Measurements Of Solar-induced Chlorophyll Fluorescence Research Articles

Impact of atmospheric dryness on solar-induced chlorophyll fluorescence: Tower-based observations at a temperate forest

Solar-induced chlorophyll fluorescence (SIF) is widely accepted as a proxy for gross primary productivity (GPP). Among the various SIF measurements, tower-based SIF measurements allow for continuous monitoring of SIF variation at a canopy scale with high temporal resolution, making it suitable for monitoring highly variable plant physiological responses to environmental changes. However, because of the strong and close relationship between SIF and absorbed photosynthetically active radiation (aPAR), it may be difficult to detect the influence of environmental drivers other than light conditions. Among the drivers, atmospheric dryness (vapor pressure deficit, VPD) is projected to increase as drought becomes more frequent and severe in the future, negatively impacting plants. In this study, we evaluated the tower-based high-frequency SIF measurement as a tool for detecting plant response to highly variable VPD. The study was performed in a mixed temperate forest in Virginia, USA, where a 40-m-tall flux tower has been measuring gas and energy exchanges and ancillary environmental drivers, and the Fluospec 2 system has been measuring SIF. We show that a proper definition of light availability to vegetation can reproduce SIF response to changing VPD that is comparable to GPP response as estimated from eddy covariance measurement: GPP decreased with rising VPD regardless of how aPAR was defined, whereas SIF decreased only when aPAR was defined as the PAR absorbed by chlorophyll (aPARchl) or simulated by a model (Soil Canopy Observation, Photochemistry and Energy fluxes, SCOPE). We simulated the effect of VPD on SIF with two different simulation modes of fluorescence emission representing contrasting moisture conditions, ‘Moderate’ and ‘Soil Moisture (SM) Stress’ modes. The decreasing SIF to rising VPD was only found in the SM Stress mode, implying that the SIF-VPD relationship depends on soil moisture conditions. Furthermore, we observed a similar response of SIF to VPD at hourly and daily scales, indicating that satellite measurements can be used to study the effects of environmental drivers other than light conditions. Finally, the definition of aPAR emphasizes the importance of canopy structure research to interpret remote sensing observations properly.

A scalable crop yield estimation framework based on remote sensing of solar-induced chlorophyll fluorescence (SIF)

Projected increases in food demand driven by population growth coupled with heightened agricultural vulnerability to climate change jointly pose severe threats to global food security in the coming decades, especially for developing nations. By providing real-time and low-cost observations, satellite remote sensing has been widely employed to estimate crop yield across various scales. Most such efforts are based on statistical approaches that require large amounts of ground measurements for model training/calibration, which may be challenging to obtain on a large scale in developing countries that are most food-insecure and climate-vulnerable. In this paper, we develop a generalizable framework that is mechanism-guided and practically parsimonious for crop yield estimation. We then apply this framework to estimate crop yield for two crops (corn and wheat) in two contrasting regions, the US Corn Belt US-CB, and India’s Indo–Gangetic plain Wheat Belt IGP-WB, respectively. This framework is based on the mechanistic light reactions (MLR) model utilizing remotely sensed solar-induced chlorophyll fluorescence (SIF) as a major input. We compared the performance of MLR to two commonly used machine learning (ML) algorithms: artificial neural network and random forest. We found that MLR-SIF has comparable performance to ML algorithms in US-CB, where abundant and high-quality ground measurements of crop yield are routinely available (for model calibration). In IGP-WB, MLR-SIF significantly outperforms ML algorithms. These results demonstrate the potential advantage of MLR-SIF for yield estimation in developing countries where ground truth data is limited in quantity and quality. In addition, high-resolution and crop-specific satellite SIF is crucial for accurate yield estimation. Therefore, harnessing the mechanism-guided MLR-SIF and rapidly growing satellite SIF measurements (with high resolution and crop-specificity) hold promise to enhance food security in developing countries towards more effective responses to food crises, agricultural policies, and more efficient commodity pricing.

Relationship between Photosynthetic CO2 Assimilation and Chlorophyll Fluorescence for Winter Wheat under Water Stress.

