Semester of Graduation

Summer 2026

Degree

Master of Science (MS)

Department

Entomology

Document Type

Thesis

Abstract

Giant salvinia (Salvinia molesta D.S. Mitchell) is one of the most damaging aquatic invasive weeds in coastal Louisiana, forming dense floating mats that degrades water quality, impede navigation, and displace native vegetation. Biological control with the salvinia weevil (Cyrtobagous salviniae Calder & Sands, Coleoptera: Curculionidae) is the most cost-effective management tool, yet evaluating infestation extent and weevil establishment across remote wetlands remains constrained by labor-intensive monitoring. This study integrated satellite and unmanned aerial vehicle (UAV) remote sensing to detect and monitor giant salvinia and its biological control at complementary spatial scales.

At a broader scale, a Google Earth Engine web application was developed to detect and monitor floating aquatic vegetation across waterbodies in coastal Louisiana. Using Sentinel-1 and Sentinel-2 satellite imagery and vegetation index thresholding, the application provides near-real-time detection, time series analysis of macrophyte cover, and downloadable data. The application updates satellite images as they become available. We used the aquatic vegetation coverage predicted by the application to make inference of the impact on two contrasting settings: an urban site in New Orleans East and a natural wetland in Cameron Parish.

At the fine scale, multispectral UAV imaging was used to detect giant salvinia stress induced by weevil herbivory under controlled mesocosm conditions across two seasons. The sensor detected weevil-induced stress through declining NDVI values. This spectral decline reflected biomass loss caused by insect feeding. Detection developed over time as feeding accumulated and differed by season, becoming evident at approximately six weeks in summer but not until twenty-one weeks in winter. Even the lowest weevil density tested produced a detectable NDVI response, indicating sensitivity to moderate herbivory. Together, these results suggests that satellite and UAV remote sensing provide a decision-support model for monitoring giant salvinia and its biological control.

Date

7-16-2026

Committee Chair

Diaz, Rodrigo

LSU Acknowledgement

1

LSU Accessibility Acknowledgment

1

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Available for download on Sunday, July 15, 2029

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Entomology Commons

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