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The role of disturbance is widely recognized as a fundamental driver of ecological organization from individual species to entire landscapes. Anthropogenic disturbances from military training provide a unique opportunity to examine effects of disturbance on vegetation dynamics, physicochemical soil properties, and ecosystem processes. Additionally, plant functional diversity has been suggested as the key to ecosystem processes such as productivity and nutrient dynamics. I investigated how disturbance and functional composition both singly and in combination affect vegetation dynamics, soil physicochemical properties, and ecosystem processes. I conducted my research at Fort Pickett, Virginia, USA to take advantage of the spatially and temporally predictable disturbance regime. In order to investigate the effect of plant functional composition on ecosystem properties, I used functional groups comprised of species with similar physiology and effects on ecosystem processes (C4 grasses, C3 grasses, legumes, forbs, woody plants). My study showed that two distinct disturbances associated with military training, vehicle maneuvers, and fire; affect functional group abundance, within functional group richness, and total species richness. I found strong effects of vehicle maneuvers on soil physical properties including an increase in bulk density and reduction in soil porosity. Fire also influenced soil physical properties but more indirectly through the reduction of above ground litter inputs. Though many of the measured physicochemical soil properties at Fort Pickett exhibited statistically significant effects of disturbance, the strength of these relationships appears to be modulated by influences of previous land use. I found statistically significant (P < 0.05) effects of disturbance on chlorophyll fluorescence, and effect of functional composition on available soil N- NH4+. In addition, I detected a significant interactive effect of disturbance class and functional composition on soil CO2 flux. The interactive effects of disturbance and functional composition on soil CO2 flux demonstrated how the loss of functional diversity could lead to instability in ecosystem processes in disturbed ecosystems.    In a dynamic ecosystem, I demonstrated that the abundance and diversity of plant functional groups was significantly influenced by disturbance. By experimentally altering the abundance and diversity of these functional groups in a disturbance-mediated ecosystem, I showed that functional groups and presumably species influence key ecosystem processes. / Ph. D.

Research was conducted using the Soil-Plant-Atmosphere-Research (SPAR) units at Mississippi State University, Starkville, MS to investigate temperature effects on warm- and cool-season turfgrasses. Data collected include clipping yield, total root biomass, and relative chlorophyll index (RCI). Cultivars and species in the study included: ‘Latitude 36’, ‘Tifway’, ‘MSB-285’, and ‘TifEagle’ bermudagrass, ‘Meyer’ zoysiagrass, ‘Penn A1/A4’ and ‘Penncross’ creeping bentgrass, ‘Midnight’ Kentucky bluegrass, ‘Fiesta 4’ perennial ryegrass, and ‘Falcon V’ tall fescue. Grasses were grown in the SPAR units at varying day/night temperature regimes. Clipping yield was collected every three days, and regression was used to determine the temperature at which clipping yield equaled zero. Root biomass was collected at the conclusion of the trial, while RCI was taken once weekly. Base temperature for warm-season grasses ranged from 12.5 to 13.2°C. Determined optimum temperatures ranged from 31.8 to 36.1°C for warm-season turfgrasses and 18.8 to 20.6°C for cool-season turfgrasses.

The progressive increase in the global population and the rapidly changing climate have put unprecedented pressure on crop production. Cowpea is one of the world’s most important leguminous crops, contributing to food security and environmental sustainability. However, cowpea productivity is limited due to waterlogging stress. The main objective of this study was to explore physiological and biochemical mechanisms to understand how cowpea genotypes respond to waterlogging stress. Four studies were conducted in controlled and field conditions to achieve these objectives. Study 1 characterized the waterlogging tolerance of 30 cowpea genotypes in a controlled environment using 24 morphophysiological parameters with waterlogging tolerance coefficients and multivariate analysis methods. 10% of the genotypes exhibited high tolerance to waterlogging stress, and the genotypes UCR 369 and EpicSelect.4 were identified as the most and least waterlogging tolerant, respectively. Study 2 evaluated the key parameters influencing carbon fixation of UCR 369 and EpicSelect.4 at the reproductive stage. The less tolerant EpicSelect.4 experienced high downregulation of stomatal and non-stomatal limiting factors during waterlogging and recovery, resulting in decreased carbon assimilation rates. UCR 369 rapidly developed adventitious roots, maintained biomass, and restored pigments and metabolites to sustain photosynthesis. A two-year field experiment was conducted in study 3 to quantify the effects of waterlogging on the yields, physiology, and biochemistry of cowpeas at different growth stages. The most apparent impact of waterlogging stress occurred at the reproductive stage, followed by the vegetative and maturity growth stages. Studies suggest that diverse cowpea genotypes have distinct physiological and biochemical mechanisms in response to waterlogging stress. In addition, the tolerant genotypes and traits identified herein can be used in genetic engineering and cowpea breeding programs that integrate increased yield with waterlogging stress tolerance.

