Understanding the link between environmental factors such as disturbance events, land cover, and soil productivity to spatial variation in animal distributions and vital rates is fundamental to population ecology and wildlife management. The Longleaf pine (Pinus palustris; hereafter, LLP) ecosystem is an archetypal fire-mediated ecosystem, which has seen drastic reductions in land area due to fire suppression. Current restoration utilizes prescribed fire and hardwood removal, but more research is needed to understand the influence of these restoration efforts on the wildlife that exist in that ecosystem. As such, we conducted field surveys on Camp Blanding Joint Training Center and Wildlife Management Area to understand how fire influences relative abundances of mammalian predators, occupancy and species richness of avian species, guilds and communities, and vital rates of white-tailed deer (Odocoileus viginianus) fawns. Our results indicated that mammalian predator space use, and avian species richness were influenced by fire and land cover. Mammalian predator space use was altered by fire conditions and land cover. This mechanism may support predator management strategies that utilizes commonly management techniques for the restoration and conservation of the LLP ecosystem to indirectly alter predator distributions, which has the potential to positively affect the management of important species within this ecosystem. Some mammalian mesocarnivores historically common throughout the southeastern United States were rarely detected, suggesting more research is needed to identify the cause of the potential decline in mesocarnivores in the Southeastern United States. Avian species richness at the community level was positively influenced by the heterogeneity of post fire conditions, or pyrodiversity. Avian species richness of the cavity nesting guild was negatively influenced by increasing time-since-fire. Our results suggest that managers can promote avian community diversity by reducing the size of burn units to create areas with multiple adjacent burn units, with unique fire histories and a mosaic of post-fire conditions. Lastly, fawn recruitment was greater on the higher productivity site than the low productivity site on CB. However, within sites soil productivity did not have a demonstrable effect. In fact, we observed differences between sites, but did not observe any effects of covariates on spatial variation in density or survival of fawns within sites. Although we did not explicitly test the factors influencing our parameters between sites, we hypothesize that the variation in coyote activity rates as well as soil productivity and its subsequent effects (i.e. forage availability, concealment cover, and land cover type) likely drove the differences we saw between sites. These results are relevant to local managers and provide support for unit-specific, deer management on CB. In conclusion, understanding the influence of fire in a frequently burned landscape allows us to better inform management of predators and avian communities using prescribed burns, and the differences in deer populations between areas allowed us to better in inform managers on harvest quotas so that the magnitude of the effect of harvest can better match the population vital rates of each area. / Master of Science / Understanding the link between environmental factors such as fire, land cover and soil productivity is essential for wildlife managers to maintain healthy wildlife populations. The Longleaf pine (Pinus palustris) ecosystem requires frequent fire and has seen drastic reductions in land area due to fire suppression. Current restoration utilizes prescribed fire, controlled burning of an area, and hardwood removal, logging hardwood trees such as oaks, but more research is needed to understand how this restoration influences the wildlife in the longleaf pine ecosystem. As such, we collected data collected from Camp Blanding Joint Training Center and Wildlife Management Area to understand how fire influences the relative numbers of mammalian predators, the distribution and species richness (i.e. number of unique species) of avian species, guilds and communities, and vital rates (i.e. births, survival to a certain age) of white-tailed deer fawns. Our results indicated that mammalian predator distributions, and avian species richness were influenced by fire and land cover. Mammalian predator space use was altered by fire conditions and landcover, which supports a predator management strategy that utilizes prescribed burning and hardwood removal used in restoration and conservation of the LLP ecosystem to indirectly alter predator distributions. Some mammalian mesocarnivores (i.e. foxes, skunks, weasels, etc.) historically common throughout the southeastern United States were rarely detected, suggesting more research is needed to identify the cause of the potential decline of cryptic mesocarnivores in the Southeastern United States. Avian species richness, number of unique species, at the community level was positively influenced by pyrodiversity, the number of unique burn years in an area. This supports and further extends the 'pyrodiversity begets biodiversity' hypothesis for avian species, which states that greater pyrodiversity increases the diversity of bird species in that area. Avian species richness of cavity nesting birds decreased with increasing time since fire. Our results suggest that managers can promote avian community diversity by reducing the size of burn units to create areas with multiple adjacent burn units, with unique fire histories and a mosaic of post-fire conditions. Lastly, fawn recruitment was greater on the higher productivity site than the low productivity site, however, within sites soil productivity did not seem to influence birth and recruitment. Although we did not statistically test the factors influencing our parameters between sites, we hypothesize that the variation in coyote activity rates as well as soil productivity and its subsequent effects (i.e. forage availability, concealment cover, and land cover type) likely drove the differences we saw between sites. These results are relevant to local managers and provide support for managing deer differently across both sites. In conclusion, understanding the influence of fire in a frequently burned landscape allows us to better inform management of predators and avian communities using prescribed burns, and the differences in deer populations between areas allowed us to better in inform managers on harvest quotas so that the magnitude of the effect of harvest can better match the population vital rates of each area.

