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For decades, the dynamic nature of chlorophyll a fluorescence (ChlaF) has provided insight into the biophysics and ecophysiology of the light reactions of photosynthesis from the subcellular to leaf scales. Recent advances in remote sensing methods enable detection of ChlaF induced by sunlight across a range of larger scales, from using instruments mounted on towers above plant canopies to Earth-orbiting satellites. This signal is referred to as solar-induced fluorescence (SIF) and its application promises to overcome spatial constraints on studies of photosynthesis, opening new research directions and opportunities in ecology, ecophysiology, biogeochemistry, agriculture and forestry. However, to unleash the full potential of SIF, intensive cross-disciplinary work is required to harmonize these new advances with the rich history of biophysical and ecophysiological studies of ChlaF, fostering the development of next-generation plant physiological and Earth-system models. Here, we introduce the scale-dependent link between SIF and photosynthesis, with an emphasis on seven remaining scientific challenges, and present a roadmap to facilitate future collaborative research towards new applications of SIF., (© 2021. Springer Nature Limited.)

The interaction of plants with their environment is very dynamic. Studying the underlying processes is important for understanding and modeling plant response to changing environmental conditions. Photosynthesis varies largely between different plants and at different locations within a canopy of a single plant. Thus, continuous and spatially distributed monitoring is necessary to assess the dynamic response of photosynthesis to the environment. Limited scale of observation with portable instrumentation makes it difficult to examine large numbers of plants under different environmental conditions. We report here on the application of a recently developed technique, laser-induced fluorescence transient (LIFT), for continuous remote measurement of photosynthetic efficiency of selected leaves at a distance of up to 50 m. The ability to make continuous, automatic, and remote measurements of photosynthetic efficiency of leaves with the LIFT provides a new approach for studying the interaction of plants with the environment and may become an important tool in phenotyping photosynthetic properties in field applications.

In the context of climate change and global sustainable development goals, future wheat cultivation has to master various challenges at a time, including the rising atmospheric carbon dioxide concentration ([CO2]). To investigate growth and photosynthesis dynamics under the effects of ambient (-434 ppm) and elevated [CO2] (-622 ppm), a Free-Air CO2 Enrichment (FACE) facility was combined with an automated phenotyping platform and an array of sensors. Ten modern winter wheat cultivars (Triticum aestivum L.) were monitored over a vegetation period using a Light-induced Fluorescence Transient (LIFT) sensor, ground-based RGB cameras and a UAV equipped with an RGB and multispectral camera. The LIFT sensor enabled a fast quantification of the photosynthetic performance by measuring the operating efficiency of Photosystem II (Fq'/Fm') and the kinetics of electron transport, i.e. the reoxidation rates Fr1' and Fr2'. Our results suggest that elevated [CO2] significantly increased Fq'/Fm' and plant height during the vegetative growth phase. As the plants transitioned to the senescence phase, a pronounced decline in Fq'/Fm' was observed under elevated [CO2]. This was also reflected in the reoxidation rates Fr1' and Fr2'. A large majority of the cultivars showed a decrease in the harvest index, suggesting a different resource allocation and indicating a potential plateau in yield progression under e[CO2]. Our results indicate that the rise in atmospheric [CO2] has significant effects on the cultivation of winter wheat with strong manifestation during early and late growth. [ABSTRACT FROM AUTHOR]

Summary: Sun‐induced fluorescence in the far‐red region (SIF) is increasingly used as a remote and proximal‐sensing tool capable of tracking vegetation gross primary production (GPP). However, the use of SIF to probe changes in GPP is challenged during extreme climatic events, such as heatwaves.Here, we examined how the 2018 European heatwave (HW) affected the GPP–SIF relationship in evergreen broadleaved trees with a relatively invariant canopy structure. To do so, we combined canopy‐scale SIF measurements, GPP estimated from an eddy covariance tower, and active pulse amplitude modulation fluorescence.The HW caused an inversion of the photosynthesis–fluorescence relationship at both the canopy and leaf scales. The highly nonlinear relationship was strongly shaped by nonphotochemical quenching (NPQ), that is, a dissipation mechanism to protect from the adverse effects of high light intensity. During the extreme heat stress, plants experienced a saturation of NPQ, causing a change in the allocation of energy dissipation pathways towards SIF.Our results show the complex modulation of the NPQ–SIF–GPP relationship at an extreme level of heat stress, which is not completely represented in state‐of‐the‐art coupled radiative transfer and photosynthesis models. [ABSTRACT FROM AUTHOR]

