Absorbed Photosynthetically Active Radiation Research Articles

Diversity of 3D APAR and LAI dynamics in broadleaf and coniferous forests: Implications for the interpretation of remote sensing-based products

Forests substantially mediate the water and carbon dioxide exchanges between terrestrial ecosystems and the atmosphere. The rate of this exchange, including evapotranspiration (ET) and gross primary production (GPP), depends mainly on the underlying vegetation type, health state, and the composition of abiotic environmental drivers. However, the complex 3D structure of forest canopies and the inherent top-view perspective of optical and thermal remote sensing complicate remote sensing-based retrievals of biotic and abiotic factors that eventually determine ET and GPP. This study investigates the sensitivity of remote sensing approaches to 3D variation of abiotic and biotic environmental drivers. We use 3D virtual scenes of two structurally different Swiss forests and the radiative transfer model DART to simulate the 3D distribution of solar irradiance and reflected radiance in the forest canopy. These simulations, in combination with LiDAR data, are used to derive the absorbed photosynthetic active radiation (APAR) and the leaf area index (LAI) in 3D space. The 3D variation of both parameters was quantified and analyzed. We then simulated images of the top-of-canopy bi-directional reflectance factor (BRF) and compared them with the hemispheric-conical reflectance factor (HCRF) data derived from HyPlant airborne imaging spectrometer measurements. The simulated BRF data was used to derive APAR and LAI, and the results were compared to their respective 3D representations. We unravel considerable spatial differences between both representations. We discuss possible reasons for the disagreement, including a potential insensitivity of the inherent top-of-canopy view for the real 3D product dynamics and limitations of the processing of remote sensing data, especially the approximation of effective surface irradiance. Our results can help understanding sources of uncertainties in remote sensing based gas exchange products and defining mitigation strategies.

Joint improvement on absorbed photosynthetically active radiation and intrinsic quantum yield efficiency algorithms in the P model betters the estimate of terrestrial gross primary productivity

Terrestrial gross primary productivity (GPP) plays a crucial role in global carbon cycle and budget. A range of light use efficiency (LUE) models have been developed to estimate GPP at different spatial scales. However, large uncertainties still remain in GPP output from such models, mainly owing to the difficulty in the proper determination of maximum light use efficiency (LUEmax). The recently developed P model directly quantifies actual LUE based on environmental and physiological factors, reducing the uncertainty in GPP estimation caused by the ambiguous LUEmax. However, the existing P models still suffer from a potential underestimation in global validation, which might be related to the calculation of absorbed photosynthetically active radiation (APAR) and intrinsic quantum yield efficiency (φ0) in the P model. In this study, we improved the P model by differentiating sunlit and shaded leaves for APAR calculation and by considering the spatial variability of the optimal temperature for φ0 (Topt_phi0). The roles of modified APAR and φ0 calculations in reducing the uncertainty of simulated GPP were assessed through model simulation experiments with monthly tower-based GPP from 120 flux sites globally distributed as the benchmark. The validation indicates that simultaneous improvements on APAR and φ0 algorithms are able to better the performance of the P model. Monthly GPP simulated with this improved P model (i.e., IP model) is in good agreement with tower-based values, with a linear R2, root mean squared error, mean error, mean absolute error, and DISO of 0.76, 1.88 g C m−2d−1, -0.14 g C m−2d−1, 1.77 g C m−2d−1 and 0.60. The total global terrestrial GPP output from the IP model (IPGPP) averaged 134.3 Pg C yr−1 during 1981—2021, in the upper range of existing GPP products.

Changes in light use efficiency explains why diversity effect on biomass production is lower at high planting density in mixed-species plantations of Eucalyptus grandis and Acacia mangium

