Browsing by Author "Wittemyer, George, committee member"
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Item Embargo A holistic evaluation of human-elephant interactions in multi-use landscapes(Colorado State University. Libraries, 2023) Carroll, Sarah Louise, author; Reid, Robin, advisor; Boone, Randy, committee member; Salerno, Jon, committee member; Wittemyer, George, committee memberIn East Africa, rangelands and savannas are complex social-ecological systems with a history of land sharing among pastoralists, their livestock and wildlife. Today, many are systems of global importance for biodiversity conservation. As in Earth's other biomes, East African rangelands and their inhabitants face growing challenges as the result of global change, namely ecological, climate, political, and socioeconomic changes that are threatening wildlife populations and straining human-wildlife relationships. African savanna elephants (Loxodonta africana) are key actors in these systems and the center of many of these challenges. Thus, sophisticated land-use planning that addresses the resource use and needs of both people and elephants that can be integrated into conservation policy at relevant scales of governance is a key need for elephant conservation. However, studies of African elephant spatial ecology rarely examine both ecological and human-elephant relationships in the ecosystems they inhabit, whereas existing studies from human dimensions disciplines, which focus on social aspects of human-elephant relationships, very rarely include landscape-specific analyses. Additionally, detailed, spatially explicit information describing human-elephant interactions is limited, particularly in regions where people interacting with elephants still herd livestock more than they grow crops. This dissertation addresses this research need by applying novel methods with a holistic approach to examine the spatial dynamics of human-elephant interactions in multi-use landscapes with a focus on elephant interactions with pastoral peoples and their livestock. Most research in this dissertation is specifically focused on the spatial ecology of human-elephant interactions in the Greater Mara Ecosystem of southwest Kenya and combines inference from images captured by remote camera traps, high-resolution GPS tracking data, and social survey data to: 1) Understand how livestock and land management influence spatiotemporal patterns of elephant occurrence, 2) Investigate elephant movement behaviors and understand how people and environmental variation influence elephant movement behaviors, 3) Map core elephant habitat and movement corridors to support conservation planning, 4) Understand how people in mixed-use savannas relate to elephants and how elephants and wildlife conservation impact their lived experiences, and 5) Map and quantify social willingness to coexist with elephants in mixed-use landscapes to support conservation planning that accounts for the needs of both people and elephants. I found that elephants shifted the quantity and timing of their activity in community conservancies where livestock are present relative to the neighboring protected area where livestock were absent. Elephants were also more likely to occur in the protected area than community conservancies even when controlling for habitat variation. Finally, I found that areas in community conservancies used with higher intensity by sheep and goats, and separately cattle, were somewhat less likely to be used by elephants during the daytime. However, this finding was not consistent across years and the estimated effects had low precision and additional alternative analyses may make this relationship clearer. I then apply network theory to analyze combined information on movement path properties, use intensity, and structural properties of movement networks calculated from GPS tracking data to delineate the functional landscape of movement for elephants in the wider Mara-Serengeti ecosystem. After identifying movement behaviors, I then investigate the environmental variables driving different movement behaviors with a focus on delineating the habitats that support high elephant use and elephant movement corridors. Finally, I contrast how movement behaviors and the environmental variables driving movement vary between elephants inhabiting the mesic, wet savannas of the wider Mara-Serengeti ecosystem with those previously published and observed in elephants inhabiting the xeric savannas of the Samburu-Laikipia ecosystem. Results showed that human presence strongly influenced elephant movement behavior in the Mara and specifically influenced the location of core areas, whereas in Samburu, water availability and vegetation productivity and predictability strongly were the most important variables explaining core area use for elephants. Although vegetation productivity also influenced elephant core area use in the Mara, predictability did not, and human presence and canopy cover strongly influenced core area use in the Mara more strongly than water availability. Overall, these findings indicate that elephants in the Mara are likely less constrained by water and forage availability than elephants in Samburu and have more