Solar-induced chlorophyll fluorescence (SIF) has a high correlation with Gross Primary Production (GPP). However, studies focusing on the impact of drought on the SIF-GPP relationship have had mixed results at various scales, and the mechanisms controlling the dynamics between photosynthesis and fluorescence emission under water stress are not well understood. We developed a leaf-scale measurement system to perform concurrent measurements of active and passive fluorescence, and gas-exchange rates for winter wheat experiencing a one-month progressive drought. Our results confirmed that: (1) shifts in light energy allocation towards decreasing photochemistry (the quantum yields of photochemical quenching in PSII decreased from 0.42 to 0.21 under intermediate light conditions) and increasing fluorescence emissions (the quantum yields of fluorescence increased to 0.062 from 0.024) as drought progressed enhance the degree of nonlinearity of the SIF-GPP relationship, and (2) SIF alone has a limited capacity to track changes in the photosynthetic status of plants under drought conditions. However, by incorporating the water stress factor into a SIF-based mechanistic photosynthesis model, we show that drought-induced variations in a variety of key photosynthetic parameters, including stomatal conductance and photosynthetic CO2 assimilation, can be accurately estimated using measurements of SIF, photosynthetically active radiation, air temperature, and soil moisture as inputs. Our findings provide the experimental and theoretical foundations necessary for employing SIF mechanistically to estimate plant photosynthetic activity during periods of drought stress.

Enhancing Solar-Induced Fluorescence Interpretation: Quantifying Fractional Sunlit Vegetation Cover Using Linear Spectral Unmixing

Solar-induced chlorophyll fluorescence (SIF) is closely related to plant photosynthetic activity and has been used in different studies as a proxy for vegetation health status. However, in order to use SIF as a relevant indicator of plant physiological stress, it is necessary to accurately quantify the amount of light absorbed by the photosynthetic plant pigments, called the absorbed photosynthetically active radiation (APAR). The ratio between fluorescence emission and light absorption (i.e., SIF and APAR) is known as the fluorescence quantum efficiency (FQE). In this work, simultaneous measurements of SIF and reflected radiance were performed both at the leaf and canopy levels for Salvia farinacea and Datura stramonium plants. With the aim of disentangling the proportion of sunlit and shaded absorbed PAR, an ad hoc experimental setup was designed to provide a wide range of fraction vegetation cover (FVC) canopy settings. A linear spectral unmixing method was proposed to estimate the contribution of soil, sunlit, and shaded vegetation from the total reflectance spectrum measured at the canopy level. Later, the retrieved sunlit FVC (FVCsunlit) was used to estimate the (dominant) green APAR flux, and this was combined with the integral of the spectrally resolved fluorescence to calculate the FQE. The results of this study demonstrated that under no-stress conditions and independently of the FVC, similar FQE values were observed when SIF was properly normalised by the green APAR flux. The results obtained showed that the reflectance spectra retrieved using a linear unmixing method had a maximum RMSE of less than 0.03 along the spectrum. The FVCsunlit evaluation showed an RMSE of 14% with an R2 of 0.84. Moreover, the FQE values obtained at the top of the canopy (TOC) were found statistically comparable to the reference values at the leaf level. These results support further efforts to improve the interpretation of fluorescence based on field spectroscopy and the further upscaling to imaging spectroscopy at airborne and satellite levels.

Elucidating climatic drivers of photosynthesis by tropical forests.

Tropical forests play a pivotal role in regulating the global carbon cycle. However, the response of these forests to changes in absorbed solar energy and water supply under the changing climate is highly uncertain. Three-year (2018-2021) spaceborne high-resolution measurements of solar-induced chlorophyll fluorescence (SIF) from the TROPOspheric Monitoring Instrument (TROPOMI) provide a new opportunity to study the response of gross primary production (GPP) and more broadly tropical forest carbon dynamics to differences in climate. SIF has been shown to be a good proxy for GPP on monthly and regional scales. Combining tropical climate reanalysis records and other contemporary satellite products, we find that on the seasonal timescale, the dependence of GPP on climate variables is highly heterogeneous. Following the principal component analyses and correlation comparisons, two regimes are identified: water limited and energy limited. GPP variations over tropical Africa are more correlated with water-related factors such as vapor pressure deficit (VPD) and soil moisture, while in tropical Southeast Asia, GPP is more correlated with energy-related factors such as photosynthetically active radiation (PAR) and surface temperature. Amazonia is itself heterogeneous: with an energy-limited regime in the north and water-limited regime in the south. The correlations of GPP with climate variables are supported by other observation-based products, such as Orbiting Carbon Observatory-2 (OCO2) SIF and FluxSat GPP. In each tropical continent, the coupling between SIF and VPD increases with the mean VPD. Even on the interannual timescale, the correlation of GPP with VPD is still discernable, but the sensitivity is smaller than the intra-annual correlation. By and large, the dynamic global vegetation models in the TRENDY v8 project do not capture the high GPP seasonal sensitivity to VPD in dry tropics. The complex interactions between carbon and water cycles in the tropics illustrated in this study and the poor representation of this coupling in the current suite of vegetation models suggest that projections of future changes in carbon dynamics based on these models may not be robust.

