Browsing by Subject "Environmental Sciences"

Spatial variability of the Earth's surface has a considerable impact on the atmosphere at all scales and understanding the mechanisms involved in land-atmosphere interactions is hindered by the scarcity of appropriate observations. A measurement gap exists between traditional point sensors and large aircraft and satellite-based sensors in collecting measurements of atmospheric quantities. Point sensors are capable of making long time series of measurements, but cannot make measurements of spatial variability. Large aircraft and satellites make measurements over large spatial areas, but with poor spatial and temporal resolution. A helicopter-based platform can make measurements on scales relevant for towers, especially close to the Earth's surface, and can extend these measurements to account for spatial variability. Thus, the Duke University Helicopter Observation Platform (HOP) is designed to fill the existing measurement gap.

Because measurements must be made in such a way that they are as uncontaminated by the platform itself as much as is possible, it is necessary to quantify the aerodynamic envelope of the HOP. The results of an analytical analysis of the location of the main rotor wake at various airspeeds are shown. Similarly, the results of a numerical analysis using the commercial Computational Fluid Dynamics software Fluent are shown. The optimal flight speed for the sampling of turbulent fluxes is found to be around 30 m/s. At this airspeed, the sensors located in front of the nose of the HOP are in advance of the wake generated by the main rotor. This airspeed is also low enough that the region of high pressure due to the stagnation point on the nose of the HOP does not protrude far enough forward to affect the sensors. Measurements of differential pressures, variables and turbulent fluxes made while flying the HOP at different airspeeds support these results. No systematic effects of the platform are seen at airspeeds above about 10 m/s.

Processing of HOP data collected using the current set of sensors is discussed, including the novel use of the Empirical Mode Decomposition (EMD) to detrend and filter the data. The EMD separates the data into a finite number of Impirical Mode Functions (IMFs), each of which is unique and orthogonal. The basis is determined by the data itself, so that it need not be known a priori, and it is adaptive. The EMD is shown to be an ideal tool for the filtering and detrending of HOP data using data gathered during the Cloud and Land Surface Interaction Campaign (CLASIC).

The ability of the HOP to accurately measure atmospheric profiles of potential temperature is demonstrated. During experiments conducted in the marine boundary layer (MBL) and the convective boundary layer (CBL), HOP profiles are evaluated using profiles from an elastic backscatter lidar. The HOP and the lidar agree on the height of the boundary layer in both cases, and the HOP effectively locates other atmospheric structures.

Atmospheric sensible and latent heat fluxes, turbulence kinetic energy (TKE) and horizontal momentum fluxes are also measured, and the resulting information is used to provide context to tower-based data collected concurrently. A brief comparison made over homogeneous ocean conditions yields good results. A more exhaustive evaluation is made using short HOP flights made over an orchard during the Canopy Horizontal Turbulence Study (CHATS).

Nature is under immediate and increasing threat. Tales of destruction and deforestation abound despite the myriad interventions and investments by government bureaucracies, non-government organizations, and private land-owners. As the extinction crisis looms larger and demands on the public purse grow greater, understanding how science becomes policy and policy practice is more important than ever. As a result, and in response to the increasing insularity of conservation biology that has consciously nourished a careful separation of knowledge and action, of scientist and actor, I use this dissertation to navigate the nexus of conservation science, policy, and practice. I employ case studies in forest hydrology and species conservation, as well as cognitive theory, to examine how conservation science becomes policy. I collected field data from Lake Mead National Recreation Area and from the World Bank to explore how policies are translated into practice.

Current assumptions in conservation biology apportions these three separate but equal disciplines - science, policy, and practice - into one greater and two lesser, one that is pure and two that are sticky. But the transmission of knowledge from the Academy to the domains of conservation policy and practice, though difficult, is our mandate. As much as technical competence matters in conservation biology, so too does political literacy. After all, conservation occurs within a dynamic social, political, and institutional landscape. Nonetheless, the current emphasis in conservation biology is on answering questions in the natural sciences and, to a lesser degree, in economics. This focus is important, as is protecting scholarship from the daily pressures of a society that demands quick and ready answers. But scientific data is only one commodity among many that policy-makers and conservation practitioners trade in a tournament of values. Its usefulness lies in the wider social and political environment. Moreover, conservation biology is not simply an applied subset of biology or ecology. It is a mission-driven discipline that dedicates itself to the pursuit of science to save wildlife and wild lands. It encapsulates certain values as axioms. We hold these truths to be self-evident: that the diversity of life matters and that the struggle to end extinctions is meaningful.