flexibility to access these key resources while minimizing the risks posed by people. I apply cognitive hierarchy theory to understand how elephants impact people in the Greater Mara Ecosystem by investigating values and attitudes associated with African elephants and elephant conservation in communities sharing space with elephants. I use data collected from semi- structured interviewers at 177 households across a mixed-use, agropastoral landscape that also functions as an unprotected elephant corridor and analyzed responses using Bayesian hierarchical models to quantify positive attitudes towards elephants while accounting for self-reporting bias. I interpret quantitative model estimates in the context of qualitative attitude assessments and sociocultural values to gain a deeper understanding of what explains attitudes towards elephants in the region. We found that although a majority of people expressed positive attitudes about elephant conservation in general, most were not also positive about sharing space with elephants on community and private lands at a local scale. Model estimates showed that people who believed that elephants had sociocultural value were the most likely to be positive towards elephant conservation in general, but experiencing conflict with any wildlife lowered the probability of respondents to have a positive attitude towards sharing space with elephants at a local scale. Qualitative data revealed that safety and well-being concerns related to the perceived threats that elephants pose to human life, livestock, and crops, coupled with few social and economic incentives to support elephant conservation in community and private lands contribute to low local positive attitudes. Our results suggest that conservation approaches focused on sustaining existing sociocultural values and relationships with wildlife while also investing in human well-being and safety measures and could improve conservation outcomes in shared landscapes. Overall, this research develops contributions to the understanding of human-elephant interactions in East African savannas and provides practical applications for elephant conservation. Specifically, this dissertation through the creation of several map products can support conservation planning that accounts for both people and elephants in the Greater Mara Ecosystem. Some of the most important takeaways come from co-interpretation of results with agropastoral communities and can thus provide direct guidance to conservation practitioners on how to better address human well-being in community-based conservation efforts. Though this research was produced in collaboration with non-government organizations, community-based conservation leaders, and government wildlife officials in Kenya, I recommend that future work can improve the collaborative research process by more successfully including local communities as stakeholders at all stages of the collaborative research process.Item Open Access Bats, elephants, and their food: a conservation perspective on trophic interactions in the Namib Desert(Colorado State University. Libraries, 2019) Laverty, Theresa Marie, author; Berger, Joel, advisor; Crooks, Kevin, committee member; Wittemyer, George, committee member; Teel, Tara, committee memberTo view the abstract, please see the full text of the document.Item Open Access Bird and mammal response to large-scale habitat mitigation for game species in the oil and gas fields of northwest Colorado(Colorado State University. Libraries, 2016) Gallo, H. Travis, author; Pejchar, Liba, advisor; Noon, Barry, committee member; Paschke, Mark, committee member; Wittemyer, George, committee memberTo view the abstract, please see the full text of the document.Item Open Access Evalutating the effects of wildfire in piñon-juniper woodlands on bighorn sheep habitat and vegetation composition(Colorado State University. Libraries, 2014) Wilson, Benjamin R., author; Boone, Randall, advisor; Evangelista, Paul, committee member; Wittemyer, George, committee memberI evaluated the efficacy of using woodland fire to alter vegetation composition in a manner that augments desert bighorn sheep (Ovis canadensis nelsoni) habitat in the Black Ridge Canyons Wilderness Area in western Colorado. I applied generalized linear mixed models to estimate pre-fire ewe habitat selection and then simulated a hypothetical widespread fire to spatially predict where fire would be most beneficial in expanding habitat. I found that ewes were avoiding habitats with high woodland canopy cover, the habitat most likely to be removed by fire. Given the removal of all woodlands, it is likely that habitat expansion would occur in areas near topographic escape terrain. Coupled with this analysis, I addressed concerns regarding potential negative effects of fire in this system by comparing vegetation composition of unburned habitats to burned habitats that were treated with a native seed mixture. I found that foliar cover in burned areas was on average two times greater than in unburned areas and that post-fire seeding efforts likely allowed for these differences to be proportionally similar between native and non-native grass species. My results provide an encompassing