Phenological assessment of transpiration: The stem-temp approach for determining start and end of season

Field-based assessment of transpiration phenology in boreal tree species is a significant challenge. Here we develop an objective approach that uses stem radius change and its correlation with sapwood temperature to determine the timing of phenological changes in transpiration in mixed evergreen species. We test the stem-temp approach using a five year stem-radius dataset from black spruce (Picea mariana) and jack pine (Pinus banksiana) trees in Saskatchewan (2016–2020). We further compare transpiration phenological transition dates from this approach with tower-based phenological assessment from green chromatic coordinate derived from phenocam images, eddy-covariance-derived evapotranspiration and carbon uptake, tower-based measurements of solar-induced chlorophyll fluorescence and snowmelt timing. The stem-temp approach identified the start and end of four key transpiration phenological phases: (i) the end of temperature-driven cycles indicating the start of biological activity, (ii) the onset of stem rehydration, (iii) the onset of transpiration, and (iv) the end of transpiration-driven cycles. The proposed method is thus useful for characterizing the timing of changes in transpiration phenology and provides information about distinct processes that cannot be assessed with canopy-level phenological measurements alone.

Sensitivity of solar-induced fluorescence to spectral stray light in high resolution imaging spectroscopy

Remote sensing of solar-induced chlorophyll fluorescence (SIF) advances our ability to monitor gross primary productivity. Because SIF is usually <5% of recorded canopy radiance, sources of measurement error must be reduced for accurate SIF retrieval. Here we quantify the impact of spectral stray light on SIF retrieval using a high-resolution imaging spectrometer. We first derived the FLD retrieval solution in the presence of stray light under the simplifying assumptions that SIF, reflectance, and stray light are constant across the region of the spectrum used in the retrieval. We show that stray light contributions from the canopy and reference spectra could cancel out if obtained from the same instrument. In practice however, the simplifying assumptions are unlikely to hold because SIF and reflectance vary across regions of the spectrum commonly exploited by the FLD retrieval, and stray light can also vary across the spectrum, as we demonstrate with an empirical example. To quantify the impact of spectral stray light on SIF retrievals in more realistic scenarios, we performed a sensitivity analysis. We used a stray light signal distribution function and measurements of spectral radiance and SIF to generate spectra with known quantities of SIF and stray light over four orders of magnitude of stray light. We then quantified the bias in retrieved SIF using four SIF retrieval approaches—standard FLD, 3FLD, a spectral fitting method (SFM), and a method based on singular value decomposition (SVD)—applied to the red and/or far-red spectral domains. We found that spectral stray light can cause either a positive or negative bias in SIF estimates. In the highest stray light scenario, with spectral stray light one order of magnitude smaller than the radiance signal, the stray light error ranged from < ± 1% of SIF (for O2-A band retrievals with FLD, 3FLD, and SFM methods, and for far-red retrievals in the 748 nm to 756 nm domain with SVD-based and 3FLD methods applied to Fraunhofer lines) to >30% of SIF (O2-B band retrieval with SFM, and 3FLD applied to Fraunhofer lines in the red domain). For context, a bias of 27% of SIF is a comparable magnitude to seasonal variation in SIF observed in the Amazon basin, and to SIF differences among plant functional types. However, when spectral stray light was three orders of magnitude smaller than the radiance signal, mean bias was < ± 2% for all retrieval methods. Our analysis informs when spectral stray light corrections must be performed for SIF remote sensing.

Land cover and latitude affect vegetation phenology determined from solar induced fluorescence across Ontario, Canada

• We assess how land cover affects phenology and magnitude of TROPOMI SIF measurements. • SIF magnitude is smaller at high latitudes and differs by land cover. • SIF start of season differs between land cover types. • Annually integrated SIF follows expected patterns of GPP variation. • Assessing phenology from SIF by land cover type allows GPP mapping at 30 m resolution. Land use decisions directly affect the terrestrial carbon balance by changing the quantity and type of vegetation present. However, such consequences are difficult for decisionmakers to account for in environmental impact assessments. Solar induced chlorophyll fluorescence ( SIF ) measured from satellite is strongly related to gross primary productivity of terrestrial vegetation and presents a new source of information from which to assess environmental impacts of land use decisions. We assess the usefulness of SIF measurements in accounting for changes in vegetation primary productivity due to land use change. We use a weighted double logistic regression based on the land cover mixture within SIF measurements from the TROPOspheric Monitoring Instrument (TROPOMI) to separate the phenology of the SIF signal by land cover for the region of Ontario, Canada. We use SIF integrated annually to determine, in relative units, the consequences of land use change on photosynthetic carbon uptake for the study region. Finally, we map GPP at a spatial resolution of 30 m across the province of Ontario using previously reported relationships between SIF and GPP . We find that SIF tracks expected biogeographical patterns of productivity: urban areas exhibit an earlier start of the growing season, lower SIF magnitude and later end of season than natural land cover classes, whereas croplands exhibit a later start of season. Patterns of phenology and SIF magnitude show land cover transitions from Broadleaf Deciduous Forests to croplands or urban environments to have the highest impacts on carbon uptake. Satellite-based SIF measurements are useful in exploring the geographic variation of vegetation productivity and can support inclusion of carbon accounting in environmental assessment at regional scale.

