Verification of an Environmental Impact Assessment Using a Multivariate Statistical Model

Abstract

Environmental impact assessment is a means of preventing and mitigating the adverse effects of economic development activities on the natural environment. It is meant to ensure that decision-makers have sufficient information to consider environmental impacts before proceeding with new projects. Despite their important role in public policy, verification of environmental impact assessments has seldom been conducted. In this study, we used principal component analysis (PCA) to identify the major sources of influence on the coastal waters adjacent to a major tourist facility (an aquarium) in southern Taiwan, followed by the construction of a structural equation model (SEM) to determine the direct and indirect effects of the abiotic factors on phytoplankton and zooplankton density and diversity. Based on the loadings of principal components 1–3, we identified that river input, suspended matter, and seasonal changes were the major factors affecting the coastal area. The SEM further suggested that phytoplankton density and diversity were affected directly by seasonal changes and suspended matter, but only indirectly by river input, owing to the latter’s effect on suspended matter. In contrast, the SEM suggested that zooplankton density and diversity were affected directly by seasonal changes, but indirectly by both river input and suspended matter owing to their effects on phytoplankton density and diversity. Q2 was the season with the highest number of visitors to the aquarium, but none of the abiotic or biotic parameters showed particular differences, implying that the variations in those parameters in the adjacent coastal waters were not related to the visitors. We suggest that PCA and SEM be used in the future in other contexts to verify environmental impact assessments.