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• SIF performs well in tracking GPP during dry conditions in a semi-arid grassland. • SIF and GPP exhibit parallel responses to environmental variables under dry conditions. • Compared to wet conditions, the role of physiological information regulation in SIF and GPP increases under dry conditions. Solar-induced chlorophyll fluorescence (SIF) has recently emerged as a promising tool for estimating gross primary production (GPP). To date, there is ongoing debate regarding whether the strong correlations between SIF and GPP persist under dry conditions. Here, we conducted continuous far-red SIF measurements in a semi-arid grassland from 2017 to 2019 to investigate its association with GPP. Our findings revealed strong correlations in the seasonal patterns of SIF and GPP during dry conditions (R2=0.79). After disentangling the effects of photosynthetically active radiation and soil water content, we observed consistent responses to environmental variables in both SIF and GPP under dry conditions. Furthermore, we conducted a dominance analysis to assess the contributions of physiological and non-physiological components to the variations in SIF and GPP. Our results demonstrated a substantial increase in the contributions of physiological components to both SIF (wet: 19.29%; dry: 60.23%) and GPP (wet: 20.89%; dry: 28.38%) during dry conditions, highlighting a shift towards enhanced physiological regulation of SIF and GPP in response to dry conditions. In conclusion, our findings provide valuable insights into the GPP-SIF relationships in semi-arid grasslands under dry conditions. These insights hold the potential to refine and constrain model predictions under climate change. [ABSTRACT FROM AUTHOR]

• A canopy-scale model is proposed to estimate the fraction of APAR allocated to PSII. • The fraction of APAR allocated to PSII for sunlit and shaded leaves is simulated. • The fraction of APAR allocated to PSII varies from about 0.5 to 0.8. • The model enhances the potential of SIF observations for accurately estimating GPP. • The contribution of PSII to SIF TOC_760 remains nearly constant. Solar-induced chlorophyll fluorescence (SIF) contains contributions from both photosystem I (PSI) and photosystem II (PSII). In theory, SIF emitted from PSII (SIF PSII) should be extracted from at-sensor SIF to quantify photosynthetic CO 2 assimilation, as PSI fluorescence yield is nearly insensitive to changes in photochemical yield. In many SIF-related studies, the fraction of chlorophyll-absorbed energy allocated to PSII (β 2), a key factor controlling the flux of excitation energy for SIF PSII , is simply assigned a fixed value. However, β 2 is regulated in response to variations in environmental conditions to avoid an energy imbalance between PSI and PSII. By quantifying the regulating effect of the cytochrome b 6 f complex (Cyt b 6 f) on the electron transport from PSII to PSI, and its interaction with energy dissipation in both photosystems, we develop a framework to estimate β 2 and PSII fluorescence yield (Φ F2), two key determinants for SIF PSII , from SIF emission, PAR, air temperature, the maximum carboxylase activity of Rubisco (V cmax), and the maximum activity of Cyt b 6 f (J CB6F_max). The framework is equipped with a two-leaf scheme, enabling us to estimate SIF PSII for sunlit and shaded leaves from top-of-canopy SIF observations (SIF TOC). Our simulation results showed that β 2 and Φ F2 tend to change in opposite directions with varying PAR, making the contribution of PSII to SIF TOC relatively constant. We compare gross primary productivity (GPP) mechanistically estimated from SIF PSII obtained with fixed (GPP SIF_Fβ) and dynamic β 2 (GPP SIF_Dβ) against the eddy-tower-derived GPP (GPP EC) at a winter-wheat experiment site. At a half-hourly time scale, GPP SIF_Dβ is better than GPP SIF_Fβ , showing higher correlations with GPP EC (R2 = 0.74 versus R2 = 0.64 and RMSE = 6.61 μmol m−2 s−1 versus RMSE = 7.67 μmol m−2 s−1). The study provides a practical way to estimate the contribution of SIF PSII to SIF TOC , giving a better theoretical basis to SIF-based GPP estimation models. [ABSTRACT FROM AUTHOR]