Can SIF and NPQ be used in the photosynthesis rate simulation of plants subjected to drought?

Solar-induced chlorophyll fluorescence (SIF) is a rapidly developed remote sensing technology and has been used to estimate leaf-level net CO 2 assimilation by a mechanistic light reaction (MLR-SIF) equation. However, the application of this model would be limited by the challenging measurement and estimation of input parameters (e.g., fraction of open PSII reaction centres, q L ). We modified the MLR-SIF model by replacing q L by the easily obtained parameters (non-photochemical quenching [NPQ]) to facilitate its application. We employed synchronous measurements of gas exchanges, ChlF parameters and SIF for Leymus chinensis , Populus tomentosa Carrières and Ulmus pumila var. sabulosa under the soil–water deficit and rehydration process to test the robustness of the modified MLR-SIF model. Our results demonstrated that for L. chinensis the net photosynthesis rate dynamics under severe drought stress and saturated water condition were effectively captured by the modified MLR-SIF model ( R 2 = 0.75–0.92, RMSE = 1.11–3.56) . For P. tomentosa Carrières and U. pumila var. sabulosa , the net photosynthesis rates were predicted by the modified MLR-SIF model with good accuracy ( R 2 = 0.86, RMSE = 9.44; R 2 = 0.88, RMSE = 4.16) across the water deficit and rehydration condition . However, the electron transport rate estimated by the modified MLR-SIF model uncoupled with the photosynthetic capacity ( r 2 = −0.13) and lowered the net photosynthesis rate simulation precision ( R 2 = 0.35, RMSE = 3.41) for L. chinensis under mild drought stress and saturated light intensities. The electron transport rate estimated by the modified MLR-SIF model downregulated the photosynthetic capacity for P. tomentosa Carrières ( r 2 = 0.32) and U. pumila var. sabulosa ( r 2 = 0.22) under mild drought stress. The shift of the Rubisco and RUBP limited state cross-points, the dynamic photosynthesis parameters across the plant species and the alternative electron sinks under soil–water deficit and rehydration process influenced the simulation precision of the modified MLR-SIF model. Our modified MLR-SIF model provided a basis for understanding and inferring the photosynthetic rate by SIF and NPQ under drought stress. • A mechanical link of SIF and NPQ to photosynthetic capacity was developed. • Carboxylation limitation state and photosynthesis parameters influence modified MLR-SIF simulation precision under drought and rehydration. • The electron transport rate estimated by SIF and NPQ uncoupled with the photosynthetic capacity under mild drought stress.

Flash drought early warning based on the trajectory of solar-induced chlorophyll fluorescence.

Flash drought often leads to devastating effects in multiple sectors and presents a unique challenge for drought early warning due to its sudden onset and rapid intensification. Existing drought monitoring and early warning systems are based on various hydrometeorological variables reaching thresholds of unusually low water content. Here, we propose a flash drought early warning approach based on spaceborne measurements of solar-induced chlorophyll fluorescence (SIF), a proxy of photosynthesis that captures plant response to multiple environmental stressors. Instead of negative SIF anomalies, we focus on the subseasonal trajectory of SIF and consider slower-than-usual increase or faster-than-usual decrease of SIF as an early warning for flash drought onset. To quantify the deviation of SIF trajectory from the climatological norm, we adopt existing formulas for a rapid change index (RCI) and apply the RCI analysis to spatially downscaled 8-d SIF data from GOME-2 during 2007-2018. Using two well-known flash drought events identified by the operational US Drought Monitor (in 2012 and 2017), we show that SIF RCI can produce strong predictive signals of flash drought onset with a lead time of 2 wk to 2 mo and can also predict drought recovery with several weeks of lead time. While SIF RCI shows great early warning potential, its magnitude diminishes after drought onset and therefore cannot reflect the current drought intensity. With its long lead time and direct relevance for agriculture, SIF RCI can support a global early warning system for flash drought and is especially useful over regions with sparse hydrometeorological data.