view on the effects of fire for a common management situation in which both land and wildlife values are of mutual interest.Item Open Access Forest elephants modulate their behavior to adapt to sounds of danger(Colorado State University. Libraries, 2023) Verahrami, Anahita K., author; Bombaci, Sara, advisor; Blanchard, Nathaniel, committee member; Wittemyer, George, committee memberThe African forest elephant (Loxodonta cyclotis) plays a critical role in upholding the structure and function of the Congo Basin, the world's second largest tropical forest which crucially contributes to global carbon sequestration. Research has demonstrated an 86% decline in forest elephant population numbers between 1990-2021, largely because of hunting for ivory. Due to the species' cryptic nature in their dense rainforest habitat, little is known on how they respond to human disturbances such as gun hunting. The studies that have been completed reveal that forest elephants may respond to disturbance by demonstrating changes in their abundance, distribution, and nocturnal activity. Changes in forest elephant distribution and activity not only have ramifications for the species' activity budgets, which when affected, may influence their foraging and reproductive behaviors and success, but may also impact the species' interspecific interactions with vegetation in certain areas, affecting forest growth and function. However, little is known on how a key population of this critically endangered species in the northern Republic of Congo is responding to disturbance such as hunting in the region. Using acoustic detection models in combination with a landscape-scale acoustic monitoring effort in and around Nouabalé-Ndoki National Park, Republic of Congo, I assess how forest elephant vocal activity is being influenced by gun hunting. Using these data, I examine (1) how forest elephant vocal activity changes across an eight-day period and (2) if forest elephants are shifting to more nighttime vocal activity following a gun hunting event. Results show that, on average, forest elephants are present and vocal at sites without gun events 53% of the time, but at sites with gun events, this value drops to 43%. Results also indicate that this change in activity following a gun hunting event is sustained over the eight-day period examined and does not vary from day-to-day. Results from the analysis exploring how the proportion of nighttime calling activity changes in response to gun hunting show that number of gunshots is an important predictor of nighttime vocal activity. Specifically, as the number of gunshots increase, there is a dramatic increase in the proportion of nighttime calling activity. Understanding the degree at which forest elephants are affected by gun hunting provides a convincing argument to focus limited conservation resources on developing more effective strategies to reduce indirect impacts from hunting on this critically endangered and ecologically important species.Item Open Access Hierarchical Bayesian models for population ecology(Colorado State University. Libraries, 2017) Ketz, Alison C., author; Hobbs, N. Thompson, advisor; Hooten, Mevin, committee member; Wittemyer, George, committee member; Webb, Colleen, committee memberModels, by their definition, are abstractions of the systems they describe and require a delicate balance of inclusion of information with reduction. Hierarchical Bayesian models are well suited for ecological problems, because they facilitate the decomposition of highly complex ecological systems into lower dimensional elements. We can partition variability that arises from the ecological processes separately from variability that arises from sampling error, thereby rigorously accounting for uncertainty. In this way, we can better answer questions pertaining to the ecology of populations and aid in better management of their ecosystems. Estimation of abundance is the central challenge in population ecology, and we begin this dissertation by addressing the problem of determining the population size of elk across multiple time and spatial scales during five winters. In Chapter 2, I build upon existing multi- state mark-recapture methods using a hierarchical Bayesian N-mixture model with multiple sources of commonly collected data on abundance, movement, and survival, to accurately estimate the abundance of a mobile population of elk on the winter range of Rocky Mountain National Park and Estes Park, CO. Classification data are used in ecology to examine population trends through model-based theoretical approaches. For ungulates such as elk, wildlife managers use sex-ratios and stable age or stage distributions to assess population growth or decline. However, physical ambiguities and observer skill can lead to biased results. In Chapter 3, I develop two hierarchical models to address the sample bias that results when data are missing-not-at-random, which occurs when individuals are observed but not classified. Forecasts are used to aid management to evaluate the probability that resource objectives will be met given different management actions. In Chapter 4, I develop a hierarchical model incorporating a discrete time, stage structured model assimilated