IN SEARCH OF THE FOREST PRIMEVAL: DATA-DRIVEN APPROACHES TO MAPPING HISTORIC VEGETATION

Biogeography is the study of the spatial distribution of biota. It is a comparative and observational science that seeks to describe the variations in the spatial patterns of biodiversity through the examination of historical (e.g. vicariance, speciation, and extinction) and ecological (e.g. climate, edaphic, and topographic) factors. Additionally, researchers are increasingly recognizing the role that anthropogenic disturbance regimes have played in shaping current biogeographic patterns. Indeed, in many parts of the world, humans have become the dominant force in alterations to biotic distributions. Since human activities can influence biotic patterns for many years, the interpretation of biogeographic phenomenon without consideration of human influence may lead to erroneous conclusions.This research is built upon the broad supposition that evaluation of current biogeographic patterns must be predicated on antecedent conditions, typically prior to widespread anthropogenic disturbance regimes. To this end, this research utilizes historical data to create baselines from which subsequent changes in biogeographic patterns can be measured. In a narrow sense, this dissertation focuses on land use, land cover, and woody plant compositional changes in the Arbuckle Mountains of south-central Oklahoma during a period of rapid demographic change (circa 1870 to 1898). In this regard, this research seeks to provide insight into the ecological processes of habitat fragmentation, woody plant encroachment, and mesophication that are believed to have occurred subsequent to the periods under investigation in this research.In a broader context, this research is an evaluation of how anthropogenic alterations in landscape pattern and processes may affect the distributions of individual woody plant taxon. Though the datasets utilized in this research are unique to the region, the methods employed in this study should be transferable to other areas of interest. Additionally, the patterns and processes under investigation are not unique to the region under investigation. The results of this research, therefore, should be placed within the context of anthropogenic change that has occurred throughout the eastern deciduous forests of North America, particularly in the western cross timbers, in the period following European settlement.In order to accomplish these goals, this dissertation is divided into two broad research themes. The first employs repeat Public Land Survey System (PLS) data from the 1870s and 1890s, respectively, to quantify changes in landscape structure, woody taxa assemblages, and anthropogenic markers in the Arbuckle Mountains during this period of rapid demographic transition. The second utilizes a Bayesian method known as weights-of-evidence to address the problem of coarse sampling structure of PLS records. The results of this research indicate that the landscape of the Arbuckle Mountains became increasingly fragmented during the approximately 27 years between the two surveys, primarily due to land clearance for agriculture, transportation networks, and anthropogenic structures. Additionally, there were changes in stand composition between the two surveys, implying that these anthropogenic disturbance regimes may be responsible for shifts in biogeographic patterns. The weights-of-evidence method proved to be a statistically valid method to map individual taxon distributions at finer resolutions than afforded from traditional methods of mapping PLS data. These findings will help further elucidate subsequent distributional shifts in these taxa, thereby providing a better understanding of contemporary biogeographic patterns

Mapping annual forest cover in sub-humid and semi-arid Regions through analysis of Landsat and PALSAR imagery