Physiological dynamics dominate the response of canopy far-red solar-induced fluorescence to herbicide treatment

Solar-induced chlorophyll fluorescence (SIF) has shown great potential for detecting changes in vegetation function under herbicide stress. However, how physiological (ΦF, canopy SIF emission efficiency) and non-physiological (e.g., structure and illumination) dynamics regulate canopy SIF, and the coupling between SIF and gross primary production (GPP) under herbicide stress remains unclear. Here, we conducted continuous eddy covariance flux and far-red SIF measurements during the early stage of maize in an herbicide-resistant maize field, where herbicide exclusively affects weeds. We investigated the performance of SIF, GPP, and vegetation indices (VIs) in capturing herbicide stress and then explored the sensitivity of SIF to the effects of herbicide treatments by disentangling canopy SIF into the physiological (ΦF) and non-physiological components (NIRvP). We found that SIF rapidly increased in response to the herbicide and that GPP decreased, and that both were more responsive than VIs in capturing the early effects of herbicides. Thus, the opposing responses in SIF and GPP disrupted their otherwise linear relationship during herbicide treatment. More importantly, we found that the increased ΦF dominated the variation of SIF during the early stages of herbicide stress, while the influence of NIRvP was prominent in the variability of SIF in the absence of herbicide. By unraveling its physiological and non-physiological contributions, our findings advance our understanding of how SIF responds to herbicide stress in heterogeneous cropland and will improve our interpretation of SIF as a tool for monitoring photosynthesis.

Attributing differences of solar-induced chlorophyll fluorescence (SIF)-gross primary production (GPP) relationships between two C4 crops: corn and miscanthus

There remains limited information to characterize the solar-induced chlorophyll fluorescence (SIF)-gross primary production (GPP) relationship in C4 cropping systems. The annual C4 crop corn and perennial C4 crop miscanthus differ in phenology, canopy structure and leaf physiology. Investigating the SIF-GPP relationships in these species could deepen our understanding of SIF-GPP relationships within C4 crops. Using in situ canopy SIF and GPP measurements for both species along with leaf-level measurements, we found considerable differences in the SIF-GPP relationships between corn and miscanthus, with a stronger SIF-GPP relationship and higher slope of SIF-GPP observed in corn compared to miscanthus. These differences were mainly caused by leaf physiology. For miscanthus, high non-photochemical quenching (NPQ) under high light, temperature and water vapor deficit (VPD) conditions caused a large decline of fluorescence yield (Φ F ), which further led to a SIF midday depression and weakened the SIF-GPP relationship. The larger slope in corn than miscanthus was mainly due to its higher GPP in mid-summer, largely attributed to the higher leaf photosynthesis and less NPQ. Our results demonstrated variation of the SIF-GPP relationship within C4 crops and highlighted the importance of leaf physiology in determining canopy SIF behaviors and SIF-GPP relationships.

Simulation of solar-induced chlorophyll fluorescence in a heterogeneous forest using 3-D radiative transfer modelling and airborne LiDAR

Solar-induced chlorophyll fluorescence (SIF) provides a means to estimate plant photosynthetic activities and to detect early plant stress. The accurate quantification of SIF emitted by various scene components (tree crowns and background) may significantly improve the interpretation of top-of-canopy SIF (SIFtoc) measurements made over heterogeneous canopies. To do so, a three-dimensional (3-D) canopy SIF model (FluorFLiES) was introduced by coupling the excitation-fluorescence matrices (EF-matrices) with a 3-D Monte Carlo canopy radiative transfer model (Forest Light Environmental Simulator, FLiES). A tool was developed to construct forest canopy scene components from LiDAR data and enable their simulated contributions in structurally complex forest scenes. FluorFLiES is able to quantify SIF measurements with good accuracy at both half-hourly (R2 = 0.72, RMSE = 0.26 mW m−2 sr−1 nm−1) and daily (R2 = 0.83, RMSE = 0.19 mW m−2 sr−1 nm−1) scales. This study showed that non-photosynthetic elements in tree crowns, the fractional vegetation cover (FVC), and the background (including understory vegetation and soils) had a strong influence on SIFtoc intensity. Non-photosynthetic woody material suppressed the propagation of photons within crowns, thereby decreasing SIFtoc by around 10%. The canopy background made a significant contribution to SIFtoc in the NIR region by scattering downward SIF photons upward, and the background contribution increased rapidly with decreasing FVC: SIFtoc increased two-fold from 0.15 to 0.3 mW m−2 sr−1 nm−1 when ground leaf area index increased from 0.5 to 1.5 m2/m2. The results showed that the fluorescence escape ratio (fesc), a key variable relating observed SIFtoc to photosynthesis CO2 rate, contained a contribution from the background with a magnitude of 42%, even for relatively dense forest canopies. Assuming fesc simulated by the FluorFLiES model as a reference value, this study demonstrated that the current reflectance-based approach may cause large uncertainties (29%) when understory vegetation and/or FVC changes, largely due to neglecting the contribution of background elements. This study highlights the need to separate scene components and to consider multiple scattering within/among these components in interpreting the SIFtoc signal when working with heterogeneous ecosystems. The source code of FluorFLiES is available for further benchmarking.

