在一个兼容的树体积,生物质和碳预测系统中的模型错误传播
James A Westfall1, Philip J Radtke2, David M Walker2
1U.S. Forest Service, Northern Research Station, York, PA, USA. james.westfall@usda.gov.
Carbon balance and management
|June 10, 2025
概括
这项研究评估了一种兼容的树木体积,生物质和碳预测系统. 结果显示,人口估计的额外不确定性最小 (低于5%),有利于森林库存数据的用户.
科学领域:
- 林业林业 林业 林业 林业
- 生态建模 生态建模
- 生物识别信息 生物识别信息
背景情况:
- 单个树的属性,如体积,生物质和碳,高度相关.
- 兼容的预测系统是首选的,但对模型错误传播提出了担忧.
- 在树属性预测中评估不确定性传播对于准确的森林库存至关重要.
研究的目的:
- 评估模型预测不确定性如何通过兼容的树体积,生物质和碳预测系统传播.
- 检查模型不确定性对人口估计的贡献.
- 确定森林库存兼容预测框架的可靠性.
主要方法:
- 对树木体积,生物质和碳的兼容预测系统进行了评估.
- 分析了从体积到生物质,然后到碳的错误传播.
- 人口估计中的不确定性是基于模型预测量化的.
主要成果:
- 不确定性从体积增加到生物质到碳,碳受到错误传播的影响最大.
- 由于数据的局限性,树枝的模型不确定性高于干部组件.
- 与构成部分相比,直接预测整个树的生物质和协调的组件减少了不确定性.
结论:
- 由于模型不确定性,人口估计的标准误差的增加始终很低 (<5%,通常<3%).
- 森林库存数据的用户可以依靠兼容的预测系统,增加最小的不确定性.
- 树木体积,生物质和碳属性之间的隐性兼容性提供了没有显著的不确定性增加的好处.
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