Soil water depletion induces discrepancies between in situ measured vegetation indices and photosynthesis in a temperate heathland

Korte inhoud:Vegetation indices (VIs) derived from optical sensors have been used as proxies for monitoring gross primary productivity (GPP). In contrast to satellite-based VIs, whose temporal resolution is typically limited, especially in cloudy areas, in situ derived VIs may have higher temporal resolution. This fine temporal frequency implies much larger sample sizes to test the performance of VIs by comparing with eddy covariance-based in situ GPP estimates. Here, we tested the potential of in situ measured VIs to estimate GPP in a temperate heathland ecosystem. We compared half-hourly GPP values derived from an eddy covariance CO2 flux measurements with several greenness-, structure-and chlorophyll-sensitive VIs (e.g., the Terrestrial Chlorophyll Index [TCI] and the Inverted Red-Edge Chlorophyll Index [IRECI], among others) obtained by multiband sensors mounted at the tower. Results showed that tested VIs differed in their ability to capture the temporal variability of GPP during non -drought condition, and that all VIs failed in describing GPP during an extreme drought event. After integrating a drought indicator (e.g., soil water content, precipitation/potential evapotranspiration ratio or actual/ potential evapotranspiration ratio) in the regression model, the performances of VIs drastically improved. Among all tested indices, IRECI and TCI were the most promising VIs, capturing best the temporal variation in GPP (R-2 = 0.73 and RMSE = 1.85, and R-2 = 0.77, RMSE = 1.69, respectively), provided that drought stress was properly accounted for. Our findings have implications for the development and improvement of global ecological models for drought monitoring based on proximal and remote sensing data. Our results have also a strong impact on our ability to upscale CO2 fluxes using satellite sensors (e.g. Sentinel-2 and Sentinel-3) of heathland ecosystem characterized by heather vegetation which is relatively resistant to the structural changes in the canopy and strongly affects the interpretation of the remote sensing signals.

Jaar van publicatie:2022

Trefwoorden:Physics, Plant- en bodemkunde en technologie, Meteorologische en atmosferische wetenschappen, ruimtewetenschap en technologie

Toegankelijkheid:Open