Phenological and physiological responses of the terrestrial ecosystem to the 2019 drought event in Southwest China: Insights from satellite measurements and the SSiB2 model

• The drought in Southwest China severely suppressed plant phenology and physiology. • Chlorophyll fluorescence sensitively responds to changes in water conditions. • Satellite chlorophyll fluorescence contributes to model evaluation and improvement. Understanding plant phenological and physiological changes in response to drought will provide key insight into the response of terrestrial ecosystems to climate change, but is still limited due to the increased drought severity and frequency in recent decades. Here, we combine solar-induced chlorophyll fluorescence (SIF) along with SSiB2 (Simplified Simple Biosphere Model) simulations to investigate the plant phenological and physiological responses to the 2019 drought in southwestern China. Our results show that this 2019 drought had substantial impacts on vegetation phenology and photosynthesis due to the soil moisture deficit in spring, while the rewatering process in July alleviated the water deficit and reduced drought damage to plants. Moreover, SIF observations provide a physiology-related vegetation response, as the recovery of plant photosynthesis indicated by fluorescence yield ( S I F yield ) is much stronger than the recovery of greenness described by vegetation indices during the rewatering in July. The SSiB2 simulations captured the physiological response of plants to moisture deficit during drought period, while the lack of realistic energy dissipation mechanisms under stressed conditions may lead to discrepancies in the timing of peak response to drought. Our findings highlight the prospective application of remote sensing SIF measurements in monitoring the timely response of plant physiology to changes in water conditions and to provide important information for model evaluation and improvement.

Different Responses of Solar-Induced Chlorophyll Fluorescence at the Red and Far-Red Bands and Gross Primary Productivity to Air Temperature for Winter Wheat

Solar-induced chlorophyll fluorescence (SIF) is closely related to the light-reaction process and has been recognized as a good indicator for tracking gross primary productivity (GPP). Nevertheless, it has not been widely examined how SIF and GPP respond to temperature. Here, we explored the linkage mechanisms between SIF and GPP in winter wheat based on continuous measurements of canopy SIF (cSIF), GPP, and meteorological data. To separately explore the structural and physiological mechanisms underlying the SIF–GPP relationship, we studied the temperature responses of the estimated light use efficiency (LUEp), canopy-level chlorophyll fluorescence yield (cSIFyield) and photosystem-level chlorophyll fluorescence yield (ΦF) estimated using canopy-scale remote sensing measurements. We found that GPP, red canopy SIF (cSIF688) and far-red canopy SIF (cSIF760) all exhibited a decreasing trend during overwintering periods. However, GPP and cSIF688 showed relatively more obvious changes in response to air temperature (Ta) than cSIF760 did. In addition, the LUEp responded sensitively to Ta (the correlation coefficient, r = 0.83, p-value &lt; 0.01). The cSIFyield_688 and ΦF_688 (ΦF at 688 nm) also exhibited significantly positive correlations with Ta (r &gt; 0.7, p-value &lt; 0.05), while cSIFyield_760 and ΦF_760 (ΦF at 760 nm) were weakly correlated with Ta (r &lt; 0.3, p-value &gt; 0.05) during overwintering periods. The results also show that LUEp was more sensitive to Ta than ΦF, which caused changes in the LUEp/ΦF ratio in response to Ta. By considering the influence of Ta, the GPP estimation based on the total SIF emitted at the photosystem level (tSIF) was improved (with R2 increased by more than 0.12 for tSIF760 and more than 0.05 for tSIF688). Therefore, our results indicate that the LUEp/ΦF ratio is affected by temperature conditions and highlights that the SIF–GPP model should consider the influence of temperature.