with abundance and classification data, to provide forecasts under a variety of management actions to aid decision makers to meet objectives. I use Bayesian hierarchical models that incorporate multiple sources of information to address common estimation problems that arise in population ecology. We are frequently interested in constructs and latent processes that are not necessarily observable in ecological systems. I use theoretical models of the underlying processes to extract information pertaining to populations and management goals. Compounding the challenge is that we must rely upon survey samples rather than complete census. I illustrate the utility of hierarchical Bayesian models using data on the population of elk (Cervus elaphus nelsoni) on the winter range of Rocky Mountain National Park in Colorado, USA.Item Open Access Integrating social and ecological predictors of human-wildlife interactions to guide conservation and management(Colorado State University. Libraries, 2018) Lischka, Stacy A., author; Crooks, Kevin, advisor; Teel, Tara, committee member; Johnson, Heather, committee member; Wittemyer, George, committee memberThere is growing recognition that interdisciplinary approaches that account for both ecological and social processes are necessary to successfully address human-wildlife interactions. However, such approaches are hindered by challenges in aligning data types, communicating across disciplines, and applying social science information to conservation actions. My dissertation builds on emerging efforts to address these challenges by proposing a conceptual model for integration of social and ecological information to understand human-wildlife interactions, and reports empirical data which tests the impact of an experimental effort to reduce human-black bear (Ursus americanus) conflicts on tolerance for bears and residential bear-proofing behavior. The conceptual model I propose adopts a social-ecological systems approach and identifies multiple, nested levels of influence on human and animal behavior. I applied this model in an exploration of the drivers of human tolerance for black bears, an important determinant of their persistence. I measured tolerance for black bears in the vicinity of Durango, Colorado, USA and monitored changes resulting from a bear-proofing experiment designed to reduced garbage-related conflicts in the community. Residents who reported higher perceptions of benefits associated with bears and more positive impacts from interactions with them had increased tolerance. Residents who reported higher perceptions of risks, more negative impacts, higher trust in managers, domination wildlife value orientations, and older age were associated with decreased tolerance. Conflicts with bears were not an important predictor, supported by our finding that changes in conflicts resulting from our experiment did not affect tolerance. While conflicts may not affect tolerance for bears, many communities struggle to reduce conflicts in residential settings. The motivators for a key method to do so, bear-proofing of residential garbage, are poorly understood, yet information about them is key to designing successful efforts to increase this behavior. I observed use of bear-resistant containers at 383 households in 2014 and 2016 and used surveys to determine the drivers of this behavior. Most residents used bear-resistant containers irregularly (containers were locked on 44% of observations); 33% of households were never compliant across observations. I found residents increased their use of containers when rates of conflicts per residential block were higher. Further, when respondents were more trusting of the management agency and perceived more benefits from bears, they used containers less often. Approaches which integrate social and ecological information to understand and manage human-wildlife conflicts could assist conservation practitioners in reducing these conflicts and their negative outcomes for wildlife and people.Item Open Access Movement, resource selection, and the physiological stress response of white-bearded wildebeest(Colorado State University. Libraries, 2015) Stabach, Jared A., author; Boone, Randall B., advisor; Florant, Gregory, committee member; Reid, Robin S., committee member; Wittemyer, George, committee memberTo view the abstract, please see the full text of the document.Item Open Access Photovoice as a technique to understand the perceptions of local people neighboring Tarangire National Park in Tanzania on the risks caused by migratory animals(Colorado State University. Libraries, 2013) Sumay, Gloria, author; Boone, Randall, advisor; Bowser, Gillian, advisor; Wittemyer, George, committee member; Bruyere, Brett, committee memberWhat is the impact of wildlife on communities neighboring national parks and protected areas? Understanding perceptions of risk by local communities on wildlife can help conservation efforts and the development of acceptable policies for parks and protected areas. This study examines communities along the eastern boundary of Tarangire National Park using a combination of Photovoice techniques and individual interviews to determine how these communities perceive risk