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树木年轮的年内密度波动是欧洲各地空气温度的代理指标。

Intra-annual density fluctuations in tree rings are proxies of air temperature across Europe.

机构信息

Department of Environmental, Biological and Pharmaceutical Sciences and Technologies, University of Campania 'L. Vanvitelli', Via Vivaldi 43, 81100, Caserta, Italy.

The Earth Institute, Tree-Ring Laboratory, Lamont-Doherty Earth Observatory of Columbia University, New York, 10964, USA.

出版信息

Sci Rep. 2023 Jul 29;13(1):12294. doi: 10.1038/s41598-023-39610-8.

DOI:10.1038/s41598-023-39610-8
PMID:37516810
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10387074/
Abstract

Intra-Annual Density Fluctuations (IADFs) are an important wood functional trait that determine trees' ability to adapt to climatic changes. Here, we use a large tree-ring database of 11 species from 89 sites across eight European countries, covering a climatic gradient from the Mediterranean to northern Europe, to analyze how climate variations drive IADF formation. We found that IADF occurrence increases nonlinearly with ring width in both gymnosperms and angiosperms and decreases with altitude and age. Recently recorded higher mean annual temperatures facilitate the formation of IADFs in almost all the studied species. Precipitation plays a significant role in inducing IADFs in species that exhibit drought tolerance capability, and a growth pattern known as bimodal growth. Our findings suggest that species with bimodal growth patterns growing in western and southern Europe will form IADFs more frequently, as an adaptation to increasing temperatures and droughts.

摘要

年内密度波动(IADFs)是一个重要的木材功能特性,决定了树木适应气候变化的能力。在这里,我们利用来自欧洲八个国家 89 个地点的 11 个树种的大型树木年轮数据库,分析气候变异如何驱动 IADF 的形成。我们发现,在裸子植物和被子植物中,IADF 的发生与轮宽呈非线性增加,而与海拔和年龄呈负相关。最近记录的较高年平均温度几乎在所有研究的物种中都有利于 IADF 的形成。降水在耐旱能力强的物种和双峰生长模式的物种中诱导 IADF 形成方面起着重要作用。我们的研究结果表明,在西欧和南欧生长的具有双峰生长模式的物种将更频繁地形成 IADF,以适应不断升高的温度和干旱。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7db0/10387074/e817c5470df1/41598_2023_39610_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7db0/10387074/92b80252e0d3/41598_2023_39610_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7db0/10387074/f1837b08446e/41598_2023_39610_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7db0/10387074/dc72f509cda6/41598_2023_39610_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7db0/10387074/2697441bda2e/41598_2023_39610_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7db0/10387074/434c6290baf1/41598_2023_39610_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7db0/10387074/e817c5470df1/41598_2023_39610_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7db0/10387074/92b80252e0d3/41598_2023_39610_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7db0/10387074/f1837b08446e/41598_2023_39610_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7db0/10387074/dc72f509cda6/41598_2023_39610_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7db0/10387074/2697441bda2e/41598_2023_39610_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7db0/10387074/434c6290baf1/41598_2023_39610_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7db0/10387074/e817c5470df1/41598_2023_39610_Fig6_HTML.jpg

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本文引用的文献

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2
Wood Growth in Pure and Mixed L. Forests: Drought Influence Depends on Site Conditions.纯林和混交落叶松林的木材生长:干旱影响取决于立地条件。
Front Plant Sci. 2019 Apr 2;10:397. doi: 10.3389/fpls.2019.00397. eCollection 2019.
3
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双峰型树木生长-气候响应模式的生理意义。
Int J Biometeorol. 2024 Sep;68(9):1897-1902. doi: 10.1007/s00484-024-02706-5. Epub 2024 May 30.
4
INTRAGRO: A machine learning approach to predict future growth of trees under climate change.INTRAGRO:一种用于预测气候变化下树木未来生长情况的机器学习方法。
Ecol Evol. 2023 Oct 20;13(10):e10626. doi: 10.1002/ece3.10626. eCollection 2023 Oct.
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Tree Physiol. 2018 Aug 1;38(8):1213-1224. doi: 10.1093/treephys/tpy061.
4
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Ann Bot. 2018 May 11;121(6):1231-1242. doi: 10.1093/aob/mcy008.
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