Understanding the effect of planting densities and species proportions on light absorption and light use efficiency can help to improve the management of mixed-species forest plantations. Our study aimed to disentangle the role of light interception and light use efficiency (LUE) on the biomass production of Eucalyptus grandis (E), a highly productive species in tropical conditions, and Acacia mangium (A), a N2-fixing species, in monocultures and mixed-species plantations for contrasting planting densities. A randomized block experiment set up over 4 ha in southern Brazil was intensively monitored for 14 months at mid rotation. The absorbed photosynthetically active radiation (APAR) was simulated for each tree of the experiment using the tri-dimensional MAESPA model parameterized with detailed in situ measurements of tree and foliage. LUE for stem wood production was estimated as the ratio of measured stem biomass production (SBP) and simulated APAR. The APAR of Eucalyptus trees did not significantly differ between monocultures and mixed plantations, the reduction of Eucalyptus density being compensated by an increase in light absorption of Eucalyptus individuals. The LUE of Eucalyptus trees in monoculture and mixed-species stands was found to be comparable only at low planting densities. The replacement of Eucalyptus trees with Acacia trees resulted in a reduction in Eucalyptus LUE only at high planting density. The SBP of Eucalyptus trees was mainly explained by differences in APAR, while both APAR and LUE explained the SBP of Acacia trees. The maximum stand production was obtained with monoculture of Eucalyptus at high density and no mixture reached this productivity. Reducing the proportion of Eucalyptus in mixture lead to a substantial decrease in stand production at high planting density due to a decrease in LUE, while this stand production reduction was offset at low planting density, underlying a higher diversity effect at low planting density. In the perspective of increasing diversity in forest plantations to foster multifunctionality, mixed plantations of Acacia and Eucalyptus at low planting density can be an interesting option to maintain a relatively high productivity, which is similar to Eucalyptus monocultures at the same low planting density.

Stress detection in vegetation based on remotely sensed light absorption coefficient

ABSTRACT Environmental stresses on plants are among the major limitations to crop productivity. Plants are naturally equipped with a set of acclimatory mechanisms enabling them to withstand stresses without irreversible damage. Here, we overhauled the approach to non-invasive gauging of the response of maize to combined drought and high-light stresses. This was done to leverage the advantages of a recently developed framework based on using the reflected signal absorption coefficient modality. We document the deployment of two responses, one based on non-photochemical quenching (NPQ) of the absorbed light energy and the second on the adjustment of leaf photosynthetically active radiation (PAR) interception. The NPQ-based response, implemented by the xanthophyll cycle and inferred from changes in the reflection of light in the blue-green region of the spectrum, engaged at the beginning of the stress but quickly reached a plateau. We demonstrate that altering leaf absorption in PAR is a fundamental plant response mechanism to diverse stresses. This response is quantified by the PAR absorption coefficient retrieved from the non-destructively measured reflectance. A profound decrease in the PAR absorption coefficient in the whole PAR region was shown to be a reliable measure of the degree of stress regardless of its cause. The effects of superficial shading and leaf position were readily detectable by the leaf PAR absorption coefficient. We consider this report a proof of concept for quantifying plant stress and monitoring the acclimation state via the absorption coefficient in the PAR region through non-destructive, remotely sensed techniques.

Fine-Scale Quantification of Absorbed Photosynthetically Active Radiation (APAR) in Plantation Forests with 3D Radiative Transfer Modeling and LiDAR Data.

Quantifying the relationship between light and stands or individual trees is of great significance in understanding tree competition, improving forest productivity, and comprehending ecological processes. However, accurately depicting the spatiotemporal variability of light under complex forest structural conditions poses a challenge, especially for precise forest management decisions that require a quantitative study of the relationship between fine-scale individual tree structure and light. 3D RTMs (3-dimensional radiative transfer models), which accurately characterize the interaction between solar radiation and detailed forest scenes, provide a reliable means for depicting such relationships. This study employs a 3D RTM and LiDAR (light detection and ranging) data to characterize the light environment of larch plantations at a fine spatiotemporal scale, further investigating the relationship between absorbed photosynthetically active radiation (APAR) and forest structures. The impact of specific tree structural parameters, such as crown diameter, crown area, crown length, crown ratio, crown volume, tree height, leaf area index, and a distance parameter assessing tree competition, on the daily-scale cumulative APAR per tree was investigated using a partial least squares regression (PLSR) model. Furthermore, variable importance in projection (VIP) was also calculated from the PLSR. The results indicate that among the individual tree structure parameters, crown volume is the most important one in explaining individual tree APAR (VIP = 4.19), while the competition from surrounding trees still plays a role in explaining individual tree APAR to some extent (VIP = 0.15), and crown ratio contributes the least (VIP = 0.03). Regarding the spatial distribution of trees, the average cumulative APAR per tree of larch plots does not increase with an increase in canopy gap fraction. Tree density and average cumulative APAR per tree were fitted using a natural exponential equation, with a coefficient of determination (R2 = 0.89), and a small mean absolute percentage error (MAPE = 0.03). This study demonstrates the potential of combining 3D RTM with LiDAR data to quantify fine-scale APAR in plantations, providing insights for optimizing forest structure, enhancing forest quality, and implementing precise forest management practices, such as selective breeding for superior tree species.

