Data from: Extracting coherent tree-ring climatic signals across spatial scales from extensive forest inventory data

Increasing access to extensively replicated and broadly distributed tree-ring collections has led to a greater use of these large data sets to investigate climate forcing on tree growth. However, the number of chronologies added to large accessible databases is declining and few are updated, while chronologies are often sparsely distributed and are more representative of marginal growing environments. On the other hand, National Forest Inventories (NFI), although poorly replicated at the plot level as compared to classic dendrochronological sampling, contain a large amount of tree-ring data with high spatial density designed to be spatially representative of the forest cover. We propose an a posteriori approach to validating tree-ring measurements and dating, selecting individual tree-ring width time series, and building average chronologies at various spatial scales based on an extensive collection of ring width measurements of nearly 94,000 black spruce trees distributed over a wide area and collected as part of the NFI in the province of Quebec, Canada. Our results show that reliable signals may be derived at various spatial scales (from 37 to 583,000 km2) from NFI increment core samples. Signals from independently built chronologies are spatially coherent with each other and well-correlated with independent reference chronologies built at the stand level. We thus conclude that tree-ring data from NFIs provide an extraordinary opportunity to strengthen the spatial and temporal coverage of tree-ring data and to improve coordination with other contemporary measurements of forest growth to provide a better understanding of tree growth-climate relationships over broad spatial scales.

随着广泛复现且广泛分布的树木年轮馆藏的获取门槛持续降低，学界对这类大型数据集的应用愈发广泛，以探究气候强迫对树木生长的调控作用。然而，大型可访问数据库中新增的年轮年表数量持续下滑，且鲜有得到更新；同时现有年轮年表往往分布稀疏，且更多对应边缘生长环境。另一方面，尽管与经典树木年代学采样相比，国家森林清查（National Forest Inventories, NFI）在样地水平上的复现性较差，但其包含的大量树木年轮数据拥有极高的空间密度，旨在实现森林覆盖范围的空间代表性。本研究提出一种后验分析方法，用于验证树木年轮测量数据与定年结果、筛选单棵树木的年轮宽度时间序列，并基于加拿大魁北克省国家森林清查项目收集的、广泛分布的近94000棵黑云杉的年轮宽度测量数据集，构建不同空间尺度下的平均年轮年表。研究结果表明，借助国家森林清查的生长钻芯样本，可在37至583000平方千米的各类空间尺度上提取可靠的气候信号。独立构建的年轮年表所提取的信号在空间上彼此一致，且与林分水平上构建的独立参考年表具有良好的相关性。综上，本研究认为国家森林清查所获树木年轮数据为拓展树木年轮数据集的时空覆盖范围、协同其他同期森林生长测量项目提供了绝佳契机，有助于更深入理解大空间尺度下树木生长与气候的关联机制。