Accurately mapping the spatial distribution of forests in sub-humid to semi-arid regions over time is important for forest management but a challenging task. Relatively large uncertainties still exist in the spatial distribution of forests and forest changes in the sub-humid and semi-arid regions. Numerous publications have used either optical or synthetic aperture radar (SAR) remote sensing imagery, but the resultant forest cover maps often have large errors. In this study, we propose a pixel- and rule-based algorithm to identify and map annual forests from 2007 to 2010 in Oklahoma, USA, a transitional region with various climates and landscapes, using the integration of the L-band Advanced Land Observation Satellite (ALOS) PALSAR Fine Beam Dual Polarization (FBD) mosaic dataset and Landsat images. The overall accuracy and Kappa coefficient of the PALSAR/Landsat forest map were about 88.2% and 0.75 in 2010, with the user and producer accuracy about 93.4% and 75.7%, based on the 3270 random ground plots collected in 2012 and 2013. Compared with the forest products from Japan Aerospace Exploration Agency (JAXA), National Land Cover Database (NLCD), Oklahoma Ecological Systems Map (OKESM) and Oklahoma Forest Resource Assessment (OKFRA), the PALSAR/Landsat forest map showed great improvement. The area of the PALSAR/Landsat forest was about 40,149 km2 in 2010, which was close to the area from OKFRA (40,468 km2), but much larger than those from JAXA (32,403 km2) and NLCD (37,628 km2). We analyzed annual forest cover dynamics, and the results show extensive forest cover loss (2761 km2, 6.9% of the total forest area in 2010) and gain (3630 km2, 9.0%) in southeast and central Oklahoma, and the total area of forests increased by 684 km2 from 2007 to 2010. This study clearly demonstrates the potential of data fusion between PALSAR and Landsat images for mapping annual forest cover dynamics in sub-humid to semi-arid regions, and the resultant forest maps would be helpful to forest management.This study was supported in part by research grants from the National Institute of Food and Agriculture, U.S. Department of Agriculture (2013-69002), the National Science Foundation (NSF) EPSCoR program (OIA-1301789), and the Department of the Interior, United States Geological Survey to AmericaView (G14AP00002).Ye

Cancer therapy shapes the fitness landscape of clonal hematopoiesis.

Acquired mutations are pervasive across normal tissues. However, understanding of the processes that drive transformation of certain clones to cancer is limited. Here we study this phenomenon in the context of clonal hematopoiesis (CH) and the development of therapy-related myeloid neoplasms (tMNs). We find that mutations are selected differentially based on exposures. Mutations in ASXL1 are enriched in current or former smokers, whereas cancer therapy with radiation, platinum and topoisomerase II inhibitors preferentially selects for mutations in DNA damage response genes (TP53, PPM1D, CHEK2). Sequential sampling provides definitive evidence that DNA damage response clones outcompete other clones when exposed to certain therapies. Among cases in which CH was previously detected, the CH mutation was present at tMN diagnosis. We identify the molecular characteristics of CH that increase risk of tMN. The increasing implementation of clinical sequencing at diagnosis provides an opportunity to identify patients at risk of tMN for prevention strategies

Cancer therapy shapes the fitness landscape of clonal hematopoiesis.

Acquired mutations are pervasive across normal tissues. However, understanding of the processes that drive transformation of certain clones to cancer is limited. Here we study this phenomenon in the context of clonal hematopoiesis (CH) and the development of therapy-related myeloid neoplasms (tMNs). We find that mutations are selected differentially based on exposures. Mutations in ASXL1 are enriched in current or former smokers, whereas cancer therapy with radiation, platinum and topoisomerase II inhibitors preferentially selects for mutations in DNA damage response genes (TP53, PPM1D, CHEK2). Sequential sampling provides definitive evidence that DNA damage response clones outcompete other clones when exposed to certain therapies. Among cases in which CH was previously detected, the CH mutation was present at tMN diagnosis. We identify the molecular characteristics of CH that increase risk of tMN. The increasing implementation of clinical sequencing at diagnosis provides an opportunity to identify patients at risk of tMN for prevention strategies

Historical accounts of the transformation of a prairie town

Prior to European settlement, the area that would later become Norman, Oklahoma was dominated by prairie vegetation. Woody vegetation was limited to riparian zones and isolated groves presumably protected from the effects of fire. The contemporary landscape of Norman, stands in stark contrast to this “treeless” prairie, and is now characterized by a so-called urban forest. In this paper, we analyze a number of archival sources, ranging from early expedition and traveler accounts to post-settlement photography in order to qualitatively assess the nature of the landscape in and around the present-day city of Norman prior to and immediately following European settlement. We also utilize repeat photography to document the floristic and vegetation changes that have occurred. We found that the pre-European settlement landscape was characterized by rolling prairies heavily influenced by the grazing of black-tailed prairie dogs (Cynomys ludovicianus), bison (Bison bison), and pronghorn antelope (Antilocapra americana). Forbs were limited and herbaceous vegetation was dominated primarily by closely grazed grasses. Woody vegetation was limited primarily to watercourses and ravines, though numerous accounts cite thickets of oaks (Quercus spp.) occurring in the adjacent cross timbers. Today, the vegetation of Norman is characterized by the dominance of woody vegetation. Within Norman’s historical residential areas, commonly occurring species include hackberry (Celtis occidentalis), Shumard’s oak (Q. shumardii), silver maple (Acer saccharinum), and sycamore (Platanus occidentalis)

