Abstract
Abstract. Photosynthesis by terrestrial plants represents the majority of CO2 uptake on Earth, yet it is difficult to measure directly from space. Estimation of gross primary production (GPP) from remote sensing indices represents a primary source of uncertainty, in particular for observing seasonal variations in evergreen forests. Recent vegetation remote sensing techniques have highlighted spectral regions sensitive to dynamic changes in leaf/needle carotenoid composition, showing promise for tracking seasonal changes in photosynthesis of evergreen forests. However, these have mostly been investigated with intermittent field campaigns or with narrow-band spectrometers in these ecosystems. To investigate this potential, we continuously measured vegetation reflectance (400–900 nm) using a canopy spectrometer system, PhotoSpec, mounted on top of an eddy-covariance flux tower in a subalpine evergreen forest at Niwot Ridge, Colorado, USA. We analyzed driving spectral components in the measured canopy reflectance using both statistical and process-based approaches. The decomposed spectral components co-varied with carotenoid content and GPP, supporting the interpretation of the photochemical reflectance index (PRI) and the chlorophyll/carotenoid index (CCI). Although the entire 400–900 nm range showed additional spectral changes near the red edge, it did not provide significant improvements in GPP predictions. We found little seasonal variation in both normalized difference vegetation index (NDVI) and the near-infrared vegetation index (NIRv) in this ecosystem. In addition, we quantitatively determined needle-scale chlorophyll-to-carotenoid ratios as well as anthocyanin contents using full-spectrum inversions, both of which were tightly correlated with seasonal GPP changes. Reconstructing GPP from vegetation reflectance using partial least-squares regression (PLSR) explained approximately 87 % of the variability in observed GPP. Our results linked the seasonal variation in reflectance to the pool size of photoprotective pigments, highlighting all spectral locations within 400–900 nm associated with GPP seasonality in evergreen forests.
Highlights
Terrestrial gross primary production (GPP), the gross CO2 uptake through photosynthesis, is the largest uptake of atmospheric CO2 (Ciais et al, 2013), yet the uncertainties are large, hampering our ability to monitor and predict the response of the terrestrial biosphere to climate change (Ahlström et al, 2012)
Remote sensing techniques are based on the optical response of vegetation to incoming sunlight, which can track photosynthesis via the absorption features of photosynthetic and photoprotective pigments (Rouse et al, 1974; Liu and Huete, 1995; Gamon et al, 1992, 2016)
We considered a variety of typical vegetation indices (VIs) using the reflectance data from PhotoSpec
Summary
Terrestrial gross primary production (GPP), the gross CO2 uptake through photosynthesis, is the largest uptake of atmospheric CO2 (Ciais et al, 2013), yet the uncertainties are large, hampering our ability to monitor and predict the response of the terrestrial biosphere to climate change (Ahlström et al, 2012). In contrast to unevenly distributed ground-level measurements such as Fluxnet (Baldocchi et al, 2001), satellites can infer GPP globally and uniformly. Remote sensing techniques are based on the optical response of vegetation to incoming sunlight, which can track photosynthesis via the absorption features of photosynthetic and photoprotective pigments (Rouse et al, 1974; Liu and Huete, 1995; Gamon et al, 1992, 2016). Progress is important for evergreen forests, which can have large seasonal dynamics in photosynthesis but low variability in canopy structure and color. These promising techniques still lack a comprehensive evaluation/validation using both continuous in situ measurements and process-based simulations
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