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Utah Lake is a really large but shallow lake located in the arid environment of the Western United States. Due to a variety of factors it is listed by the Environmental Protection Agency as an "impaired water body" and must be closely monitored. Because of its large extent and shallow depth the water quality is heterogeneous and can change rapidly. This means that traditional water quality monitoring methods, which require large investments in field personnel, equipment, and water sample analysis, cannot produce a model that is truly representative of the entire water body. This thesis examines the feasibility of using remotely sensed imagery to develop a water quality monitoring system for Utah Lake that is accurate, repeatable and cost-effective. Due to the paucity of in situ water quality information, this is primarily a pilot study using Landsat satellite imagery collected within a 5-day window of existing in situ water samples measuring chlorophyll a. The brightness values of the imagery were regressed against the water samples to produce a model to accurately predict chlorophyll a concentrations across the entire lake. The results of the pilot study conclude that Landsat imagery could be a very useful monitoring tool if sufficient in situ data for calibration were available.

Deer Creek Reservoir in Utah has a history of high algae concentrations. Despite recent nutrient reduction efforts, seasonal algae continue to present problems. Cost effective, accurate, and comprehensive monitoring is important to understand the reservoir processes driving this problem and characterizing the algae spatial and temporal distributions are an important part of this effort. Current laboratory methods for accurately measuring algae are expensive and time consuming and are based on water samples taken in the field and transported to the laboratory. This approach only provides data for relatively few point samples because of the time and expense of sample collection and analysis. These relatively few samples do not describe the complex spatial and temporal trends in the algal data. Algae exhibit non-uniform distributions, especially in the vertical direction. In situ probes are able to measure chlorophyll-a and provide a less expensive measuring alternative than laboratory methods. These probes provide relatively quick, high resolution vertical profile measurements, which allows for more comprehensive horizontal and temporal sampling. To have confidence in the probe data, good correlations between in situ chlorophyll-a measurements and laboratory algae or chlorophyll measurements are important, but these correlations can be reservoir and time dependant as reservoir conditions change. Therefore, they must be developed for each study site. This study reports on efforts at Deer Creek Reservoir to develop these correlations and provide a general description of the dynamic reservoir algal processes. I found that chlorophyll-a is weakly correlated to most algae species in the reservoir. However, it correlated well with total phytoplankton biovolume and the dominant algal species, which for this study was the diatom. Variations in correlation strength among the several algae species was assumed to most likely be affected by environmental factors, sample methods, algae species diversity, and the accuracy of the optical chlorophyll-a sensor. The data analysis indicate that the field methods used to obtain laboratory samples may have been a significant source of error because of the difficulty of matching the location of a probe measurement to the location of a sample. Field samples were not taken at the same depths as probe measurements and field samples from two locations were either mixed before laboratory analysis or the sample was a composite over a 2-meter range. Based on my observations, I have made several recommendations to improve the accuracy of the correlation between algae and chlorophyll-a.

This study shows the results of testing previous research that used remote sensing techniques to determine chlorophyll-a concentrations in turbid surface waters, and developing similar methods and models for Utah Lake using Landsat 7 ETM+ satellite imagery and field measured concentrations of chlorophyll-a. The data for the study included images acquired on June 22 and July 8, 2009. The field data included ground measurements taken on June 22 and July 6, 2009 from seven water quality sampling locations. The 48 hour time difference between the Landsat image acquisition (July 8) and the field measurement (July 6), and the small sample size for the data analysis were potential sources of error. The log transformation of red/near-infrared reflectance (i.e. ln[Band3/Band4]) had a high correlation with the field measured chlorophyll-a concentrations (R^2 = 0.9337). With this relationship, a model and 19 contour maps showing the spatial distribution of chlorophyll-a concentrations over Utah Lake was developed for the spring, summer, and fall seasons of 2003 to 2010. Generally about 90% of the Lake area had chlorophyll-a concentrations lower than 20µg/L. High concentrations of Chlorophyll-a (355µg/L and over) were observed mostly at the Provo Bay and Goshen Bay areas of the Lake. Occasionally, elevated levels of chlorophyll-a were observed at the northeastern, middle, and western sections of the lake. Utah Lake's average chlorophyll-a concentration is declining over time. In spring, the Lake average chlorophyll-a concentration reduced from 30.51µg/L in 2004 to 7.08µg/L in 2010. In summer, this average reduced from 132.13µg/L in 2003 to 36.58µg/L in 2010. Finally, in fall, the Lake average chlorophyll-a concentration reduced from 273.40µg/L in 2006 to 33.59µg/L in 2010. Field measured concentrations of phosphorus and model estimates for chlorophyll-a concentrations were highly correlated (R^2 = 0.9046). This suggests that the elevated levels of chlorophyll-a might be a result of the point and non-point discharge of phosphorus-laden wastewater from treatment plants, municipal storm drains, and agricultural activities.

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