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根据卫星衍生的现象学和最大碳吸收能力,估计全球年初级生产总值
1State Key Laboratory of Subtropical Silviculture, Zhejiang A&F University, Hangzhou, 311300, Zhejiang, China; Key Laboratory of Carbon Cycling in Forest Ecosystems and Carbon Sequestration of Zhejiang Province, Zhejiang A&F University, Hangzhou, 311300, Zhejiang, China; College of Environment and Resources, College of Carbon Neutrality, Zhejiang A&F University, Hangzhou, 311300, Zhejiang, China.
Environmental research
|May 13, 2024
概括
这项研究引入了一种新的模型,通过整合表象学和生理学来估计全球初级生产总值 (GPP). 该模型准确预测年度GPP,为全球碳循环研究提供了一种实用方法.
科学领域:
- 地球系统科学 地球系统科学
- 生态生态学 生态生态学
- 遥感 遥感 遥感 遥感
背景情况:
- 全球初级生产总值 (GPP) 估计面临重大不确定性,阻碍了准确的气候建模.
- 了解GPP对于评估全球碳循环和植被动态至关重要.
研究的目的:
- 为准确的全球GPP估计开发和验证综合现象学和生理学的统计模型.
- 提供一种切实可行的替代方案,用于使用卫星数据来估计年度GPP.
主要方法:
- 使用来自145个FLUXNET网站的GPP数据开发了综合表象和生理学的统计模型 (SMIPP).
- 利用卫星数据集来确定全球碳吸收期 (CUP) 和最大碳吸收能力 (GPPmax),以推动SMIPP模型.
- 估计了2001-2018年期间的全球年度GPP,并进行了敏感性分析.
主要成果:
- 对于大多数植被类型,SMIPP模型在预测年度GPP方面具有很高的准确性,对于湿地,灌木和常青森林的准确性较低.
- 据估计,全球每年的GPP平均为132.6 Pg C yr−1,在2001-2018年期间的趋势为0.25 Pg C yr−2和1.57 Pg C yr−1的年际变化.
- 敏感性分析表明,GPPmax对全球GPP的影响比CUP更大,尤其是在全球范围内.
结论:
- SMIPP模型提供了一种简单,实用和准确的方法来估计全球年度GPP.
- 现象学和生理学因素,特别是GPPmax,显著影响全球年度GPP估计.
- 这项研究有助于减少全球GPP评估中的不确定性,并改善碳循环建模.
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