An island subspecies endemic to the remote St Kilda archipelago, Apodemus sylvaticus hirtensis is considered of national importance but has been little studied, despite its inclusion in the criteria for the islands’ designation as a World Heritage Site. This study expands our knowledge of the core ecology of the mice; distribution, morphology, age structure, breeding phenology, population density, range size, survival and fecundity are all described and quantified using data collected from 4462 captures of 787 individuals between 2009-2012 on three sites (Carn Mor, Glen Bay & Village Bay), 1-2km apart on the main island of Hirta. Morphological analysis confirmed the reputed gigantism the mice, with maximum body weights of 60g for males and 50.5g for a non-gravid female both being approximately double that of a mainland specimen (the heaviest gravid female caught weighed 56g). Sexual dimorphism was evident, with males >1 year old being 8.7% heavier than females on average. Significant geographical variation in size was also found; mice on the seabird breeding colony of Carn Mor were heavier, longer and in better condition than mice elsewhere. Mice were observed to have a well-defined breeding season between April and September, shorter than on the mainland, with most individuals not breeding until their second year and very few surviving two winters. No geographical differences were found in the proportion of adult mice more than a year old that were in breeding condition at any given time, although there were significant geographical differences in the proportion of individuals in breeding condition for ‘young adult’ mice entering their first spring and sub adult mice in the autumn of the year in which they were. Spatially explicit capture-recapture (SECR) methods were used to quantify population densities free from ad hoc methods of trapping area estimation. Temporal variation in population size typical of temperate small mammals was found, with densities as low as 2 mice/ha in spring, increasing through summer and autumn with juvenile recruitment until reaching a peak at the beginning of winter of up to 50 mice/ha. Geographical variation was again observed, with frequent significant differences between trapping sites and an overall trend of highest population densities on the seabird breeding site. Mean individual range sizes varied between 0.3-3.0ha and were largest in Village Bay and in males in breeding condition. Pradel robust design recruitment models were used to quantify monthly survival (0.67-1.00) and fecundity (0.03- 0.41) and overall rate of population change (0.81-1.52) between sessions. Survival varied little between grids outside of the breeding season, but tended to be greater in Carn Mor than Village Bay during the summer. Fecundity rates varied little between years and grids, with one exception where increased summer fecundity followed a severe winter decline on Carn Mor. The possible role of differences in the quality of the food supply (in particular the seabird breeding colony and spatial variation in sheep grazing pressure) on creating geographical variation in body size, condition, breeding phenology, density and population dynamics are discussed in detail, as is the overall pattern of insular traits found in the mice.

Longitudinal data are common in biological research. However, real data sets vary considerably in terms of their structure and complexity and present many challenges for statistical modelling. This thesis proposes a series of methods using random coefficients for modelling two broad types of longitudinal response: normally distributed measurements and binary recapture data. Biased inference can occur in linear mixed-effects modelling if subjects are drawn from a number of unknown sub-populations, or if the residual covariance is poorly specified. To address some of the shortcomings of previous approaches in terms of model selection and flexibility, this thesis presents methods for: (i) determining the presence of latent grouping structures using a two-step approach, involving regression splines for modelling functional random effects and mixture modelling of the fitted random effects; and (ii) flexible of modelling of the residual covariance matrix using regression splines to specify smooth and potentially non-monotonic variance and correlation functions. Spatially explicit capture-recapture methods for estimating the density of animal populations have shown a rapid increase in popularity over recent years. However, further refinements to existing theory and fitting software are required to apply these methods in many situations. This thesis presents: (i) an analysis of recapture data from an acoustic survey of gibbons using supplementary data in the form of estimated angles to detections, (ii) the development of a multi-occasion likelihood including a model for stochastic availability using a partially observed random effect (interpreted in terms of calling behaviour in the case of gibbons), and (iii) an analysis of recapture data from a population of radio-tagged skates using a conditional likelihood that allows the density of animal activity centres to be modelled as functions of time, space and animal-level covariates.