from wildlife to their agriculture, livestock and economies. Here Photovoice was used to articulate participants' perception of risks to their livelihoods from migratory wildlife that transversed the national park. Three villages (Terrat, Narakauwo and Emboreet) were chosen based on their proximity to wildlife migration corridors and 12 participants from each village were asked to document their perceptions of risk from wildlife using digital cameras. Photovoice uses images taken by participants on a pre-determined topic, followed by interviews of the participants on the photographs to determine themes. In addition, twenty participants from the same villages were interviewed on their perception of risk from wildlife damage using survey questions and narratives. The characteristics of each village (size, distance from each other and distance from park boundary) were determined using GIS and satellite imaginary. The villages had different perceptions (p = 0.003) based on the three categories of risk: wildlife damage, crop damage and shared resources. Village size had no influence on the peoples' perceptions of risk; however land use patterns (farm land and associated activities) showed some influence on perceptions of risk. Changes in land use for two of the villages, Emboreet and Narakauwo, indicated a large increase in farming activities, which are likely to influence peoples' perception of risk. In Emboreet village, which has more farm land, the greatest risk was perceived as crop damage. The results of this study demonstrate the complex relationships between protected areas, migratory wildlife and community villages. To balance the needs to protect highly migratory species such as the wildebeest, conservation managers need to incorporate the perceived risks among villages and the factors that influence those perceptions.Item Open Access Reproductive success, habitat selection, and neonatal mule deer mortality in a natural gas development area(Colorado State University. Libraries, 2016) Peterson, Mark E., author; Doherty, Paul F., Jr., advisor; Anderson, Charles R., Jr., committee member; Meiman, Paul, committee member; Wittemyer, George, committee memberMule deer (Odocoileus hemionus) populations have periodically declined throughout the western United States, with notable declines during the late 1960s, early 1970s, and 1990s (Unsworth et al. 1999) to present. Declining population levels can be attributed to low fawn survival and subsequently low population recruitment (Unsworth et al. 1999, Pojar and Bowden 2004) caused by declining habitat availability and quality (Gill 2001, Lutz et al. 2003, Watkins et al. 2007, Bergman et al. 2015). Although, general public perception is that declining deer numbers are attributed exclusively to predation (Barsness 1998, Willoughby 2012), predator control research suggests otherwise (Hurley et al. 2011, Kilgo et al. 2014) and compelling evidence exists that improving habitat quality can enhance deer populations (Bishop et al. 2009, Bergman et al. 2014). Complicating this story is the large-scale habitat alterations driven by natural gas development, which may also influence deer population dynamics. Natural gas development and associated disturbances that can affect deer habitat and population dynamics include conversion of native plant communities to drill pads, roads, or noxious weeds and noise pollution from compressor stations, drilling rigs, increased traffic, and year round occurrence of human activities. Natural gas development alters mule deer habitat selection through direct and indirect habitat loss (Sawyer et al. 2006, Sawyer et al. 2009, Northrup et al. 2015). Direct habitat loss results from construction of well pads, access roads, compressor stations, pipelines, and transmission lines. Activity, traffic, and noise associated with increased human presence and development may lead to indirect habitat loss. Indirect habitat loss is exacerbated because active wells produce gas for 40 years or longer (Sawyer et al. 2006, Sawyer et al. 2009). In addition, indirect habitat loss affects considerably larger areas than direct habitat loss (Sawyer et al. 2006, Sawyer et al. 2009). Recent research suggests direct and indirect losses can lead to behavioral responses to development (Sawyer et al. 2006, Dzialak et al. 2011b, Northrup et al. 2015). However, deer can behaviorally mediate these impacts by altering activity patterns or selecting habitat with topographic diversity that provides refuge from development (Northrup et al. 2015). Obtaining a more complete understanding of the potential impacts of development is critical to comprehend population dynamics of deer and to develop viable mitigation options. Understanding how natural gas development and other factors influence reproductive success metrics (e.g., pregnancy, in utero fetal, and fetal survival rates), fetal sex ratio, habitat characteristics of birth and predation sites (i.e., habitat selection), and neonatal (i.e., 0–6 months old) mule deer mortality have been identified as knowledge gaps. Thus, my dissertation focused on addressing these knowledge gaps through individual reproductive success monitoring using vaginal implant transmitters. I conducted this