增长趋势聚类:一种用于检测森林干扰和提取树木环中的气候信号的新方法
Yao Jiang1, Zhou Wang2, Martin P Girardin3
1Key Laboratory of Vegetation Restoration and Management of Degraded Ecosystems, Guangdong Provincial Key Laboratory of Applied Botany, South China Botanical Garden, Chinese Academy of Sciences, Guangzhou 510650, China; University of Chinese Academy of Sciences, 19(A) Yuquan Road, Shijingshan, District, Beijing 100049, China.
The Science of the total environment
|August 2, 2024
概括
一种新方法,增长趋势集群 (GTC),准确地将森林干扰与树环中的气候信号分开. 这一进步提高了对气候变化下的森林动态的理解.
科学领域:
- 登德罗年代学 登德罗年代学
- 森林生态 森林生态
- 气候科学 气候科学
背景情况:
- 树环提供了关于森林干扰和气候变化的历史数据.
- 区分气候信号与树环中的干扰仍然是一个挑战,特别是在气候异常期间.
研究的目的:
- 开发一种新的方法,增长趋势集群 (GTC),使用树环数据准确区分气候影响与森林干扰.
- 加强对森林干扰制度和气候对树木生长影响的分析.
主要方法:
- 使用高斯混合模型分析年环宽度指数 (RWI) 的概率密度分布.
- 建立了歧视性标准,以将子分布聚合到增长释放,抑制或正常趋势中.
- 在加拿大六个地点的树环数据上验证了GTC方法,使用常见的干扰,如昆虫脱叶和稀薄.
主要成果:
- 在检测过去的森林干扰方面,GTC方法在传统的时间序列分析中表现出优越性.
- GTC有效地确定了森林干扰的发生,持续时间和严重程度.
- 该方法显著提高了树环数据中气候信号的检测.
结论:
- GTC方法提供了一种新的统计方法,可以准确地区分森林干扰和树环中的气候信号.
- 这一进展对于理解森林对气候变化的反应以及制定减缓战略至关重要.
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