Evident influence of water availability on the relationship between solar-induced chlorophyll fluorescence and gross primary productivity in the alpine grasslands of the Tibetan Plateau

• Published in: International journal of applied earth observation and geoinformation Vol. 129; p. 103821
• Main Authors: Zheng, Zhoutao, Cong, Nan, Zhao, Guang, Zhao, Bo, Zhu, Yixuan, Zhang, Yangjian, Zhu, Juntao, Zhang, Tao, Chen, Ning, Gao, Jie, Zhang, Yu, Sun, Yihan
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.05.2024; Elsevier
• Subjects: Alpine grasslands; Gross primary productivity; Solar-induced chlorophyll fluorescence; Vegetation index; Water availability; Water availability; Alpine grasslands; Solar-induced chlorophyll fluorescence; Vegetation index; Gross primary productivity
• ISSN: 1569-8432; 1872-826X
• DOI: 10.1016/j.jag.2024.103821

•SIF outperforms GVI and PRI in tracking GPP.•Temporal aggregation enhances the SIF-GPP relationship.•SIF-GPP relationship varies with water availability.•SIF in combination with SWC can improve GPP estimation. Solar-induced chlorophyll fluorescence (SIF) is strongly physiologically associated with vegetation photosynthesis, and has been broadly employed to monitor gross primary productivity (GPP). However, for some understudied ecosystems, such as the alpine grasslands of the Tibetan Plateau (TP), it is highly uncertain about how SIF performs in tracking GPP. Here, by collecting eddy covariance-derived GPP and climatic data at four grassland sites in the TP, the performances of remotely sensed SIF products (CSIF and GOSIF) in estimating GPP at different time scales (8-day, monthly and growing season) were evaluated and compared against reflectance-based greenness vegetation indices (GVIs) and photochemical reflectance indices (PRIs). Moreover, the SIF-GPP relationship was further examined under different water conditions. The results showed that SIF performed best in tracking GPP variations at all temporal scales compared with GVIs and PRIs. With temporal aggregation, the SIF-GPP relationship was markedly enhanced. We further found that both determination coefficient (R2) values and slopes of the SIF-GPP relationship tended to be lower with decreasing soil water content or increasing vapor pressure deficit. This indicates SIF and GPP will be decoupled with aggravating water stress and their relationship is not universal under different water conditions. Morever, integrating soil water content with SIF improved GPP estimation, underscoring the vital role of water availability in influencing the SIF-GPP relationship. This study can boost our understanding on the variant SIF-GPP relationship and suggests that the regulation effect of water availability need be considered to improve the SIF-derived GPP estimation.