Laboratory of Tree-Ring Research, University of Arizona, 1215 East Lowell Street, Tucson, AZ, 85721, USA.
U.S. Forest Service, Rocky Mountain Research Station, Forest Inventory and Analysis, 507 25th Street, Ogden, UT, 84401, USA.
Nat Commun. 2018 Dec 17;9(1):5336. doi: 10.1038/s41467-018-07800-y.
Climate-tree growth relationships recorded in annual growth rings have recently been the basis for projecting climate change impacts on forests. However, most trees and sample sites represented in the International Tree-Ring Data Bank (ITRDB) were chosen to maximize climate signal and are characterized by marginal growing conditions not representative of the larger forest ecosystem. We evaluate the magnitude of this potential bias using a spatially unbiased tree-ring network collected by the USFS Forest Inventory and Analysis (FIA) program. We show that U.S. Southwest ITRDB samples overestimate regional forest climate sensitivity by 41-59%, because ITRDB trees were sampled at warmer and drier locations, both at the macro- and micro-site scale, and are systematically older compared to the FIA collection. Although there are uncertainties associated with our statistical approach, projection based on representative FIA samples suggests 29% less of a climate change-induced growth decrease compared to projection based on climate-sensitive ITRDB samples.
近年来，树木年轮的年生长量与气候的关系记录被广泛应用于预测气候变化对森林的影响。然而，国际树木年轮数据库（ITRDB）中大多数树木和采样点的选择都是为了最大限度地提高气候信号，其生长条件较差，不能代表更大的森林生态系统。我们利用美国林务局森林清查和分析（FIA）计划收集的空间无偏树木年轮网络来评估这种潜在偏差的幅度。结果表明，由于 ITRDB 树木是在更温暖和干燥的位置上采样的，无论是在宏观还是微观尺度上，并且与 FIA 采集的树木相比，其年龄也更大，因此 ITRDB 样本高估了美国西南部的森林气候敏感性 41-59%。尽管我们的统计方法存在不确定性，但基于有代表性的 FIA 样本的预测表明，与基于气候敏感的 ITRDB 样本的预测相比，气候变化引起的生长减少幅度减少了 29%。
