Mechanistically linking gross primary productivity (GPP) and sun-induced chlorophyll fluorescence (SIF) is an essential step to unleash the full potential of SIF for remote sensing-based predictions of GPP across biomes, climates, and spatiotemporal scales. The latest SIF-based mechanistic light response model that includes the fraction of open photosystem II reaction centers as key parameter (qMLR-SIF model), can accurately reproduce leaf-scale photosynthesis under various conditions. However, it remains unclear to what extent the qMLR-SIF model is suitable for estimating GPP at larger scales such as the canopy scale. Therefore, canopy-scale data of tower-based far-red SIF, GPP and key environmental variables from 10 study sites were collected to analyze the SIF-GPP relationship and to compare the qMLR-SIF model with the widely used Farquhar, von Caemmerer, Berry (FvCB) model and with a light use efficiency (LUE) model for different plant functional types (PFTs), photosynthetic pathways (C3 and C4), and temporal scales (hourly, daily and 4-day). Results showed that the nonlinear SIF-GPP relationship existed in all PFTs and the degree of linearity increased at larger temporal scales. The qMLR-SIF model exhibited wide applicability to quantify canopy GPP for different PFTs (R2 = 0.55–0.80, RMSE = 2.72–11.03 μmol CO2 m-2 s-1), photosynthetic pathways (R2 = 0.70–0.78, RMSE = 5.29–9.05 μmol CO2 m-2 s-1) and temporal scales (R2 = 0.82–0.97, RMSE = 3.42–8.32 μmol CO2 m-2s-1). Compared with the two other models, the qMLR-SIF model performed best overall, which is mainly due to its simpler model structure and the mechanistic link between SIF and photosynthesis. Particularly, the qMLR-SIF model could more accurately estimate GPP in C4 species, with higher R2 (0.78) and lower RMSE (8.46 μmol CO2 m-2s-1). These findings highlight the advantages of the qMLR-SIF model in GPP estimation at the canopy scale, showing its potential in applications at regional and global scales.

中文翻译：

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基于 SIF 的机械模型在冠层尺度 GPP 估算中的适用性


在机械上将总初级生产力 (GPP) 和太阳诱导的叶绿素荧光 (SIF) 联系起来是充分发挥 SIF 潜力的重要一步，用于基于遥感的跨生物群落、气候和时空尺度的 GPP 预测。最新的基于SIF的机械光响应模型以开放光系统II反应中心的分数作为关键参数（qMLR-SIF模型），可以准确地再现各种条件下的叶尺度光合作用。然而，目前尚不清楚 qMLR-SIF 模型在多大程度上适合估计更大尺度（例如冠层尺度）的 GPP。因此，收集了10个研究点的塔基远红SIF、GPP和关键环境变量的冠层尺度数据，分析SIF-GPP关系，并将qMLR-SIF模型与广泛使用的Farquhar、von Caemmerer、 Berry (FvCB) 模型和针对不同植物功能类型 (PFT)、光合途径（C3 和 C4）和时间尺度（每小时、每天和 4 天）的光利用效率 (LUE) 模型。结果表明，所有 PFT 中都存在非线性 SIF-GPP 关系，并且线性程度在较大时间尺度上增加。 qMLR-SIF 模型在量化冠层 GPP 的不同 PFT（R2 = 0.55–0.80，RMSE = 2.72–11.03 μmol CO2 m-2 s-1）、光合作用途径（R2 = 0.70–0.78，RMSE = 5.29–）方面表现出广泛的适用性。 9.05 μmol CO2 m-2 s-1）和时间尺度（R2 = 0.82–0.97，RMSE = 3.42–8.32 μmol CO2 m-2s-1）。与其他两个模型相比，qMLR-SIF模型总体表现最好，这主要是由于其更简单的模型结构以及SIF与光合作用之间的机制联系。特别是，qMLR-SIF 模型可以更准确地估计 C4 物种的 GPP，具有更高的 R2（0.78) 和较低的 RMSE (8.46 μmol CO2 m-2s-1)。这些发现凸显了 qMLR-SIF 模型在冠层尺度 GPP 估计中的优势，显示了其在区域和全球尺度的应用潜力。