Groundwater Governance and the Growth of Center Pivot Irrigation in Cimarron County, OK and Union County, NM: Implications for Community Vulnerability to Drought

Cimarron County, Oklahoma and Union County, New Mexico, neighboring counties in the Southern High Plains, are part of a vital agricultural region in the United States. This region experiences extended periods of cyclical drought threatening its ability to produce, creating an incentive for extensive center pivot irrigation (CPI). Center pivots draw from the rapidly depleting High Plains Aquifer System. As a result, the prospect of long-term sustainability for these agricultural communities is questionable. We use Remote Sensing and Geographic Information Systems to quantify growth in land irrigated by CPI between the 1950s and 2014, and key informant interviews to explore local perspectives on the causes and impact of such growth. In Cimarron County, OK, CPI increased by the mid-1980s, and has continually increased since. Results suggest adaptation to drought, a depleting aquifer, high corn prices, and less rigid groundwater regulations contribute to CPI growth. Conversely, CPI in Union County, NM, increased until 2010, and then declined. Results also suggest that drought-related agricultural changes and more aggressive well drilling regulations contribute to this decrease. Nevertheless, in both counties, there is a growing concern over the depleting aquifer, the long-term sustainability of CPI, and the region’s economic future

Lessons from the Archives: Understanding Historical Agricultural Change in the Southern Great Plains

In the US, agriculture rapidly expanded beginning in the 1850s, influenced by homesteader policies and new technologies. With increased production also came widespread land-use/land-cover change. We analyze historical agricultural policies and associated land and water use trajectories with a focus on the Southern Great Plains (SGPs). Rapid changes in agriculture and reoccurring drought led to the infamous Dust Bowl, triggering new agricultural and land management policies, with lasting impacts on the landscape. To understand historical agricultural change, we use mixed methods, including archival literature and historical agricultural census data (1910 to 2017) from three counties in a tri-state (Oklahoma, New Mexico, Colorado) area of the SGPs. Our archival policy and agricultural census analysis illustrates 110 years of agricultural change, showing that agricultural policies and technological advances play an integral role in the development of agroecological systems, especially the Conservation Reserve Program (CRP), the Environmental Quality Incentives Program (EQIP), and the Livestock Forage Disaster Program (LFP). Further, while communities began with distinct agricultural practices, agricultural policy development resulted in increasing uniformity in crop and livestock practices. The results suggest that there are sustainability lessons to be learned by looking to the land and water trajectories and accompanying unintended consequences of the past

A Land Systems Science Framework for Bridging Land System Architecture and Landscape Ecology: A Case Study from the Southern High Plains

Resource-use decisions affect the ecological and human components of the coupled human and natural system (CHANS), but a critique of some frameworks is that they do not address the complexity and tradeoffs within and between the two systems. Land system architecture (LA) was suggested to account for these tradeoffs at multiple levels/scales. LA and landscape ecology (LE) focus on landscape structure (i.e., composition and configuration of land-use and land-cover change [LULCC]) and the processes (social-ecological) resulting from and shaping LULCC. Drawing on mixed-methods research in the Southern Great Plains, we develop a framework that incorporates LA, LE, and governance theory. Public land and water are commons resources threatened by overuse, degradation, and climate change. Resource use is exacerbated by public land and water policies at the state- and local-levels. Our framework provides a foundation for investigating the mechanisms of land systems science (LSS) couplings across multiple levels/scales to understand how and why governance impacts human LULCC decisions (LA) and how those LULCC patterns influence, and are influenced by, the underlying ecological processes (LE). This framework provides a mechanism for investigating the feedbacks between and among the different system components in a CHANS that subsequently impact future human design decisions