Influence of crown and canopy structure on light absorption, light use efficiency, and growth in mixed and pure Pseudotsuga menziesii and Fagus sylvatica forests

Mixed-species forests can provide higher levels of ecosystem functions and services and can be more resistant and resilient in the face of global change. While many studies focus on the growth and yield of mixed forests, fewer have examined the underlying processes. Inter- or intra-specific differences and interactions influence tree- and stand-level light absorption by determining the vertical structure of stratified canopies, stand density, leaf area index, and the size or allometry of trees. While canopy light absorption is a very important process, it is difficult to quantify it for individual species within a mixture and is rarely examined. A detailed tree-level model (MAESTRA) was used in combination with measurements of tree sizes and stand structures to examine effects of mixing on absorbed photosynthetically active radiation (APAR) in 41–63-year-old stands of Pseudotsuga menziesii and Fagus sylvatica at three sites in Bavaria, Germany. The effects of initial stand density on APAR were analysed in 46-year-old P. menziesii stands of a spacing experiment at two sites. At the tree level, mixing increased mean height and leaf area, growth (185% higher) and APAR (85% higher) of P. menziesii at all sites. Mean tree heights and crown sizes of F. sylvatica were larger in mixtures, while recent growth rates and APAR were not significantly different to monocultures. Planting density did not influence mean tree variables (e.g. height, leaf area, crown volume), because any initial spacing effects had been gradually removed by thinning across all treatments. At the stand level, there were no differences in growth, basal area or in the annual growth per annual APAR (light use efficiency, LUE) between monocultures and mixtures. The highest APAR values were observed in P. menziesii monocultures, while the lowest APAR values were observed in F. sylvatica monocultures. While mixing these species may not increase stand-level growth during later phases of development, mixing accelerated initial growth of individual trees and reduced the time to reach target diameters, which are both important aspects in adapting forests to global change.

The molecular composition of leaf lipids changes with seasonal gradients in temperature and light among deciduous and evergreen trees in a sub-humid ecosystem

Forest canopy structure is a fundamental ecosystem attribute affecting regional and global climate through primary production by CO2 drawdown and evapotranspirative feedback. Environmental changes in temperature and light affect leaf physiology and thus canopy functioning. Leaf physiological changes may be reflected in expressed chemical compounds (e.g., leaf lipid biomarkers), that offer opportunities to characterize and quantify climatic effects on plant canopies in the present and the past. To assess this possibility, we systematically investigated the lipids from leaves of deciduous angiosperm (Quercus buckleyi, April–October 2019) and evergreen gymnosperm (Juniperus ashei, April–October 2019 and January 2020) tree species at monthly sampling intervals over one growing season in a natural sub-humid ecosystem of central Texas. Fatty acid unsaturation in Q. buckleyi and J. ashei leaves was negatively correlated with air temperature. The average chain lengths of leaf wax n-alkanols of Q. buckleyi were strongly correlated with leaf area index (LAI) and absorbed photosynthetically active radiation (APAR) (r2 > 0.5). The stigmasterol/β-sitosterol ratio was correlated with light transmittance in the canopy of Q. buckleyi, with values of the sterol ratio three-fold higher in shaded leaves than in sparse canopies. The observed seasonal changes in leaf lipid molecular composition and chain-lengths might be related to their biosynthetic responses to temperature and light stresses. Finally, we developed multi-lipid regression models resolving seasonal differences in temperature, LAI, and APAR. We posit that the specific lipid biosynthetic responses to variations in temperature and light are a basis for reconstructing terrestrial paleoenvironmental changes.

