Understanding the Spatial Pattern and Driving Factors Associated with Timberland Ownership Change in the Northern United States
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Journal of Forestry
This study analyzes changes in timberland ownership from 2003 to 2012 across the northern United States based on Forest Inventory and Analysis data identified according to five ownership categories. A total of 26,940 FIA plots that were remeasured between selected years were used for the analysis. Publicly available corporate ownership data were investigated and used to differentiate industrial and institutional (timber investment management organizations [TIMO] and real estate investment trusts [REIT]) ownership. Kernel density, Ripley’s K-function, and multinomial logistic regression (MLR) methods were used to study spatial patterns of timberland ownership and to explore statistical relationships. Among FIA plots showing ownership changes, the largest observed shift was from industrial to institutional ownership, with a 45% increase in the number of plots, equivalent to almost 1.4 million acres of timberland area. Bivariate Ripley's K-function showed significant clustering for shifts between industrial and institutional ownership. A MLR model identified forest type as a significant factor associated with the transition of industrial timberlands to either institutional or family forest ownership. In addition, shifts from industrial to institutional ownership were related to road access and population density.
KeywordsFIA; multinomial logistic regression; timberland ownership; TIMO; REIT; Ripley’s K-function; kernel density estimation
Pandit, Karun; Bevilacqua, Eddie; Newman, David H; Butler, Brett J. 2021. Understanding the Spatial Pattern and Driving Factors Associated with Timberland Ownership Change in the Northern United States. Journal of Forestry. 119(4): 376-392. https://doi.org/10.1093/jofore/fvab017.