Environmental management

This empirical study examines decision-making in project selection in the face of overwhelming flood infrastructure needs and inadequate resources, particularly in vulnerable communities. The motivation for this study is to explore the interconnectedness between socioeconomic dimensions and environmental risks in the decision-making process for selecting projects. The study evaluates the Palm Beach County project selection framework and the impact of multi-criteria decision-making on project selection by proposing a new framework. The new project selection framework emphasizes the integration of flood risk and social vulnerability index criteria to evaluate the relationship between the new criteria in the decision-making framework and project selection.
The analysis is comprised of 24 models grouped into three distinct groups and compared using paired t-tests. The analysis reveals that of the three groups, the group which incorporates both flood risks and social vulnerability criteria consistently outperforms the others, demonstrating its effectiveness in providing a more equitable investment for vulnerable communities that are more susceptible to floods. The findings provide valuable insights and recommendations for practitioners and scholars, emphasizing the need for a theoretical framework with objectivity to guide optimal infrastructure investments for decision makers.

Human activities in the past century have caused a variety of environmental
problems in South Florida. In 2000, Congress authorized the Comprehensive Everglades
Restoration Plan (CERP), a $10.5-billion mission to restore the South Florida ecosystem.
Environmental projects in CERP require salinity monitoring in Florida Bay to provide
measures of the effects of restoration on the Everglades ecosystem. However current
salinity monitoring cannot cover large areas and is costly, time-consuming, and laborintensive.
The purpose of this dissertation is to model salinity, detect salinity changes, and
evaluate the impact of salinity in Florida Bay using remote sensing and geospatial
information sciences (GIS) techniques. The specific objectives are to: 1) examine the
capability of Landsat multispectral imagery for salinity modeling and monitoring; 2)
detect salinity changes by building a series of salinity maps using archived Landsat images; and 3) assess the capability of spectroscopy techniques in characterizing plant
stress / canopy water content (CWC) with varying salinity, sea level rise (SLR), and
nutrient levels.
Geographic weighted regression (GWR) models created using the first three
imagery components with atmospheric and sun glint corrections proved to be more
correlated (R^2 = 0.458) to salinity data versus ordinary least squares (OLS) regression
models (R^2 = 0.158) and therefore GWR was the ideal regression model for continued
Florida Bay salinity assessment. J. roemerianus was also examined to assess the coastal
Everglades where salinity modeling is important to the water-land interface. Multivariate
greenhouse studies determined the impact of nutrients to be inconsequential but increases
in salinity and sea level rise both negatively affected J. roemerianus. Field spectroscopic
data was then used to ascertain correlations between CWC and reflectance spectra using
spectral indices and derivative analysis. It was determined that established spectral
indices (max R^2 = 0.195) and continuum removal (max R^2= 0.331) were not significantly
correlated to CWC but derivative analysis showed a higher correlation (R^2 = 0.515 using
the first derivative at 948.5 nm). These models can be input into future imagery to
predict the salinity of the South Florida water ecosystem.

Hypoxia and sulfide exposure, increased using glucose, are considered major environmental stressors in seagrass communities. Quantum efficiency, total soluble protein and catalase activity were quantified to evaluate the applicability of each of these bioindicators to detect environmental stress in three tropical seagrass species, Thalassia testudinum (Banks ex Kèoenig), Halodule wrightii (Ascherson) and Syringodium filiforme (Kuetz). Hypoxia + sulfide treatments significantly decreased the quantum efficiency of all three species, but showed no response in protein and catalase activity. Although no treatment effect was found, catalase activity was enhanced in T. testudinum leaves and H. wrightii roots relative to other tissues, while S. filiforme showed no location-specific catalase activity. These results indicate that quantum efficiency is a more sensitive indicator than protein and catalase activity to hypoxia and sulfide stress in seagrasses.