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对叶子光合作用能力数据集进行比较评估,以估计陆地总初级生产率

Mingzhu Xu¹, Jing M Chen², Yihong Liu³

¹Key Laboratory of Humid Subtropical Eco-Geographical Process (Ministry of Education), School of Geographical Sciences, Fujian Normal University, Fuzhou 350007, China.

The Science of the total environment

|March 10, 2024

概括

准确估计最大Rubisco碳氧化率 (V_cmax25) 对于模拟全球碳循环至关重要. 使用来自叶子含量 (LCC) 和太阳引起的光 (SIF) 的V_cmax25显著改善了总初级生产率 (GPP) 模拟.

科学领域:

陆地生物圈建模模型
生态系统的碳循环循环.
遥感在生态学中的应用.

背景情况:

在地球系统模型中模拟陆地碳循环时,最大的Rubisco碳氧化率 (V_cmax25) 是至关重要的.
现有的全球V_cmax25数据集来源于现场测量,生态最佳性理论 (EOT),叶子含量 (LCC) 和太阳引起的光 (SIF) 缺乏直接验证,因为基本真相数据有限.

研究的目的:

通过使用生物圈-大气交换过程模拟器 (BEPS) 评估它们对原始生产率 (GPP) 模拟的影响,间接评估四个V_cmax25数据集.
为了确定哪些V_cmax25数据源最好地提高GPP模拟在现场和全球规模的准确性.

主要方法:

采用间接验证方法,使用BEPS模型在196个FLUXNET2015站点和全球模拟GPP.
四个V_cmax25数据集 (PFT固定的,EOT衍生的,LCC衍生的和SIF+LCC衍生的) 被集成到BEPS中进行比较分析.
模拟的GPP与现场级流量塔数据进行了评估,并与全球GPP产品 (FLUXCOM,GOSIF) 相比较.

主要成果:

来自SIF+LCC和单独LCC的V_cmax25数据集显著减少了年度和每日GPP模拟错误 (23.225.1%降低了地点水平的平均绝对偏差).
与PFT固定的V_cmax25相比,EOT衍生的V_cmax25略有增加了GPP误差 (2.2%),主要是由于常青宽叶森林和耕地中的偏差.
使用LCC和SIF+LCC衍生V_cmax25的全球年度GPP模拟显示,与PFT固定V_cmax25相比,V_cmax25降低了4.37.3%,并且与FLUXCOM和GOSIF产品显示出更好的一致性.

结论:

准确地描述V_cmax25的时空变化对于提高全球植被生产力模拟的准确性至关重要.
从LCC和SIF等遥感代理产生的V_cmax25数据为增强陆地生物圈模型提供了一个有前途的途径.
该研究强调了基于EOT的V_cmax25的局限性,以及将季节性变化的V_cmax25估计纳入的好处.

关键词:

这是BEPS.生态最佳性理论生态最佳性理论在 GPP GPP GPP 中.叶子中的叶绿素含量.V ((cmax25)) 的时间.

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