to older deer.

Quaking aspen (Populus tremuloides) is the most widely distributed tree in North America (Lindroth and St Clair 2013), and a keystone species in our western montane forests (Worrall et al. 2015). Aspen has become a model organism for studies of genetics and physiology in woody plants (Bradshaw et al. 2000, Taylor 2002). Aspen is also economicallyimportant (Worrall et al. 2015) – wood is harvested for various uses, its scenic beauty helps sustain the tourism economy in many areas, and it has recently been studied as a possible source of biofuel (Sannigrahi et al. 2010). Aspen is also a species of conservation concern, due to recent large-scale deterioration and decline of many aspen forests in the last two decades (Worrall et al. 2013). Several causal factors have been identified: fire suppression (Calder et al. 2011, Smith et al. 2011), increased ungulate herbivory (Kay and Bartos 2000), disease (Marchetti et al. 2011), and climate change (Worrall et al. 2013). My thesis focuses on two different biotic stressors of aspen: a fungal pathogen and ungulate herbivory. Understanding the relationship between aspen and their biotic stressors adds to our knowledge of aspen ecology and helps manage the increasing risk of decline in our aspen forests. Chapter 1 is a study of the relationship between aspen and a necrotrophic fungal pathogen (Drepanopeziza sp.) during a major disease outbreak in 2015. I quantified the relationship between Drepanopeziza infection severity and aspen leaf functional traits, including morphological, chemical and phenological traits. I found that severe Drepanopeziza infection was associated with low concentrations of a key class of herbivore defense compounds (phenolic glycosides), and strongly associated with early budbreak and leaf-out in aspen stands. The association between infection and early budbreak was likely caused by unusually rainy conditions in May of 2015, which may have exposed leaf tissue to wet conditions that favor thedispersal of Drepanopeziza spores. Chapter 2 is an experiment designed to determine whether the mode and timing of herbivory can influence aspen's defensive response. I specifically asked whether removing leaves, twigs and meristems together and removing leaves alone had unique effects on aspen sucker growth, survival, and phytochemistry. Additionally, I applied these simulated herbivory treatments to suckers on different dates to see whether early- or late-summer herbivory had greater effects on suckers. I found strong mode and timing effects on growth and survival, but not foliar chemistry.

Shed antler hunting has increased in popularity during the past decade, but little is known about how this recreational activity affects ungulate movements and space use. We placed geographic positioning system (gps)-collars on 133 bighorn sheep (Ovis canadensis), bison (Bison bison), and mule deer (Odocoileus hemionus) to quantify their movements, space use, and resource selection during shed antler hunts on Antelope Island Utah, USA, from 2012 to 2015. In Chapter 1, we calculated means and 95% confidence intervals for distance moved during 90-minute segments (16 points/day); pre-event (control, seven consecutive days prior to event), event (one to two days), and post-event (seven consecutive days after event) for shed hunts and helicopter surveys. We also compared each species use of space during these events. Female bighorn sheep did not increase distance moved or substantially change space use during shed hunts and helicopter surveys. Male bighorn sheep increased distance moved 41% on average during shed hunts and by 2.02 times during helicopter surveys but did not change space use during those events. Female bison increased distance moved 15% on average during shed hunts and 30% during helicopter surveys. Mule deer increased distance moved and altered space use the most during shed hunts; females increased distance moved 97%, and 54% of females moved a mean distance of 742 ± 642 (SD) m outside of their home ranges during those hunts for a mean of 9.2 ± 9.4 hours (range = 1.5 to 41 hr). Male mule deer increased distance moved by 2.10 times on average during shed hunts, and 82% of males moved a mean distance of 1,264 ± 732 m outside of their home ranges during those hunts for a mean of 12.6 ± 7.6 hours. In Chapter 2, we analysed 177,138 gps locations to quantify space use and movements of 12 mule deer and 25 bighorn sheep in response to shed hunting. Twenty-five percent of mule deer and 44% of bighorn sheep responded differently to shed antler hunting across two years. We tracked four mule deer for three and four consecutive years, and all those deer responded to shed hunting differently across subsequent years. Mule deer increased movement (paired t-test = -3.9, p < 0.001) during shed hunts compared to pre-event movement. Bighorn sheep increased movement (paired t-test = -6.9, p < 0.001) during shed hunts compared to pre-event movement. In Chapter 3, we placed gps-collars on 27 mule deer and 29 bighorn sheep to quantify habitat selection during shed hunts compared with resources selection seven days prior and seven days following these hunts. Mule deer (n = 6) remained in the same area (response 1), moved to another area within their home range (n = 7; response 2), or moved beyond their home range boundaries (n = 14; response 3). Bighorn sheep (n = 17) remained in the same area (response 1), moved to another area within their home range (n = 11; response 2), or moved beyond their home range boundaries (n = 1; response 3). Shifts in resource selection by mule deer and bighorn sheep were detected during shed hunts regardless of the initial response of the individual animal during those hunts.