Summary: Solar‐induced fluorescence (SIF) is highly relevant in mapping photosynthesis from remote‐sensing platforms. This requires linking SIF to photosynthesis and understanding the role of nonphotochemical quenching (NPQ) mechanisms under field conditions. Hence, active and passive fluorescence were measured in Arabidopsis with altered NPQ in outdoor conditions.Plants with mutations in either violaxanthin de‐epoxidase (npq1) or PsbS protein (npq4) exhibited reduced NPQ capacity. Parallel measurements of NPQ, photosystem II efficiency, SIF and spectral reflectance (ρ) were conducted diurnally on one sunny summer day and two consecutive days during a simulated cold spell.Results showed that both npq mutants exhibited higher levels of SIF compared to wild‐type plants. Changes in reflectance were related to changes in the violaxanthin–antheraxanthin–zeaxanthin cycle and not to PsbS‐mediated conformational changes. When plants were exposed to cold temperatures, rapid onset of photoinhibition strongly quenched SIF in all lines.Using well‐characterized Arabidopsisnpq mutants, we showed for the first time the quantitative link between SIF, photosynthetic efficiency, NPQ components and leaf reflectance. We discuss the functional potential and limitations of SIF and reflectance measurements for estimating photosynthetic efficiency and NPQ in the field. [ABSTRACT FROM AUTHOR]

In November 2015, the FLuorescence EXplorer (FLEX) was selected as the eighth Earth Explorer mission of the European Space Agency. The tandem mission concept will provide measurements at a spectral and spatial resolution enabling the retrieval and interpretation of the full chlorophyll fluorescence spectrum emitted by the terrestrial vegetation. This paper provides a mission concept overview of the scientific goals, the key objectives related to fluorescence, and the requirements guaranteeing the fitness for purpose of the resulting scientific data set. We present the mission design at the time of selection, i.e., at the end of project phase Phase A/B1, as developed by two independent industrial consortia. The mission concepts both rely on a single payload Fluorescence Imaging Spectrometer, covering the spectral range from 500 to 780 nm. In the oxygen absorption bands, its spectral resolution will be 0.3 nm with a spectral sampling interval of 0.1 nm. The swath width of the spectrometer is 150 km and the spatial resolution will be 300 \times 300~\textm^2 . The satellite will fly in tandem with Sentinel-3 providing different and complementary measurements with a temporal collocation of 6 to 15 s. The FLEX launch is scheduled for 2022. [ABSTRACT FROM AUTHOR]

Measurements of sun-induced chlorophyll fluorescence (SIF) over plant canopies provide a proxy for plant photosynthetic capacity and are of high interest for plant research. Together with spectral reflectance, SIF has the potential to act as a noninvasive approach to quantify photosynthetic plant traits from field to air and spaceborne scales. However, SIF is a small signal contribution to the reflected sunlight and often not distinguishable from sensor noise. SIF estimation is, therefore, affected by an unquantified uncertainty, making it difficult to estimate accurately how much SIF is truly emitted from the plant. To investigate and overcome this, we designed a device based on a spectrometer covering the visible range and equipped it with an LED emitting at the wavelength of SIF. Using this as a reference and applying thorough calibrations, we present consistent evidence of the instrument’s capability of SIF retrieval and accuracy estimations. The LED’s intensity was measured under sunlight with 1.27 \pm 0.27\textrm mW\times \textrm sr^-1\textm^-2 nm ^-1 stable over the day. The large increase of SIF due to the Kautsky effect was measured spectrally and temporally proving the biophysical origin of the signal. We propose rigorous tests for instruments intended to measure SIF and show ways to further improve the presented methods. [ABSTRACT FROM PUBLISHER]

The photosynthesis of various species or even a single plant varies dramatically in time and space, creating great spatial heterogeneity within a plant canopy. Continuous and spatially explicit monitoring is, therefore, required to assess the dynamic response of plant photosynthesis to the changing environment. This is a very challenging task when using the existing portable field instrumentation. This paper reports on the application of a technique, laser-induced fluorescence transient (LIFT), developed for ground remote measurement of photosynthetic efficiency at a distance of up to 50 m. The LIFT technique was used to monitor the seasonal dynamics of selected leaf groups within inaccessible canopies of deciduous and evergreen tree species. Electron transport rates computed from LIFT measurements varied over the growth period between the different species studied. The LIFT canopy data and light-use efficiency measured under field conditions correlated reasonably well with the single-leaf pulse amplitude-modulated measurements of broadleaf species, but differed significantly in the case of conifer tree species. The LIFT method has proven to be applicable for a remote sensing assessment of photosynthetic parameters on a diurnal and seasonal scale; further investigation is, however, needed to evaluate the influence of complex heterogeneous canopy structures on LIFT-measured chlorophyll fluorescence parameters. [ABSTRACT FROM AUTHOR]

