Chlorophyll fluorescence-gross primary productivity relationships during the spring awakening of an evergreen needleleaf forest

2021 ◽  
Author(s):  
Michaela Schwarz ◽  
Karolina Sakowska ◽  
Klaudia Ziemblińska ◽  
Paulina Dukat ◽  
Marek Urbaniak ◽  
...  
Keyword(s):  
Chlorophyll Fluorescence ◽  
Primary Productivity ◽  
Seasonal Pattern ◽  
Canopy Structure ◽  
Strong Relationship ◽  
Gross Primary Productivity ◽  
Photochemical Quenching ◽  
Spring Awakening ◽  
Fluorescence Measurements ◽  
Spectrometer System

<p>Solar-induced chlorophyll fluorescence (SIF) has been shown as a promising approach for the estimation of gross primary productivity (GPP), but whether SIF is merely a function of canopy structure or also contains precious physiological information, is presently heavily discussed. In this study, the SIF-GPP relationship was quantified at a Pinus sylvestris forest (Mezyk, Poland) during a series of short-term cold spells throughout the spring awakening to investigate the potential of SIF as a proxy for GPP during this period characterized by cold stress. GPP was inferred from the net ecosystem CO<sub>2 </sub>exchange measured by the eddy covariance technique. Canopy-scale SIF was measured using a high-resolution spectrometer system and retrieved via spectral fitting (SFM) algorithms. Active leaf-scale chlorophyll fluorescence measurements were conducted on seven branches using an automated field-deployable fluorometer system. Our results demonstrate a clear difference in GPP and the utilization of chlorophyll-absorbed energy between cold spell and warm days. At short, sub-daily time scales, the correlation between SIF and GPP was minor, but increased significantly when observed over extended temporal periods, when SIF exhibited a seasonal pattern that was more closely aligned with the GPP. Furthermore, the strong relationship between non-photochemical quenching (NPQ) and the photochemical reflectance index (PRI) shows good potential to better estimate GPP when integrated in the SIF-GPP model, as the integration of PRI overall increased the relation between SIF and GPP.</p>

scholarly journals Estimation of Gross Primary Productivity (GPP) Phenology of a Short-Rotation Plantation Using Remotely Sensed Indices Derived from Sentinel-2 Images

2020 ◽  
Vol 12 (13) ◽  
pp. 2104
Author(s):  
Maral Maleki ◽  
Nicola Arriga ◽  
José Miguel Barrios ◽  
Sebastian Wieneke ◽  
Qiang Liu ◽  
...  
Keyword(s):  
Primary Productivity ◽  
Seasonal Pattern ◽  
Vegetation Indices ◽  
Canopy Structure ◽  
Growing Season ◽  
Gross Primary Productivity ◽  
Imaging Spectrometer ◽  
Short Rotation ◽  
Medium Resolution ◽  
Sentinel 2

This study aimed to understand which vegetation indices (VIs) are an ideal proxy for describing phenology and interannual variability of Gross Primary Productivity (GPP) in short-rotation coppice (SRC) plantations. Canopy structure- and chlorophyll-sensitive VIs derived from Sentinel-2 images were used to estimate the start and end of the growing season (SOS and EOS, respectively) during the period 2016–2018, for an SRC poplar (Populus spp.) plantation in Lochristi (Belgium). Three different filtering methods (Savitzky–Golay (SavGol), polynomial (Polyfit) and Harmonic Analysis of Time Series (HANTS)) and five SOS- and EOS threshold methods (first derivative function, 10% and 20% percentages and 10% and 20% percentiles) were applied to identify the optimal methods for the determination of phenophases. Our results showed that the MEdium Resolution Imaging Spectrometer (MERIS) Terrestrial Chlorophyll Index (MTCI) had the best fit with GPP phenology, as derived from eddy covariance measurements, in identifying SOS- and EOS-dates. For SOS, the performance was only slightly better than for several other indices, whereas for EOS, MTCI performed markedly better. The relationship between SOS/EOS derived from GPP and VIs varied interannually. MTCI described best the seasonal pattern of the SRC plantation’s GPP (R2 = 0.52 when combining all three years). However, during the extreme dry year 2018, the Chlorophyll Red Edge Index performed slightly better in reproducing growing season GPP variability than MTCI (R2 = 0.59; R2 = 0.49, respectively). Regarding smoothing functions, Polyfit and HANTS methods showed the best (and very similar) performances. We further found that defining SOS as the date at which the 10% or 20% percentile occurred, yielded the best agreement between the VIs and the GPP; while for EOS the dates of the 10% percentile threshold came out as the best.