Monitoring population trend and estimating vital demographic parameters are essential for effective management of a mule deer (Odocoileus hemionus) population. Because of financial constraints, many wildlife agencies use computer models to obtain indirect indices of population size and trend as an alternative to annual field-based estimates of population size. These models are based primarily on herd composition counts and harvest rates from hunter-harvest surveys, and are rarely field validated. I developed an alternative method for monitoring population dynamics of wintering populations of mule deer. I designed a hybrid monitoring program that combined annual vital rate monitoring to track changes in population growth rate with a field-based approach for estimating population abundance. The program allocated resources optimally towards the most critical components of mule deer population dynamics, and consisted of 4 field surveys: annual monitoring of age ratios, overwinter fawn survival, and annual doe survival, with field-based estimates of population size only once every 4 years. Surveys were conducted from 2006 to 2008 in Wildlife Management Unit (WMU) 2, Utah, and cost $29,298 per year, prorated over 4 years. Unfortunately, financial constraints prohibit the implementation of this monitoring program in every WMU in Utah. Instead, the program can be implemented in select WMUs throughout the state, with survival data collected in these core units, providing estimates for nearby satellite units. To establish core-satellite unit pairs, I developed a proxy method for determining correlation in survival rates between core and satellite units using model-simulated estimates. I demonstrated this core-satellite method using WMU 2 as a core and WMU 3, an adjacent unit, as a satellite. Finally, I compared a multiple data sources (MDS) model with a herd composition-based population model, POP-II. The MDS model better approximated observed data, and provided statistical rigor. Overall, the hybrid program was less costly and provided more precise estimates of population trend than could be achieved with a monitoring program focused on abundance alone, and was more defensible than herd composition monitoring. After establishing correlations in doe and fawn survival between core and satellite units, data collected in core units via the hybrid program could then be used to model the mule deer population dynamics of other units using MDS modeling procedures. This combined approach could be an effective statewide program for monitoring mule deer populations.

As human populations continue to grow and encroach into wildlife habitats, instances of human-wildlife conflict are on the rise. Increasing numbers of reported wildlife-vehicle collisions (WVCs) provide tangible evidence of anthropogenic impacts on wildlife as well as increasing threats to human health and safety. Increasing WVCs are of particular concern, especially those involving large-bodied ungulates such as moose (Alces spp.), because of the increased risk of property damage, personal injuries, and human fatalities. Motorists directly involved in a WVC are at risk of injury or mortality, but other motorists are also put at risk due to road obstructions and traffic congestion associated with WVCs. Mitigating these impacts on motorists and wildlife requires investigation into the temporal and spatial factors leading to WVCs. In Alaska, most WVCs involve moose (Alces alces), a large bodied ungulate capable of threatening human life when involved in a collision. Each moose-vehicle collision (MVC) in Alaska is estimated to cost $33,000 in damages. With this analysis, I analyzed the plethora of factors contributing to moose and motorist occurrence on the road system and motorist detection based on a historical dataset of MVC reports throughout Alaska from 2000 to 2012 and a dataset of field-derived measurements at MVC locations within the Matanuska-Susitna Borough from 2016 to 2018. My first analysis focused on the daily and annual trends in MVC rates as compared to expected moose and human behavioral patterns with a focus on guiding mitigation strategies. Fifty percent of the MVCs reported between 2000 and 2012 occurred where the commuter rush hours overlapped with dusk and dawn in winter, and the artificial lighting differences between boroughs suggest a link between artificial lighting and reduced MVCs. To focus more specifically on roadside features contributing to MVC risk, I collected and analyzed local and regional scale land cover and road geometry data at reported MVC sites in an area with a rapidly growing human population. I compared these data to similar data collected at random locations near documented MVC sites and at locations where moose that were fitted with global-positioning system (GPS) transmitters crossed highways. I used generalized additive mixed models to delineate which of the variables impacted the risk of both moose road crossings and MVCs. Moose road crossings were influenced by approximations of spatial, seasonal, and daily moose density as well as the proportion of deciduous-coniferous and coniferous forest in the area and the number of possible corridor or land cover types surrounding the site. The best MVC risk model was described by expected seasonal and daily changes in moose density and local scale measurements, including the sinuosity of the road, the height of vegetation near the road, and the angle between the road surface and the roadside. Together this information should guide transportation and urban planners in the Matanuska-Susitna Borough to use roadside vegetation removal, seasonal speed reduction, improved lighting strategies, dynamic signage, or partnerships with mobile mapping services to reactively reduce MVCs and to focus future road planning in areas with lower moose abundance and build roads that increase visibility and detection distances in areas where moose are common.

