Master of Science (MS), Ohio University, 2020, Geography (Arts and Sciences)

In this study it was investigated if ecoregion type and hurricane-induced vegetation damage are related to recovery period in landfall areas by observing similar and different intensity hurricanes making landfall in different and similar ecoregions. Understanding of the interaction between hurricane intensity and its effects on vegetation could potentially benefit hurricane management plans and policies by observing the trend in damage and recovery period. To analyze the relation between ecoregion and hurricane, this research analyzed two comparative case studies utilizing remote sensing-based satellite images and geographic information system (GIS) tools. Results from the considered cases indicate that there is not a one-to-one relation between ecoregion type and the damage-recovery pattern of hurricanes. It cannot be generalized that hurricanes would affect vegetation similarly in similar ecoregions or differently in different ecoregions. Rather, it was found that pre-existing conditions associated with local weather and climate events and storm-scale meteorological parameters were playing a more dominant role in the characteristics of the damage footprint on vegetation in the studied cases.

Committee: Jana Houser (Advisor) Subjects: Geographic Information Science; Geography; Remote Sensing

MS, Kent State University, 2024, College of Arts and Sciences / Department of Geography

Wildfire and drought are key drivers of shrubland expansion in southwestern US landscapes. Stand-replacing fires in dry conifer forests induce shrub-dominated stages, and changing climatic patterns may cause a long-term shift from coniferous forests to deciduous shrublands. This study assessed recent changes in deciduous fractional shrub cover (DFSC) in the eastern Jemez Mountains from 2019-2023 using topographic and Sentinel-2 satellite data in a random forest model. Sentinel-2 provides multispectral bands at 10 and 20 meters, including three 20 meter red edge bands, which are highly sensitive to variation in vegetation. There is no consensus in the literature on whether upscaling imagery to 20 meters or downscaling to 10 meters is more advantageous. Therefore, an additional goal of this study was to evaluate the impact of spatial scale on DFSC model performance. Two random forest models were built, a 10 and 20 meter model. The 20 meter model outperformed the 10 meter model, achieving an R-squared value of 0.82 and an RMSE of 7.85, compared to the 10 meter model (0.76 and 9.99, respectively). The 20 meter model, built from 2020 satellite imagery, was projected to the other years of the study, by replacing the spectral variables with satellite imagery from the respective year, resulting in yearly predictions of DFSC from 2019-2023. DFSC decreased from 2019-2022, coinciding with severe drought and a 2022 fire, followed by a significant increase in 2023, particularly within the 2022 fire footprint. Overall trends showed a general increase in DFSC despite high interannual variability, with elevation being a key topographic variable influencing these trends. This study revealed yearly vegetation dynamics in a semi-arid system and provided a close look at post-fire regeneration patterns in deciduous resprouting shrubs. Understanding this complex system is crucial for informing management strategies as the landscape continues to shift from conifer forest to shrubland du (open full item for complete abstract)

Committee: Scott Sheridan (Advisor); Christie Bahlai (Committee Member); Timothy Assal (Advisor) Subjects: Ecology; Geography

Master of Science in Botany, Miami University, 2016, Biological Sciences

A floristic study of plant communities was conducted on the islands of Eleuthera, Little San Salvador, and Cat Island. The objectives of this analysis were to explore the species composition and distribution of dry forest communities among the three study sites, and to propose new classification types to facilitate plant conservation in The Bahamas, as outlined by the International Classification of Ecological Communities for Caribbean vegetation types. Unconstrained ordination, cluster analysis and indicator species analysis indicated two dominant forest types across the three study sites: the Coccothrinax argentata-Reynosia septentironalis and Coccoloba diversifolia-Bursera simaruba Alliances. Nested within these forest types were 8 species associations: Coccothrinax argentata-Reynosia septentrionalis-Pithecellobium keyense association; Zanthoxylum flavum-Jacquinia keyensis-Casasia clusiifolia association; Acacia choriophylla-Pithcellobium keyense-Guapira discolor association; Coccoloba diversifolia-Sideroxylon americanum-Pseudophoenix sargentii association; Maytenus buxifolia-Sideroxylon salicifolium association; Exothea paniculata-Tabebuia bahamensis-Metopium toxiferum association; Guaiacum sanctum association; Eugenia foetida-Exostema caribeaum-Bourreria succulenta association.