Solar-induced chlorophyll fluorescence extraction based on heterogeneous light distribution for improving in-situ chlorophyll content estimation

Accurate estimation of leaf chlorophyll content (LCC) in field for wheat crops is important to provide guidance for precision management. Solar-induced chlorophyll fluorescence (SIF) extraction based on hyperspectral imaging is an effective tool for LCC estimation, which is because SIF is a signal directly and intrinsically related to photosynthetic activity of crops. However, soil background and structural difference always lead to mixing of soil, shadowed and sunlit canopy components, and heterogeneous light distribution among canopy, which increase the complexity of SIF extraction and reduce the LCC estimation accuracy. The purpose of this study is to propose an accurate SIF extraction method by eliminating above challenges to improve the LCC estimation accuracy. Hyperspectral image and LCC measurements were conducted at the jointing and heading stages of wheat crops. Firstly, to eliminate the effect of soil background, two image segmentation methods, excess green index (ExG) and optimized soil-adjusted vegetation index (OSAVI), are compared to extract the crop region. Secondly, to reduce the canopy structure effect, light distribution condition is evaluated by the brightness, which is extracted from intensity component of hue-saturation-intensity color space. Then K-means clustering based on the brightness distribution is utilized to divide the segmented crop region further into shadowed and sunlit regions. Finally, SIF was extracted based on the Fraunhofer line discriminator method at 687 and 761 nm, and was modified by normalization of brightness to reduce the influence of heterogeneous light distribution. The performance of random forest regression models, which are built by extracting SIF based on raw image, segmented crop by ExG segmentation, segmented crop by OSAVI segmentation, and shadowed and sunlit regions, respectively, is compared. Results show the estimation accuracy of the models increases when image segmentation is performed (determination coefficient of prediction set (RP2) = 0.37 for ExG segmentation; RP2 = 0.47 for OSAVI segmentation) compared with raw image (RP2 = 0.30). Moreover, shadowed region clustering based on brightness was optimal region for SIF extraction (RP2 = 0.54) compared with the sunlit region (RP2 = 0.27). The modified SIF at shadowed regions, normalized by the brightness of crops to reduce the effect of heterogeneous light distribution, yields the highest relationship with LCC (RP2 = 0.79), which outperforms SIF normalized by the absorbed photosynthetically active radiation (APAR). The reason is that brightness is more related to LAI, a parameter representing canopy structure, than APAR. It suggests that OSAVI segmentation for soil background effect elimination and SIF extraction considering canopy structure and heterogeneous light distribution facilitate the improvement of LCC estimation accuracy for high-throughput phenotyping in field.

Drought-related mortality modifies mixing effects on light absorption and growth in mono-specific and mixed stands of Fagus sylvatica, Alnus glutinosa, and Betula pendula

Abstract Little is known about how drought-related mortality influences light absorption of surviving trees and consequent changes in tree species interactions. Here, we used the detailed tree-level light model (Maestra) in combination with measurements of tree dimensions, crown architectures, and stand structures to examine experimental mixing effects of Fagus sylvatica, Alnus glutinosa, and Betula pendula on light dynamics following a drought in Bangor, Wales. The experimental stands, planted in 2004, were composed of clusters with one to three species in different combinations. Droughts occurred in 2011 and 2014 during the growing seasons, and trees were measured in 2014 and 2015. Species mixing resulted, on average, in higher tree growth, absorption of photosynthetically active radiation (APAR), and light-use efficiency (LUE) compared with the mean of the monocultures. An exception was the monoculture of B. pendula, which was the most productive species and had higher growth, APAR, or LUE than some mixtures. Drought-related mortality reduced the stand basal area across all plots by an average of 8.3% and tree density by 11%. This moderate change in the structure did not result in significant increases in individual tree APAR, LUE, or growth. From a management perspective, mortality might need to reduce stand density more strongly than it did in this study before light absorption or LUE is altered.

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.

Estimation of photosynthetic dynamics in forests from daily measured fluorescence and PRI data with adjustment for canopy shadow fraction

