Whitetop Mountain is Virginia's second highest peak and hosts two globally rare, insular ecosystems: a southern Appalachian grass bald and a red spruce-dominated forest. These areas provide important ecosystem services and habitat for rare and endangered species. They are highly prized for their cultural value and recreational areas that support nearby rural economies. This thesis investigated spatial patterns in both ecosystems on Whitetop. We documented a 24.73% decrease of in the extent of the southern Appalachian grass bald across 68 years through analysis of historical aerial photography. In the red spruce-dominated forest, we used a consumer grade unmanned aerial vehicle (UAV) to survey the health of all trees within a 46 ha sample plot. We assessed (dead, dying, healthy) over 9,000 individual trees based on visual patterns in the imagery and produced spatial products that will inform land managers about where resources are most needed. About 7.4% of the red spruce trees in our study area were classified as dead or dying. A model relating spruce mortality to biophysical landscape factors identified no single predictive factor related to mortality. The addition of optical information from the UAV imagery into the model proved utility for remotely-sensed data in identification of dead spruce within the forest canopy at Whitetop and possibly in other similarly structured forests. This research contributed to the limited body of knowledge surrounding the decline of both southern Appalachian grass balds and red spruce forests and provided technical insights for future mortality monitoring. / Master of Science / This thesis investigates land cover changes in two rare ecosystems on Whitetop Mountain, Virginia. The mountain has important biological significance and is a cultural landmark. The high-elevation summit hosts plant and animal species characteristic of northern climates, including a red spruce-dominated forest and a southern Appalachian grass bald. This work documented a 24.73% decrease in the size of the rare southern Appalachian grass bald ecosystem at Whitetop Mountain over 68 years and discussed potential drivers and proposed management for conservation. We also successfully used a camera-equipped unmanned aerial vehicle (drone) to produce high quality imagery for spruce mortality detection within the red spruce forest. Of over 9,000 standing spruce trees, 7.4% were categorized as either dead or dying. We built a predictive model to investigate the relationship between mortality and biophysical environmental factors, but did not identify a single causal factor. A second model that included the color band information from the drone camera revealed that different types of aerial imagery could play a valuable role in detection of tree mortality in forests of similar structure. Overall this research contributes to the body of knowledge surrounding the decline of both southern Appalachian grass bald and red spruce ecosystems and provides insights for management.

Wildfire processes in Canada are expected to change as a result of climate change. Predictive modeling of wildfire occurrence and susceptibility requires knowledge of ignition expectations and landscape conditions leading to burn. This research examines and quantifies the spatial and temporal patterns of wildfire across Canada with focus on wildfire occurrence and national scale drivers of susceptibility. Baseline ignition expectations and trends are identified and used to create unique fire ignition regimes, assess anthropogenic influence on ignitions, and determine regions with anomalously high ignitions. The aspatial and spatial characteristics of land cover were characterized for pre- and post-fire landscapes. These included land cover composition, configuration, and abiotic covariates. Temporal trends in forest pattern following ignition are examined and national scale drivers of wildfire susceptibility determined. Fire ignition regimes and anomalous ignition regions provide spatially explicit outputs for exploring ignition expectation in Canada. Wildfire was identified to burn mainly in coniferous forests with little fragmentation. Fragmentation increased after wildfire and regeneration of pre-fire forest pattern took 20 years. Additionally, anthropogenic proximity positively influenced ignition expectation, ignition trend, and wildfire susceptibility. This research provides broad scale methods to assess wildfire occurrence and susceptibility across Canada and will facilitate understanding of changing wildfire processes in the future. Additionally, this research highlights the importance of anthropogenic activity on natural fire processes.

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Wildlife management and natural resource policy decisions are increasingly being made at the landscape level. Understanding the relationship between modification and the pattern of land classes may minimize potential impacts and enhance the complement of wildlife species. Twenty-four expressions were selected for landscape analysis that describe the spatial heterogeneity, fragmentation, edge characteristics, and connectivity of pattern. Metric relationships were characterized across a variety of landscapes. Cluster analysis organized the metrics into classes quite different from the classification categories used in the literature. Cluster membership reflected the number of land classes, the amount and distribution of forest cover, number of forest patches, patch position, patch shape, patch radius, and edge length. Cartographic modeling was used to determine how modification influenced landscape pattern. The models depicted spatial relationships resulting from proposed landscape changes. Timber harvest schemes with a few large units and those in clustered arrangements led to less fragmentation than those schemes with several small units or those dispersed across the landscape. The placement of roads had either an invasive or partitioning effect on landscape pattern. Discriminant analysis rated the effectiveness of pattern expressions for environmental assessment. Metric effectiveness differed among the timber harvest, road expansion, and deforestation modification schemes. The utility and limitations of each expression was discussed. Sensitivity analyses examined the effects of changing spatial scale on pattern description. Scale influence was dependent upon landscape complexity, distribution of land classes, and the size and shape of those classes. The loss of ability to detect localized variability, to differentiate among spatial patterns, and to represent boundary detail accompanied the use of large pixels (420m²). There was evidence that spatial scale influences habitat evaluation. Semivariogram analysis assessed the constancy of expression behavior during changes in scale and presented the limits of tolerance for using large pixels in pattern analyses. The variability observed suggested that pattern misrepresentation occurred at coarse resolution levels. The successful application of landscape analysis depends on the ability to quantify pattern. By analyzing and understanding selected aspects of landscape pattern, I have examined how wildlife management can be enhanced through a knowledge of the landscape. / Ph. D.

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No Abstract Provided / Thesis / Bachelor of Arts (BA)

The island of La Gonave, ~50 km northwest of Port-au-Prince, represents the subsistence Haitian lifestyle. Little is known about human--environment interactions on La Gonave. The first objective of this research was to investigate landscape dynamics through image classification, change detection, and landscape pattern analysis using Landsat 5 (TM) imagery from 1990--2010. Five land cover classes were considered: Agriculture, Forest/Dense Vegetation (DV), Shrub, Barren/Eroded, and Nonforested Wetlands. Overall image classification accuracy was 87%. The area percent change was -39.7, -22.7, 87.4, -7.0, 10.2%, for the respective classes. Landscape pattern analysis illustrated the encroachment of Shrub in core Forest/DV patches and the decline of Agricultural patch integrity. Agricultural abandonment, deforestation, and forest regrowth generated an increasingly fragmented landscape. The second objective of this research was to better understand the survival of the red-tailed hawk (RTH) on La Gonave by exploring the human--RTH relationship. We implemented a survey (n = 121) in 10 rural villages on La Gonave regarding their perceptions and interactions with the RTH during May--June, 2012. During fieldwork we sighted seven RTHs and found one nest. Many respondents noted the aggressive behavior of RTHs during nesting, suggesting reproductive behavior on the island. Our results indicate that RTHs inhabiting this island were not persecuted, despite intense predation of domestic chickens. Aside from predation near homes, villagers do not interact with the hawk as it remains out of sight. The RTH currently has no known predators, but it remains in danger of island extirpation due to ecological degradation. / Master of Science