为什么模型低估了西非热带森林的初级生产力?
Huanyuan Zhang-Zheng1,2, Xiongjie Deng3, Jesús Aguirre-Gutiérrez3,4
1Environmental Change Institute, School of Geography and the Environment, University of Oxford, Oxford, United Kingdom. huanyuan.zhang@ouce.ox.ac.uk.
Nature communications
|November 6, 2024
概括
西非热带森林的总初级生产率 (GPP) 比以前建模的更高. 通过使用局部数据来改进模型,例如分量吸收光合作用辐射 (fAPAR),可以解决这些差异.
科学领域:
- 生态生态学 生态生态学
- 地球系统科学 地球系统科学
- 森林科学 森林科学 森林科学
背景情况:
- 热带森林对于全球光合作用至关重要.
- 与现场数据相比,现有的模型往往低估了西非森林的生产力.
- 数据模型的不匹配妨碍了准确的碳循环评估.
研究的目的:
- 调查热带森林总初级生产率 (GPP) 的现场测量和模型估计之间的差异.
- 通过全球模型确定西非森林中GPP低估的原因.
- 为GPP估计模型和输入数据提出改进建议.
主要方法:
- 生物识别GPP测量与西非研究地点的多个全球GPP产品进行了比较.
- 一个标准的光合作用模型被更新为局部场测量的分数吸收光合作用辐射 (fAPAR) 和光合作用特征.
- 分析了由于云污染导致的远程传感产品对fAPAR的系统低估.
主要成果:
- 在研究地点,生物识别GPP测量平均比全球GPP产品高56.3%.
- 当将本地fAPAR和特征数据结合起来时,GPP的模型低估明显减少.
- 遥感产品平均低估了faPAR的33.9%,主要是由于云层覆盖.
结论:
- 全球GPP模型可能会系统地低估热带森林的生产力,特别是在西非等地区.
- 准确的现场衍生数据,特别是fAPAR和光合作用特征,对于改善光合作用模型至关重要.
- 通过遥感解决云污染问题,并整合本地测量是推动热带森林碳循环研究的关键.
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