Over the 21st century, climate change and wetland habitat loss will pose major threats to the Eastern Massasauga (Sistrurus catenatus), a federally threatened and Great Lakes region endemic rattlesnake. I collected capture-recapture data from sites across the range and modeled the effect of climatic variables on growth rate and asymptotic size. I found that high snow residence time was associated with larger asymptotic sizes but slower growth, while high spring precipitation increased growth rate. I then projected future growth and size under different carbon emission scenarios. Given the threat posed by successional encroachment of woody vegetation, I used spatially explicit capture-recapture models to examine the effects of landscape characteristics and phenology on the spatial distribution of density for a population in Michigan. I found highest density in areas close to a stream and with low vegetation intensity, which can inform prescribed burn programs and give additional insights into life history.

Tigers (Panthera tigris tigris) can be viewed as a proxy for intact and healthy ecosystems. Their wild populations have plummeted to fewer than 3,200 individuals in the last four decades and threats to these apex predators are mounting rather than diminishing. Global conservation bodies (Global Tiger Initiative, World Wildlife Fund, Wildlife Conservation Society, Panthera etc.) have recently called for solidarity and scaling up of conservation efforts to save tigers from extinction. In South Asia, tiger habitat ranges from tropical evergreen forests, dry arid regions and sub-tropical alluvial floodplains, to temperate mixed deciduous forest. The churia habitat is relatively unstudied and is considered a young and geologically fragile mountain range in Nepal. The contribution of the churia habitat to tiger conservation has not been considered, since modern conservation started in 1970's. This study focuses on the ecology of the tiger with respect to population density, habitat use, and prey occupancy and density, in the churia habitat of Chitwan National Park. This study also includes the first assessment of genetic diversity, genetic structure, and gene flow of tigers across the Terai Arc Landscape- Nepal. The Terai Arc Landscape harbors the only remaining tiger population found across the foothills of the Himalayas in Nepal and northwest India. I used a combination of camera-trapping techniques, which have been a popular and robust method for monitoring tiger populations across the landscape, combined with a noninvasive genetic approach to gain information on tigers, thus adding new information relevant to global tiger conservation. I investigated tiger, leopard (Panthera pardus fusca), and prey densities, and predicted the tiger density across the Churia habitat in Chitwan National Park. I used a camera-trap grid with 161 locations accumulating 2,097 trap-nights in a 60 day survey period during the winter season of 2010-2011. Additionally, I used distance sampling techniques for estimating prey density in the churia habitat by walking 136 km over 81 different line transects. The team photographed 31 individual tigers and 28 individual leopards along with 25 mammalian species from a sampling area of 536 km² comprising Churia and surrounding areas. Density estimates of tigers and leopards were 2.2 (SE 0.42) tigers and 4.0 (SE 1.00) leopards per 100 km². Prey density was estimated at 62.7 prey animals per 100 km² with contributions from forest ungulates to be 47% (sambar Rusa unicolor, chital Axis axis, barking deer Muntiacus muntjak, and wild pigs Sus scrofa). Churia habitat within Chitwan National Park is capable of supporting 5.86 tigers per 100 km² based on applying models developed to predict tiger density from prey density. My density estimates from camera-traps are lower than that predicted based on prey availability, which indicates that the tiger population may be below the carrying capacity. Nonetheless, the churia habitat supports 9 to 36 tigers, increasing estimates of current population size in Chitwan National Park. Based on my finding, the Churia habitat should no longer remain ignored because it has great potential to harbor tigers. Conservation efforts should focus on reducing human disturbance to boost prey populations to potentially support higher predator numbers in Churia. I used sign surveys within a rigorous occupancy framework to estimate probability of occupancy for 5 focal prey species of the tiger (gaur Bos gaurus, sambar, chital, wild pig, and barking deer); as well as probability of tiger habitat use within 537 km² of churia habitat in Chitwan National Park. Multi-season, auto-correlation models allowed me to make seasonal (winter versus summer) inferences regarding changes in occupancy or habitat use based on covariates influencing occupancy and detection. Sambar had the greatest spatial distribution across both seasons, occupying 431-437 km² of the churia habitat, while chital had the lowest distribution, occupying only 100-158 km². The gaur population showed the most seasonal variation from 318- 413 km² of area occupied, with changes in occupancy suggesting their migration out of the lowland areas in the summer and into the churia in the winter. Wild pigs showed the opposite, moving into the churia in the summer (444 km² area occupied) and having lower occupancy in the winter (383 km²). Barking deer were widespread in both seasons (329 - 349 km²). Tiger probability of habitat use Ψ SE(Ψ) was only slightly higher in winter 0.63 (SE 0.11) than in summer 0.54 (SE 0.21), but confidence intervals overlapped and area used was very similar across seasons, from 