Dollar spot, caused by the pathogen S. homoeocarpa (F.T. Bennett), is a common disease that infects a wide variety of turfgrasses all over the world. Yet it is significant problem on golf course putting greens and fairways consisting of creeping bentgrass (Agrostis stolonifera L.) and annual bluegrass (Poa annua L.). It is active in a wide variety of environmental conditions ranging from 16-30˚C but favors warm, humid days, followed by cool nights. Sclerotinia homoeocarpa overwinters as dormant mycelium in dead plant tissue. In the spring, germinating mycelia begin to infect leaf blades causing foliar lesions, which then spread via mycelium by means of wind, rain, animals and equipment. While there are a number of cultural practices that can reduce disease severity, frequent fungicide applications are required to maintain acceptable playing conditions on a golf course. The repeated use of fungicides with the same mode of action has led to the development of fungicide resistance of S. homoeocarpa to certain fungicide classes. Most notably, demethylase inhibitor (DMI) fungicides have been found to have varying levels of inefficacy against S. homoeocarpa across North America. The cause for reduced efficacy is suspected to the shifted sensitivity levels of many S. homoeocarpa populations, which are resulted from repeated use of the DMI fungicide. Recently, “early-spring fungicide applications” targeting to reduce initial inoculum density of dollar spot have gained popularity in an attempt to reduce dollar spot severity. In addition, preventative fungicide applications (from late October through mid-November) containing DMI fungicides have been traditionally practiced to target snow molds (caused by Microdochium nivale, Typhula spp.) in the northeastern United States. To date, there is not a clear understanding as to what effect, if any, these applications have on S. homoeocarpa DMI sensitivity or residual dollar spot control the following year. Traditional preventative snow mold applications were also investigated on the effect of S. homoeocarpa DMI sensitivity and early-season dollar spot control. The objective of this study was to investigate the effect of early-spring dollar spot application and late-fall snow mold application on S. homoeocarpa population with a bimodal distribution of DMI sensitive and insensitive isolates.

Rhododendron maximum L. is a dominant subcanopy species in the southern Appalachian Mountains. R. maximum undergo distinct thermonastic leaf movements (TLM). The purpose of these movements has not yet been determined. Previous studies have suggested TLM are a photoprotective mechanism for the dynamic light environment of the subcanopy in a deciduous forest during winter. The present study aimed to determine the effects of restricting TLM on photoinhibition, net photosynthesis, and other gas exchange parameters, particularly during the early spring. After restricting TLM on certain leaves, we observed the above parameters from autumn 2005 to late spring 2006. Our results indicated that photoinhibition increased (lower Fv/Fm) in treatment leaves over reference leaves throughout the winter. The difference became greater during the early spring, when reference leaves began to return to normal levels of photochemical efficiency and treatment leaves sustained low Fv/Fm. Net photosynthesis was lower for treatment leaves than reference leaves. This became most significant during the early spring, when maximum carbon gain is possible. Finally, gas exchange parameters as measured by light and CO2 response curves did not indicate any significant difference between treatment and reference leaves post canopy closure. Out results suggest that TLM are an important mechanism for photoprotection, allowing leaves of R. maximum to recover quickly during the early spring and maximize their early spring carbon gain. / Master of Science

Several warm winter events have occurred across the Southeast in the past decade, including 2 major events in 2017 and 2018 in Georgia and South Carolina. Plants will begin their spring growth sooner than climatology would suggest and then be damaged by early spring frosts in what is commonly known as a "false spring" event. Some species of plants, like peaches and blueberries, which produce buds early in the season, are just an example of some of the agricultural products more at risk than others. As an important measure of dormancy time in plants, chill hours present a measurement capable of tracking phenological shifts in plants. While a lack of required chill hours can delay spring emergence, intense warm periods can override the chilling hour requirement and induce spring emergence. This project involves training self-organizing maps (SOMs) to identify periods of anomalous winter warming based on a reduced number of chill hours within a 5-day temporal period compared to the period's climatological average. A second SOM is nested in the node that produced the most anomalous events to identify the range of warming that occurs in the most anomalous events, the synoptic setups of these events, and when these occurred. Hourly 2-meter temperature from ERA5 is used to conduct this analysis over a domain centered primarily over South Carolina and Georgia with a temporal period of 1980-2020. Climatological examination of chill hour accumulations in the past 4 decades show an overall decrease in chill hour accumulation across the past decade (2011-2020) Results indicated that periods of higher-than-average temperatures are increasing with time while periods of average or lower than average temperatures are decreasing with time. Both results were statistically significant by Mann-Kendall test. The results of the nested SOMs suggest that an increase in patterns of southerly flow (a common pattern for warmer temperatures) is occurring through time. A third SOM investigating early spring hard freezes was inconclusive but illustrated that some years had more early spring frosts than others independent of how many warmer than average periods occurred in the main winter. The use of SOMs for investigating climatological and synoptic changes in winter and early spring proved successful and effective. Future modifications to these SOMs could be used to identify more trends that exist within these seasons. / Master of Science / Several warm winter events have occurred across the Southeast in the past decade, including 2 major events in 2017 and 2018 in Georgia and South Carolina. Plants will begin their spring growth sooner than climatology would suggest and then be damaged by early spring frosts in what is commonly known as a "false spring" event. Some species of plants, like peaches and blueberries, which produce buds early in the season, are just an example of some of the agricultural products more at risk than others. As an important measure of dormancy time in plants, chill hours present a measurement capable of tracking shifts from normal winter to spring transition in plants. While a lack of required chill hours can delay leaf emergence and spring blooms, intense warm periods can override the chilling hour requirement and induce this spring emergence. This project involves training self-organizing maps (SOMs), a machine learning model, to identify periods of anomalous winter warming based on a reduced number of chill hours within a 5-day temporal period compared to the period's climatological average. A second SOM is nested in the node that produced the most anomalously warm events to identify the range of warming that occurs in the most anomalous events, the large-scale meteorological setups of these events, and when these occurred. Hourly 2-meter temperature from ERA5, a climatological dataset, is used to conduct this analysis over a domain centered primarily over South Carolina and Georgia with a temporal period of 1980-2020. Climatological examination of chill hour accumulations in the past 4 decades show an overall decrease in chill hour accumulation across the past decade (2011-2020) Results indicated that periods of higher-than-average temperatures are increasing with time while periods of average or lower than average temperatures are decreasing with time. Both of these trend findings were statistically significant by Mann-Kendall test. The results of the nested SOMs suggest that an increase in patterns of southerly flow (a common pattern for warmer temperatures) is occurring through time. A third SOM investigating early spring hard freezes (temperatures low enough to cause damage to plant cellular structures) was inconclusive but illustrated that some years had more early spring frosts than others independent of how many warmer than average periods occurred in the main winter. The use of SOMs for investigating climatological and synoptic changes in winter and early spring proved successful and effective. Future modifications to these SOMs could be used to identify more trends that exist within these seasons.