Simulation of solar-induced chlorophyll fluorescence by modeling radiative coupling between vegetation and atmosphere with WPS

Recent advances in instruments and retrieval methods enable measurements of solar-induced chlorophyll fluorescence (SIF) across a wide range of scales. Radiative transfer (RT) models for simulating scattering and (re-)absorption of SIF provide a powerful tool to study the upscaling of SIF signal from leaf level to terrestrial ecosystems. Based on the Monte Carlo ray-tracing (MCRT) model, WPS (Weighted Photon Spread), we made major extensions with new functionalities and systematic evaluation of the new modules. By modeling the radiative coupling between atmosphere and land surface with the same MCRT method, the non-fluorescent and SIF radiance received by sensors can be simulated at levels from top-of canopy to top-of-atmosphere (TOA) in a coherent manner. New extension to represent the three-dimensional (3-D) canopies with geometrical primitives composed of turbid medium makes the hyperspectral simulation (especially SIF) for a sensor with medium spatial resolution at kilometer-scale feasible and practical. Evaluations through ROMC (Radiation transfer model intercomparison Online Model Checker) show that the accuracy of the new module of 3-D structure representation in WPS is within 1% of the reference solution. The spectra of TOA radiance and SIF and their components simulated at nadir by WPS agree closely with those simulated by the coupled SCOPE and MODTRAN models with the coefficient of determination (R2) higher than 0.99 and the average absolute relative error (AARE) lower than 6.39%; for angular distributions of TOA radiance and SIF at 685 nm and 740 nm, R2 is higher than 0.81 and AARE is lower than 6.94%. Comparisons of the spectra of TOA radiance and SIF and their components simulated at nadir by WPS and the DART model give R2 higher than 0.99 and AARE lower than 3.5%; R2 is higher than 0.92 and AARE is lower than 5.92% for the TOA angular simulations. The WPS model was also evaluated by hyperspectral measurements through unmanned aerial vehicle at different altitudes, which shows that WPS can reproduce the spectral features of a rapeseed crop. WPS can be used as a versatile tool to assess the impacts of various factors on the SIF signal and to evaluate the SIF retrieval methods under different conditions.

A convolutional neural network for spatial downscaling of satellite-based solar-induced chlorophyll fluorescence (SIFnet)

Abstract. Gross primary productivity (GPP) is the sum of leaf photosynthesis and represents a crucial component of the global carbon cycle. Space-borne estimates of GPP typically rely on observable quantities that co-vary with GPP such as vegetation indices using reflectance measurements (e.g., normalized difference vegetation index, NDVI, near-infrared reflectance of terrestrial vegetation, NIRv, and kernel normalized difference vegetation index, kNDVI). Recent work has also utilized measurements of solar-induced chlorophyll fluorescence (SIF) as a proxy for GPP. However, these SIF measurements are typically coarse resolution, while many processes influencing GPP occur at fine spatial scales. Here, we develop a convolutional neural network (CNN), named SIFnet, that increases the resolution of SIF from the TROPOspheric Monitoring Instrument (TROPOMI) on board of the satellite Sentinel-5P by a factor of 10 to a spatial resolution of 500 m. SIFnet utilizes coarse SIF observations together with high-resolution auxiliary data. The auxiliary data used here may carry information related to GPP and SIF. We use training data from non-US regions between April 2018 until March 2021 and evaluate our CNN over the conterminous United States (CONUS). We show that SIFnet is able to increase the resolution of TROPOMI SIF by a factor of 10 with a r2 and RMSE metrics of 0.92 and 0.17 mW m−2 sr−1 nm−1, respectively. We further compare SIFnet against a recently developed downscaling approach and evaluate both methods against independent SIF measurements from Orbiting Carbon Observatory 2 and 3 (together OCO-2/3). SIFnet performs systematically better than the downscaling approach (r=0.78 for SIFnet, r=0.72 for downscaling), indicating that it is picking up on key features related to SIF and GPP. Examination of the feature importance in the neural network indicates a few key parameters and the spatial regions in which these parameters matter. Namely, the CNN finds low-resolution SIF data to be the most significant parameter with the NIRv vegetation index as the second most important parameter. NIRv consistently outperforms the recently proposed kNDVI vegetation index. Advantages and limitations of SIFnet are investigated and presented through a series of case studies across the United States. SIFnet represents a robust method to infer continuous, high-spatial-resolution SIF data.