We conducted year-long measurements of the photochemical reflectance index (PRI) and solar-induced fluorescence in the O2A oxygen band (SIFA) at a Norway spruce forest and a European beech forest to study relationships of these remote sensing variables to photosynthesis by trees in grown forest stands. Measured PRI and SIFA values were linked to changes in forest gross primary productivity (GPP) and light-use efficiency (LUE). Changes in the shadow fraction (αS) within tree crowns influenced PRI and fluorescence signals. In the spruce forest, the quantum yield of SIFA (FYSIFA) decreased around midday together with photosynthesis and GPP. Such decreases in FYSIFA were accompanied by an increase in the αS. In the beech forest, we detected an increase in FYSIFA together with a decrease in αS in the afternoon hours. The overall sensitivity of PRI to LUE was variable according to the season, presumably influenced by complex changes in photosynthetic pigments. PRI and FYSIFA showed weak correlations with canopy LUE; however, when considered together, the correlation was strengthened (R2 was 0.63 and 0.34 in spruce and beech forest, respectively). Our model predicting LUE dynamics includes a diurnal minimum of PRI and canopy αS to make allowances for seasonal changes in photosynthetic pigments and for diurnal variability of the shadow fraction in forests. The incorporation of these correcting factors allowed us to estimate LUE at R2 = 0.68 (spruce) and 0.53 (beech). The modeling equations appeared sensitive to the absorbed photosynthetically active radiation (APAR), but less sensitive to the GPP of these forests. Substituting pigments correction with introducing differential PRI (ΔPRI) into the model did not significantly improve the LUE estimation across the season. Our results show that the joint use of PRI and fluorescence improves LUE and GPP estimation accuracy in both daily and seasonal observations.

NIRvP as a remote sensing proxy for measuring gross primary production across different biomes and climate zones: Performance and limitations

The product of near-infrared radiation reflected by vegetation (NIRv) and PAR (NIRvP) is a promising proxy for the remote estimation of gross primary production (GPP). However, the efficiency of NIRvP in estimating the GPP and its limitations across multiple biomes and climate zones remain unclear. In this study, we aimed to evaluate the performance and limitations of NIRvP in estimating the GPP in comparison to absorbed photosynthetically active radiation (APAR), solar-induced chlorophyll fluorescence (SIF), and the MOD17A2H GPP product. Overall, the correlation between NIRvP and eddy covariance (EC) GPP was stronger than that of APAR, SIF, and MOD17A2H GPP across most biomes with usually similar seasonal variations in radiation, air temperature (TA), and precipitation. The near-​infrared (NIR) reflectance (ρNIR) and light use efficiency (LUE) exhibited a covarying relationship under these environmental conditions, which suggested that the ρNIR contributed positively to the NIRvP-GPP relationship under such climatic conditions. However, the performance of NIRvP was poor in some biomes and climate zones, which exhibited different variations in the seasonal patterns of radiation, TA, and precipitation. The resulting inconsistencies between ρNIR and LUE implied that the ρNIR contributed negatively to the NIRvP-GPP relationship in these regions. Altogether, the findings demonstrated that the NIRvP-GPP relationship was robust but attained a moderate overall relationship across ecosystems (R2 < 0.50) in the majority of biomes and climate zones. In addition, this study also elucidated the limitations of NIRvP as a GPP proxy in certain climate zones, which was attributed to the synergistic contributions of APAR and ρNIR in the NIRvP-GPP relationship.

Temporal upscaling of MODIS instantaneous FAPAR improves forest gross primary productivity (GPP) simulation

Gross primary productivity (GPP) is a measure of carbon uptake by terrestrial ecosystems for carbon neutrality and serves as a key indicator for the Sustainable Development Goals. The instantaneous Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) is applied in GPP estimation by light use efficiency (LUE) models. However, an obvious time scale mismatch exists between instantaneous FAPAR and daily accumulated GPP. In the study, we explored the potential of temporal upscaling instantaneous FAPAR in improving GPP simulation. The absorbed photosynthetically active radiation (APAR) derived from instantaneous and upscaled FAPARs were first compared. GPPs were estimated from instantaneous and upscaled FAPAR by MOD17 LUE model using default and optimized parameters. The optimized GPP was finally compared with three GPP products: GLASS, MOD17A2H and MYD17A2H GPP. The APARs and GPPs were evaluated with the Eddy Covariance (EC) GPP at 78 forest sites from the Fluxnet community. Results showed that when compared with EC GPP, the upscaled FAPAR-derived APAR held a higher R2 (0.26–0.73) than that from instantaneous FAPARs. The upscaled FAPAR-based GPPs by MOD17 LUE model with default or optimized parameters had a larger R2 and smaller RMSE reducing uncertainties by 6.82–7.8% (maximum value: 27.9–49%). The optimized upscaled FAPAR-derived GPP was far superior to the GPP products with larger R2 (0.69–0.85) and smaller RMSE (12.8–14.6 g C/m2/8d). It is concluded that temporal upscaling of MODIS instantaneous FAPAR can well improve the estimation of forest GPP and the parameters of MOD17 LUE model should be further optimized. Our study is an effort toward reducing the uncertainties from FAPAR in the GPP estimation for better assessing the achievement of carbon neutrality and Sustainable Development Goals.

