Over the last century, millions of hectares of wetlands have been lost due to urban development and agricultural activities throughout the world. In the U.S., efforts have been made by federal and state legislation to restore wetland habitat in exchange for development on wetlands. To restore ecosystem function by reestablishing hydrological metrics (e.g., groundwater level fluctuations), wetland restoration aims to facilitate the growth of wetland vegetation to approximate the original conditions as a proxy for ecological integrity. In 1992, the first landscape-scale off-site mitigation project, the Disney Wilderness Preserve (DWP) was funded by the Walt Disney Company in Poinciana, Florida. My objective was to use digitized land cover categories based on aerial photography (1941-2019) and 35 years of Landsat satellite imagery (1985-2019) to analyze landscape and spectral properties of DWP to better understand the trajectories of bayhead, cypress, and marsh wetland types before and after the eco-hydrological enhancement. After the enhancement, the areal extent of cypress and mixed hardwood swamps and marsh lands slightly increased, while the area of the bayhead swamps slightly decreased. From the spectral trajectory analyses, the initial responses to the enhancement varied among wetland communities and more overall variability among patches was observed through the post-enhancement periods compared to pre-enhancement periods. Post-enhancement trajectories returned to similar levels to pre-enhancement for the majority of the wetlands. This study illustrates the opportunities and challenges associated with monitoring complex wetlands systems for future planning and adaptive management by conservation managers and scientists.
Identifer | oai:union.ndltd.org:ucf.edu/oai:stars.library.ucf.edu:etd2020-1541 |
Date | 01 January 2021 |
Creators | Parker, Sarah |
Publisher | STARS |
Source Sets | University of Central Florida |
Language | English |
Detected Language | English |
Type | text |
Format | application/pdf |
Source | Electronic Theses and Dissertations, 2020- |
Page generated in 0.0014 seconds