Therefore, though conservation science, the design of conservation policies, and the practice of conservation are separate disciplines, they are closely related. For we must understand their different rules of evidence, speak their distinctive languages, and achieve credibility in all three disciplines while maintaining a sense of intellectual integrity in each. This requires respect for their differences as well as recognizing their shared mission in the service of wildlife and wild lands.

The Amazon basin is a center of deep atmospheric convection and thus acts as a major engine for global atmospheric circulation. From this basin, one fifth of the world's freshwater flux is discharged into the Atlantic and nearly two-thirds of the global rain forest resides herein. Yet despite its significance, little is known about past Amazon climate variability and the response of the forest ecosystem to climate.

Here, I attempt to reconstruct the paleoclimate history of a portion of the Amazon basin using both tree ring growth and the carbon and oxygen isotopes of tree ring cellulose from the Madre de Dios department of Southeastern Peru. Bomb 14C dating identifies annual rings in tropical species Cedrela odorata and Dipteryx micrantha. A ring width chronology spanning 189 years (1817-2006) is developed for Cedrela odorata and 5 trees of Dipteryx micrantha are utilized for isotope reconstruction. The oldest tree used in the isotope reconstructions has an error-adjusted age of about 473 years (1533-2006). Using the species Cedrela odorata, Ceiba pentandra, Hymenaea courbaril, Myroxylon balsamum, and Tabebuia serratifolia, I develop 5 tree ring chronologies using relative ring width measurements and chart the growth behaviors of over 40 trees. Ring width chronologies from tree species Cedrela odorata and Ceiba pentandra show a significant correlation with wet season precipitation (r = 0.42, and 0.37, respectively, p<0.05). The ring width chronology developed from the species Hymenaea courbaril is significantly correlated (r = 0.68, p<0.05) with January river discharge. Correlations between wet season precipitation and ring growth in Cedrela odorata are used to identify extreme wet and dry events. Nine historic droughts of the 20th century are identified in the C. odorata record. An increase in the frequency of extreme events (mean recurrence interval = 5-6 years) is observed in the 20th century and both Atlantic and Pacific sea surface temperature (SST) forcing mechanisms are implicated. The chronology shows a moderate correlation with both ENSO and tropical North Atlantic SST anomalies, suggesting that both basins play a role in precipitation variability over tropical South America.

Carbon and oxygen isotopic measurements (proxies of moisture stress and precipitation amount, respectively), in tree ring cellulose from 5 Dipteryx micrantha trees are used to reconstruct an error adjusted 473 year long record of precipitation variability. Because an error correction factor is applied to the chronologies of the trees of this species, assessment of annual-scale variability is precluded. Instead lower frequency trends are examined. No long term trends are identified in the oxygen isotopic records from individual trees. The carbon isotopic records of all five individual trees track the depletion of atmospheric δ13C during the 20th century due to the anthropogenic input of fossil fuel CO₂ (The Suess effect). Relatively large variability in the oxygen isotopic records between trees suggests that site-specific and tree-specific conditions dominate this signal. Carbon isotopic records reveal a better correlation between records from multiple trees (r = 0.47, p<0.01) suggesting that a common climate signal is more robustly recorded by the δ13C of these trees. At interannual frequencies (5 year), both carbon and oxygen isotopic records correlate significantly with wet season precipitation (r = -0.50, and -0.55 respectively, p<0.05). Spectral analysis reveals dominant 8-10 year and 3-5 year periodicities in both the carbon and oxygen isotopic records of individual trees. The oldest tree examined reveals a shift from this 8-10 year periodicity during the early part of the record to a lower frequency (20-24 year) variability during the last century. The lower frequency variability identified in the records is associated with both the Pacific Decadal Oscillation and the decadal and multidecadal variability observed in the tropical North Atlantic.

Collectively, these data show that tropical tree ring growth and isotopic composition in the southwestern Amazon basin are precipitation dependent and these measures can be exploited to reconstruct a hydrologic history for this region.