337 - 291 km². Fine-scale variation in tiger habitat use showed that tigers intensively use certain areas more often than others across the seasons. The proportion of available habitat positively influenced occupancy for the majority of prey species and tigers. Human disturbance had a strong negative influence on the distribution of the majority of prey species but was positively related to tiger habitat use. Tigers appear to live in areas with high disturbance, thus increasing the risk of human-tiger conflict in the churia habitat. Thus, efforts to reduce human disturbance would be beneficial to reducing human wildlife conflict, enriching prey populations, and would potentially support more tigers in churia habitat of Nepal. Overall, I found high prey occupancy and tiger habitat use, suggesting that the churia is highly valuable habitat for tigers and should no longer be neglected or forgotten in tiger conservation planning. Thirdly, I assessed genetic variation, genetic structure, and gene flow of the tigers in the Terai Arc Landscape, Nepal. I opportunistically collected 770 scat samples from 4 protected areas and 5 hypothesized corridors across the Terai Arc Landscape. Historical landuse change in the Terai Arc was extracted from Anthrome data sets to relate landuse change to potential barriers and subsequent hypothesized bottleneck events in the landscape. I used standard genetic metrics (allelic diversity and heterozygosity) to estimate genetic variation in the tiger population. Using program Structure (non-spatial) and TESS (spatial), I defined the putative genetic clusters present in the landscape. Migrant analysis was carried out in Geneclass and Bayesass for estimating contemporary gene flow. I tested for a recent population bottleneck with the heterozygosity test using program Bottleneck. Of the 700 samples, 396 were positive for tiger (57% success). Using an 8 multilocus microsatellite assay, I identified 78 individual tigers. I found large scale landuse changes across the Terai Arc Landscape due to conversion of forest into agriculture in last two centuries and I identified areas of suspected barriers. I found low levels of genetic variation (expected heterozygosity = 0.61) and moderate genetic differentiation (F_ST = 0.14) across the landscape, indicative of sub-population structure and potential isolation of sub-populations. I detected three genetic clusters across the landscape consistent with three demographic tiger sub-populations occurring in Chitwan-Parsa, Bardia, and Suklaphanta protected areas. I detected 10 migrants across all study sites confirming there is still some dispersal mediated gene flow across the landscape. I found evidence of a bottleneck signature, especially around the lowland forests in the Terai, likely caused by large scale landuse change in last two centuries, which could explain the low levels of genetic variation detected at the sub-population level. These findings are highly relevant to tiger conservation indicating that efforts to protect source sites and to improve connectivity are needed to augment gene flow and genetic diversity across the landscape. Finally, I compared the abundance and density of tigers obtained using two non-invasive sampling techniques: camera-trapping and fecal DNA sampling. For cameras: I pooled the 2009 camera-trap data from the core tiger population across the lowland areas of Chitwan National Park. I sampled 359 km² of the core area with 187 camera-trap locations spending 2,821 trap-nights of effort. I obtained 264 identifiable photographs and identified a total of 41 individual tigers. For genetics, I sampled 325 km² of the core area along three spatial routes, walking a total of 1,173 km, collecting a total of 420 tiger fecal samples in 2011. I identified 36 tigers using the assay of 8 multilocus genotypes and captured them 42 times. I analyzed both data types separately for estimating density and jointly in an integrated model using both traditional, and spatial, capture-recapture frameworks. Using Program MARK and the model averaged results, my abundance estimates were 46 (SE 1.86) and 44 (SE 9.83) individuals from camera and genetic data, respectively. Density estimates (tigers per 100 km²) via traditional buffer strip methods using half of the Mean Maximum Distance Moved (½ MMDM) as the buffer surrounding survey grids, were 4.01 (SE 0.64) for camera data and 3.49 (SE 1.04) for genetic data. Spatially explicit capture recapture models resulted in lower density estimates both in the likelihood based program DENSITY at 2.55 (SE 0.59) for camera-trap data and 2.57 (SE 0.88) for genetic data, while the Bayesian based program SPACECAP estimates were 2.44 (SE 0.30) for camera-trap data and 2.23 (SE 0.46) for genetic data. Using a spatially explicit, integrated model that combines data from both cameras and genetics, density estimates were 1.47 (SD 0.20) tigers per 100 km² for camera-trap data and 1.89 (SD 0.36) tigers per 100 km² for genetic data. I found that the addition of camera-trap data improved precision in genetic capture-recapture estimates, but not visa-versa, likely due to low numbers of recaptures in the genetic data. While a non-invasive genetic approach can be used as a stand-alone capture-recapture method, it may be necessary to increase sample size to obtain more recaptures. Camera-trap data may provide a more precise estimates, but genetic data returns more information on other aspect of genetic health and connectivity. Combining data sets in an integrated modeling framework, aiding in pinpointing strengths and weaknesses in data sets, thus ultimately improving modeling inference. / Ph. D.

