Date of Award

8-2024

Document Type

Thesis

Degree Name

Master of Science (MS)

Department

Forest Resources

Committee Chair/Advisor

Dr. Bo Song

Committee Member

Dr. Thomas M. Williams

Committee Member

Dr. Thomas L. O’Halloran

Committee Member

Dr. Nilesh Timilsina

Abstract

Accessing the mortality of the trees following any disturbances is of great interest to researchers in forestry science. This thesis project assessed topographic factors to explain the patterns of tree mortality after Hurricane Hugo in 1989 and investigated continuous tree mortality in relationship to important covariates using long-term data. Aerial photographs were taken one year after Hurricane Hugo, and long-term monitoring plots were set up five years after the hurricane to collect multi-year data. Analysis and visualization showed higher mortality in concave areas near the marsh at approximately 1-2m elevation and 120-180m far from streams after Hurricane Hugo. A model was derived using the logistic regression analysis, and tree mortality after Hurricane Ian 2023 was predicted based on the model. The actual tree mortality map was generated using the Leaf Area Index change. Two maps were compared visually, and the model underestimated the mortality. Using the data from the long-term monitoring plots, we performed a nonparametric Kaplan-Meier method to describe the effects of covariates (biotic, climatic and hydrologic) on the survival probability of trees. The Kaplan-Meier Curve indicated that any tree has a survival probability of around 20% after 29 years or upon reaching a diameter at breast height (DBH) of 10 cm. Understanding how various factors interact and contribute to tree mortality will enhance our capacity to evaluate the susceptibility of coastal forests to mortality due to periodic hurricane events and how they shape the growth and resilience of coastal forests.

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