Coastal eutrophication is a complex process that is caused largely by anthropogenic nutrient enrichment. Estuaries are particularly susceptible to nutrient impairment, owing to their intimate connection with the contributing watersheds. Estuaries experiencing accelerating eutrophication are subject to a loss of key ecological functions and services. This doctoral dissertation presents the development and implementation of an integrated approach toward assessing the water quality in the Neuse Estuary following the implementation of the total maximum daily load (TMDL) program in the Neuse River basin. In order to accomplish this task, I have developed a series of water quality models and modeling strategies that can be effectively used in assessing nutrient based eutrophication. Two watershed-level nutrient loading models that operate on a different temporal scale are developed and used to quantify nitrogen loading to the Neuse Estuary over time. The models are used to probabilistically assess the success of the adopted mitigation measures in achieving the 30 % load reduction goal stipulated by the TMDL. Additionally, a novel structure learning approach is adopted to develop a Bayesian Network (BN) model that describes chlorophyll dynamics in the Upper Neuse Estuary. The developed BN model is compared to pre-TMDL models to assess any changes in the role that nutrient loading and physical forcings play in modulating chlorophyll levels in that section of the estuary. Finally, a set of empirical models are developed to assess the water quality monitoring program in the estuary, while also exploring the possibility of incorporating remotely sensed satellite data in an effort to augment the existing in-situ monitoring programs.

Urbanization causes myriad changes in watershed processes, ultimately disrupting the structure and function of stream ecosystems. Urban development introduces contaminants (human waste, pesticides, industrial chemicals). Impervious surfaces and artificial drainage systems speed the delivery of contaminants to streams, while bypassing soil filtration and local riparian processes that can mitigate the impacts of these contaminants, and disrupting the timing and volume of hydrologic patterns. Aquatic habitats where biota live are degraded by sedimentation, channel incision, floodplain disconnection, substrate alteration and elimination of reach diversity. These compounding changes ultimately lead to alteration of invertebrate community structure and function. Because the effects of urbanization on stream ecosystems are complex, multilayered, and interacting, modeling these effects presents many unique challenges, including: addressing and quantifying processes at multiple scales, representing major interrelated simultaneously acting dynamics at the system level, incorporating uncertainty resulting from imperfect knowledge, imperfect data, and environmental variability, and integrating multiple sources of available information about the system into the modeling construct. These challenges can be addressed by using a Bayesian modeling approach. Specifically, the use of multilevel hierarchical models and Bayesian network models allows the modeler to harness the hierarchical nature of the U.S. Geological Survey (USGS) Effect of Urbanization on Stream Ecosystems (EUSE) dataset to predict invertebrate response at both basin and regional levels, concisely represent and parameterize this system of complicated cause and effect relationships and uncertainties, calculate the full probabilistic function of all variables efficiently as the product of more manageable conditional probabilities, and includes both expert knowledge and data. Utilizing this Bayesian framework, this dissertation develops a series of statistically rigorous and ecologically interpretable models predicting the effect of urbanization on invertebrates, as well as a unique, systematic methodology that creates an informed expert prior and then updates this prior with available data using conjugate Dirichlet-multinomial distribution forms. The resulting models elucidate differences between regional responses to urbanization (particularly due to background agriculture and precipitation) and address the influences of multiple urban induced stressors acting simultaneously from a new system-level perspective. These Bayesian modeling approaches quantify previously unexplained regional differences in biotic response to urbanization, capture multiple interacting environmental and ecological processes affected by urbanization, and ultimately link urbanization effects on stream biota to a management context such that these models describe and quantify how changes in drivers lead to changes in regulatory endpoint (the Biological Condition Gradient; BCG).

