Wade Christopher M, Baker Justin S, Latta Gregory, Ohrel Sara B, Allpress Justine
RTI International, Research Triangle Park, NC 27709.
Natural Resources and Society, University of Idaho, Moscow, ID 83844.
J For. 2019;117(6):560-578. doi: 10.1093/jofore/fvz054.
As the demand for forest products and carbon storage in standing timbers increases, intensive planting of forest resources is expected to increase. With the increased use of plantation practices, it is important to understand the influence that forest plot characteristics have on the likelihood of where these practices are occurring. Depending on the goals of a policy or program, increasing forest planting could be a desirable outcome or something to avoid. This study estimates a spatially explicit logistical regression function to assess the likelihood that forest plots will be planted based on physical, climate, and economic factors. The empirical results are used to project the potential spatial distribution of forest planting, at the intensive and extensive land-use margins, across illustrative future scenarios. Results from this analysis offer insight into the factors that have driven forest planting in the United States historically and the potential distribution of new forest planting in the coming decades under policy or market scenarios that incentivize improved forest productivity or certain ecosystem services provided by intensively managed systems (e.g., carbon sequestration).
随着对林产品的需求以及立木碳储存需求的增加,预计森林资源的集约种植将会增多。随着人工造林实践的更多应用,了解林地特征对这些实践发生地点可能性的影响至关重要。根据政策或项目的目标,增加森林种植可能是一个理想的结果,也可能是需要避免的情况。本研究估计了一个空间明确的逻辑回归函数,以评估基于自然、气候和经济因素进行林地种植的可能性。实证结果用于预测在未来不同情景下,森林种植在集约和粗放土地利用边际的潜在空间分布。该分析结果有助于深入了解美国历史上推动森林种植的因素,以及在激励提高森林生产力或集约管理系统提供的某些生态系统服务(如碳固存)的政策或市场情景下,未来几十年新森林种植的潜在分布。