Terrestrial gross primary production (GPP) is an important parameter to explore and quantify carbon fixation by plant ecosystems at various scales. Remote sensing (RS) offers a unique possibility to investigate GPP in a spatially explicit fashion; however, budgeting of terrestrial carbon cycles based on this approach still remains uncertain. To improve calculations, spatio-temporal variability of GPP must be investigated in more detail on local and regional scales. The overarching goal of this study is to enhance our knowledge on how environmentally induced changes of photosynthetic light-use efficiency (LUE) are linked with optical RS parameters. Diurnal courses of sun-induced fluorescence yield ( FSyield) and the photochemical reflectance index of corn were derived from high-resolution spectrometric measurements and their potential as proxies for LUE was investigated. GPP was modeled using Monteith's LUE-concept and optical-based GPP and LUE values were compared with synoptically acquired eddy covariance data. It is shown that the diurnal response of complex physiological regulation of photosynthesis can be tracked reliably with the sun-induced fluorescence. Considering structural and physiological effects, this research shows for the first time that including sun-induced fluorescence into modeling approaches improves their results in predicting diurnal courses of GPP. Our results support the hypothesis that air- or spaceborne quantification of sun-induced fluorescence yield may become a powerful tool to better understand spatio-temporal variations of fluorescence yield, photosynthetic efficiency and plant stress on a global scale. [ABSTRACT FROM AUTHOR]

Determining the spatial and temporal diversity of photosynthetic processes in forest canopies presents a challenge to the evaluation of biological feedbacks needed for improvement of carbon and climate models. Limited access with portable instrumentation, especially in the outer canopy, makes remote sensing of these processes a priority in experimental ecosystem and climate change research. Here, we describe the application of a new, active, chlorophyll fluorescence measurement system for remote sensing of light use efficiency, based on analysis of laser-induced fluorescence transients (LIFT). We used mature stands of Populus grown at ambient (380 ppm) and elevated CO2 (1220 ppm) in the enclosed agriforests of the Biosphere 2 Laboratory (B2L) to compare parameters of photosynthetic efficiency, photosynthetic electron transport, and dissipation of excess light measured by LIFT and by standard on-the-leaf saturating flash methods using a commercially available pulse-modulated chlorophyll fluorescence instrument (Mini-PAM). We also used LIFT to observe the diel courses of these parameters in leaves of two tropical forest dominants, Inga and Pterocarpus, growing in the enclosed model tropical forest of B2L. Midcanopy leaves of both trees showed the expected relationships among chlorophyll fluorescence-derived photosynthetic parameters in response to sun exposure, but, unusually, both displayed an afternoon increase in nonphotochemical quenching in the shade, which was ascribed to reversible inhibition of photosynthesis at high leaf temperatures in the enclosed canopy. Inga generally showed higher rates of photosynthetic electron transport, but greater afternoon reduction in photosynthetic efficiency. The potential for estimation of the contribution of outer canopy photosynthesis to forest CO2 assimilation, and assessment of its response to environmental stress using remote sensing devices such as LIFT, is briefly discussed. [ABSTRACT FROM AUTHOR]

In this study, we are testing a proxy for red and far-red Sun-induced fluorescence (SIF) using an integrated fuzzy logic modelling approach, termed as SIFfuzzy and SIFfuzzy-APAR. The SIF emitted from the core of the photosynthesis and observed at the top-of-canopy is regulated by three major controlling factors: (1) light interception and absorption by canopy plant cover; (2) escape fraction of SIF photons (fesc); (3) light use efficiency and non-photochemical quenching (NPQ) processes. In our study, we proposed and validated a fuzzy logic modelling approach that uses different combinations of spectral vegetation indices (SVIs) reflecting such controlling factors to approximate the potential SIF signals at 760 nm and 687 nm. The HyPlant derived and field validated SVIs (i.e., SR, NDVI, EVI, NDVIre, PRI) have been processed through the membership transformation in the first stage, and in the next stage the membership transformed maps have been processed through the Fuzzy Gamma simulation to calculate the SIFfuzzy. To test whether the inclusion of absorbed photosynthetic active radiation (APAR) increases the accuracy of the model, the SIFfuzzy was multiplied by APAR (SIFfuzzy-APAR). The agreement between the modelled SIFfuzzy and actual SIF airborne retrievals expressed by R2 ranged from 0.38 to 0.69 for SIF760 and from 0.85 to 0.92 for SIF687. The inclusion of APAR improved the R2 value between SIFfuzzy-APAR and actual SIF. This study showed, for the first time, that a diverse set of SVIs considered as proxies of different vegetation traits, such as biochemical, structural, and functional, can be successfully combined to work as a first-order proxy of SIF. The previous studies mainly included the far-red SIF whereas, in this study, we have also focused on red SIF along with far-red SIF. The analysis carried out at 1 m spatial resolution permits to better infer SIF behaviour at an ecosystem-relevant scale. [ABSTRACT FROM AUTHOR]