Committee: Michael A. Vincent (Advisor); R. James Hickey (Committee Member); Richard C. Moore (Committee Member) Subjects: Biology; Botany; Conservation

Doctor of Philosophy, The Ohio State University, 2016, Civil Engineering

Land-surface and ecosystem models classify trees into functional types by phenology, leaf traits, and bioclimatic limits, while excluding their hydraulic properties. Frequently, trees are grouped within the same plant functional type, despite having opposing hydraulic strategies. Errors in the prediction of transpiration and carbon uptake by land-surface models have been linked to the coarse resolution of plant functional types. We pair a field and modeling study comparing tree species typically classified together within the same functional class to highlight their divergent responses to drought and disturbance, which result, in part, from contrasting hydraulic strategies. We measured sap flux, stem water storage, stomatal conductance, photosynthesis, rooting depth, and bole growth in tree species in disturbed and undisturbed field sites in Michigan from 2010-2015. Within our research site, two of these species represent opposing extremes of the proposed whole-plant hydraulic safety-efficiency spectrum. Red oak employs an efficient but high-risk hydraulic strategy (i.e., anisohydric stomatal regulation, highly conductive xylem, deep roots) while red maple relies on an `ultra' safe strategy (i.e., isohydric stomatal regulation, less conductive xylem, shallow roots). Species-specific differences significantly influenced temporal patterns of stomatal conductance and overall transpiration responses to both drought and disturbance. Use of emergent tree-level hydraulic traits has the potential to improve model predictions of ecosystem-level transpiration and growth, particularly during periods of drought and disturbance. The implementation of such functional properties could be accomplished through either the recasting the plant functional type classification system to include whole-plant hydraulic traits, or explicitly representing plant hydrodynamics within land-surface models. Databases of species-specific hydraulic traits, such as the TRY Global Plant Trait Databas (open full item for complete abstract)

Committee: Gil Bohrer PhD (Advisor); Peter Curtis PhD (Committee Member); Gajan Sivandran PhD (Committee Member); Jeffrey Bielicki PhD (Committee Member) Subjects: Biogeochemistry; Biographies; Civil Engineering; Earth; Ecology; Hydrologic Sciences; Hydrology; Water Resource Management

Doctor of Philosophy, University of Akron, 2013, Integrated Bioscience

Climate change threatens to alter the current distribution, productivity, and community composition of wetlands in the Midwestern United States. Increasing rainfall variability and rising temperatures will yield unique stresses for wetland vegetation, including an increase in flooding severity and a higher frequency of potentially harmful heat events. This dissertation explores the interactions and impacts of climate warming and hydrologic variability on productivity, morphological plasticity, reproduction, and functional composition within wetland communities, followed by an evaluation of the connection between wetland distribution and climate on a regional scale. Climate warming led to depressions in productivity during the warmest months while hydrologic variation consistent with climate projections yielded decreases in spring production and peak biomass. Reproductive allocation and other functional trait differences suggested that the future climate will limit productivity in many wetland ecosystems in the Midwest. A distribution model based on Artificial Neural Networks projected significant increases in flooding leading to wetland expansion concentrated in the Midwestern Corn Belt and potential declines in wetland area in Minnesota and northern Michigan. These results suggest that, though wetland area is projected to increase for the Midwest, without hydrologic management, many wetland systems are at risk of community turnover and degradation resulting from a shifting climate.