Canopy structure and stress induced changes in chlorophyll fluorescence – a mesocosm experiment

2021 ◽  
Author(s):  
Albin Hammerle ◽  
Mirco Migliavacca ◽  
Felix Spielmann ◽  
Javier Pacheco-Labrador ◽  
Georg Wohlfahrt
Keyword(s):  
Chlorophyll Fluorescence ◽  
Drought Stress ◽  
Soil Water ◽  
Trifolium Repens ◽  
Canopy Structure ◽  
Mesocosm Experiment ◽  
Pronounced Increase ◽  
Treatment Groups ◽  
Fluorescence Measurements ◽  
Spectrometer System

<p>Solar radiation absorbed by chlorophyll in plants is either used for photosynthesis, dissipated as heat or is re-emitted as fluorescence at a slightly higher wavelength. Sun induced chlorophyll fluorescence (SIF) has thus the potential to act as a sensitive indicator for early stress detection in ecosystems. SIF signals at the top of the canopy are however influenced by canopy structure and not only by plant physiology, due to light scattering and (re)absorption.</p><p>In this study we present the first results of a mesocosm experiment on the effect of drought stress on chlorophyll fluorescence in two plant stands differing in their canopy structure. In total we investigated 24 plots of planophile (Trifolium repens) and erectophile (Lolium perenne) plant stands. 12 plots acted as a control plots, while the remaining 12 plots underwent a progressively intensifying drought stress treatment. During the course of the experiment regular measurements of SIF using a passive spectrometer system were conducted. Furthermore, active chlorophyll fluorescence measurements with a multiplexed field spectrometer system were used to derive the maximum PSII efficiency (Fvm) and non-photochemical quenching (NPQ). Ancillary measurements included meteorological, leaf physiological, soil water and canopy structure variables.</p><p>The drought treatment led to a relatively stronger decrease in NDVI and a relatively higher increase in PRI in the Trifolium repens stand, which also experienced a more pronounced increase in NPQ, especially during hot days. For both stands surface temperatures were clearly higher in the treatment groups, with a larger effect in the Trifolium stand. SIF-yield (SIF/aPAR) did remain more or less constant or increased slightly for the control groups. In both stands it dropped towards the end of the experiment for both treatment groups at very low soil water content levels, about at the same time when the active chlorophyll fluorescence measurements started to indicate persistent reductions in Fvm. The relative decrease in SIF and SIF-yield for the treatment groups was not significantly different between the two stands.</p>

scholarly journals Tree–grass phenology information improves light use efficiency modelling of gross primary productivity for an Australian tropical savanna

2017 ◽  
Vol 14 (1) ◽  
pp. 111-129 ◽  
Author(s):  
Caitlin E. Moore ◽  
Jason Beringer ◽  
Bradley Evans ◽  
Lindsay B. Hutley ◽  
Nigel J. Tapper
Keyword(s):  
Primary Productivity ◽  
Vegetation Index ◽  
Temporal Dynamics ◽  
Seasonal Pattern ◽  
Gross Primary Productivity ◽  
Perennial Grasses ◽  
Light Use Efficiency ◽  
Tropical Savanna ◽  
Flux Tower ◽  
Use Efficiency