Sun-Induced fluorescence at 760 nm (F760) is increasingly being used to predict gross primary production (GPP) through light use efficiency (LUE) modeling, even though the mechanistic processes that link the two are not well understood. We analyzed the effect of nitrogen (N) and phosphorous (P) availability on the processes that link GPP and F760 in a Mediterranean grassland manipulated with nutrient addition. To do so, we used a combination of process-based modeling with Soil-Canopy Observation of Photosynthesis and Energy (SCOPE), and statistical analyses such as path modeling. With this study, we uncover the mechanisms that link the fertilization-driven changes in canopy nitrogen concentration (N%) to the observed changes in F760 and GPP. N addition changed plant community structure and increased canopy chlorophyll content, which jointly led to changes in photosynthetic active radiation (APAR), ultimately affecting both GPP and F760. Changes in the abundance of graminoids, (%graminoids) driven by N addition led to changes in structural properties of the canopy such as leaf angle distribution, that ultimately influenced observed F760 by controlling the escape probability of F760 (Fesc). In particular, we found a change in GPP–F760 relationship between the first and the second year of the experiment that was largely driven by the effect of plant type composition on Fesc, whose best predictor is %graminoids. The P addition led to a statistically significant increase on light use efficiency of fluorescence emission (LUEf), in particular in plots also with N addition, consistent with leaf level studies. The N addition induced changes in the biophysical properties of the canopy that led to a trade-off between surface temperature (Ts), which decreased, and F760 at leaf scale (F760leaf,fw), which increased. We found that Ts is an important predictor of the light use efficiency of photosynthesis, indicating the importance of Ts in LUE modeling approaches to predict GPP. [ABSTRACT FROM AUTHOR]

Hyperspectral remote sensing (RS) provides unique possibilities to monitor peatland vegetation traits and their temporal dynamics at a fine spatial scale. Peatlands provide a vital contribution to ecosystem services by their massive carbon storage and wide heterogeneity. However, monitoring, understanding, and disentangling the diverse vegetation traits from a heterogeneous landscape using complex RS signal is challenging, due to its wide biodiversity and distinctive plant species composition. In this work, we aim to demonstrate, for the first time, the large heterogeneity of peatland vegetation traits using well-established vegetation indices (VIs) and Sun-Induced Fluorescence (SIF) for describing the spatial heterogeneity of the signals which may correspond to spatial diversity of biochemical and structural traits. SIF originates from the initial reactions in photosystems and is emitted at wavelengths between 650–780 nm, with the first peak at around 687 nm and the second peak around 760 nm. We used the first HyPlant airborne data set recorded over a heterogeneous peatland area and its surrounding ecosystems (i.e., forest, grassland) in Poland. We deployed a comparative analysis of SIF and VIs obtained from differently managed and natural vegetation ecosystems, as well as from diverse small-scale peatland plant communities. Furthermore, spatial relationships between SIF and VIs from large-scale vegetation ecosystems to small-scale peatland plant communities were examined. Apart from signal variations, we observed a positive correlation between SIF and greenness-sensitive VIs, whereas a negative correlation between SIF and a VI sensitive to photosynthesis was observed for large-scale vegetation ecosystems. In general, higher values of SIF were associated with higher biomass of vascular plants (associated with higher Leaf Area Index (LAI)). SIF signals, especially SIF760, were strongly associated with the functional diversity of the peatland vegetation. At the peatland area, higher values of SIF760 were associated with plant communities of high perennials, whereas, lower values of SIF760 indicated peatland patches dominated by Sphagnum. In general, SIF760 reflected the productivity gradient on the fen peatland, from Sphagnum-dominated patches with the lowest SIF and fAPAR values indicating lowest productivity to the Carex-dominated patches with the highest SIF and fAPAR values indicating highest productivity. [ABSTRACT FROM AUTHOR]