Committee: Randall Mitchell Dr. (Advisor); Linda Barrett Dr. (Committee Member); Lauchlan Fraser Dr. (Committee Member); Stephen Weeks Dr. (Committee Member); Gregory Smith Dr. (Committee Member); John Senko Dr. (Committee Member) Subjects: Ecology; Geographic Information Science; Geography

Master of Science, The Ohio State University, 2009, Natural Resources

Flatiron Lake Bog in NE Ohio is one of the few remaining kettle-hole bogs in the state and is owned by The Nature Conservancy (TNC). In order to help refine the management of this property, three main goals were set to classify and describe Flatiron Lake Bog. The first goal was to classify the vegetation community types within the Flatiron Lake Bog landholding to aid in long-term planning and management of this unique resource. Seven different community types were found: mixed mesophytic forest, beech-oak-red maple forest, oak-hickory forest, aspen stands, mixed swamp, tamarack-hardwood bog, and buttonbush shrub swamp. A diversity of management issues exists in these different community types, including control of invasive species, effects of water level changes using a managed outlet structure, and agricultural runoff from neighboring landowners. The second goal of this study was to determine any changes in vegetation, water chemistry, and adjacent land use over a 24-year period. A study conducted by Kent State in 1984 provided a baseline data set of vegetation and water chemistry for the bog, which was compared to the vegetation and water chemistry currently present to determine any changes with the changing land uses. The final goal of this study was to analyze relationships along the upland-wetland gradient with differing adjacent land uses (forest or agriculture). All of these results will provide a knowledge base to allow TNC to better manage the Flatiron Lake Bog property.

Committee: Dawn Ferris PhD (Advisor); P. Charles Goebel PhD (Committee Member); Donald Eckert PhD (Committee Member) Subjects: Ecology; Environmental Science; Forestry; Freshwater Ecology; Hydrology; Soil Sciences

Master of Science, The Ohio State University, 2007, Graduate School

Committee: Not Provided (Other) Subjects:

Master of Science (MS), Ohio University, 2023, Environmental Studies (Voinovich)

As stream restoration is performed, riparian vegetation should be considered during any required construction. Since riparian inputs affect the carbon budget and the biogeochemistry of aquatic ecosystems, it is critical that carbon dynamics are examined when replanting is necessary. Floodplain reconstruction was implemented within the Robinson Fork catchment in Western Pennsylvania requiring widespread replanting. With future restoration to occur at Ryerson Station State Park and growth in stream and wetland restoration, it is imperative to ensure that the constructed riparian zones meet the restoration targets. This study asks if floodplain reconnection restoration including change in riparian vegetation impacts the amount of total organic carbon available in water and sediment. I measured aquatic total organic carbon alongside carbon sources, such as woody debris, leaf litter, and riparian vegetation, to analyze this relationship. With streams in Ryerson Station State Park representing a pre-restoration or unrestored condition, this thesis compares the the effects of the construction on carbon in the ecosystem. Statistical analysis showed that, when compared to total organic carbon, woody debris, leaf litter accumulation, soil organic matter and area weighted mean coefficient of conservatism were found not statistically different between restored and unrestored conditions, however the change in soil organic matter and area weighted mean coefficient of conservatism calculated from vegetation analysis were found to be statistically different between restoration statuses. It can be concluded from this study that after floodplain reconnection restoration as implemented in Robinson Fork, the replanted riparian vegetation does not differently affect the aquatic total organic carbon at Ryerson Station State Park and Robinson Fork.

Committee: Natalie Kruse-Daniels (Committee Chair); Sarah Davis (Committee Member); Kelly Johnson (Committee Member) Subjects: Earth; Ecology; Environmental Science; Environmental Studies; Freshwater Ecology; Hydrology

PHD, Kent State University, 2023, College of Arts and Sciences / Department of Geography

Unmanned Aerial Vehicles (UAVs) have been a popular tool for close-range remote sensing of vegetation for the past decade. They are often equipped with multispectral cameras, making them a cost-effective option for data collection in precision agriculture, forestry, and other research fields. These UAVs typically process imagery data using vegetation indices to detect plant stress and estimate vegetation coverage. Recently, consumer-level UAVs with RGB cameras have become more common for vegetation detection and extraction. A growing number of studies using these UAVs have successfully applied RGB vegetation indices for vegetation detection and extraction. However, the effectiveness of these indices still has room for improvement. This study aims to evaluate the performance of seven commonly used RGB vegetation indices in three different environmental settings. A consumer-level UAV was used to conduct three data collection sessions. The study applied two image-thresholding methods, Iterative Thresholding and Otsu's Method, to analyze the index maps obtained from each RGB-based vegetation index and assess their effectiveness for vegetation extraction.

