Understanding the internal and external driving factors that impact specific gravity in Longleaf Pine through a spatial and temporal perspective
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Date
2025-04-30Type of Degree
Master's ThesisDepartment
Forestry and Wildlife Science
Restriction Status
EMBARGOEDRestriction Type
Auburn University UsersDate Available
04-30-2026Metadata
Show full item recordAbstract
Specific gravity (SG, also called relative density) is a dimensionless quantity defined as the ratio of a substance's density (mass per unit volume) to the density of a given reference material. In forestry, wood SG is often measured as the ratio of the mass of wood of a unit volume to water at a given temperature of 4 °C. It is a critical factor in estimating tree carbon storage. This study aims to identify the key environmental variables influencing the SG of longleaf pine (Pinus palustris), examine their interactions, and explore regional variations in SG across its native southern range. Additionally, anthropogenic climate change altering weather patterns may drastically impact carbon storage because carbon storage heavily relies on available moisture. Additionally, past the ring count of 62, there is very little information on how carbon is stored in high ring count trees. Therefore, we must understand how ring count and climate, with their interactions, affect carbon storage from a temporal perspective. This study attempts to understand how different climate variables (PDSI, precipitation, temperature, and vapor pressure deficit) and soil (available water capacity, sand, silt, clay, and organic matter) impact wood specific gravity. Our main finding was a strong negative relationship between SG and ring count after year 62. We also found that both precipitation and very coarse particles had a positive relationship with SG. We found negative relationships between SG and spring precipitation, annual maximum temperature, coarse sand, and organic matter. Additionally, we found one positive relationship with rainfall during June through December. We also identified the interactions between spring precipitation, precipitation between June and December, annual maximum temperature, available water capacity, and sand. For the local coefficients in the GWR, we found that most of the spatial distribution aligned with our global coefficient. However, there were specific locations within each factor where the relationship with SG remained unexplained.