Highlights • Canopy conductance and SIF show similar diurnal and seasonal patterns. • Tower-based and satellite-based SIF significantly correlate with canopy conductance. • Model integrated SIF generally yields reasonable estimation of transpiration. • Drought decouples the relationship between carbon and water exchange. Abstract Vegetation transpiration (T) is the process of plant water loss through the stomata on the leaf surface and plays a key role in the energy and water balance of the land surface, especially with dense vegetation cover. To date, however, estimation of ecosystem-scale T is still rather uncertain mainly due to errors in modeling canopy resistance or conductance. Considering the intrinsic link between photosynthesis and chlorophyll fluorescence, the recent available remote sensing of solar-induced chlorophyll fluorescence (SIF) provides a valuable opportunity to estimate plants T at large scales. In this study, we demonstrate how remote sensing of SIF relates to canopy stomatal conductance and transpiration at diurnal and seasonal scales with continuous ground measurements of SIF at three flux sites in forest, cropland and grassland ecosystems. The results show that both ground and spaceborne SIF observations are good indicators of canopy conductance at both diurnal and seasonal scales (R2 = 0.57 and 0.74 for forest, R2 = 0.62 and 0.80 for cropland, R2 = 0.52 and 0.63 for grassland, respectively). Then, empirical SIF-based canopy conductance models are employed to estimate hourly and daily transpiration. We evaluate our ecosystem T estimations against latent heat fluxes measured by eddy covariance systems with more satisfactory results for forest (R2 = 0.57 and 0.71), and cropland (R2 = 0.77 and 0.83) than for grassland (R2 = 0.13 and 0.22) at hourly and daily time scales. Our results suggest the potential of remotely-sensed SIF for estimating canopy conductance and plant transpiration, but a more mechanistic understanding is needed for their link. [ABSTRACT FROM AUTHOR]

• The physiological and non-physiological dynamics of SIF under herbicide stress are quantified. • SIF captures herbicide-induced photosynthetic anomalies in heterogeneous cropland ecosystems. • SIF, NIRv and GPP have different responses to herbicide stress. • The link between SIF and GPP was disturbed after herbicide treatment. • ΦF dominates the variation of SIF in the early stage after 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. [ABSTRACT FROM AUTHOR]

• We compared vegetation phenology from a SIF product (CSIF) and from MODIS NDVI. • We found similar spatial patterns in CSIF and NDVI derived phenology. • NDVI data indicated an earlier start and later end of the growing season than CSIF. • Models based on leaf greenness may overestimate photosynthesis active period. Vegetation phenology is highly sensitive to climate change, although the data and methods used to estimate key phenological states can influence this sensitivity. Because of its direct relation to leaf photosynthetic carbon uptake, remotely sensed solar-induced chlorophyll fluorescence (SIF) can provide new insight assessing changes in vegetation phenology. Here, we investigated the potential of using a SIF time series product named contiguous SIF (CSIF) to estimate spring, summer, and autumn phenology in the extratropical Northern Hemisphere (>30°N) and compared the results with those based on Moderate Resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI) for the period 2001–2018. Overall, we found similar spatial patterns in phenological states. However, specific dates of key phenological events differed when using CSIF vs. MODIS NDVI data. NDVI data indicated that the growing season started earlier (by 10.1 days on average) and ended later (11.5 days on average) relative to CSIF data. This implies that actual periods for photosynthetic activity are shorter (by 21.6 days on average) than those estimated from vegetation indices more directly related to changes in canopy structure. These large differences between results from NDVI and that from CSIF suggest that vegetation indices such as NDVI seem to overestimate the period for active photosynthesis over the extratropical Northern Hemisphere. Furthermore, while phenology of the early growing season is dominated by temperature for both NDVI and CSIF data, phenology of the late growing season is mainly controlled by temperature for NDVI but by precipitation for CSIF. Our findings were further confirmed by other SIF (GOME-2 SIF) and vegetation index (MODIS EVI) datasets. Phenology modes in Earth system modelling are often parameterized using leaf unfolding and senescence from either station or satellite observations. Our results imply that canopy structure-based parameterization schemes may have overestimated photosynthesis active period, and thus productivity responses. We conclude that SIF data offers a novel and unique approach for assessing phenological change - one that is more directly tied to the carbon cycle and how it is being influenced by climate change. [ABSTRACT FROM AUTHOR]