Abstract. The coexistence of trees and grasses in savanna ecosystems results in marked phenological dynamics that vary spatially and temporally with climate. Australian savannas comprise a complex variety of life forms and phenologies, from evergreen trees to annual/perennial grasses, producing a boom–bust seasonal pattern of productivity that follows the wet–dry seasonal rainfall cycle. As the climate changes into the 21st century, modification to rainfall and temperature regimes in savannas is highly likely. There is a need to link phenology cycles of different species with productivity to understand how the tree–grass relationship may shift in response to climate change. This study investigated the relationship between productivity and phenology for trees and grasses in an Australian tropical savanna. Productivity, estimated from overstory (tree) and understory (grass) eddy covariance flux tower estimates of gross primary productivity (GPP), was compared against 2 years of repeat time-lapse digital photography (phenocams). We explored the phenology–productivity relationship at the ecosystem scale using Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation indices and flux tower GPP. These data were obtained from the Howard Springs OzFlux/Fluxnet site (AU-How) in northern Australia. Two greenness indices were calculated from the phenocam images: the green chromatic coordinate (GCC) and excess green index (ExG). These indices captured the temporal dynamics of the understory (grass) and overstory (trees) phenology and were correlated well with tower GPP for understory (r2 =  0.65 to 0.72) but less so for the overstory (r2 =  0.14 to 0.23). The MODIS enhanced vegetation index (EVI) correlated well with GPP at the ecosystem scale (r2 =  0.70). Lastly, we used GCC and EVI to parameterise a light use efficiency (LUE) model and found it to improve the estimates of GPP for the overstory, understory and ecosystem. We conclude that phenology is an important parameter to consider in estimating GPP from LUE models in savannas and that phenocams can provide important insights into the phenological variability of trees and grasses.

scholarly journals Unveiling spatial and temporal heterogeneity of a tropical forest canopy using high-resolution NIRv, FCVI, and NIRvrad from UAS observations

2021 ◽  
Author(s):  
Trina Merrick ◽  
Stephanie Pau ◽  
Matteo Detto ◽  
Eben North Broadbent ◽  
Stephanie Bohlman ◽  
...  
Keyword(s):  
Tropical Forest ◽  
Primary Productivity ◽  
Forest Canopy ◽  
Vegetation Index ◽  
Near Infrared ◽  
Canopy Structure ◽  
Gross Primary Productivity ◽  
Spatiotemporal Variability ◽  
Individual Tree ◽  
Tropical Forest Canopy

Abstract. Presented here for the first time are emerging vegetation indicators: near-infrared reflectance (NIRv) of vegetation, the fluorescence correction vegetation index (FCVI), and radiance (NIRvrad) of vegetation, for a tropical forest canopy calculated using UAS-based hyperspectral data. Fine-scale tropical forest heterogeneity represented by NIRv, FCVI, and NIRvrad, is investigated using unmanned aerial vehicle data and eddy covariance-based gross primary productivity estimates. By exploiting near-infrared signals, emerging vegetation indicators captured the greatest spatiotemporal variability, followed by the enhanced vegetation index (EVI), then the normalized difference vegetation index (NDVI), which saturates. Wavelet analyses showed the dominant spatial variability of all indicators is driven by tree clusters and larger-than-tree-crown size gaps (not individual tree crowns or leaf clumps), but emerging indices and EVI captured structural information at smaller spatial scales (~50 m) than NDVI (~90 m) and lidar (~70 m). As predicted in previous studies, we confirm that NIRv and FCVI are virtually identical for a dense green canopy despite the differences in how these indices were derived. Furthermore, we show that NIRvrad, which does not require separate irradiance measurements, correlated most strongly with gross primary productivity and photosynthetically active radiation. These emerging indicators, which are related to canopy structure and the radiation regime of vegetation canopies are promising tools to improve understanding of tropical forest canopy structure and function.

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