Sampling bias overestimates climate change impacts on forest growth in the southwestern United States
Sampling bias overestimates climate change impacts on forest growth in the southwestern United States
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DOI：
10.1038/s41467-018-07800-y
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发表时间：
2018-12-17
影响因子：
16.6
通讯作者：
Evans, Margaret E. K.
中科院分区：
文献类型：
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作者：
Klesse, Stefan;DeRose, R. Justin;Evans, Margaret E. K.
年轮记录的气候-树木生长关系最近成为预测气候变化对森林影响的基础。然而，国际树轮数据库（ITRDB）中的大多数树木和采样点都是为了最大限度地提高气候信号而选择的，其特点是边际生长条件不代表较大的森林生态系统。我们评估这种潜在的偏见使用空间无偏的树木年轮网络收集的USFS森林调查和分析（FIA）计划的幅度。我们表明，美国西南部ITRDB样本高估了区域森林气候敏感性41- 59%，因为ITRDB树木是在宏观和微观地点尺度上的温暖和干燥地点采样的，并且与FIA收集的树木相比系统性较老。虽然我们的统计方法存在不确定性，但基于代表性FIA样本的预测表明，与基于气候敏感ITRDB样本的预测相比，气候变化引起的增长减少了29%。
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.