Imaging and non-imaging spectroscopy employed in the field and from aircraft is frequently used to assess biochemical, structural, and functional plant traits, as well as their dynamics in an environmental matrix. With the increasing availability of high-resolution spectroradiometers, it has become feasible to measure fine spectral features, such as those needed to estimate sun-induced chlorophyll fluorescence (F), which is a signal related to the photosynthetic process of plants. The measurement of F requires highly accurate and precise radiance measurements in combination with very sophisticated measurement protocols. Additionally, because F has a highly dynamic nature (compared with other vegetation information derived from spectral data) and low signal intensity, several environmental, physiological, and experimental aspects have to be considered during signal acquisition and are key for its reliable interpretation. The European Cooperation in Science and Technology (COST) Action ES1309 OPTIMISE has produced three articles addressing the main challenges in the field of F measurements. In this paper, which is the second of three, we review approaches that are available to measure F from the leaf to the canopy scale using ground-based and airborne platforms. We put specific emphasis on instrumental aspects, measurement setups, protocols, quality checks, and data processing strategies. Furthermore, we review existing techniques that account for atmospheric influences on F retrieval, address spatial scaling effects, and assess quality checks and the metadata and ancillary data required to reliably interpret retrieved F signals. [ABSTRACT FROM AUTHOR]

Plant phenotyping is an emerging discipline in plant biology. Quantitative measurements of functional and structural traits help to better understand gene-environment interactions and support breeding for improved resource use efficiency of important crops such as bean (Phaseolus vulgaris L.). Here we provide an overview of state-of-the-art phenotyping approaches addressing three aspects of resource use efficiency in plants: belowground roots, aboveground shoots and transport/allocation processes. We demonstrate the capacity of high-precision methods to measure plant function or structural traits non-invasively, stating examples wherever possible. Ideally, high-precision methods are complemented by fast and high-throughput technologies. High-throughput phenotyping can be applied in the laboratory using automated data acquisition, as well as in the field, where imaging spectroscopy opens a new path to understand plant function non-invasively. For example, we demonstrate how magnetic resonance imaging (MRI) can resolve root structure and separate root systems under resource competition, how automated fluorescence imaging (PAM fluorometry) in combination with automated shape detection allows for high-throughput screening of photosynthetic traits and how imaging spectrometers can be used to quantify pigment concentration, sun-induced fluorescence and potentially photosynthetic quantum yield. We propose that these phenotyping techniques, combined with mechanistic knowledge on plant structure-function relationships, will open new research directions in whole-plant ecophysiology and may assist breeding for varieties with enhanced resource use efficiency varieties. [ABSTRACT FROM AUTHOR]

Many laboratory studies investigating chlorophyll fluorescence (F) of plants have provided sufficient evidence of the functional link between dynamic changes in photosynthetic activity and F emissions. Far fewer studies, however, have been devoted to detailed analysis of F emission under steady-state conditions, which may be amenable to measurement by passive spectroradiometers onboard airborne or satellite missions. Here, we provide a random-effects meta-analysis of studies using both passively (sun-induced) and actively (e.g. laser-induced) measured steady-state F for detecting stress reactions in terrestrial vegetation. Specifically, we review behaviour of F in red and far-red wavelengths, and also the red to far-red F ratio, for plants physiologically stressed by water deficit, temperature extremes, and nitrogen insufficiency. Results suggest that water stress is, in general, associated with a decline in red and far-red F signal intensity measured at both leaf and canopy levels, whereas the red to far-red F ratio displays an inconsistent behaviour. Chilling, for which only studies with active measurements at the leaf level are available, significantly increased red and far-red F, whereas heat stress produced a less convincing decrease in both F emissions, notably in canopies measured passively. The clearest indicator of temperature stress was the F ratio, which declined significantly and consistently. The F ratio was also the strongest indicator of nitrogen deficiency, revealing a nearly uniformly increasing pattern driven by predominantly declining far-red F. Although significant knowledge gaps were encountered for certain scales and F measurement techniques, the analyses indicate that future airborne or space-borne acquisitions of both red and far-red F signals would be beneficial for timely detection of plant stress events. [ABSTRACT FROM AUTHOR]

