Diurnal and Seasonal Solar Induced Chlorophyll Fluorescence and Photosynthesis in a Boreal Scots Pine Canopy

Abstract

Solar induced chlorophyll fluorescence has been shown to be increasingly an useful proxy for the estimation of gross primary productivity (GPP), at a range of spatial scales. Here, we explore the seasonality in a continuous time series of canopy solar induced fluorescence (hereafter SiF) and its relation to canopy gross primary production (GPP), canopy light use efficiency (LUE), and direct estimates of leaf level photochemical efficiency in an evergreen canopy. SiF was calculated using infilling in two bands from the incoming and reflected radiance using a pair of Ocean Optics USB2000+ spectrometers operated in a dual field of view mode, sampling at a 30 min time step using custom written automated software, from early spring through until autumn in 2011. The optical system was mounted on a tower of 18 m height adjacent to an eddy covariance system, to observe a boreal forest ecosystem dominated by Scots pine. (Pinus sylvestris) A Walz MONITORING-PAM, multi fluorimeter system, was simultaneously mounted within the canopy adjacent to the footprint sampled by the optical system. Following correction of the SiF data for O2 and structural effects, SiF, SiF yield, LUE, the photochemicsl reflectance index (PRI), and the normalized difference vegetation index (NDVI) exhibited a seasonal pattern that followed GPP sampled by the eddy covariance system. Due to the complexities of solar azimuth and zenith angle (SZA) over the season on the SiF signal, correlations between SiF, SiF yield, GPP, and LUE were assessed on SZA <50° and under strictly clear sky conditions. Correlations found, even under these screened scenarios, resulted around ~r2 = 0.3. The diurnal responses of SiF, SiF yield, PAM estimates of effective quantum yield (ΔF/Fm′), and meteorological parameters demonstrated some agreement over the diurnal cycle. The challenges inherent in SiF retrievals in boreal evergreen ecosystems are discussed.

Linking In Situ Photochemical Reflectance Index Measurements With Mangrove Carbon Dynamics in a Subtropical Coastal Wetland

“…Fifth, the fitted temperature‐respiration exponential regression model was extrapolated to derive daytime R eco ( t ) from daytime T ( t ), and then GPP was estimated from daytime NEE (equation ). Sixth, the LUE (equation ) was calculated as the ratio of GPP and absorbed PAR (APAR; the product of PAR and f APAR ; equation ), where f APAR was derived from SW in and SW out (equation ; Nichol et al, ). The sign convention used in meteorology (i.e., the downward flux is negative and the upward one is positive) was used for indicating carbon fluxes.…”

Do all chlorophyll fluorescence emission wavelengths capture the spring recovery of photosynthesis in boreal evergreen foliage?

“…SIF is a promising methodology for the estimation of GPP dynamics in terrestrial ecosystems either using statistical methods based on Equation (Guanter et al, ; Li et al, ; Sun et al, ) or by assimilation into the photosynthetic modules of land surface models (Lee et al, ; Macbean et al, ; Thum et al, ). SIF could be particularly useful for evergreen ecosystems by capturing part of the temporal dynamics of GPP that remains hidden to traditional reflectance‐based vegetation indices due to low variation in greenness (Magney, Bowling, et al, ; Nichol et al, ; Smith et al, ; Walther et al, ; Zuromski et al, ).…”

The Instrument Design of the DLR Earth Sensing Imaging Spectrometer (DESIS)

“…The off-nadir capability of DESIS with ±15° along the track during a datatake enables investigations of the BRDF (Bi-Directional Reflectance Distribution Function) of objects on Earth and thus provides additional target-specific information. The variable recording times due to the non-polar or non-sun-synchronous orbit allow investigations of solar-induced chlorophyll fluorescence and photosynthesis, which is subject to strong daily fluctuations [1]. And as soon as additional sensors are placed on the MUSES platform, multi-modal observations become possible, which allow sensor fusion approaches employing the same sun-target-sensor geometry, the same atmospheric conditions, and the same object properties.…”

“…These spectral signatures support the identification of elements or the measurement of concentrations. Remote sensing capabilities extend spectroscopy from a local measurement to a global Earth coverage measurement method for the identification of atmospheric, land, and water constitutions [1]. Typical applications of hyperspectral remote sensing are, amongst others, monitoring of the vegetation, forestry and agriculture [2,3], coastal and inland water [4], mining, geology [5], and soils [6].…”