Theses and Dissertations

ORCID

https://orcid.org/0000-0003-2878-7987

Issuing Body

Mississippi State University

Advisor

Granger, Joshua J.

Committee Member

Zhou, Qian

Committee Member

Poudel, Krishna P.

Committee Member

Yang, Yun

Committee Member

Self, Brady

Date of Degree

12-13-2024

Original embargo terms

Worldwide

Document Type

Dissertation - Open Access

Major

Forest Resources (Forestry)

Degree Name

Doctor of Philosophy (Ph.D.)

College

College of Forest Resources

Department

Department of Forestry

Abstract

This dissertation addresses critical challenges in forest management and restoration in the Lower Mississippi Alluvial Valley (LMAV) through a series of interconnected studies focused on improving habitat suitability modeling and growth prediction for oak species. The research employs advanced modeling techniques to enhance our understanding of species-habitat relationships and forest dynamics in the context of climate change. Initial studies focused on developing ensemble habitat suitability models for American chestnut (Castanea dentata) and butternut (Juglans cinerea), two historically important but currently threatened tree species. These models predict suitable habitats and potential range shifts under various climate change scenarios, highlighting the species' vulnerabilities and informing conservation strategies. Building on these approaches, the research expands to model habitat suitability for eight key oak species in the LMAV. This multi-species analysis reveals both shared and distinct ecological requirements among the oak species, providing valuable insights for targeted restoration efforts. Niche overlap analysis further elucidates potential species interactions and habitat partitioning within the region. The dissertation culminates in the development of improved climate-sensitive growth and yield models for bottomland oaks. By incorporating habitat suitability predictions as a modifier, these models demonstrate significantly enhanced accuracy compared to traditional approaches. This integrated modeling framework offers a more comprehensive understanding of oak growth dynamics under changing environmental conditions. Throughout the research, the importance of key environmental drivers, such as temperature, precipitation, and soil characteristics, is consistently highlighted. The studies also underscore the potential impacts of climate change on species distributions and forest composition in the LMAV. This research contributes to the advancement of forest modeling techniques and provides practical insights for sustainable forest management, conservation of threatened species, and climate change adaptation strategies. The findings have important implications for decision-making in forestry and conservation, particularly in the LMAV but with potential applications to other regions. Future research directions are suggested, including the use of higher-resolution datasets and validation across diverse ecosystems to further improve model applicability and accuracy.

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