Row orientation influences the diurnal cycle of solar-induced chlorophyll fluorescence emission from wheat canopy, as demonstrated by radiative transfer modeling

Although multiple studies have used solar-induced chlorophyll fluorescence (SIF) of the crop canopy to estimate photosynthetic activity, the effect of canopy geometry (row orientation) on diurnal SIF remains uncertain. Using a combination of 3D canopy radiative transfer modeling and spectroscopic observations collected in a winter wheat field, we investigated (i) the relationships between observed SIF and factors including temperature, humidity, absorbed photosynthetically active radiation (APAR), and row orientation; (ii) the temporal pattern and multi-angle distribution of diurnal canopy SIF; and (iii) the mechanisms influencing components of diurnal SIF under the effect of row orientation. The relationship between observed SIF and APAR was relatively strong at the early growth period, but SIF was influenced by various factors (temperature, humidity, and row–sun angle) at the middle of the growth period. To test an asymmetric crop row effect as a potential cause of this skewness, we evaluated the modeled SIF with a 3D northwestward (315°) crop row alignment and other orientations. Each row orientation resulted in a trough-like depression parallel to the row in simulated canopy SIF, which could cause a diurnal asymmetry of canopy SIF, a fraction of fluorescence escape, and a fraction of APAR. View angles, the dimension of canopy objects (1D/3D), inter-row width, and leaf structure parameters impacted the representativeness of these simulations. An increased shade SIF, synchronized with the time when row–sun angles become zero at the incident sunlight being parallel to the crop row, was linked to decreasing canopy SIF emissions and would cause a non-linear SIF–APAR relationship at certain row orientations especially facing diagonally to the south. The concept of row orientation provides a novel viewpoint of diurnal canopy SIF from which to test the effect of row geometry in cropland, and will promote a mechanistic understanding of photosynthesis and canopy light use.

Environmental Drivers of Gross Primary Productivity and Light Use Efficiency of a Temperate Spruce Forest

AbstractVarious environmental variables drive gross primary productivity (GPP) and light use efficiency (LUE) of forest ecosystems. However, due to their intertwined nature and the complexity of measuring absorbed photosynthetically active radiation (APAR) of forest canopies, the assessment of LUE and the importance of its environmental drivers are difficult. Here, we present a unique combination of measurements during the 2021 growing season including eddy covariance derived GPP, sap flow, Sentinel‐2 derived canopy chlorophyll content and in situ measured APAR. The importance of environmental variables for GPP models is quantified with state‐of‐the‐art machine learning techniques. A special focus is put on photosynthesis‐limiting conditions, which are identified by a comparison of GPP and sap flow hysteretic responses to Vapor pressure deficit (VPD) and APAR. Results demonstrate that (a) LUE of the canopy's green part was on average 4.0% ± 2.3%, (b) canopy chlorophyll content as a seasonal variable for photosynthetic capacity was important for GPP predictions, and (c) on days with high VPD, tree‐scale sap flow and ecosystem‐scale GPP both shift to a clockwise hysteretic response to APAR. We demonstrate that the onset of such a clockwise hysteretic pattern of sap flow to APAR is a good indicator of stomatal closure related to water‐limiting conditions at the ecosystem‐scale.

Global photosynthetic capacity of C3 biomes retrieved from solar-induced chlorophyll fluorescence and leaf chlorophyll content