No description available.

Human activities and expansion have created novel disturbance patterns across Earth’s landscapes. Disturbance is an ecological interruption after which ecosystem recovery or transition into a new state can occur, affecting biodiversity, ecosystem functioning, and theavailability of ecosystem services. Fire and herbivory are two of the most widespread forces of disturbance which shape ecosystems globally. In temperate forest ecosystems, fire affects forest composition, which influences the diversity and resilience of ecosystems (chapters 1 and 2) and forest canopy structure, which is important to snowpack accumulation and the availability of water resources (chapters 3 and 4). In chapter one, the effects of conifer competition, which occurs under fire suppression, and ungulate herbivory on aspen regeneration and recruitmentwere examined. It was found that conifer competition, and ungulate herbivory both drastically reduced successful aspen regeneration and recruitment and had a larger effect than climatic or topographical variables. In chapter two, this understanding was used to investigate mechanicaland fire interventions by the National Forest Service in a mixed aspen conifer forest experiencing fire suppression and heavy ungulate herbivory. Untreated forests failed to recruit aspen suckers successfully due to conifer competition and ungulate browsing. Fire treatments were successful in restoring aspen habitat, but mechanical treatments failed due to heavy ungulate use, despitethe treatment eliciting high sucker densities. In chapter three, fire severity was found to have important implications for snowpack accumulation and snow-water content in alpine forests. High burn severity, which is projected to become more common under future climaticconditions, led to deeper and denser snowpack possibly buffering the effects of water loss in a warmer climate. In chapter four, the interaction between topography and vegetation in burned forest conditions was evaluated. It was found that topographical aspect likely mediates the effect of vegetation on snowpack and may have an opposite effect on snow accumulation and melt on north vs south facing aspects. A synthesis of studies from different regions further supports the idea that this relationship between fire and snow is heavily dependent on latitude, elevation, and slope angle. Together, these findings demonstrate that the resilience and persistence of aspenforest ecosystems in changing disturbance regimes depend on complex interactions among disturbance type, disturbance severity, landscape position, and hydrology. These interactions should be integrated into management strategies to protect ecosystems and ensure ecosystemservices for growing human populations in the western United States.

Roads acts as barriers for wildlife and together with wildlife-vehicle collisions (WVC) they can threaten populations size and genetic diversity. Wildlife fences are a common measure to reduce WVC which can increase the barrier. Mitigation measures often used to increase landscape connectivity are fauna passages such as overpasses and underpasses that allow animals to cross the roads. These types of fauna passages are often very expensive and therefore it is of interest to find an alternative for roads that might not have the financial motivation to build such structures. This study examined the behaviour of animals in an at-grade fauna passage with an animal detection system in Sjödiken, Sweden, which was installed in 2019. A previous study of the fauna passage showed that roe deer spent a long time grazing in the entering zone and the road verge of the passage was therefore sanded. The aim of this study was to evaluate how the time in the passage changed after sanding as well as how it affected the crossing success of the animals. Results showed a decrease in time spent in the entering zone for roe deer, red deer and wild boar as well as a decrease in total time in passage for red deer and wild boar. Crossing success increased after sanding for roe deer, and red deer also showed a tendency to increased crossing success. Wild boars crossing success did not change but was high both before and after sand treatment.