Zhao et al. (2025) Limited capability of current satellite solar-induced chlorophyll fluorescence reconstructions to capture stomatal responses to environmental stresses

Identification

• Journal: Communications Earth & Environment
• Year: 2025
• Date: 2025-12-09
• Authors: Jiacheng Zhao, Athanasios Paschalis, Pierre Gentine, Zhaozhong Feng, Simone Fatichi
• DOI: 10.1038/s43247-025-03035-0

Research Groups

• State Key Laboratory of Climate System Prediction and Risk Management, Nanjing University of Information Science and Technology, Nanjing, Jiangsu, China
• Key Laboratory of Ecosystem Carbon Source and Sink, China Meteorological Administration (ECSS-CMA), School of Ecology and Applied Meteorology, Nanjing University of Information Science and Technology, Nanjing, Jiangsu, China
• Department of Civil and Environmental Engineering, Imperial College London, London, UK
• Department of Civil and Environmental Engineering, University of Cyprus, Nicosia, Cyprus
• Department of Earth and Environmental Engineering, Columbia University, New York, NY, USA
• Department of Civil and Environmental Engineering, National University of Singapore, Singapore, Singapore

Short Summary

Current satellite solar-induced chlorophyll fluorescence (SIF) reconstructions have limited capability to capture stomatal responses to environmental stresses, leading to an overestimation of gross primary productivity (GPP) during dry periods due to a decoupling between stomatal responses and the physiological SIF emission yield.

Objective

• To assess whether current satellite reconstructions of solar-induced chlorophyll fluorescence (SIF) can accurately capture plant physiological responses, particularly stomatal responses, to environmental stresses across various biomes.

Study Configuration

• Spatial Scale: Global, with satellite SIF reconstructions at 0.05° resolution (approximately 5.5 km at the equator), TROPOMI SIF at 3.5 km × 7 km (nadir), and flux tower footprints.
• Temporal Scale: Hourly, daily, 4-day, 8-day, biweekly (16-day), monthly, and long-term (e.g., 1995-2020).

Methodology and Data

• Models used:
  • Standardized anomalies (z-scores) for seasonality removal.
  • Pixel-wise ridge regression model to assess sensitivity to environmental variables.
  • Boosted regression trees (BRT) model to distinguish structural from physiological contributions to GPP.
  • Theoretical "big-leaf" energy budget model and Penman-Monteith (PM) equation inversion to infer stomatal conductance (gs).
• Data sources:
  • In-situ: CO2 and water flux data from 103 globally distributed eddy-covariance (EC) towers (OzFlux, FLUXNET2015, La Thuile datasets).
  • Satellite SIF products: GOME-2 (JJ, PK), SIF005, CSIF, GOSIF, RTSIF, LTSIF (all reconstructed to 0.05°), and raw L3 TROPOMI SIF (3.5 km × 7 km).
  • Satellite Vegetation Indices (VIs): NDVI, EVI, NIRv from MODIS (MOD13C1, MYD13C1, MCD43A4).
  • Satellite Land Surface Temperature (LST): MODIS Aqua LST (MYD11A1).
  • Satellite LAI/FPAR: Sensor-independent (SI) LAI/FPAR dataset.
  • Satellite PAR: Breathing Earth System Simulator (BESS) PAR product.
  • Reanalysis: ERA5-Land reanalysis (soil moisture, air temperature, dew-point temperature, solar radiation, longwave radiation, wind speed, atmospheric pressure).

Main Results

• At a biweekly scale, SIF reconstructions correlate highly with GPP (Pearson ρ = 0.74), outperforming VIs (ρ = 0.62). This correlation is lower for evergreen broadleaf forests (EBFs, ρ = 0.37) but high for evergreen needleleaf forests (ENFs, ρ = 0.82).
• After removing seasonality using z-scores, the correlation between GPPz and SIFz significantly weakens to ρ = 0.36, only marginally higher than VIz (ρ = 0.3).
• In semi-arid or seasonally dry biomes, SIFz variability is largely explained by structural responses (e.g., drought deciduousness, grass wilting), especially at coarser time scales. Daily TROPOMI SIF shows weaker sensitivity to soil moisture, indicating less capture of early physiological responses.
• In energy-limited mid and high latitudes, SIFz variability is explained by temperature and solar radiation, tracking physiological responses (e.g., electron transport) not observed by conventional VIs. However, SIF reconstruction sensitivity to these anomalies decreases at time scales shorter than 8 days.
• During dry periods in Mediterranean evergreen forests with stable canopy structure, SIF reconstructions fail to capture water stress; they do not decrease proportionally with GPP, evapotranspiration (ET), and stomatal conductance (gs). The physiological SIF emission yield (ΦF) shows a clear decoupling from light use efficiency (LUE).
• Raw TROPOMI SIF, despite considerable noise, shows a more comparable response to gs and LUE during dry periods than SIF reconstructions, suggesting better capture of stomatal closure.
• GPP exhibits a stronger coupling to ET than SIF reconstructions, indicating that current 0.05° SIF reconstructions are less sensitive to stomatal responses to environmental stresses.

Contributions

• Provides a comprehensive assessment of the limitations of current 0.05° satellite SIF reconstructions in monitoring plant water stress and capturing early physiological responses.
• Identifies a critical decoupling between stomatal responses and the physiological SIF emission yield (ΦF) in SIF reconstructions during soil and atmospheric dry periods, leading to GPP overestimation.
• Demonstrates that SIF reconstructions primarily reflect vegetation structural changes in arid/semi-arid regions and light limitations in boreal evergreen needleleaf forests, but generally fail to capture early physiological stress in evergreen forests where canopy structure remains stable.
• Highlights that raw TROPOMI SIF, with higher temporal resolution, shows greater sensitivity to stomatal conductance compared to machine learning-based SIF reconstructions.
• Concludes that current satellite SIF reconstructions and traditional VIs alone are insufficient for detecting early warning signals of vegetation physiological stress that manifest through stomatal changes without altering canopy structure.

Funding

• National Natural Science Foundation of China (No. 32361143869, No. 42407606)
• NERC (NE/Y000471/1)
• NASA 80NSSC18K0998 project
• NOAA NA17OAR4310127 grant
• Singapore's Ministry of Education (MoE) Academic Research Fund Tier 2, Project ID: MOE-000379-00/MOE-000379-01, Award Number: MOE-T2EP50122-0004

Citation

@article{Zhao2025Limited,
  author = {Zhao, Jiacheng and Paschalis, Athanasios and Gentine, Pierre and Feng, Zhaozhong and Fatichi, Simone},
  title = {Limited capability of current satellite solar-induced chlorophyll fluorescence reconstructions to capture stomatal responses to environmental stresses},
  journal = {Communications Earth & Environment},
  year = {2025},
  doi = {10.1038/s43247-025-03035-0},
  url = {https://doi.org/10.1038/s43247-025-03035-0}
}