• The influence of PAR on LUE and SIFyield for maize was investigated. • A hyperbolic function response model for LUE to PAR was built for maize. • SIFyield was proven less sensitive to PAR than LUE is for unstressed maize. Solar-induced chlorophyll fluorescence (SIF) has been shown to be an ideal indicator of vegetation gross primary productivity (GPP), but the variation in the ratio of the photosynthetic light use efficiency (LUE = GPP/APAR) to the total SIF quantum yield (SIF yield = SIF total /APAR) is an important source of uncertainty in SIF‒GPP models. Incident radiation is one of the key factors influencing LUE and SIF yield. In this study, to investigate the influence of PAR on LUE and SIF yield , pulse-amplitude-modulated (PAM) fluorometry was carried out at the leaf level along with tower-based continuous SIF‒GPP measurements at the canopy level for maize. LUE was found to decrease as PAR increased, following a hyperbolic function, at both the leaf level (R2 = 0.978) and canopy level (R2 = 0.460 for half-hourly averaged dataset; R2 = 0.341 for daily averaged dataset). However, the variation of SIF yield with PAR was found to be very small. By integrating the influence of PAR on LUE, the GPP estimation model based on the red band and near-infrared (NIR) band SIF for maize became more linear. For both the half-hourly and daily datasets, the values of R2 for the SIF-GPP model increased (e.g. from 0.573 to 0.718 for the half-hourly NIR band SIF), and the RMSE for the estimated GPP reduced (e.g. from 8.30 to 6.75 μmol CO 2 m−2 s−1 for the half-hourly NIR band SIF). These results highlight that the ratio of LUE to SIF yield is an important source of uncertainty in SIF‒GPP models and should be carefully corrected. The results also show that PAR is a key factor influencing this ratio. This PAR-based LUE model can be integrated not only in SIF‒GPP models but also in other LUE-related GPP estimation models for unstressed maize. [ABSTRACT FROM AUTHOR]

• An approach for coupling BEPS and SCOPE was presented. • The BEPS-SCOPE coupling model provided an efficient solution for regional/global SIF and GPP simulations. • Performance of the coupling model was assessed by compared with the GOME-2 SIF and the SCOPE model. • The factors that mostly affect the fluorescence upscaling process from leaf to canopy were assessed. Remotely sensed solar-induced chlorophyll fluorescence (SIF) has been increasingly used to probe photosynthesis and model the gross primary productivity (GPP). Although SIF at the top of canopy (TOC) can be simulated using the coupled photosynthesis-fluorescence model SCOPE (Soil Canopy Observation, Photochemistry and Energy fluxes), simulating spatially distributed TOC SIF usually requires extensive calculations, entailing some challenges when applying the model to the regional and the global scales. This study puts forward a coupling framework that combines SIF and global terrestrial biosphere models (TBMs). The theory for fluorescence emissions and the fluorescence radiative transfer algorithm described in the SCOPE model were integrated with the "two-leaf"-based BEPS (Boreal Ecosystem Productivity Simulator) model. To simplify the fluorescence radiative transfer physics, we put forward a canopy-averaged leaf-level fluorescence to represent the fluorescence emitted from sunlit and shaded leaf groups and performed a sensitivity analysis to assess the determining factors in upscaling fluorescence from leaf scale to canopy scale. We found that the relationship between the leaf and canopy fluorescence at 740 nm was mainly affected by LAI. Although brown pigments and leaf inclination angle demonstrate some impacts on the scaling process, an LAI-based coefficient can well characterize the upscaling from leaf to canopy scale. Since our BEPS-SCOPE coupling model deploys the sunlit-shaded leaf separation strategy, we expect that it can efficiently characterize the nonlinear responses of photosynthesis and the associated fluorescence to environmental factors. The performance of our model was evaluated at both site and global scales, which demonstrated a good performance for most plant functional types (PFTs) except for needleleaf types that have a more clumped nature. Apart from these limitations, the presented model can contribute to efficiently simulating SIF at regional and global scales, and has the potential to reduce uncertainties in GPP estimation. [ABSTRACT FROM AUTHOR]