Committee: Jay Lee (Committee Chair); Ye Zhao (Committee Member); Timothy Assal (Committee Member); He Yin (Committee Member) Subjects: Environmental Studies; Geographic Information Science; Geography; Remote Sensing

Master of Science in Botany, Miami University, 2022, Biology

Direct effects of white-tailed deer (Odocoileus virginianus) and the invasive shrub Lonicera maackii on woody vegetation are well documented, but studies exploring their long-term interactive effects are limited. I investigated effects after 11 years of deer exclusion or access and L. maackii removal or presence on woody vegetation responses in the Miami University Natural Areas in Oxford, Ohio. Deer exclusion resulted in greater tree seedling richness, density, and basal area, native and non-native shrub richness, native vine density and basal area, change in understory tree richness since 2015, and cover at 0.3 m above ground. Deer exclusion also resulted in greater basal area growth of L. maackii shrubs. Lonicera maackii, in contrast, had no direct effects. Deer and L. maackii interactions impacted native tree seedling richness and density, and total vine density. All significant interactions revealed synergy between deer exclusion and L. maackii removal, most likely due to deer reducing L. maackii cover (via herbivory) and therefore mitigating its negative competitive effects on seedlings and vines Therefore, in areas with high deer densities and dense L. maackii stands, I recommend a reduction of both stressors to prevent tree regeneration failure.

Committee: David Gorchov (Advisor); Jonathan Bauer (Committee Member); Thomas Crist (Committee Member) Subjects: Biology; Botany; Ecology

Master of Science (MS), Bowling Green State University, 2022, Applied Geospatial Science

Sustainable conservation of a vital ecosystem like a wetland demands continuous monitoring with sophisticated technologies and analytical approaches. In recent times, due to numerous advantages, analyzing remote sensing images with machine learning approaches has become a substantial way of wetland monitoring. This study employed a fine resolution multispectral image of WorldView-3 for vegetation classification of Old Woman Creek (OWC) which is a significant freshwater wetland in Ohio, USA. The classification approaches include three pixel-based (one parametric: Maximum Likelihood (ML), two nonparametric: Support Vector Machine (SVM), Neural Network (NN)) and three object-based (one parametric: Naive Bayes (NB), two nonparametric: Support Vector Machine (SVM), k-nearest neighbors (kNN)) classifiers.The study was designed to classify five dominant species over the study area namely Common reed (Phragmites australis), American water lotus (Nelumbo lutea), White water lily (Nymphaea odorata), Lesser duckweed (Lemna minor), and cattail (Typha). The primary concern of this study was to explore all eight bands of WorldView-3 and numerous features like band indices, texture, and PCA to find potential combinations that could ensure vegetation classification of OWC with optimal accuracy. Among pixel-based classifiers, SVM outperformed with the combination of eight original bands and achieved 93.76% overall accuracy (OA). The study found both N1 and N2 important for classification and suggested using the average of N1 and N2 for calculating band indices and texture analysis. Of several features, Normalized Difference Vegetation Index (NDVI) and variance image were found effective for increasing classification accuracy. Among object-based classifiers, NB performed best (93.30% OA) with the input of all eight bands and variance together. Out of five species, the lotus was identified with the highest OA (97.69%) whereas Phragmites was identified with the lowest OA (86.65%). Ob (open full item for complete abstract)

Committee: Anita Milas Ph.D. (Committee Chair); Ganming Liu Ph.D. (Committee Member); Yu Zhou Ph.D. (Committee Member) Subjects: Remote Sensing

Doctor of Philosophy, The Ohio State University, 2022, Evolution, Ecology and Organismal Biology

