Chlorophyll a fluorescence illuminates a path connecting plant molecular biology to Earth-system science.

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.

In vivo photoprotection mechanisms observed from leaf spectral absorbance changes showing VIS-NIR slow-induced conformational pigment bed changes.

Regulated heat dissipation under excessive light comprises a complexity of mechanisms, whereby the supramolecular light-harvesting pigment-protein complex (LHC) shifts state from light harvesting towards heat dissipation, quenching the excess of photo-induced excitation energy in a non-photochemical way. Based on whole-leaf spectroscopy measuring upward and downward spectral radiance fluxes, we studied spectrally contiguous (hyperspectral) transient time series of absorbance A(λ,t) and passively induced chlorophyll fluorescence F(λ,t) dynamics of intact leaves in the visible and near-infrared wavelengths (VIS-NIR, 400-800 nm) after sudden strong natural-like illumination exposure. Besides light avoidance mechanism, we observed on absorbance signatures, calculated from simultaneous reflectance R(λ,t) and transmittance T(λ,t) measurements as A(λ,t) = 1 - R(λ,t) - T(λ,t), major dynamic events with specific onsets and kinetical behaviour. A consistent well-known fast carotenoid absorbance feature (500-570 nm) appears within the first seconds to minutes, seen from both the reflected (backscattered) and transmitted (forward scattered) radiance differences. Simultaneous fast Chl features are observed, either as an increased or decreased scattering behaviour during quick light adjustment consistent with re-organizations of the membrane. The carotenoid absorbance feature shows up simultaneously with a major F decrease and corresponds to the xanthophyll conversion, as quick response to the proton gradient build-up. After xanthophyll conversion (t = 3 min), a kinetically slower but major and smooth absorbance increase was occasionally observed from the transmitted radiance measurements as wide peaks in the green (~ 550 nm) and the near-infrared (~ 750 nm) wavelengths, involving no further F quenching. Surprisingly, in relation to the response to high light, this broad and consistent VIS-NIR feature indicates a slowly induced absorbance increase with a sigmoid kinetical behaviour. In analogy to sub-leaf-level observations, we suggest that this mechanism can be explained by a structure-induced low-energy-shifted energy redistribution involving both Car and Chl. These findings might pave the way towards a further non-invasive spectral investigation of antenna conformations and their relations with energy quenching at the intact leaf level, which is, in combination with F measurements, of a high importance for assessing plant photosynthesis in vivo and in addition from remote observations.

Quantifying Vegetation Biophysical Variables from Imaging Spectroscopy Data: A Review on Retrieval Methods.

An unprecedented spectroscopic data stream will soon become available with forthcoming Earth-observing satellite missions equipped with imaging spectroradiometers. This data stream will open up a vast array of opportunities to quantify a diversity of biochemical and structural vegetation properties. The processing requirements for such large data streams require reliable retrieval techniques enabling the spatiotemporally explicit quantification of biophysical variables. With the aim of preparing for this new era of Earth observation, this review summarizes the state-of-the-art retrieval methods that have been applied in experimental imaging spectroscopy studies inferring all kinds of vegetation biophysical variables. Identified retrieval methods are categorized into: (1) parametric regression, including vegetation indices, shape indices and spectral transformations; (2) nonparametric regression, including linear and nonlinear machine learning regression algorithms; (3) physically based, including inversion of radiative transfer models (RTMs) using numerical optimization and look-up table approaches; and (4) hybrid regression methods, which combine RTM simulations with machine learning regression methods. For each of these categories, an overview of widely applied methods with application to mapping vegetation properties is given. In view of processing imaging spectroscopy data, a critical aspect involves the challenge of dealing with spectral multicollinearity. The ability to provide robust estimates, retrieval uncertainties and acceptable retrieval processing speed are other important aspects in view of operational processing. Recommendations towards new-generation spectroscopy-based processing chains for operational production of biophysical variables are given.

Variability and Uncertainty Challenges in Scaling Imaging Spectroscopy Retrievals and Validations from Leaves Up to Vegetation Canopies.

Imaging spectroscopy of vegetation requires methods for scaling and generalizing optical signals that are reflected, transmitted and emitted in the solar wavelength domain from single leaves and observed at the level of canopies by proximal sensing, airborne and satellite spectroradiometers. The upscaling embedded in imaging spectroscopy retrievals and validations of plant biochemical and structural traits is challenged by natural variability and measurement uncertainties. Sources of the leaf-to-canopy upscaling variability and uncertainties are reviewed with respect to: (1) implementation of retrieval algorithms and (2) their parameterization and validation of quantitative products through in situ field measurements. The challenges are outlined and discussed for empirical and physical leaf and canopy radiative transfer modelling components, considering both forward and inverse modes. Discussion on optical remote sensing validation schemes includes also description of a multiscale validation concept and its advantages. Impacts of intraspecific and interspecific variability on collected field and laboratory measurements of leaf biochemical traits and optical properties are demonstrated for selected plant species, and field measurement uncertainty sources are listed and discussed specifically for foliar pigments and canopy leaf area index. The review concludes with the main findings and suggestions as how to reduce uncertainties and include variability in scaling vegetation imaging spectroscopy signals and functional traits of single leaves up to observations of whole canopies.

