解读秋季现象学:解开观察方法与检测到的环境线索之间的联系
Simon Kloos1, Anne Klosterhalfen2, Alexander Knohl2,3
1TUM School of Life Sciences, Ecoclimatology, Technical University of Munich, Freising, Germany.
Global change biology
|March 14, 2024
概括
秋季现象学,或生长季节的结束 (EOS),是复杂的. 不同的方法产生不同的结果,突出需要对所有数据源进行整体分析,以获得准确的气候变化指标见解.
科学领域:
- 生态生态学 生态生态学
- 气候科学 气候科学
- 林业林业 林业 林业 林业
背景情况:
- 秋季现象学,标志着叶子的颜色,意味着生长季节的结束 (EOS).
- EOS对于营养循环,生态相互作用至关重要,并作为气候变化指标.
- 预测未来的秋季现象是具有挑战性的,因为多个环境线索和方法变化.
研究的目的:
- 研究不同衍生方法对秋季现象学 (EOS) 和其环境驱动因素的影响.
- 使用多个数据源和方法分析生长季节的开始 (SOS) 和EOS.
- 确定方法上的不确定性是否会影响叶子衰老的环境线索.
主要方法:
- 利用德国中部一个混合树林的独特的长期数据集 (2000-2020年).
- 应用了四种不同的导出方法,使用现场数据,天花板图像,旋共变率和卫星遥感.
- 进行了叶子衰老的预测分析,受SOS和EOS在不同方法中的变化影响.
主要成果:
- 在各种方法中观察到SOS (39.5天) 和EOS (28.6天) 的平均发病日期的实质范围.
- 年间变化和SOS趋势一致,而EOS趋势有所变化 (先进或延迟),但显示出良好的相关性.
- 温暖,干燥和生产力较低的季节推迟了EOS;更冷,更潮湿和更生产力的季节推进了EOS. 没有检测到日转前植被活动对衰老的明确影响.
结论:
- 在比较衍生方法时,发现了潜在驱动因素的标志和强度的显著差异.
- 对各种现象学数据源和导出方法的综合分析对于关于秋季现象学的强有力的结论至关重要.
- 在生态系统模型中精确实施衰老过程需要考虑方法上的不确定性.
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