• Fluorescence and photosynthesis were not linearly related across a phosphorus gradient. • Quantum use efficiency (Φ PSII) could not be predicted from fluorescence yield alone. • Pigment corrected PRI and fluorescence ratio allowed to estimate Φ PSII at leaf level. 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 (Φ PSII), can be estimated by the fluorescence efficiency parameters, APAR normalized fluorescence (F yield) 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 Φ PSII and F yield is non-monotonic across a P limitation gradient, rendering the prediction of Φ PSII by F yield alone unfeasible. We show, however, that the pigment corrected PRI (cPRI) and F ↑ratio (cF ↑ratio) share a strong linear relationship with Φ PSII , thereby enabling the estimation of Φ PSII. We demonstrate that a compensation for reabsorption effects improved the estimation of Φ PSII by F ratio at foliar level. This may allow improved predictions of photosynthetic light use efficiency parameters without the need of measuring green APAR. [ABSTRACT FROM AUTHOR]

The upcoming Fluorescence Explorer (FLEX) satellite mission aims to provide high quality radiometric measurements for subsequent retrieval of sun-induced chlorophyll fluorescence (SIF). The combination of SIF with other observations stemming from the FLEX/Sentinel-3 tandem mission holds the potential to assess complex ecosystem processes. The calibration and validation (cal/val) of these radiometric measurements and derived products are central but challenging components of the mission. This contribution outlines strategies for the assessment of in situ radiometric measurements and retrieved SIF. We demonstrate how in situ spectrometer measurements can be analysed in terms of radiometric, spectral and spatial uncertainties. The analysis of more than 200 k spectra yields an average bias between two radiometric measurements by two individual spectrometers of 8%, with a larger variability in measurements of downwelling radiance (25%) compared to upwelling radiance (6%). Spectral shifts in the spectrometer relevant for SIF retrievals are consistently below 1 spectral pixel (up to 0.75). Found spectral shifts appear to be mostly dependent on temperature (as measured by a temperature probe in the instrument). Retrieved SIF shows a low variability of 1.8% compared with a noise reduced SIF estimate based on APAR. A combination of airborne imaging and in situ non-imaging fluorescence spectroscopy highlights the importance of a homogenous sampling surface and holds the potential to further uncover SIF retrieval issues as here shown for early evening acquisitions. Our experiments clearly indicate the need for careful site selection, measurement protocols, as well as the need for harmonized processing. This work thus contributes to guiding cal/val activities for the upcoming FLEX mission. • Spectral, radiometric and SIF retrieval-related uncertainties are explored. • The investigated sources of uncertainty are relevant for SIF cal/val activities. • This work contributes to the design and implementation of SIF cal/val networks. • A thorough design of site infrastructure and analysis capability is important. • Spatial heterogeneity is a crucial aspect in SIF mission cal/val. [ABSTRACT FROM AUTHOR]

Abstract: Chlorophyll fluorescence is related to photosynthesis and can serve as a remote sensing proxy for estimating photosynthetic energy conversion and carbon uptake. Recent advances in sensor technology allow remote measurements of the sun-induced chlorophyll fluorescence signal (Fs) at leaf and canopy scale. The commonly used Fraunhofer Line Depth (FLD) principle exploits spectrally narrow atmospheric oxygen absorption bands and relates Fs to the difference of the absorption feature depth of a fluorescensing and a non-fluorescensing surface. However, due to the nature of these narrow bands, Fs retrieval results depend not only on vegetation species type or environmental conditions, but also on instrument technology and processing algorithms. Thus, an evaluation of all influencing factors and their separate quantification is required to further improve Fs retrieval and to allow a reproducible interpretation of Fs signals. Here we present a modeling study that isolates and quantifies the impacts of sensor characteristics, such as spectral sampling interval (SSI), spectral resolution (SR), signal to noise ratio (SNR), and spectral shift (SS) on the accuracy of Fs measurements in the oxygen A band centered at 760nm (O2-A). Modeled high resolution radiance spectra associated with known Fs were spectrally resampled, taking into consideration the various sensor properties. Fs was retrieved using the three most common FLD retrieval methods, namely the original FLD method (sFLD), the modified FLD (3FLD) and the improved FLD (iFLD). The analysis investigates parameter ranges, which are representative for field and airborne instruments currently used in Fs research (e.g., ASD FieldSpec, OceanOptics HR, AirFLEX, AISA, APEX, CASI, and MERIS). Our results show that the most important parameter affecting the retrieval accuracy is SNR, SR accounts for≤40% of the error, the SSI for≤12%, and SS for≤7% of the error. A trade-off study revealed that high SR can partly compensate for low SNR. There is a strong interrelation between all parameters and the impact of specific parameters can compensate or amplify the influence of others. Hence, the combination of all parameters must be considered by the evaluation of sensors and their potential for Fs retrieval. In general, the standard FLD method strongly overestimates Fs, while 3FLD and iFLD provide a more accurate estimation of Fs. We conclude that technical sensor specifications and the retrieval methods cause a significant variability in retrieved Fs signals. Results are intended to be one relevant component of the total uncertainty budget of Fs retrieval and have to be considered in the interpretation of retrieved Fs signals. [Copyright &y& Elsevier]