Desert plant communities throughout the arid Southwest are being impacted by a rapidly changing climate. In the Mojave and Sonoran Deserts, severe drought, linked to global climate change, is causing widespread mortality of long-lived species. Biotic interactions, both competitive and facilitative, mediate plant responses to stressful conditions. Consequently, the spatial pattern of plants on the landscape, which determines the intensity of interactions between individuals, is a legacy of past conditions, a moderator of present drought mortality, and a driver of future community change. To better understand how interactions between adjacent individuals affects the rates of growth, survival, and mortality of desert shrubs in a changing climate, in Chapter One I investigated the spatial demography of the numerically dominant species, Ambrosia dumosa (Asteraceae), using a size and neighbor-classified matrix model parameterized with twenty years of data from a permanent one-hectare site in Joshua Tree National Park that spanned periods of historically average climate and extreme drought. I classified 9,215 Ambrosia individuals into six size classes and two neighbor states. Differences in the demography of isolated and neighbored population subsets of this species shifted with drought, illustrating how spatial pattern mediates the impact of climate change. High interannual and intra-annual variability in rainfall challenges desert shrub seedlings with a tradeoff between drought tolerance and competitive ability. I hypothesized that Ambrosia seedlings can acclimate to wetter or drier conditions by modifying their proportion of roots and leaves, based on early-life moisture cues. In Chapter Two I performed a greenhouse experiment to investigate how root/shoot allocation of Ambrosia was affected by variation in the timing of water availability. Seedlings received the same total quantity of water, differing only in the timing of water delivery. Seedlings lacking wa (open full item for complete abstract)

Committee: Maria Miriti (Advisor); Stephen Hovick (Committee Member); G. Matthew Davies (Committee Member); Elizabeth Marschall (Committee Member) Subjects: Biostatistics; Conservation; Demography; Ecology

MS, University of Cincinnati, 2020, Arts and Sciences: Geology

Understanding past changes in vegetation, hydroclimate, and fire is crucial for constraining future change as a consequence of climate change. In the northern Great Plains, at least during the Holocene, fire disturbance is controlled by drought, plant community dynamics, and fuel availability (Winkler et al., 1997; Brown et al., 2005; Nelson et al., 2004). Unfortunately, fire-vegetation dynamics are poorly defined in the central US as records of vegetation, hydroclimate, and fire that extend past the Wisconsin glaciation are rare. To better understand past changes in this region, we have reconstructed vegetation, hydroclimate, and fire conditions using plant compounds (long chain n-alkanes and terpenoids), long chain n-alkane carbon (d13C) and hydrogen (d2H) isotopes, and polycyclic aromatic hydrocarbons (PAHs) preserved in sediments from Ben Lake in central Illinois (USA). This site is unique in that it is located in an area of high loess deposition during past glaciation, a time when few records are preserved. This provides an opportunity to reconstruct paleovegetation, paleohydrology, and fire for this region during the Wisconsin glaciation. Based on the plant compounds and their isotopes, we identify two mixed vegetation regimes that capture changes distinct changes between biomes 1) a forest and mixed C3/C4 grassland regime, and 2) a C3 grassland and mixed C3/C4 grassland. We find that fire and vegetation dynamics are markedly different for each of these two regimes. In the forest – C3/C4 grassland regime, the forest biome is associated with low fire input and the mixed C3/C4 grassland biome is associated with high fire input. In the C3 grassland – mixed C3/C4 grassland regime, the C3 grassland biome is associated with high fire, but the mixed C3/C4 grassland biome is associated with lower fire input. The results of this study will be useful for better predicting the effect of future climatic change on vegetation and fire in the central US.

Committee: Aaron Diefendorf Ph.D. (Committee Chair); Thomas Lowell Ph.D. (Committee Member); Dylan Ward Ph.D. (Committee Member) Subjects: Geology

Master of Arts, University of Toledo, 2020, Geography

For several decades, urban crime has been a major problem for cities around the world. There is much debate about whether the amount of vegetation in an urban area leads to more or less crime. When studying this matter, geographic information systems (GIS) and remote sensing play an important role in the analysis of this relationship. This research draws from analytical methods found in contemporary literature as a means to discover a relationship between crime and vegetation in Toledo, Ohio. Socioeconomic factors are another aspect in this analysis, because vegetation is not the sole predictor of crime. The research furthers the understanding of the need for community initiatives to lower the impact of urban crime by highlighting a local neighborhood-based organization, the Cherry Street Legacy Project, which incorporates Crime Prevention Through Environmental Design (CPTED) principles into its work.