Carnivore are undoubtedly among the most threatened of the mammal species in Africa because of the low density at which they occur and their large home range requirements that do not match with human propensity to develop and alter wildlife habitat. However, the degree of threat is unevenly distributed within the continent, with western and central African carnivores being the most threatened and the least studied. I estimated population size, density, and proportion of area occupied in relation to environmental factors of one medium-size (serval – Leptailurus serval) and two large carnivores (lion – Panthera leo and leopard – P. pardus) in the Niokolo Koba National Park, Senegal, West Africa, using remote camera surveys and both traditional (CR), spatially explicit capture-recapture (SECR) techniques for servals and leopards, and non-spatial (MR) and spatial mark resight (SMR) methods for lions. Lions selected optimal sites with both high tree density and prey activity; leopards occupied areas with high tree density but with less prey activity; and servals selected habitats with more dense canopy cover where leopards were absent. The presence of lions was favorable to serval presence, as we presume leopards avoid lions, although we did not have strong evidence to support it. Moreover, the half mean maximum distance moved (½ MMDM) method under CR methods appeared to overestimate leopard and serval density while full MMDM estimates were close to SECR methods density estimates. For lions, both ½ MMDM and full MMDM methods in MR framework overestimated density whereas the SMR method resulted in more reasonable estimates, especially in light of previous assessments of lion densities in West Africa.. These results are of high importance for conservation and management purposes of the imperiled Niokolo Koba carnivore community. / Master of Science

Estimates of animal abundance or density are fundamental quantities in ecology and conservation, but for many species such as rare, small mammals, obtaining robust estimates is problematic. In this thesis, I combine elements of two standard abundance estimation methods, capture-recapture and distance sampling, to develop a method called trapping point transects (TPT). In TPT, a "detection function", g(r) (i.e. the probability of capturing an animal, given it is r m from a trap when the trap is set) is estimated using a subset of animals whose locations are known prior to traps being set. Generalised linear models are used to estimate the detection function, and the model can be extended to include random effects to allow for heterogeneity in capture probabilities. Standard point transect methods are modified to estimate abundance. Two abundance estimators are available. The first estimator is based on the reciprocal of the expected probability of detecting an animal, ^P, where the expectation is over r; whereas the second estimator is the expectation of the reciprocal of ^P. Performance of the TPT method under various sampling efforts and underlying true detection probabilities of individuals in the population was investigated in a simulation study. When underlying probability of detection was high (g(0) = 0:88) and between-individual variation was small, survey effort could be surprisingly low (c. 510 trap nights) to yield low bias (c. 4%) in the two estimators; but under certain situations, the second estimator can be extremely biased. Uncertainty and relative bias in population estimates increased with decreasing detectability and increasing between-individual variation. Abundance of the Key Largo woodrat (Neotoma floridana smalli), an endangered rodent with a restricted geographic range, was estimated using TPT. The TPT method compared well to other viable methods (capture-recapture and spatially-explicit capture-recapture), in terms of both field practicality and cost. The TPT method may generally be useful in estimating animal abundance in trapping studies and variants of the TPT method are presented.