Remote sensing of solar-induced chlorophyll fluorescence (SIF) in vegetation: 50 years of progress.

Remote sensing of solar-induced chlorophyll fluorescence (SIF) is a rapidly advancing front in terrestrial vegetation science, with emerging capability in space-based methodologies and diverse application prospects. Although remote sensing of SIF - especially from space - is seen as a contemporary new specialty for terrestrial plants, it is founded upon a multi-decadal history of research, applications, and sensor developments in active and passive sensing of chlorophyll fluorescence. Current technical capabilities allow SIF to be measured across a range of biological, spatial, and temporal scales. As an optical signal, SIF may be assessed remotely using highly-resolved spectral sensors and state-of-the-art algorithms to distinguish the emission from reflected and/or scattered ambient light. Because the red to far-red SIF emission is detectable non-invasively, it may be sampled repeatedly to acquire spatio-temporally explicit information about photosynthetic light responses and steady-state behaviour in vegetation. Progress in this field is accelerating with innovative sensor developments, retrieval methods, and modelling advances. This review distills the historical and current developments spanning the last several decades. It highlights SIF heritage and complementarity within the broader field of fluorescence science, the maturation of physiological and radiative transfer modelling, SIF signal retrieval strategies, techniques for field and airborne sensing, advances in satellite-based systems, and applications of these capabilities in evaluation of photosynthesis and stress effects. Progress, challenges, and future directions are considered for this unique avenue of remote sensing.

Error Budget for Geolocation of Spectroradiometer Point Observations from an Unmanned Aircraft System.

We investigate footprint geolocation uncertainties of a spectroradiometer mounted on an unmanned aircraft system (UAS). Two microelectromechanical systems-based inertial measurement units (IMUs) and global navigation satellite system (GNSS) receivers were used to determine the footprint location and extent of the spectroradiometer. Errors originating from the on-board GNSS/IMU sensors were propagated through an aerial data georeferencing model, taking into account a range of values for the spectroradiometer field of view (FOV), integration time, UAS flight speed, above ground level (AGL) flying height, and IMU grade. The spectroradiometer under nominal operating conditions (8 ∘ FOV, 10 m AGL height, 0.6 s integration time, and 3 m/s flying speed) resulted in footprint extent of 140 cm across-track and 320 cm along-track, and a geolocation uncertainty of 11 cm. Flying height and orientation measurement accuracy had the largest influence on the geolocation uncertainty, whereas the FOV, integration time, and flying speed had the biggest impact on the size of the footprint. Furthermore, with an increase in flying height, the rate of increase in geolocation uncertainty was found highest for a low-grade IMU. To increase the footprint geolocation accuracy, we recommend reducing flying height while increasing the FOV which compensates the footprint area loss and increases the signal strength. The disadvantage of a lower flying height and a larger FOV is a higher sensitivity of the footprint size to changing distance from the target. To assist in matching the footprint size to uncertainty ratio with an appropriate spatial scale, we list the expected ratio for a range of IMU grades, FOVs and AGL heights.

Remote monitoring of dynamic canopy photosynthesis with high time resolution light-induced fluorescence transients.

Understanding the net photosynthesis of plant canopies requires quantifying photosynthesis in challenging environments, principally due to the variable light intensities and qualities generated by sunlight interactions with clouds and surrounding foliage. The dynamics of sunflecks and rates of change in light intensity at the beginning and end of sustained light (SL) events makes photosynthetic measurements difficult, especially when dealing with less accessible parts of plant foliage. High time resolved photosynthetic monitoring from pulse amplitude modulated (PAM) fluorometers has limited applicability due to the invasive nature of frequently applied saturating flashes. An alternative approach used here provides remote (<5 m), high time resolution (10 s), PAM equivalent but minimally invasive measurements of photosynthetic parameters. We assessed the efficacy of the QA flash protocol from the Light-Induced Fluorescence Transient (LIFT) technique for monitoring photosynthesis in mature outer canopy leaves of potted Persea americana Mill. cv. Haas (Avocado) trees in a semi-controlled environment and outdoors. Initially we established that LIFT measurements were leaf angle independent between ±40° from perpendicular and moreover, that estimates of 685 nm reflectance (R685) from leaves of similar chlorophyll content provide a species dependent, but reasonable proxy for incident light intensity. Photosynthetic responses during brief light events (≤10 min), and the initial stages of SL events, showed similar declines in the quantum yield of photosystem II (ΦII) with large transient increases in 'constitutive loss processes' (ΦNO) prior to dissipation of excitation by non-photochemical quenching (ΦNPQ). Our results demonstrate the capacity of LIFT to monitor photosynthesis at a distance during highly dynamic light conditions that potentially may improve models of canopy photosynthesis and estimates of plant productivity. For example, generalized additive modelling performed on the 85 dynamic light events monitored identified negative relationships between light event length and ∆ΦII and ∆electron transport rate using either ∆photosynthetically active radiation or ∆R685 as indicators of leaf irradiance.