Committee: Yanqing Xu (Committee Chair); Beth Schlemper (Committee Member); Bhuiyan Alam (Committee Member) Subjects: Criminology; Geographic Information Science; Geography

Doctor of Philosophy, The Ohio State University, 2020, City and Regional Planning

This dissertation presents a comprehensive analytical framework for examining urban green infrastructure and its urban planning implications. Comprised of four essays, this research investigates the concepts, measurement, modeling and implications of urban green spaces and vegetation (UGSV). Leveraging the increasing variety and precision of geospatial big data and techniques, this research characterizes the heterogeneity of UGSV in terms of physical form and functions to inform the effective environmental design of UGSV. The first and second essays present methods for the assessment of spatial patterns of UGSV and their socioeconomic accessibility using various green measures. Remote sensing, GIS and pattern recognition techniques are used to measure UGSV over large geographic areas with fine thematic resolution. The third and fourth essays deal with planning applications, focusing on the relationship between UGSV, sustainable mobility and microclimate moderation. The results imply that urban and suburban neighborhoods experience significant disparities in terms of socioenvironmental benefits provided by UGSV, and the assessment of how and where the inequity occurs varies with green measures and applications. UGSV relates closely to the long-term sustainability of active travel and thermal environment, while the benefits are likely to be spatially and socially limited to certain groups, requiring targeted planning interventions. This dissertation highlights the importance of a multidisciplinary understanding of `greenness' in urban areas, suggesting that divergent understandings in different fields should be integrated to formulate a coherent strategy for green infrastructure planning.

Committee: Jean-Michel Guldmann (Advisor); Gulsah Akar (Advisor); Desheng Liu (Committee Member) Subjects: Urban Planning

Master of Science, The Ohio State University, 2020, Environmental Science

In the arctic region, permafrost exists as a deep, frozen layer of soil, some of which formed during cold glacial periods thousands of years ago. This freeze effectively trapped carbon and other nutrients from decomposing and/or cycling into the ecosystem. However, due to climate warming, this frozen layer is thawing, releasing long-storage carbon stocks and transforming the landscape as ground sinks to fill space left by ice. This consequently drives shifts in hydrology (i.e., water-levels) and in plant communities, with their own impacts on carbon balance. My master's thesis work examines arctic wetland plants under climate change, as part of an interdisciplinary US Department of Energy-funded exploration of carbon cycling of these wetland systems that spans microbiology to models, and via which I get to actively and regularly engage with project colleagues from 13 institutions across 3 continents (The IsoGenie Project). A major goal of this work is to better understand and predict changing carbon budgets in the Arctic, and the magnitude of their climate feedbacks, thereby directly informing climate mitigation and adaptation efforts. The IsoGenie Project has been studying this phenomenon at Stordalen Mire, a northern peatland in Sweden, which is actively thawing. This active thaw allows us to observe three unmistakable habitat-types in one location, each with their own distinct hydrology and plant community. After thaw-associated inundation, the Stordalen Mire dwarf-shrub dominated palsa experiences an intermediate shift to moss dominated (Sphagnum sp.) bog and finally into a graminoid dominated (Eriophorum sp.) fen. We refer to this linear progression of habitat and vegetation changes as the thaw gradient. Prior studies have supported that post-thaw shifts in community composition, coupled with shifts in environmental conditions, will influence the vegetation's role in rate of C and nutrient cycling after thaw. My thesis research asks how permafrost thaw ch (open full item for complete abstract)

Committee: Virginia Rich (Advisor); Gil Bohrer (Committee Member); Scott Saleska (Committee Member); Mark Dilley (Committee Member) Subjects: Climate Change; Environmental Studies; Freshwater Ecology; Plant Biology