Abstract: The frequency of extreme drought events is projected to increase under global climate change, causing damage to plants and crop yield despite potential acclimation. We investigated whether grasses remain acclimated to drought even after a harvest and remember early summer drought exposure over a whole vegetation period. For this, we compared the response of Arrhenatherum elatius plants under a second, late, drought (they were pre-exposed to an early drought before), to plants exposed to a single, only late, extreme drought. Surprisingly, the percentage of living biomass after a late drought increased for plants that were exposed to drought earlier in the growing season compared to single-stressed plants, even after harvest and resprouting after the first drought. Relative leaf water content did not differ between the two treatments. Net photosynthesis was non-significantly reduced by 25% in recurrent drought treatment. Maximum quantum efficiency (F v/F m) and maximum fluorescence (F m) were reduced in plants that were exposed to recurrent drought. These findings indicated improved photoprotection in double-stressed plants. Our results provide first hints towards a “drought memory” over an entire vegetation period, even after harvest and resprouting. However, the advantage of improved photoprotection might also cause reductions in photosynthesis that could have adverse effects on crop yield under more severe or longer droughts. [Copyright &y& Elsevier]

• Simulation reveals influences of PSF calibration procedure on signal deconvolution. • Deconvolving measured PSFs before deconvolving signals improves performance. • Classic Wiener filtering together with sharpened PSF yields best results. • Proposed deconvolution approach reduces error in SIF estimation by factor 3.8 We propose a signal deconvolution procedure for imaging spectrometer data, where a measured point spread function (PSF) is deconvolved itself before being used for deconvolution of the signal. We evaluate the effectiveness of our procedure for improvement of the spatio-spectral signal, as well as our target application, i.e. estimation of sun-induced fluorescence (SIF). Imaging spectrometers are well established instruments for remote sensing. When used for scientific purposes these instruments are usually calibrated on a regular basis. In our case the point spread function of the optics is measured in an elaborate procedure with a tunable monochromator point light source. PSFs are measured at different pixel positions of the imaging sensor, i.e. at different spatio-spectral locations, and averaged in order to get an as accurate PSF as possible. We investigate error sources in this calibration process by simulating the procedure in silico. Averaging as well as the spectral and spatial width of the point source introduce some smoothness in the measured PSF. We propose corrective measures, i.e. deconvolution of the PSF itself and median instead of mean averaging, leading to a set of sharper PSFs. We test the performance of these PSFs in deconvolving simulated as well as real hyperspectral images. For deconvolution we test a set of well-known, off the shelf deconvolution algorithms. Quantitatively in terms of PSNR (Peak Signal to Noise Ratio) a combination of Wiener filtering and sharpened PSFs yields strongest improvements, while using Wiener filtering with non-sharpened PSFs even deteriorates the signal. Comparing deconvolution results of the simulated data with results of real data reveals, that visually very similar effects can be observed. This well supports the assumption, that our findings are also valid for real spatio-spectral data. Surprisingly, the choice of PSF, sharpened or not, is of little effect for SIF estimation with the iFLD algorithm in the O 2 A band. Quantitatively we find that deconvolution reduces the overall error of SIF by a factor of 3.8, when using Wiener filtering instead of the currently used 1 iteration of vanCittert's method. For SIF estimation in the O 2 B band we observe a totally different behavior, where all deconvolution methods yield unreliable results with mostly well above 200% relative error and high standard deviations. In the discussion we can only speculate on possible reasons for this unreliability. As conclusion we therefore propose to use the O 2 A band for SIF estimation together with classic Wiener filtering for deconvolution of spatio-spectral data. [ABSTRACT FROM AUTHOR]

