基于植物群体特征预测生态系统的初级生产力:理论基础和研究进展
Nian-Peng He1,2,3, Pu Yan1,2, Hong-Bo Guo4,3
1Institute of Carbon Neutrality/School of Ecology, Northeast Forestry University, Harbin 150040, China.
Ying yong sheng tai xue bao = The journal of applied ecology
|September 1, 2025
概括
一个新的基于特征的生产力 (TBP) 框架解决了预测生态系统生产力的规模不匹配问题. 这种以物理为灵感的模型使用社区层面的植物特征来改善全球变化下的碳封存估计.
科学领域:
- 生态学
- 生态系统科学
- 遥感技术
背景情况:
- 生态系统的初级生产力对于物质循环和能源流动至关重要.
- 目前用于预测生态系统生产率 (基于辐射或大叶) 的模型存在差异,限制了对碳封存的理解.
- 在个人层面的植物特征和社区层面的生产力预测之间存在规模不匹配,导致模型不确定性.
研究的目的:
- 开发一种基于特征的生产力 (TBP) 框架,以提高生态系统生产力预测的准确性.
- 弥合植物个体特征与生态系统水平生产力之间的差距.
- 将社区层面的植物特征纳入下一代工艺模型.
主要方法:
- 引入基于物理的发动机功率模型,以开发基于特征的生产力 (TBP) 框架.
- 在社区范围内定义了所有TBP框架参数,考虑数量和效率特征.
- 利用中国生态系统的现场多特征数据库进行实证验证.
主要成果:
- 结核计划框架成功地弥合了个体特征和生态系统初级生产力之间的规模差距.
- 环境因素通过在TBP框架内调节植物群体特征,直接或间接地影响生态系统的生产力.
- 通过三项实证研究证明了TBP框架的应用场景.
结论:
- 通过结合流量观测,超光谱传感和遥感数据,TBP框架为改善生态系统生产率预测提供了显著的潜力.
- 需要对TBP框架进行进一步的理论创新和方法改进.
- 需要使用地面和遥感数据进行广泛的验证,以建立新一代机械工艺模型的TBP框架.
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