Surface mining is a major industry in eastern Tennessee that removes much of the native forest. To restore the forest, reclamation practices are used. These include planting a ground cover species with native hardwoods. Competition between the ground cover and tree species for soil resources could hinder growth and decrease survival of the trees. Northern red oak (Quercus rubra) was used for this study to examine the possible effects of this competition and the relationships between root growth and soil moisture through a field and a greenhouse experiment. A field experiment was designed using four different ground cover treatments (Soldiago nemoralis, Medicago sativa, Panicum virgatum, and bare ground) with four different hardwood species. Northern red oak was measured for this study. The results showed that the site physical factors (slope position, soil temperature, and soil moisture) were not related to each other. Soil moisture varied by depth with the lower depths (46 cm to 76 cm) was much higher than the upper depths (0 to 46 cm). Root growth did not differ by treatment or percent cover. Both soil temperature and ground cover percentage increased over the growing season. Root growth showed a relationship with depth with the upper depths of soil having more roots than the lower depths. Annual rye was used as well as switchgrass, alfalfa, and bare ground treatments for a green house study. Two-year-old Northern red oak seedlings were first planted in pots and then ground covers were established and grown for 9 weeks. Then water stress was imposed over two dry down periods during which transpiration and soil moisture were measured. Root growth was measured after harvest. The results showed a relationship between transpiration and soil moisture. Soil moisture was highest in the bare ground treatment and lowest in the annual rye treatment. Fine root development of trees was greatest in the bare and alfalfa and lowest in the annual rye. Switchgrass had the second highest soil moisture and third highest fine root development. Root growth was related to both soil moisture and transpiration.

<p dir="ltr">For several decades, the ecological dominance of white oak (<i>Quercus alba</i>) has been declining throughout the species’ native range in eastern North America with failure to recruit new individuals into the overstory. White oak’s decline is concerning as the species is of great cultural, ecological, and economic value. Planting artificial regeneration is one approach to bolstering flagging natural white oak regeneration insufficient in vigor or quantity to supplant mature canopy white oak. Shelterwood harvests and artificial regeneration alone or in combination are frequently suggested to be an effective means of securing sufficient white oak regeneration in central hardwood understories. Because there is a much more comprehensive body of work examining northern red oak (<i>Quercus rubra</i>) than white oak artificial regeneration, managerial prescriptions for artificial regeneration of white oak are commonly generalized from northern red oak prescriptions. If the two species are silvically different, however, they should be managed differently to achieve maximum effectiveness of regenerative prescriptions.</p><p><br></p><p dir="ltr">I conducted both a silvicultural field trial and a more controlled shade and competition study to examine artificial white oak regeneration responses to light and competition gradients. In the silvicultural field trial, I tested the impacts of varied lengths of competition control, geographical seed source, and canopy cover on growth and survival of artificial white oak regeneration within an expanding shelterwood system. After three growing seasons, my results indicated that seedlings grow and survive at the greatest rates in areas of up to approximately 50% canopy closure, or conditions found in harvest gaps.</p><p dir="ltr">In a shade and competition study, I compared artificial northern red oak and white oak growth, morphology, and physiology responses to three light levels (10% or low, 30% or medium, and full sun or high) under the presence or absence of an invasive competitor (Amur honeysuckle (<i>Lonicera maackii</i>)). After two years, my results indicated that medium light levels resulted in the greatest height and diameter growth as well as the greatest nonstructural carbohydrate amounts in both root and shoot organs of both species. Interestingly, my physiology results indicated that northern red oak seedlings displayed lower light compensation points and greater quantum yields than white oak seedlings. These traits potentially indicate greater shade tolerance of northern red oak than white oak. Further, white oak foliar nitrogen in shaded treatments, quantum yield, and light compensation points were impacted more severely by competition than equivalent northern red oak measures, indicating that white oak seedlings may not be as well equipped to handle invasive competition pressures. These results indicate that these two upland oak species are fundamentally different, and these differences should be considered when writing management prescriptions.</p>

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<p dir="ltr">Reflectance spectroscopy has been increasingly used in forestry due to its ability to rapidly, efficiently, and non-destructively detect tree stress, enabling timely and cost-effective forest management decisions. This dissertation synthesizes three studies and five experiments to understand and improve our ability to use spectral data to estimate a variety of foliar physiochemical traits and identify spectral responses in multi-stress environments, thus, advancing our understanding and application of hyperspectral data in forest management.</p><p dir="ltr">The first study seeks to refine the hyperspectral approach to monitoring tree stress by selecting optimal wavelength ranges to enhance the estimation of foliar traits, such as CO₂ assimilation rate, specific leaf area, leaf water content, and concentrations of foliar nitrogen, sugars, and gallic acid. The study revealed that model performance varied significantly across the different wavelength ranges tested and consistently, including longer wavelength regions improved trait estimation for all traits modeled. This research also established a framework for discovering novel or previously unknown absorption features associated with functional traits, thereby laying the groundwork for expanded spectral applications. This advancement enables the estimation of diverse foliar traits and facilitates detailed stress detection in trees.</p><p dir="ltr">The second study focuses on assessing the effectiveness of hyperspectral data in estimating foliar functional trait responses to various biotic and abiotic stressors and to differentiate those stressors in black walnut (<i>Juglans nigra </i>L.) and red oak (<i>Quercus rubra</i> L.) seedlings. We demonstrated that spectral data can reliably estimate a wide range of foliar traits, highlighting its potential as a surrogate for reference data in understanding plant responses to stress. This research revealed that spectral leaf predictions can effectively provide stress-specific insights into tree physiochemical responses to biotic and abiotic stressors.</p><p dir="ltr">The third study explores the application of hyperspectral reflectance to identify drought-induced foliar responses in black walnut seedlings during their initial field establishment. Chemometric models developed from greenhouse experiments were applied to spectral data collected in the field to assess their transferability and accuracy in predicting various leaf traits under drought stress. Using only spectral data, we demonstrated that seedlings show distinct spectral responses to past and ongoing drought stress, with varying degrees depending on seed provenances. This research aims to provide practical insights for utilizing spectral analysis in real-world conditions and understanding the challenges of using spectral tools in the field.</p><p dir="ltr">Collectively, this dissertation demonstrates the robust potential of hyperspectral reflectance technology in advancing the monitoring of tree health. By optimizing spectral range selection, reliably estimating tree foliar traits under stress conditions, differentiating various stressors in controlled environments, and effectively detecting current and past drought stress in field conditions, this research offers valuable insights for improving forest health monitoring and management strategies in response to environmental challenges.</p>