The maximum Ribulose-1,5-bisphosphate carboxylase/oxygenase (Rubisco) carboxylation rate (Vcmax) has been widely used to help determine the photosynthetic capacity for carbon cycle modelling. Field measurements of Vcmax are very limited, so fixed Vcmax values over growing seasons are often used, causing considerable uncertainties in modelled results. Also, the lack of a global Vcmax dataset with seasonal variations limits our understanding of the spatial and temporal patterns of Vcmax, and hence photosynthesis. This study proposes a refined data assimilation scheme to retrieve daily Vcmax using remotely sensed solar-induced chlorophyll fluorescence (SIF) and leaf chlorophyll content (LCC) data. Using the refined method, we produced a global Vcmax dataset with daily 0.1° × 0.1° resolutions. The seasonal variations in Vcmax have been successfully retrieved. Vcmax retrieved in this study was compared with field-measured Vcmax from past literature. Good agreements were achieved in relation to Vcmax measured at 201 sites (R2 is 0.78, and relative RMSE is 34%) and the seasonal variation in Vcmax measured at 9 sites (R2 ranges from 0.57 to 0.99, and the relative RMSE ranged from 6% to 28%). Our method effectively utilizes the information from both SIF and LCC, showing advantages over previous approaches that estimate Vcmax based solely on using SIF or LCC. Our results suggest that the spatial distribution of Vcmax depends on the spatial distribution of biomes, along with air temperature and absorbed photosynthetically active radiation (APAR). Higher seasonal mean air temperature and APAR tend to lead to higher seasonal mean Vcmax. The seasonal variation in Vcmax is driven by the seasonal variations in air temperature and APAR, rather than their seasonal means. We also derived and analyzed Vcmax25, which is Vcmax normalized to 25 °C (Vcmax25) and has been found to be more closely related to the Rubisco content. Vcmax25 also has considerable spatiotemporal variations, and the variations differ to that in Vcmax. Different biomes have different ratios of Vcmax25 to LCC. Air temperature and APAR exert weak but positive effects on the seasonal variation in Vcmax25. Vcmax retrieved in this study enhances our understanding of the spatiotemporal pattern of leaf photosynthetic capacity on the global scale and is potentially useful to terrestrial carbon cycle modelling.

Dynamic of Fluorescence Emissions at O2A and O2B Telluric Absorption Bands in Forested Areas with Seasonal APAR and GPP Variations

We measured dynamics of solar-induced chlorophyll fluorescence at telluric oxygen absorption bands O2A and O2B in evergreen spruce and deciduous beech forests. Seasonal variations in fluorescence emissions were compared with NDVI. Daily changes in fluorescence emissions were compared with canopy shadow fraction (αS) dynamics, which showed impact of branch and leaf positions on detected fluorescence signals based on comparison with canopy height model. Absorbed photosynthetically active radiation (APAR) was recognized as a large determinant of fluorescence changes within the O2A band (SIFA), with R2 &gt; 0.68. Fluorescence within the O2B band was more directly linked to NDVI. Although, the seasonal dynamics of fluorescence within the O2B band (SIFB) were similar to SIFA in the spruce forest. In the beech forest, SIFB showed different seasonal dynamics as compared with SIFA. SIFA in the spruce forest showed a relationship to gross primary productivity (GPP), with R2 = 0.48, and a relationship of R2 = 0.37 was estimated for the SIFA-GPP connection in the beech forest. SIFB was better linked to seasonal GPP in the beech forest, but with a negative slope in the relationship with R2 = 0.61. We have shown that measurements of passive fluorescence signals at telluric oxygen absorption bands can contribute to understanding to photosynthesis processes in forest canopies.

Radiation use efficiency and biomass production of maize under optimal growth conditions in Northeast China.

Accurate crop growth and radiation use efficiency (RUE) measurements under optimal growth conditions are required to predict grain yield near the genetic growth potential and estimate climate change effects on crop production. Research was conducted to quantify RUE of maize during the whole growth period, vegetative period (VP, phenological development stage DVS < 1.0), and reproductive period (RP, DVS ≥ 1.0) under the optimal growth condition in Northeast China. Maize was grown in three population density treatments (9.0, 7.5, and 6.0 plants m-2, referred to HD, MD, and LD respectively) over three growing seasons (2017-2019). The maximum Leaf Area Index (LAI) was observed after the anthesis period (DVS = 1.2), ranged from to 4.9 to 6.9, and then gradually decreases. Photosynthetically active radiation (PAR) intercepted by the canopy of maize was approximate 10% during the early stage of the vegetative period (DVS < 0.3). Then greatest differences occurred during the late vegetative period (DVS = 0.3 to 0.8). When DVS > 1.0, there is no significant difference between the three population density conditions. Estimates of RUE were obtained based on the intercepted PAR (IPAR) and absorbed PAR (APAR). RUE value was 3.97 g MJ-1 APAR or 3.73 g MJ-1 IPAR in the whole growth period, and did not vary among density treatments. Moreover, maximum RUE occurred during VP (4.11 g MJ-1 APAR) and declined during RP (3.95 g MJ-1 APAR). Therefore, we recommend that maize models that rely on RUE for aboveground biomass accumulation should be using a value of 3.97 g MJ-1 APAR for predicting optimum maize grain yield in Northeast China, especially for the potential yield.