• A novel unmanned aerial system with bi-hemispherical spectral acquisition. • Simultaneous solar-induced chlorophyll fluorescence and hyperspectral reflectance. • Emulates and correlates well with a tower system, enabling synergistic application. • Characterizes seasonal and diurnal dynamics of crop photosynthetic activity. Unmanned aerial system (UAS)-based remote sensing can provide high spatial- and temporal-resolution crop monitoring for precision management. Existing crop monitoring UAS primarily use conventional techniques such as multi-spectral broadband vegetation indices (VIs) to track canopy structure/biomass. Recently developed lightweight hyperspectral sensors can track crop physiology and performance via complementary signals such as solar-induced chlorophyll fluorescence (SIF) and photochemical reflectance index (PRI) that can be derived from hyperspectral reflectance. However, few existing UAS can acquire high-quality SIF and hyperspectral reflectance. We designed a novel UAS that simultaneously captures far-red SIF and hyperspectral reflectance, using a single bifurcated fiber and motorized arm to measure downwelling and upwelling irradiance. The UAS was tested over (1) a heterogeneous corn field with spatially varying crop yield potential and (2) a set of soybean and corn plots under differing nutrient treatments. Our UAS can maintain stability under low-to-moderate winds (2–3 m/s) with <0.4 m geolocation accuracy, <0.1 m altitude drift, and <1.5° error of the fiber optic from nadir position during scanning. Weekly seasonal campaigns reveal that SIF outperforms conventional VIs such as the normalized difference vegetation index (NDVI) for distinguishing plots with different crop yield potential, especially after canopy closure when NDVI tends to saturate. The UAS can capture the diurnal dynamics of SIF and PRI for both corn and soybean. At the seasonal scale, SIF acquired from the UAS correlates well with that from a fixed SIF tower system (R 2 = 0.81), which measured the same target albeit with different footprints, demonstrating the capability of UAS in characterizing the seasonal progression of crop activity. In conclusion, our newly developed UAS provides high-quality SIF and hyperspectral reflectance, facilitating mechanistic understanding of the physiological control on photosynthesis dynamics. Our findings also imply that this UAS could enable extension of fixed tower-based systems to monitor multiple targets from diurnal to seasonal scales and improve monitoring of heterogeneous fields. [ABSTRACT FROM AUTHOR]

• A simple method to estimate SIF emission at the photosystem level is proposed. • Only canopy BRF and NDVI are needed for SIF downscaling at the red and NIR bands. • Red-band SIF at the photosystem level has great potential for monitoring GPP. Numerous studies have proved that solar-induced chlorophyll fluorescence (SIF) is a good proxy of gross primary production (GPP). The SIF spectrum covers the spectral window from about 640 nm to 850 nm. Due to the strong chlorophyll absorption effect at the red band, the red SIF is much more influenced by the radiative transfer effect inside the canopy than the near infrared (NIR) SIF is. Therefore, at the canopy level, the NIR SIF shows more potential for use in estimating GPP. However, the red-band SIF contains more information about PS II, which is more sensitive to photosynthesis. So, in theory, if the canopy radiative transfer effect could be corrected for, the potential of the red SIF for estimating GPP would be greatly improved. In this paper, we propose a new simple reflectance-based method for estimating the photosystem-level SIF at both the NIR band and the red band. Long-term observations of SIF and GPP at two crop sites in two years (four datasets in total) were used to investigate the SIF−GPP relationship at the canopy or photosystem level. The SIF downscaled by the simple reflectance-based approach is found to be consistent with that found using the random forest regression method proposed formerly. For the NIR band, the performance of the canopy-level SIF and PS-level SIF for GPP estimation is similar while, for the red band, the correlation between the SIF and GPP is greatly improved after downscaling the canopy-level SIF to the PS level. For the four test datasets, at the red band, the values of R 2 for the SIF−GPP relationship increase from 0.213−0.599 to 0.398−0.759 after the downscaling. At the PS level, the performance of the red SIF for GPP estimation is as good as or even better than that of the NIR-band SIF. The results of this study indicate that estimation of the SIF photosystem level to canopy level escape probability is important, and that more importance should be paid to the red-band SIF in the monitoring of GPP. [ABSTRACT FROM AUTHOR]