research during 2012–2014 in the Piceance Basin of northwestern Colorado in study areas with relatively high (0.04–0.90 well pads/km2) or low (0.00–0.10 well pads/km2) levels of natural gas development. In chapter 1, I examined the influence of adult female, natural gas development, and temporal factors on reproductive success metrics (i.e., pregnancy rate, in utero fetal rate, and fetal survival rate) and fetal sex ratio. Pregnancy rates were high, did not vary across years, and were essentially equal between study areas. In utero fetal rates were lower for yearling females (n = 10) and varied annually compared to adult females (n = 204) possibly from annual weather patterns that influenced forage quality and digestibility. Fetal survival rates increased over time and were lower in the high development study areas than the low development study area in 2012 possibly caused by a compounding influence of development disturbance during extreme environmental conditions (i.e., drought). Higher road density in a female’s core area (i.e., 50% minimum convex polygon) on summer range possibly contributed to better maternal body condition through increased forage quality along roads. Following the Trivers-Willard hypothesis which predicts females in good versus poor condition will produce more males, my results suggested females had a higher probability of producing more male offspring as road density increased. However, under my proposed mechanism, I would expect body condition and road density to be strongly correlated, but they were only weakly correlated (r = 0.07). I also note that I did not detect a biased sex ratio at the population level. Thus, I am uncertain of the exact mechanism influencing the relationship between road density and fetal sex ratio. In chapter 2, I used global positioning system collar data in conjunction with VITs and linear mixed models to validate the use of maternal deer movement rates (m/day) to determine timing of parturition. Daily movement rate of maternal deer decreased by 39% from 1 day before parturition ((x ) ̅ = 1,243.56, SD = 1,043.03) to 1 day after parturition ((x ) ̅ = 805.30, SD = 652.91). Thus, I suggest that a mule deer female whose daily movement rate significantly decreases to ≤ 800 m/day has likely given birth. In the future, I will analyze an independent data set to validate the recommended threshold value and possibly develop a movement rate algorithm. In chapter 3, I fit resource selection functions to examine the influence of natural gas development and environmental factors on birth site selection and habitat characteristics of predation sites. Females selected birth sites farther from producing well pads and with increased cover for concealing neonates and appeared to select habitat (e.g., north-facing slopes and further from treed edges) that minimized neonate predation risk. Predation sites were characterized as being closer to development and in habitat (e.g., woodlands, aspen-conifer stands, and north-facing slopes) that possibly provided favorable microclimates for neonates and abundant high quality forage for lactating females. However, I note that predation sites were on average relatively far (2,057 m) from producing well pads and I have difficulty proposing a mechanism to explain how well pads that far away can influence predation site characteristics. My results suggest natural gas development and environmental factors (e.g., slope, habitat type, and aspect) can influence birth site selection with predation site characteristics possibly related to foraging habitat selection. In chapter 4, I tested hypotheses about the influence of adult female, natural gas development, neonate, and temporal factors on neonatal mortality using a multi-state model. Predation and death by malnutrition decreased from 0–14 days old. Predation of neonates was positively correlated with rump fat thickness of adult females, but negatively correlated with the distance (0–0.4 km) from a female’s core area (i.e., 50% kernel density estimate) to a producing well pad on winter or summer range. Death by malnutrition was positively correlated with the distance from a female’s core area to a road on winter range and weakly, but negatively correlated with temperature. During my study, predation was the leading cause of neonatal mortality in both areas and mean daily predation probability was 9% higher in the high versus low development areas. However, black bear (Ursus americanus) predation was the leading cause of neonatal mortality in the high development areas (22% of all mortalities) compared to cougar (Felis concolor) predation in the low development areas (36% of all mortalities). Reduced precipitation and patchy habitat further fragmented by development possibly contributed to less hiding cover or edge effects, potentially leading to increased predation in the high development areas. Overall, my results suggest natural gas development may decrease fetal survival, influence birth site selection, and increase neonatal mortality, especially through predation, which may have consequences for mule deer recruitment and population dynamics depending on development intensity, habitat, and environmental conditions (e.g., drought). Consequently, developers and managers should consider strategies to mitigate impacts from development and improve forage and habitat quality and availability to minimize fitness consequences of deer. Such strategies could include development planning to avoid important habitats during critical time periods, implementing habitat treatments to rehabilitate areas, and minimizing habitat fragmentation and removal of hiding cover when constructing well pads and roads.Item Open Access Statistical models for animal telemetry data with applications to harbor seals in the Gulf of Alaska(Colorado State University. Libraries, 2017) Brost, Brian M., author; Hooten, Mevin B., advisor; Small, Robert J., committee member; Wittemyer, George, committee member; Boone, Randall B., committee memberMuch is known about the general biology and natural history of harbor seals (Phoca vitulina), but questions remain about the aquatic and terrestrial space use of these marine mammals. This is in large part because methods for examining the spatial ecology of harbor seals are poorly developed. The objective of this dissertation is to pair existing telemetry data with contemporary spatio-temporal modeling to quantify the space use and resource selection of harbor seals in the coastal waters of southern Alaska. Recent extensions to models for analyzing animal telemetry data address complications such as autocorrelation and telemetry measurement error; however, additional challenges remain, especially in the context of analyzing Argos satellite telemetry data collected on marine mammals like harbor seals. For example, existing methods assume elliptical (or circular) patterns of measurement error, even though Argos satellite telemetry devices impose more complicated error structures on the data. Constraints, or barriers, to animal movement present another complication. Harbor seals and other marine mammals are constrained to move within the marine environment, and mechanistic models that do not adhere to movement barriers yield unreliable inference. Therefore, a primary goal of this research is to develop statistical tools that account for these nuances and provide rigorous, ecologically relevant inference. Even though the models presented in this dissertation were specifically developed with Argos satellite telemetry data and harbor seals in mind, the methods are general and can be applied to other species and types of telemetry data. This dissertation consists of five chapters. In Chapter 1, I briefly discuss the general biology of harbor seals, focusing on what is known about their spatial habits in Alaska. I then summarize trends in Alaskan harbor seal abundance, a topic that motivated my research as well as the work of many others. I describe the existing Alaska Department of Fish and Game telemetry data sets that are available for examining harbor seal spatial ecology, commonly-used statistical methods for analyzing animal telemetry data, and conclude with the objectives of my research and an outline for the remainder of the dissertation. In Chapter 2, I propose an approach for obtaining resource selection inference from animal location data that accounts for complicated error structures, movement constraints, and temporally autocorrelated observations. The model consists of two general components: a model for the true, but unobserved, animal locations that reflects prior knowledge about constraints to animal movement, and a model for the observed telemetry locations that is conditional on the true locations. I apply the model to simulated data, showing that it outperforms common ad hoc approaches used when confronted with telemetry measurement error and movement constraints. I then apply the framework to obtain inference concerning aquatic resource selection and space use for harbor seals near Kodiak Island, Alaska. Chapters 3 and 4 shift the focus from inference concerning aquatic space use and resource selection, to inference concerning the use of coastal resources (i.e., haul-out sites) by harbor seals. In Chapter 3, I present a fully model-based approach for estimating the location of central places (e.g., haul-out sites, dens, nests, etc.) from telemetry data that accounts for multiple sources of uncertainty and uses all of the available locational data. The model consists of an observation model to account for large telemetry measurement error and animal movement, and a highly flexible mixture model (a Dirichlet process) to identify the location of central places. Ancillary behavioral data (e.g., harbor seal dive data obtained from the satellite-linked depth recorders) are also incorporated into the modeling framework to obtain inference concerning temporal patterns in central place use. Based on the methods developed in Chapter 3, I present a comprehensive analysis of the spatio-temporal patterns of haul-out use for harbor seals near Kodiak Island in Chapter 4. Chapter 4 also extends previously developed methods to examine the affect of covariates on haul-out site selection and to obtain population-level inference concerning haul-out use. I conclude, in Chapter 5, with some general thoughts about analyzing animal telemetry data, as well as potential future research directions.