Date of Award

January 2020

Document Type

Thesis

Degree Name

Master of Science (MS)

Department

Earth System Science & Policy

First Advisor

Sean T. Hammond

Abstract

Vida is an explicit biometric simulator tool used to predict multiple aspects of plant populations and community dynamics. Vida is a growth model combined with a reiterative algorithm. The software is written in Python and uses species-specific growth data to model virtual forest ensembles based on each species’ growth parameters. Biometric modeling tools like Vida are reliable because they are based on mathematically observed biological truths, of which scientists can use to enhance the predictive power of ecological approaches in different areas. These simulation outputs can be used to demonstrate the ways a forest grows over time. The user can also model the ensemble’s response(s) to various environmental disturbances using “event files” which the Vida program recognizes. We have elected to use this tool in a multi-scale study of BC3F3 American-Chinese Chestnut tree reintroduction into Beanfield Mountain of Giles County, Virginia. Using Vida, we parameterized the Beanfield Mountain environment, introduced the BC3F3 American-Chinese Chestnut tree, observed how the environment reacted to the reintroduction, and reported on the most successful reintroduction method at that location based on Vida outputs. The completion of this research revealed that among three commonly used reintroduction techniques (random, one large center grid, and four small quads) the intervention consisting of small plots and slow, steady reintroduction coupled with clear-cutting the plots generated the most successful and sustainable reintroduction approach. Overall, the most successful method of BC3F3 American-Chinese species reintroduction at the Beanfield Mountain site is the four quads method, where the species is reintroduced using four small plots every two years. The results of this study are specific to the BC3F3 American-Chinese Chestnut tree reintroduction into a Virginia site, on Beanfield Mountain in Giles county.

Share

COinS