Master of Science, The Ohio State University, 2019, Environment and Natural Resources

Early successional bird species have exhibited population declines across North America coinciding with a loss in early successional forest habitats. Additionally, forest conversion and fragmentation has increased with the recent boom in unconventional shale gas development throughout Appalachia; a critically important region for songbird conservation. However, pipeline ROWs, which represent the largest proportion of the modern shale gas development footprint, provide new opportunities for early successional habitat management. This potential has been demonstrated for similarly configured powerline ROWs managed using Integrated Vegetation Management (IVM) approaches, but minimal research is available for corridors with underground infrastructure that require more strict vegetation management regulations. To understand the potential of natural gas pipelines to harbor shrubland habitat, I investigated the application of forest edge-notch techniques and IVM treatments to pipeline ROW edges to promote increased structural complexity of vegetation and to mitigate the negative effects of high contrast edges. The goals of this study were to describe the current avian community structure at the pipeline-forest interfaces and how it compares with similar landscapes and core forest habitats. Additionally, I wanted to assess the response of early successional bird communities to edge-notch vegetation treatments that promote increased shrubland structure and edge complexity along pipeline ROWs. Finally, I aimed to estimate avian breeding parameters, including rates of nest survival, predation, and nest parasitism of early successional birds that nest along pipeline edges to assess the viability of these nesting habitats for declining species. Forest-edge plots (control=11, experimental=12) were established at 10 sites across five counties in Eastern Ohio. Edge-notch treatments significantly decreased basal area (76%, P < 0.001), canopy cover (46%, P = < 0.001), and understor (open full item for complete abstract)

Committee: Stephen Matthews PhD (Advisor); Gabriel Karns PhD (Committee Member); Robert Gates PhD (Committee Member); Chris Tonra PhD (Committee Member) Subjects: Ecology; Environmental Science; Wildlife Conservation; Wildlife Management

Master of Science (MS), Bowling Green State University, 2018, Geology

Evapotranspiration (ET) is a hydrologically and eco-agronomically important process that can be altered by soil properties, crop type and mechanisms of photosynthesis (e.g. C3 and C4), crop status, agricultural practices (crop rotation and monoculture), and meteorology. In particular, corn monoculture, which is widely used in the U.S, may affect over agricultural fields differently than soybean and wheat deu to the different (C4) photosynthesis mechanism, and thus can have an impact on local hydrologic cycle and climate. Satellite observations are the most sophisticated technology to monitor different rates of ET at large scale. This study used data from two satellites, Landsat 8 and Sentinel 2, to examine the capability of combining those data in ET time series to explore the differences between ET rates for C3 (soybean and winter wheat) and C4 (corn) crops. ET was estimated for a study area located in the Western Lake Erie basin for 2016 and 2017 using satellite data and the Boreal Ecosystem Productivity simulator (BEPS), a process based ecosystem model, modified for the agricultural ecosystem. Satellite images (from which land cover/land use data, and leaf area index were generated), weather (Gridmet data), and soil data (SSURGO data) were main inputs to BEPS. In addition, a sensitivity analysis was conducted to estimate ET for different percent increments of the total area covered by corn to the point of becoming a monoculture using synthetically developed land covers and LAI images. For both years, corn and soybean reach the maximum ET rate in the mid-growing season as expected with the peak being somewhat later in the season for soybean. The ET relationship between two sensors was strong during the mid-season (r = 0.95 for July) when LAI was high, and at the end of the season, when many crops were harvested and soil exposed (r = 0.98 for iv October). A high correlation was also observed when data were acquired within a short period of time (open full item for complete abstract)

Committee: Anita Simic Dr. (Advisor); Peter Gorsevski Dr. (Committee Member); Ganming Liu Dr. (Committee Member) Subjects: Agriculture; Agronomy; Earth; Ecology; Environmental Geology; Geobiology; Geology; Remote Sensing

