基于沙漠植物功能特征的最小数据集,预测生态系统功能的空间分布特征
Yudong Chen1,2,3, Jinlong Wang1,2,3, Lamei Jiang1,2,3
1College of Ecology and Environment, Xinjiang University, Urumqi, China.
Frontiers in plant science
|June 19, 2023
概括
植物功能特征的最小数据集 (MDS) 有效地预测生态系统功能,如在沙漠生态系统中的碳 (C), (N) 和 (P) 循环. 这些基于特征的模型为了解生物多样性和生态系统过程提供了一种新的方法.
科学领域:
- 生态研究生态研究
- 生态系统功能 生态系统功能
- 生物多样性和生态系统功能
背景情况:
- 植物的功能特征对于生态系统的功能至关重要.
- 确定预测温带沙漠生态系统功能的关键特征是必不可少的.
研究的目的:
- 构建木质和草本植物的最低数据集 (MDS).
- 评估MDS对生态系统C,N和P循环的预测能力.
- 探索C,N和P循环的空间分布模式.
主要方法:
- 开发了木质植物 (wMDS) 和草本植物 (hMDS) 功能特征的最低数据集 (MDS).
- 使用线性回归进行交叉验证和非线性模型 (RF,BPNN) 进行空间预测.
- 使用回归策略来可视化基于特征的预测.
主要成果:
- 在预测生态系统功能时,MDS准确地取代了总数据集.
- 非线性模型成功预测了C,N和P循环的空间分布.
- 使用MDSs预测的特征值与原始数据预测密切匹配.
结论:
- MDS是预测生态系统C,N和P循环的有效工具.
- 植物的功能特征会影响生态系统过程,尤其是在水分限制下.
- 这项研究为生物多样性与生态系统功能关系提供了新的视角.
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