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.

随着经过广泛复样且广泛分布的树木年轮数据集获取门槛持续降低，此类大型数据集被愈发广泛地应用于探究气候对树木生长的驱动机制。然而，新增至大型可访问数据库的年轮年表（chronology）数量呈下滑趋势，且鲜有得到更新；同时现有年表往往分布稀疏，且更多代表了边缘生境下的生长状况。另一方面，国家森林清查（National Forest Inventories, NFI）虽相较于经典树木年代学采样，在样地尺度上的复现性偏弱，但其中蕴含了大量高空间密度的树木年轮数据——这些数据的空间布设旨在精准代表区域森林覆盖特征。本研究提出一种后验方法，可用于验证树木年轮的测量与定年结果、筛选单株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（NFI）项目采集的、广泛分布的近94000株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，依托国家森林清查（NFI）的树芯样本，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。独立构建的年表所提取的信号在空间上具有良好的一致性，且与林分尺度下生成的独立参考年表存在显著相关性。综上，本研究认为国家森林清查（NFI）所提供的树木年轮数据，为拓展树木年轮数据的时空覆盖范围、优化与其他同期森林生长监测数据的协同整合提供了绝佳契机，进而有助于更深入地理解大空间尺度下树木生长与气候的关联机制。