Key points are not available for this paper at this time.
Satellite earth observation (EO) data plays a vital role quantifying vegetation structural and functional metrics across spatio-temporal scales. However, the degree of coupling between satellite derived spectral signals and the rate of photosynthesis , as estimated by Gross Primary Productivity (GPP), both before and after bushfire remain understudied, yet these are a critical part of the global carbon cycle . This study evaluated a combination of passive optical and active LiDAR satellite data to quantify the disturbance and recovery of photosynthesis from a major fire event. The work was completed at the Tumbarumba long-term tall eucalypt flux site following a catastrophic bushfire in December 2019. TROPOMI solar-induced fluorescence (SIF) and Sentinel 2 derived greenness and burn severity metrics (NDVI, EVI , NIRv, and NBR) were investigated, termed ‘spectral metrics’ herewith. Detailed in-situ observations from leaf-to-canopy scales were utilised to examine variations in vegetation structural-functional parameters. We found the rate of vegetation spectral metrics recovery largely outpaced GPP recovery at the one- and two-year post-fire mark. Specifically, SIF recovered to 80–90 % compared to pre-fire levels, whereas GPP recovered only 45–50 %. This indicated that separate SIF:GPP functions were required for pre- and post-fire data to account for different recovery trajectories due to changes in canopy structure and species composition. The use of TROPOMI SIF for monitoring canopy productivity at seasonal (monthly) time-scales was advantageous over traditional greenness-based indices, as SIF tracked GPP seasonality both pre- and post-fire. Spaceborne GEDI LiDAR data effectively captured post-fire changes in forest structure, albeit at sparse spatio-temporal sampling intervals, revealing a significant reduction in overstorey vegetation density and a concurrent increase in understorey vegetation density. This contributed to reduced carbon uptake, compared to pre-fire, due to the lower light use efficiency of understorey species, which was verified with in-situ gas exchange measurements. Overall, this study highlights the importance of accounting for disturbance history and the relative abundance of overstorey and understorey vegetation for tracking GPP from satellite platforms. Our results also highlight the crucial role of longitudinal field-based data for calibration and validation of EO data, ultimately enhancing our understanding of forest recovery processes.
Woodgate et al. (Thu,) studied this question.