Ph.D., Antioch University, 2018, Antioch New England: Environmental Studies

Changes in forest cover especially changes within tropical forests, affect global climate change, together with ecosystems and forest carbon. Forests play a key role in both carbon emission and carbon sequestration. Efforts to reduce emissions through reduced deforestation and degradation of forests have become a common discussion among scientists and politicians under the auspices of the United Nations Programme on Reducing Emissions from Deforestation and Forest Degradation (UN-REDD Programme). This dissertation research assessed the impacts of land use land cover change upon ecosystem services from a protected area focusing on forest carbon distribution and vegetation mapping using remote sensing and geographical information systems (GIS). I also assessed Rwanda's preparedness in the United Nations global program, Reducing Emissions from Deforestation and forest Degradation, Measuring, Monitoring, Reporting, and Verifying (REDD+MMRV). I carried out research in Nyungwe National Park (NNP), one of four National Parks of Rwanda. NNP is a montane tropical forest located in the Albertine Rift, one of the most biodiverse places in central and east Africa. I used remote sensing and field data collection from December 2011 and July 2012 in the western part of the Park to assess distribution and quantities of aboveground (ABG) forest carbon using generalized allometric functions. Using Landsat data together with 2009 high resolution color orthophotos and groundtruthing, I analyzed land cover changes between 1986 and 2011 for NNP. The land-use land cover change analysis showed that between 1986 and 1995 there was a minor increase in forest cover from 53% to 58% while from 1995-2003 a substantial decrease in forest cover occurred. Between 2003 and 2011 was a period of recovery with forest cover increasing by 59%. Vegetation analysis based on a 2009 Park biodiversity survey yielded 13 vegetation communities based on dominant and co-dominant species. Macaranga kilimandschar (open full item for complete abstract)

Committee: Beth Kaplin PhD (Committee Chair); Peter Palmiotto DF (Committee Member); Naikoa Aguilar-Amuchastegui PhD (Committee Member) Subjects: Environmental Studies; Geographic Information Science; Remote Sensing

PhD, University of Cincinnati, 2017, Arts and Sciences: Geology

In order to confidently use sulfur isotopes in archaeological and ecological research, it is necessary to establish the extent to which natural and anthropogenic sources of sulfur are integrated into terrestrial biological systems. In particular, it is necessary to discern the relative impact of atmospheric sulfur sources on the sulfur isotope values in vegetation, and consequently, to animals consuming vegetation. Terrestrial vegetation uses sulfur from geologic and atmospheric sulfur sources to help form essential compounds such as amino acids. There has been less sulfur isotope work on terrestrial vegetation than on soils, air, or wet and dry deposition. Furthermore, previous sulfur isotope studies have been geographically limited; there has been an absence of sulfur isotope work concerning pollution in the midwestern United States, and an absence of sulfur isotope work in general in the Caribbean on terrestrial biological systems. In this dissertation, I address these gaps in the existing literature. In Chapter 2, I investigate the degree to which coastal proximity, wind direction, and precipitation amount influence the distribution of marine sulfur in terrestrial vegetation on Trinidad. I found that both precipitation amount and wind direction are important controls, and vegetation at locations with high precipitation amounts and an oceanic wind have the highest sulfur isotope values; additionally, although high sulfur isotope values for plants from locations <1.5 km from the ocean indicate a heavy influence of marine sulfur, sulfur isotope values for vegetation growing up to 10 km from the ocean still demonstrate the impact of marine sulfur. In Chapter 3, I use my results from Chapter 2 to investigate foraging strategies for prehistoric Trinidadians. Specifically, I assess the degree to which the combination of sulfur, carbon, and nitrogen isotope values in bone collagen from zooarchaeological remains can be used to identify reliance on terrestrial prey (open full item for complete abstract)

Committee: Brooke Crowley Ph.D. (Committee Chair); Nicholas Dunning Ph.D. (Committee Member); Warren Huff Ph.D. (Committee Member); Kenneth Tankersley Ph.D. (Committee Member); Yurena Yanes Ph.D. (Committee Member) Subjects: Biogeochemistry