Sea turtles have experienced dramatic population declines during the last century as a consequence of direct harvest, by-catch in fisheries, and habitat loss. Despite almost 50 years of partial international protection, several populations of sea turtles are still at imminent risk of extinction. Our knowledge of their complex life histories is still far from complete; these knowledge gaps hinder our ability to provide scientific advice regarding their conservation and management. It is the very complexity of their life histories, which allows them to exploit widely separated habitats during development, often over the course of decades, which makes them inherently difficult to study. I used satellite telemetry (n=60) to investigate the movements and habitat use patterns of juvenile loggerhead (Caretta caretta), green (Chelonia mydas), and Kemp's ridley (Lepidochelys kempii) sea turtles on their summer feeding grounds in North Carolina estuaries. These turtles migrate into and out of the estuarine waters each spring and autumn, encountering a gauntlet of fishing gear on each journey. The by-catch of sea turtles is an important conservation issue in North Carolina, and throughout the world's oceans. I evaluated conservation measures established to reduce the by-catch of sea turtles in Pamlico Sound's autumnal large-mesh gill net fishery for southern flounder (Paralichthys lethostigma), using a spatially explicit predator/prey model. My findings indicated that species-specific habitat preferences contributed to a turtles' risk of encountering fishing gear and that areas of high by-catch are predictable from patterns of overlap between sea turtle habitat use and flounder fishing effort. I then examined how the behavior of green turtles affected their vulnerability to incidental capture in estuarine commercial fisheries. Individual green turtles interact with multiple gears per season as a result of strong site fidelity to habitats also preferred by fishers. Telemetry also allowed me to examine individual variation in movements, habitat use, and site fidelity patterns of juvenile loggerhead turtles, both within the estuary and as the turtles migrated out into the North Atlantic. I used these observations to test the hypothesis of a discrete ontogenetic shift in habitat and diet in juvenile loggerheads. Approximately one-third of large juvenile loggerheads tagged in North Carolina estuaries return to oceanic habitat, sometimes for several years, where they are vulnerable to by-catch in pelagic fisheries. This led me to conclude that the long held notion of a discrete ontogenetic habitat shift between the oceanic and neritic habitat was incorrect for juvenile loggerheads (and possibly also for green turtles). Finally, I explored variation in migratory destinations in these animals through multivariate analyses of carbon and nitrogen stable isotope ratios in blood plasma and red blood cells, and through analysis of sex, genetic, haplotype, body size, and remigration records, and described the trophic niche of these turtles with Bayesian isotope mixing models. Variation in migratory destination (oceanic or neritic habitat) was best described by stable isotope ratios of nitrogen and remigration tendency. Turtles that returned to the open ocean had significantly lower nitrogen ratios than those animals that remained in the neritic zone and their diets retained a substantial contribution of epipelagic prey items. The diet composition of neritic turtles, on the other hand, consisted primarily of estuarine benthic invertebrates during the summertime and autumn foraging season but shifted toward pelagic jellyfish, fish, and Sargassum during the overwintering period. Oceanic turtles likely came from open ocean regions prior to entering the summer foraging grounds while neritic turtles likely overwintered at the edge of the Gulf Stream. The agreement between the dietary compositions and migration patterns between the two groups of turtles suggest that these feeding and habitat use strategies were persistent characteristics in the turtles I sampled. My work has improved our understanding of sea turtle habitats in North Carolina estuaries and identified their migratory destinations and overwintering habitats. I hope that this work lays the groundwork for future studies that will explore how variation in habitat use and feeding strategies are manifested in life history traits that affect fitness directly, such as survivorship, growth rates, stage durations, and fecundity.

Dibenzothiophene (DBT) is a constituent of creosote and petroleum waste contamination, it is a model compound for more complex thiophenes, and its degradation by mixed microbial communities has received little attention. The chemical characteristics, environmental fate and ecotoxicology of DBT degradation products are not well understood. This research investigated DBT degradation in an enrichment culture derived from creosote-contaminated estuarian sediment using a suite of assays to monitor bacterial populations, bacterial growth, degradation products, DBT loss, and toxicity. Ultraviolet (UV) irradiation was evaluated as a sequential treatment following biodegradation. Additionally, to advance SYBR-Green qPCR methodology for characterizing mixed microbial communities, an alternative approach for evaluating qPCR data using a sigmoidal model to fit the amplification curve was compared to the conventional approach in artificial mixed communities. The overall objective of this research was to gain a comprehensive understanding of the degradation of a model heterocyclic PAH, DBT, by a mixed microbial community, particularly within the context of remediation goals.

DBT biodegradation was evaluated in laboratory scale cultures with and without pH control. The microbial community was monitored with 10 primer sets using SYBR-Green quantitative polymerase chain reaction (qPCR). Twenty-seven degradation products were identified by gas chromatography and mass spectrometry (GC/MS). The diversity of these products indicated that multiple pathways functioned in the community. DBT degradation appeared inhibited under acidic conditions. Toxicity to bioluminescent bacteria Vibrio fischeri more than doubled in the first few days of degradation, was never reduced below initial levels, and was attributed in part to one or more degradation products. UV treatment following biodegradation was explored using a monochromatic (254 nm) low-pressure UV lamp. While DBT was not extensively photooxidized, several biodegradation products were susceptible to UV treatment. At higher doses, UV treatment following DBT biodegradation exacerbated cardiac defects in Fundulus heteroclitus embryos, but slightly reduced toxicity to V. fischeri.