Difference in seasonal peak timing of soybean far-red SIF and GPP explained by canopy structure and chlorophyll content

Recent advances in remotely sensed solar-induced chlorophyll fluorescence (SIF) have provided an exciting and promising opportunity for estimating gross primary production (GPP). Previous studies mainly focused on the linear correlation between SIF and GPP and the slope of the SIF-GPP relationship, both of which lack rigorous consideration of the seasonal trajectories of SIF and GPP. Here, we investigated the timing of seasonal peaks of far-red SIF and GPP in soybean fields by integrating tower data, satellite data, and process-based Soil Canopy Observation of Photosynthesis and Energy (SCOPE, v2.0) model simulations. We found inconsistency between the seasonal peak timing of far-red SIF and GPP in three of four soybean fields based on tower far-red SIF and eddy-covariance measurements. In particular, far-red SIF reached its seasonal maximum 14–17 days earlier than GPP. This far-red SIF-GPP difference in peak timing degraded the correlation between sunny-day far-red SIF and GPP at daily scale (Pearson r = 0.83–0.87 at the site with 14–17 days difference and Pearson r = 0.96 at the site with no difference), and it can be explained by a divergence in the seasonality between absorbed photosynthetic active radiation (APAR) and canopy chlorophyll content (ChlCanopy). We found that the seasonality of far-red SIF - a byproduct of the light reactions of photosynthesis - was primarily controlled by APAR, whereas GPP seasonality was dominated by ChlCanopy. Further, SCOPE model simulations showed that the seasonal patterns of leaf area index (LAI), leaf chlorophyll content (ChlLeaf) and leaf angle distribution (LAD) could affect the different peak timing of SIF and GPP and consequently the seasonal relationship between far-red SIF and GPP. A further increase in LAI after the fraction of light absorption (FPAR) saturates and a later peak of ChlLeaf compared to LAI results in a later peak of GPP compared to far-red SIF. More horizontal leaf angles can further exacerbate this difference. Our results advance mechanistic understanding of the SIF-GPP relationships and combining chlorophyll content information with SIF could potentially improve remote-sensing-based GPP estimation.

Fluorescence ratio and photochemical reflectance index as a proxy for photosynthetic quantum efficiency of photosystem II along a phosphorus gradient

Sun-induced chlorophyll fluorescence (SIF) is one of the most promising remote-sensing signals to assess spatio-temporal variation in photosynthesis. Yet, it has been shown that the positive linear relationship of SIF and photosynthesis, often reported from satellite and proximal remote sensing, is mainly driven by the amount of absorbed photosynthetic active radiation (APAR). By normalizing SIF by APAR these structural first-order effects can accounted for and SIF is then reflecting physiological regulation of photosynthetic efficiency. However, because of the confounding contribution of non-photochemical energy dissipation, the relationship between SIF and photosynthetic efficiency is non-linear, and therefore additional measurements have to be included to constrain the predictions of photosynthetic efficiency and photosynthetic electron transport.We grew Zea mays at different phosphorus (P) levels to assess if P-induced reduction in quantum efficiency of PSII (ΦPSII), can be estimated by the fluorescence efficiency parameters, APAR normalized fluorescence (Fyield) and the ratio of the two emitted fluorescence peaks (F↑ratio), at leaf level. Results were compared to the photochemical reflectance index (PRI), a well-established index related to the activity of the xanthophyll cycle, a protection mechanism which activates under light-stress conditions. We demonstrate that the relationship between ΦPSII and Fyield is non-monotonic across a P limitation gradient, rendering the prediction of ΦPSII by Fyield alone unfeasible. We show, however, that the pigment corrected PRI (cPRI) and F↑ratio (cF↑ratio) share a strong linear relationship with ΦPSII, thereby enabling the estimation of ΦPSII. We demonstrate that a compensation for reabsorption effects improved the estimation of ΦPSII by Fratio at foliar level. This may allow improved predictions of photosynthetic light use efficiency parameters without the need of measuring green APAR.