Dr. Matthew C Schwartz

The UWF GeoScholars program was designed based on the inherently interdisciplinary nature of geoscience research and careers. Specifically, we sought to demonstrate to undergraduate geoscience students the need for including content and skills from other academic areas, while also showing non-geoscience undergraduate majors the application of their fields of study to a range of geoscience topics, including climatology, soil science, and geomorphology. We secured NSF IUSE funding to pair faculty and undergraduate researchers from the UWF Department of Earth & Environmental Sciences with faculty-student partners from non-geoscience UWF departments, including Biology, Chemistry, Computer Science, Information Technology, and Mathematics & Statistics. Research team faculty mentors collaborated to identify an interdisciplinary geoscience research project that employed specific areas of interest and expertise from the geoscience and non-geoscience participants. Faculty then worked with the UWF GeoScholars directors to identify and recruit students from a targeted pool of eligible undergraduate students. Research teams then conducted related research, with students funded as part of the UWF Summer Undergraduate Research Program (SURP) and continuing through the subsequent academic year(s) culminating in each student presenting research at a regional or national geoscience conference, also attended by the non-geoscience faculty mentors. Additionally, the UWF GeoScholars program developed a series of professional development engagement activities that began in the UWF SURP program and continued in regular GeoScholars programs during the academic year. Professional development highlights included student researcher sessions with regional geoscience employers and representatives from national geoscience PhD graduate programs. Now in its third year, the UWF GeoScholars has facilitated multiple new interdisciplinary faculty collaborations, trained more than 20 undergraduate students in research and professional skills, and engaged regional industry partners with the University community as demonstration of the multitude of paths into the geosciences.

Online analytical processing databases allow for the efficient analysis of vast amounts of data. In this paper, we describe the design of an online analytical processing data cube structure for use in the analysis of multiple measures of environmental water quality data. The measures, also known as facts, will be the quantitative values returned by various water quality tests while the dimensions will be the attributes that describe the what, when and where of the water quality test measures. The data model and build process presented here will allow for varying types of tests and for the insertion of new data as it becomes available. The overall goal of this design is to provide business intelligence capabilities to water quality decision makers.

Submarine groundwater discharge (SGD) is described as groundwater flowing from land into water in coastal environments via a submerged shoreline. Determining the spatial distribution of SGD flux is important because this hydrologic flux can have a significant influence on nutrient and water volume input into coastal environments. The objectives of this study were to identify locations of submarine groundwater discharge, and to determine if there was a relationship between the spatial distribution of SGD and the seagrass beds along the coast of the Naval Live Oaks Preserve, Santa Rosa County, Florida. Surface water and groundwater samples were taken to determine nutrient concentrations in nearshore groundwater as well as near depth surface water over seagrass beds. Nutrient analysis was done initially to begin looking for variability in the water composition. Identification of possible SGD sites was done via detection of naturally occurring radioisotopes, Rn-220 and Rn-222 using a RAD7 instrument. From this study, most of the possible SGD sites were identified nearshore within the study area, especially within the approximately 10 meters closest to shore based on elevated Rn-220 and Rn-222 concentrations. Despite a possible correlation between higher radon signals and seagrass beds from visual reviews of the data, the relationship between seagrass and SGD distribution are still indeterminate for the study area.