This research provides a uniquely comprehensive view of the DBT degradation process, identifying bacterial populations previously unassociated with PAH biodegradation, as well as potentially hazardous products that may form during biodegradation. Additionally, this research contributes to development of unconventional remediation strategies combining microbial degradation with subsequent UV treatment.

Plants respond to changes in their local environment and, at the same time, influence the environment at a global scale. The molecular and physiological mechanisms regulating this interaction are not completely understood and this limits our capacity to predict the response of vegetation to future environmental changes. This dissertation combined tools from genomics, physiology, and ecology to examine the response of plants to environmental change. Specifically, it focused on processes affecting carbon and water exchange in forest trees because (1) trees are long-lived species that might face repeated environmental challenges; (2) relatively little information exists about the genes and the molecular mechanisms regulating structural and physiological traits in adult, long-lived woody plants; and (3) forest trees exchange a significant amount of carbon and water with the atmosphere and are therefore major players in the global carbon and water cycles.

Water flux through forests depends both on environmental conditions (e.g., soil moisture) and on the hydraulic architecture of individual trees. Resistance to xylem cavitation is an important hydraulic trait that is often associated with drought tolerance but potentially at the cost of reduced carbon uptake. The second chapter of this dissertation evaluated the variation in resistance to xylem cavitation, hydraulic conductivity, wood anatomy traits, and leaf gas exchange across 14 co-occurring temperate tree species including both angiosperms and gymnosperms. The relationship between vulnerability to cavitation (ψ₅₀) and hydraulic conductivity within specific organs (i.e. stems and roots) was not significant when considering the phylogenetic association between species. However, even after phylogenetic correction, photosynthetic carbon uptake (A) was positively correlated with both stem and root ψ₅₀, and stomatal conductance (g_s ) was strongly correlated with root ψ₅₀ . These results suggest that there is a trade-off between vulnerability to cavitation and water transport capacity at the whole-plant level, and that this functional relationship reflects an adaptive response to the environment.

Forests are an important component of the global carbon cycle that can be directly impacted by a rise in atmospheric CO₂ concentration.. The third chapter of this dissertation investigated the effects of long-term exposure to elevated CO2 on the gene expression of mature, field-grown loblolly pine trees. Using cDNA microarrays, I compared the expression of 1784 pine transcripts in trees growing under ambient and those under elevated CO₂ at monthly intervals throughout a growing season. Overall, more genes were upregulated than downregulated by elevated CO₂, although the total number of genes differentially expressed varied throughout the season. The pattern of increasing number of differentially expressed genes until the peak of the growing season (July and August) followed by a decrease in that number, matched the seasonal trend of tree growth and photosynthetic response to elevated CO₂ in this species. The seasonal trend also reflected the interaction among multiple abiotic factors intrinsic to field conditions and emphasized the relevance of evaluating the role of genes in their natural environment. Genes consistently upregulated by elevated CO₂ were functionally associated with environmental sensing, cellular signaling, and carbon metabolism, in particular the degradation of carbohydrates through respiration. An increase in carbohydrates degradation is particularly relevant in the context of carbon balance of forest trees because of the potential for enhanced leaf and tree respiration leading to a reduced sink capacity for CO₂.

Loblolly pine produces several flushes of needles throughout the year each with an average lifespan of 19 months. Each year, two age classes of needles contribute to the annual carbon sequestration of the loblolly pine forest. To address the impact of leaf age on the effects of elevated CO₂ in carbon metabolism regulation, I compared the gene expression profiles from trees under ambient and elevated CO₂ conditions in two needle cohorts: one-year-old and current-year. Differential expression under elevated CO₂ was seven times more frequent in current-year than in one-year-old needles. Despite differences in magnitude, many of the patterns within specific groups of genes were similar across age classes. For instance, there was a trend for downregulation of genes involved in the light-reactions of photosynthesis and those in photorespiration in both age classes, while genes associated with dark respiration were largely upregulated by elevated CO₂ in both cases. The difference between the two cohorts was particularly evident in the group of genes related to energy production (ATP synthesis) and the group associated with carbon partitioning (sucrose and starch metabolism). Because sucrose and starch metabolism categories included many genes known to be important regulators of gene expression and plant physiological processes, this suggests that this stage of carbon metabolism might be an important control point in age-dependent foliar responses to elevated CO₂.

