Divergent Estimates of Forest Photosynthetic Phenology Using Structural and Physiological Vegetation Indices

Abstract

The accurate estimation of photosynthetic phenology using vegetation indices (VIs) is important for measuring the interannual variation of atmospheric CO 2 concentrations, but the relative performances of structural and physiological VIs remain unclear. We found that structural VIs (normalized difference VI, enhanced VI, and near-infrared reflectance of vegetation) were suitable for estimating the start of the photosynthetically active season in deciduous broadleaf forests using gross primary production measured by FLUXNET as a benchmark, and a physiological VI (chlorophyll/carotenoid index) was better at identifying the end of the photosynthetically active season for deciduous broadleaf forests and both the start and end of season for evergreen needleleaf forests. The divergent performances were rooted in the combined control of structural and physiological regulations of carbon uptake by plants. Most existing studies of photosynthetic phenology have been based on structural VIs, so we suggest revisiting the dynamics of photosynthetic phenology using physiological VIs, which has significant implications on global plant phenology and carbon uptake studies. Plain Language Summary The uptake of photosynthetic carbon by forests is strongly seasonal, which can be characterized by photosynthetic phenology, e.g., the start and end of the photosynthetically active season (SOS and EOS, respectively). Satellite vegetation indices (VIs) can detect photosynthesis in canopies either structurally or physiologically. Clarifying the convergence or divergence of the performance of structural and physiological VIs is therefore crucial. This study compared the capacity of three structural VIs and one physiological VI for estimating SOS and EOS. Their performances were jointly controlled by structural and physiological regulations of carbon uptake by plants. The structural and physiological controls for deciduous broadleaf forests (DBFs) were nearly synchronous during green-up, and canopy structural changes were visible, so structural VIs were reliable for estimating SOS. Canopies, however, change slowly in evergreen needleleaf forests (ENFs) throughout the year and in DBFs during autumn, and the capacity to take up carbon is mainly limited by physiological stress, so physiological VIs outperformed structural VIs. Our study highlights the unique advantage of physiological VIs for estimating photosynthetic phenology. These findings constitute a step toward improving our understanding of the roles of the structural and physiological regulations of the dynamics of terrestrial carbon.

A Broadband Green-Red Vegetation Index for Monitoring Gross Primary Production Phenology

“…Winter acclimated leaves, which often have a lower chlorophyll/carotenoid pigment ratio [34], are characterized by higher reflectance except around 531 nm (MODIS band 11), leading to lower CCI values (Equation ( 1)). CCI is therefore a reliable indicator of the temporal variation of the chlorophyll/carotenoid pigment ratio, which indicates photosynthetic downregulation during autumn and winter [7,20,21,24,26].…”

“…CCI has been widely used to track GPP dynamics [20][21][22][23][24]. Especially, CCI was found suitable to timely capture the photosynthesis downregulation around the end of growing season, improving the accuracy of traditional broadband red and near-infrared vegetation indices such as NDVI for photosynthetic phenology estimation [25,26].…”

Canopy Solar-Induced Chlorophyll Fluorescence and Its Link to Transpiration in a Temperate Evergreen Needleleaf Forest during the Fall Transition

“…Canopy structure, including canopy LAI and leaf orientation influence the SIF scattering and re-absorption [34]. Evergreens hold relative constant canopy structure during the season transition [6,7]. To shed more absorbed energy as nonphotochemical quenching (NPQ) over winter months, ENF gradually changes pigment ratios of carotenoids and chlorophyll with meteorological shifts in season transition [35][36][37][38].…”

“…However, ENF transpiration (T) estimation is still imprecise with the currently used empirical/semi-empirical models (e.g., Penman Monteith (PM) equation) and ecohydrological remote sensing models which rely on meteorological factors and remote-sensing vegetation parameters (e.g., NDVI and LAI) [4,5]. This is because ENF canopy structure and green needle leaf area show no significant change during season transitions [6], but photosynthetic activity and water exchange undergo seasonal shifts in evergreen ecosystems [7,8]. Previous studies showed that land surface models (LSM) underestimated daily evapotranspiration (ET) by up to 20% in the fall and by approximately 25% across the entire season for evergreen needleleaf forest [9].…”

Comparison of Vegetation Phenology Derived from Solar-Induced Chlorophyll Fluorescence and Enhanced Vegetation Index, and Their Relationship with Climatic Limitations

“…For example, the global land surface phenology product MCD12Q2 was generated by Zhang et al [6,8] using the EVI (Enhanced Vegetation Index) time series, which is the only global land surface phenology product available in recent years. However, as VIs are not capable of providing us with a direct proxy of physiological processes, they cannot be perfectly applied to modeling frameworks [9]. In this case, some studies have explored the potential of vegetation phenology extraction from an photosynthetic perspective.…”