Diurnal and Seasonal Dynamics of Solar‐Induced Chlorophyll Fluorescence, Vegetation Indices, and Gross Primary Productivity in the Boreal Forest

AbstractRemote sensing of solar‐induced chlorophyll fluorescence (SIF) provides a powerful proxy for gross primary productivity (GPP). It is particularly promising in boreal ecosystems where seasonal downregulation of photosynthesis occurs without significant changes in canopy structure or chlorophyll content. The use of SIF as a proxy for GPP is complicated by inherent non‐linearities due to both physical (illumination effects) and ecophysiological (light use efficiencies) controls at fine spatial (tower/leaf) and temporal (half‐hourly) scales. To study the SIF‐GPP relationship, we investigated the diurnal and seasonal dynamics of continuous tower‐based measurements of SIF, GPP, and common vegetation indices at the Southern Old Black Spruce Site (SOBS) in Saskatchewan, CA over the course of two years. We find that SIF outperforms other vegetation indices as a proxy for GPP at all temporal scales but shows a non‐linear relationship with GPP at a half‐hourly resolution. At small temporal scales, SIF and GPP are predominantly driven by light and non‐linearity between SIF and GPP is due to the light saturation of GPP. Averaged over daily and monthly scales, the relationship between SIF and GPP is linear due to a reduction in the observed PAR range. Seasonal changes in the light responses of SIF and GPP are driven by changes in light use efficiency which co‐vary with changes in temperature, while illumination and canopy structure partially linearize the SIF‐GPP relationship. Additionally, we find that the SIF‐GPP relationship has a seasonal dependency. Our results help clarify the utility of SIF for estimating carbon assimilation in boreal forests.

Far-Red Chlorophyll Fluorescence Radiance Tracks Photosynthetic Carbon Assimilation Efficiency of Dark Reactions

Solar-induced chlorophyll fluorescence (SIF) observations from space have shown close relationships with terrestrial photosynthesis rates. SIF originates from the light reactions of photosynthesis, whereas carbon fixation takes place during the dark reactions of photosynthesis. Questions remain regarding whether SIF is able to track changes in the efficiency of the dark reactions in photosynthesis. Using concurrent measurements of leaf-scale gas exchange, pulse amplitude-modulated (PAM) fluorescence, and fluorescence spectral radiances, we found that both far-red fluorescence radiances and PAM fluorescence yields responded rapidly to changes in photosynthetic carbon assimilation due to changes in environmental factors or induced stomatal closure under constant light conditions. Uncertainties in outgoing and incoming irradiance mismatch for SIF measurements may very likely obscure the contributions of the dark reactions, thereby causing the inconsistent findings previously reported, which were no change in far-red SIF and PAM fluorescence yields after clear reductions in the photosynthetic carbon assimilation efficiency of dark reactions. Our results confirm that high-quality SIF measurements have the potential to provide insights into the dark reactions of photosynthesis. This study is particularly relevant for better interpreting satellite SIF observations that are obtained under roughly constant overpass times and relatively stable light intensities.

Comparative Analysis on the Estimation of Diurnal Solar-Induced Chlorophyll Fluorescence Dynamics for a Subtropical Evergreen Coniferous Forest

Solar-induced chlorophyll fluorescence (SIF) is considered as a prospective indicator of vegetation photosynthetic activity and the ecosystem carbon cycle. The current coarse spatial-temporal resolutions of SIF data from satellite missions and ground measurements still cannot satisfy the corroboration of its correlation with photosynthesis and carbon flux. Practical approaches are needed to be explored for the supplementation of the SIF measurements. In our study, we clarified the diurnal variations of leaf and canopy chlorophyll fluorescence for a subtropical evergreen coniferous forest and evaluated the performance of the canopy chlorophyll concentration (CCC) approach and the backward approach from gross primary production (GPP) for estimating the diurnal variations of canopy SIF by comparing with the Soil Canopy Observation Photosynthesis Energy (SCOPE) model. The results showed that the canopy SIF had similar seasonal and diurnal variations with the incident photosynthetically active radiation (PAR) above the canopy, while the leaf steady-state fluorescence remained stable during the daytime. Neither the CCC nor the raw backward approach from GPP could capture the short temporal dynamics of canopy SIF. However, after improving the backward approach with a correction factor of normalized PAR incident on leaves, the variation of the estimated canopy SIF accounted for more than half of the diurnal variations in the canopy SIF (SIF687: R2 = 0.53, p &lt; 0.001; SIF760: R2 = 0.72, p &lt; 0.001) for the subtropical evergreen coniferous forest without water stress. Drought interfered with the utilization of the improved backward approach because of the decoupling of SIF and GPP due to stomatal closure. This new approach offers new insight into the estimation of diurnal canopy SIF and can help understand the photosynthesis of vegetation for future climate change studies.