Effects of Water Table Depth and Edaphic Characteristics on Plant Diversity in a Southern Mississippi Pitcher Plant Bog

<p>This study examined the effects that water table depth and soil characteristics have on plant species richness and species composition within pitcher plant bogs across seasons. Eight piezometers were installed at random distances to monitor long-term water table depth and pressure fluctuations along a ~710-meter line transect traversing upland and bog habitats. Vegetation sampling quadrats (n=128) were set up near each piezometer. Cover data and water table depths were collected in spring and late summer. Soil samples collected from each treatment group were used to obtain soil texture and nutrient data. The summer collection period yielded a total gdiversity of 152 taxa, while the spring resulted in agdiversity of 149 taxa. Grasses, sedges, and forbs were the most abundant species across both sampling seasons. Regression indicatedthat mean species richness was not significantly dependent on mean water table depth [<em>P</em>=0.1313]. Regression also concluded that mean percentage of sand in the soil had a significant, positive effect on mean water table depth [<em>P</em>=0.003].It was proposed that soil moisture levels are contributing to levels of diversity due to the mesic treatments exhibiting the highest levels of plant diversity across both sampling seasons. Statistical analyses provided evidence that soil moisture and soil texture could be gradients driving plant species composition.</p>

Name thesis:degree_name

Master of Science (MS)

Level thesis:degree_level

Masters Thesis

Year dc:date.available

2019

Author dc:creator

• Kirby, Patrick

Contributors dc:contributor

• Micheal Davis
• Mac Alford
• Frank Heitmuller

• Diversity
• Bog
• Edaphic
• Water Table
• Ecology
• DeSoto
• Biodiversity
• Biology
• Botany
• Ecology and Evolutionary Biology
• Forest Biology
• Hydrology
• Plant Biology
• Soil Science

Repository record dc:identifier

https://aquila.usm.edu/masters_theses/695

OAI identifier oai:identifier

oai:aquila.usm.edu:masters_theses-1748