Plant functional diversity, defined as the range of plant chemical, physiological and structural properties within plants, is a key component of biodiversity which controls the ecosystem functioning and stability. Monitoring its variations across space and over time is critical in ecological studies. So far, several reflectance-based metrics have been tested to achieve this objective, yielding different degrees of success. Our work aimed at exploring the potential of a novel metric based on far-red sun-induced chlorophyll fluorescence (F 760) to map the functional diversity of terrestrial ecosystems. This was achieved exploiting high-resolution images collected over a mixed forest ecosystem with the HyPlant sensor, deployed as an airborne demonstrator of the forthcoming ESA-FLEX satellite. A reference functional diversity map was obtained applying the Rao's Q entropy metric on principal components calculated on key plant functional trait maps retrieved from the hyperspectral reflectance cube. Based on the spectral variation hypothesis, which states that the biodiversity signal is encoded in the spectral heterogeneity, two moving window-based approaches were tested to estimate the functional diversity from continuous spectral data: i) the Rao's Q entropy metric calculated on the normalized difference vegetation index (NDVI) and ii) the coefficient of variation (CV) calculated on hyperspectral reflectance. Finally, a third moving window approach was used to estimate the functional diversity based on F 760 heterogeneity quantified through the calculation of the Rao's Q entropy metric. Results showed a strong underestimation of the functional diversity using the Rao's Q index based on NDVI and the CV of reflectance. In both cases, a weak correlation was found against the reference functional diversity map (r2 = 0.05, p <.001 and r2 = 0.04, p <.001, respectively). Conversely, the Rao's Q index calculated on F 760 revealed similar patterns as the ones observed in the reference map and a better correlation (r2 = 0.5, p <.001). This corroborates the potential of far-red F for assessing the functional diversity of terrestrial ecosystems, opening unprecedented perspectives for biodiversity monitoring across different spatial and temporal scales. • Far-red fluorescence heterogeneity provides information on functional diversity. • Far-red fluorescence outperforms diversity measures based on NDVI heterogeneity. • Far-red fluorescence captures the spatial variability of functional traits (LCC, LMA). [ABSTRACT FROM AUTHOR]

Terrestrial gross primary productivity (GPP) plays an essential role in the global carbon cycle, but the quantification of the spatial and temporal variations in photosynthesis is still largely uncertain. Our work aimed to investigate the potential of remote sensing to provide new insights into plant photosynthesis at a fine spatial resolution. This goal was achieved by exploiting high-resolution images acquired with the FLuorescence EXplorer (FLEX) airborne demonstrator HyPlant. The sensor was flown over a mixed forest, and the images collected were elaborated to obtain two independent indicators of plant photosynthesis. First, maps of sun-induced chlorophyll fluorescence (F), a novel indicator of plant photosynthetic activity, were successfully obtained at both the red and far-red peaks (r2 = 0.89 and p < 0.01, r2 = 0.77 and p < 0.01, respectively, compared to top-of-canopy ground-based measurements acquired synchronously with the overflight) over the forested study area. Second, maps of GPP and absorbed photosynthetically active radiation (APAR) were derived using a customised version of the coupled biophysical model Breathing Earth System Simulator (BESS). The model was driven with airborne-derived maps of key forest traits (i.e., leaf chlorophyll content (LCC) and leaf area index (LAI)) and meteorological data providing a high-resolution snapshot of the variables of interest across the study site. The LCC and LAI were accurately estimated (RMSE = 5.66 μg cm−2 and RMSE = 0.51 m2 m−2, respectively) through an optimised Look-Up-Table-based inversion of the PROSPECT-4-INFORM radiative transfer model, ensuring the accurate representation of the spatial variation of these determinants of the ecosystem's functionality. The spatial relationships between the measured F and modelled BESS outputs were then analysed to interpret the variability of ecosystem functioning at a regional scale. The results showed that far-red F is significantly correlated with the GPP (r2 = 0.46, p < 0.001) and APAR (r2 = 0.43, p < 0.001) in the spatial domain and that this relationship is nonlinear. Conversely, no statistically significant relationships were found between the red F and the GPP or APAR (p > 0.05). The spatial relationships found at high resolution provide valuable insight into the critical role of spatial heterogeneity in controlling the relationship between the far-red F and the GPP, indicating the need to consider this heterogeneity at a coarser resolution. • High-resolution LCC and LAI maps were obtained from HyPlant through RTM inversion. • High-resolution GPP and APAR maps were obtained driving BESS with HyPlant data. • High-resolution F 687 and F 760 maps were obtained from HyPlant using SFM in a forest. • F 687 showed a non-significant relation with GPP and APAR in the spatial domain. • F 760 showed a positive nonlinear relation with GPP and APAR in the spatial domain. [ABSTRACT FROM AUTHOR]