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.

中文翻译：

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了解与美国北部 Timberland 所有权变化相关的空间格局和驱动因素

本研究基于根据五种所有权类别确定的森林清查和分析数据，分析了 2003 年至 2012 年美国北部林地所有权的变化。在选定年份之间重新测量的总共 26,940 个 FIA 地块用于分析。公开的公司所有权数据被调查并用于区分工业和机构（木材投资管理组织 [TIMO] 和房地产投资信托 [REIT]）的所有权。使用核密度、Ripley 的 K 函数和多项逻辑回归 (MLR) 方法来研究林地所有权的空间模式并探索统计关系。在显示所有权变化的 FIA 图中，观察到的最大转变是从工业所有权到机构所有权，地块数量增加了 45%，相当于近 140 万英亩的林地面积。双变量 Ripley 的 K 函数显示出产业所有权和机构所有权之间转移的显着聚类。MLR 模型将森林类型确定为与工业林地向机构或家庭森林所有权过渡相关的重要因素。此外，从工业所有权向机构所有权的转变与道路通行和人口密度有关。MLR 模型将森林类型确定为与工业林地向机构或家庭森林所有权过渡相关的重要因素。此外，从工业所有权向机构所有权的转变与道路通行和人口密度有关。MLR 模型将森林类型确定为与工业林地向机构或家庭森林所有权过渡相关的重要因素。此外，从工业所有权向机构所有权的转变与道路通行和人口密度有关。