于健^1,,
林万众²,
闫伯前^2,,,
刘琪璟¹
1. 北京林业大学林学院, 北京 100083
2. 北京农学院植物科学技术学院, 北京 110016

基金项目: 国家自然科学基金项目（批准号：31370587）资助


详细信息

作者简介: 于健, 男, 32岁, 博士研究生, 树轮气候学研究, E-mail:yujian1986829@sina.com

通讯作者: 闫伯前, E-mail:yanboq@sohu.com

中图分类号: P532

收稿日期:2017-11-13
修回日期:2018-03-20
刊出日期:2018-07-30

Tree-ring reconstruction of June-August mean minimum temperature back to 1872 A.D. in the Qinling Mountains, Northwest China

Yu Jian^1,,
Lin Wanzhong²,
Yan Boqian^2,,,
Liu Qijing¹
1. College of Forestry, Beijing Forestry University, Beijing 100083
2. College of Plant Science and Technology, Beijing University of Agriculture, Beijing 110016


More Information

Corresponding author: Yan Boqian,E-mail:yanboq@sohu.com

MSC: P532

--> Received Date: 13 November 2017
Revised Date: 20 March 2018
Publish Date: 30 July 2018


摘要
摘要:基于树木年代学方法，建立太白红杉（Larix chinensis）树木年轮宽度年表，明确影响太白红杉径向生长的关键气候因子。相关分析表明：温度是限制秦岭太白山太白红杉径向生长的主要因子，尤其是生长季温度；降水对其生长的影响相对薄弱。树木生长与当年6~8月最低温度（r=0.673，p < 0.01）相关性最高。利用一元线性回归方程重建秦岭北坡过去137 a以来的6~8月最低温度，该方程的方差解释量为45.3%，经逐一剔除（leave-one-out）和分段检验法（calibration-verification）进行方程检验，发现该重建序列结果稳定可靠。过去137 a间该地区存在4个偏冷期（1881~1901年、1908~1926年、1946~1957年和1963~1978年）和1个偏暖期（1990~2008年）。文章重建序列的冷暖时期与秦岭山脉东南部地区树轮记录的温度事件具有很好的一致性，进一步表明重建结果的可靠性。空间分析发现重建序列对于采样点周边较大范围地区6~8月最低温度变化特征都具有很好的代表性；与海温数据空间分析显示，温度重建序列与太平洋海温呈显著正相关；多窗谱分析（MTM）分析表明，重建的最低温度序列存在2.5 a和5.7 a的显著周期（p < 0.01）；与此同时，6~8月最低温度与ENSO、PDO在年际和年代际尺度的对比上也具有较好的对应关系。综上表明，ENSO和PDO对研究区6~8月最低温度有较大影响。
关键词: 秦岭/
树木年轮/
气候变化/
温度重建/
太白红杉

Abstract:Here we present a 137-year June-August mean minimum temperature reconstruction based on tree-ring widths of Larix chinensis in the Taibai Mountain National Nature Reserve in the central area of the Qinling Mountains, Shaanxi Province in Northwestern China. A total of 45 cores from 45 living trees were extracted from this area(33.97°N, 107.7°E; 3274 m a.s.l.) in August, 2008. All cores were air-dried prior to mounting and sanding, and samples were prepared following standard dendrochronological techniques. To mitigate potential trend distortion problem in traditionally detrended chronology, we used a signal-free method to detrend tree-ring series using RCSigFree program. Finally, the stabilized signal-free chronology was used for the subsequent analysis. Climate-growth correlation analysis revealed that the growing season temperature was the main climatic factor controlling tree-ring growth in the Taibai Mountain. The precipitation on the growth effect is relatively weak. According to the stronger relationship(r=0.673, p < 0.01) between June-August mean minimum temperature in the current year and tree-ring widths chronology, we reconstruct the June-August mean minimum temperature in the Qinling Mountains using a simple liner regression model. The reconstruction equation explained 45.3%of the variance of the mean minimum temperature(1959~2008). The equation is checked by leave-one-out and calibration-verification methods. The regression equation is deemed stable and reliable. Four cold periods(1881~1901, 1908~1926, 1946~1957, and 1963~1978) and one warm periods(1990~2008) occurred in this region for the past 137 a. We found that the cold and warm periods of the reconstructed sequences were in accordance with other temperature events in the southeastern Qinling Mountains on decadal timescales, which further demonstrated the reliability of the reconstructed results. Spatial correlation analyses with a gridded temperature dataset showed that our temperature reconstruction sequences has a good representation for the variation of June-August mean minimum temperature in the Qinling Mountains(26°~43°N, 104°~122°E). In addition, the spatial analysis with SST data also showed that the temperature reconstruction sequences of this study had a significant positive correlation with the Pacific Ocean sea-surface temperatures(SSTs). Power spectrum reveals the existence of significant frequency cycles of variability at 2.5 a and 5.7 a(p < 0.01), which may be linked to large-scale atmospheric-oceanic variability, such as the El Ni?o -Southern Oscillation(ENSO). At the same time, June-August mean minimum temperature had a better correspondence with ENSO and PDO in the comparison of interannual and decadal scales. To sum up, ENSO and PDO may influence June-August mean minimum temperature through their teleconnection in the Qinling Mountains. This reconstruction is not only useful in improving our knowledge of long-term temperature variation but also useful in predicting the tree growth dynamics in the future in the study area.
Key words:Qinling Mountains/
tree-ring/
climate change/
temperature reconstruction/
Larix chinensis



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