This dissertation examined both structural and physiological components of plant water and carbon relations (Chapter 2) across different biological scales of organization (whole-plant level in Chapter 2; gene-level response to ecosystem-level changes in Chapters 3 and 4) and reflecting adjustments at distinct temporal scales (life-span of the organism vs. evolutionary selection of traits). An integrative approach was used to advance our understanding of how plants acclimate and adapt to their environment, and to provide a mechanistic framework for predictive models of plant response to environmental change.

Coastal plain ponds are an understudied and threatened wetland ecosystem with many unique environmental attributes. Research in these ponds can investigate species-environment relationships, while simultaneously providing ecosystem-specific information crucial to their continued conservation and management. This dissertation explores patterns in coastal plain pond vegetation composition and species-environment relationships across space, through time, and in the seed bank and standing vegetation.

In a two-year field study at 18 coastal plain ponds across the island of Martha's Vineyard, Massachusetts, I investigated species-environment relationships within and among ponds. I identified vegetation species presences and abundances within 1 m2 quadrats, which ran continuously along transects established perpendicular to the water's edge. Species data were analyzed against local and landscape-scale environmental data. I also conducted a one-year seed bank study in which sediments from four coastal plain ponds were incubated in growth chambers and composition was compared to the standing vegetation. One hundred and thirty-four plant species were identified during vegetation sampling and 38 species were identified from incubated sediments.

I found significant compositional change across space in response to environmental gradients, with patterns in species composition occurring at both local and landscape scales. Elevation was the only local factor strongly correlated with species composition. Significant landscape-scale environmental factors included surficial geology and pond water salinity. Species composition was significantly correlated with hydrologic regime in 2005 but not in 2006. Overall patterns in vegetation species composition and abundance were more closely related to landscape-scale environmental variables than to local environmental variables.

I also found that coastal plain ponds undergo significant compositional change from one year to the next. Interannual variability disproportionately affected certain ponds and quadrats more than others, highlighting patterns in the relationships between compositional change and environmental attributes. Specifically, ephemeral ponds, ponds located on the moraine, ponds with high specific conductance values, and quadrats located closer to the waterline exhibited greater compositional change from 2005 to 2006 than permanent ponds, ponds located on the outwash plain, ponds with low specific conductance values, and quadrats located further from the waterline.

Finally, I found that coastal plain ponds exhibit a low degree of similarity between composition in sediments and standing vegetation. More species were identified in the standing vegetation than in the seed bank, and in most cases average species richness per quadrat was higher in the standing vegetation than in the seed bank. Seed bank and standing vegetation samples from ponds with different surficial geology were compositionally distinct. Seed bank samples from permanent and ephemeral ponds were compositionally distinct whereas standing vegetation samples were not.

To conserve biodiversity, it is critical to understand the dynamic landscapes and climates through which species move and how the environment influences movement choices. In particular, I am interested in how species respond to human modifications to landscapes and climates. Chapter 1 uses datasets on the spatial and temporal coverage of remotely sensed land cover datasets to examine gaps in the monitoring of environmental priorities. Temporal gaps in Landsat and spatial gaps in commercial high resolution satellites such as QuickBird may hinder land cover change monitoring efforts.

Chapter 2 uses Global Climate Models and museum specimens to projects the impact of climate change on the flora of California, a global biodiversity hotspot. With anticipated climate change, up to 66% may experience >80% reductions in range size within a century. These projections are less severe if plants are able to disperse in time. With no constraints on dispersal, plant centroids move an average of up to 150 km. The projections identify regions where species undergoing severe range reductions may persist. Protecting these potential future refugia and facilitating species dispersal may be essential to maintain biodiversity in the face of climate change.

Chapter 3 analyzes the movements of 73 elephants fitted with GPS collars against 4 remotely sensed datasets spanning a strong rainfall gradient across 7 southern African countries. Movements show strong seasonal and geographic differences across the study area. Two major human interventions, artificial water and fences, distort these movement patterns by increasing dry season ranging patterns and increasing the density of wet season movements.

Chapter 4 uses the datasets described in chapter 3 to explore elephant vegetation preferences. Elephants consistently prefer greener vegetation throughout the year. Vegetation preferences vary seasonally. Elephants prefer less variable vegetation such as forests in the dry season and ephemeral vegetation such as grasslands in the wet season.

Chapter 5 uses telemetry and remotely sensed landcover data to ask how climatic factors - snow cover - and land cover - agriculture and roads - influence pronghorn movements in South Eastern Alberta. Analysis using a Bayesian movement model reveals that each of these features significantly influences pronghorn movement choices.