Antarctic moss stress assessment based on chlorophyll content and leaf density retrieved from imaging spectroscopy data.

The health of several East Antarctic moss-beds is declining as liquid water availability is reduced due to recent environmental changes. Consequently, a noninvasive and spatially explicit method is needed to assess the vigour of mosses spread throughout rocky Antarctic landscapes. Here, we explore the possibility of using near-distance imaging spectroscopy for spatial assessment of moss-bed health. Turf chlorophyll a and b, water content and leaf density were selected as quantitative stress indicators. Reflectance of three dominant Antarctic mosses Bryum pseudotriquetrum, Ceratodon purpureus and Schistidium antarctici was measured during a drought-stress and recovery laboratory experiment and also with an imaging spectrometer outdoors on water-deficient (stressed) and well-watered (unstressed) moss test sites. The stress-indicating moss traits were derived from visible and near infrared turf reflectance using a nonlinear support vector regression. Laboratory estimates of chlorophyll content and leaf density were achieved with the lowest systematic/unsystematic root mean square errors of 38.0/235.2 nmol g(-1) DW and 0.8/1.6 leaves mm(-1) , respectively. Subsequent combination of these indicators retrieved from field hyperspectral images produced small-scale maps indicating relative moss vigour. Once applied and validated on remotely sensed airborne spectral images, this methodology could provide quantitative maps suitable for long-term monitoring of Antarctic moss-bed health.

Modelling plant species distribution in alpine grasslands using airborne imaging spectroscopy.

Remote sensing using airborne imaging spectroscopy (AIS) is known to retrieve fundamental optical properties of ecosystems. However, the value of these properties for predicting plant species distribution remains unclear. Here, we assess whether such data can add value to topographic variables for predicting plant distributions in French and Swiss alpine grasslands. We fitted statistical models with high spectral and spatial resolution reflectance data and tested four optical indices sensitive to leaf chlorophyll content, leaf water content and leaf area index. We found moderate added-value of AIS data for predicting alpine plant species distribution. Contrary to expectations, differences between species distribution models (SDMs) were not linked to their local abundance or phylogenetic/functional similarity. Moreover, spectral signatures of species were found to be partly site-specific. We discuss current limits of AIS-based SDMs, highlighting issues of scale and informational content of AIS data.

Daily and seasonal dynamics of remotely sensed photosynthetic efficiency in tree canopies.

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.

Response of green reflectance continuum removal index to the xanthophyll de-epoxidation cycle in Norway spruce needles.

A dedicated field experiment was conducted to investigate the response of a green reflectance continuum removal-based optical index, called area under the curve normalized to maximal band depth between 511 nm and 557 nm (ANMB511-557), to light-induced transformations in xanthophyll cycle pigments of Norway spruce [Picea abies (L.) Karst] needles. The performance of ANMB511-557 was compared with the photochemical reflectance index (PRI) computed from the same leaf reflectance measurements. Needles of four crown whorls (fifth, eighth, 10th, and 15th counted from the top) were sampled from a 27-year-old spruce tree throughout a cloudy and a sunny day. Needle optical properties were measured together with the composition of the photosynthetic pigments to investigate their influence on both optical indices. Analyses of pigments showed that the needles of the examined whorls varied significantly in chlorophyll content and also in related pigment characteristics, such as the chlorophyll/carotenoid ratio. The investigation of the ANMB511-557 diurnal behaviour revealed that the index is able to follow the dynamic changes in the xanthophyll cycle independently of the actual content of foliar pigments. Nevertheless, ANMB511-557 lost the ability to predict the xanthophyll cycle behaviour during noon on the sunny day, when the needles were exposed to irradiance exceeding 1000 µmol m(-2) s(-1). Despite this, ANMB511-557 rendered a better performance for tracking xanthophyll cycle reactions than PRI. Although declining PRI values generally responded to excessive solar irradiance, they were not able to predict the actual de-epoxidation state in the needles examined.

Relation of chlorophyll fluorescence sensitive reflectance ratios to carbon flux measurements of montanne grassland and norway spruce forest ecosystems in the temperate zone.

We explored ability of reflectance vegetation indexes (VIs) related to chlorophyll fluorescence emission (R686/R630, R740/R800) and de-epoxidation state of xanthophyll cycle pigments (PRI, calculated as (R531- R570)/(R531-R570) to track changes in the CO2 assimilation rate and Light Use Efficiency (LUE) in montane grassland and Norway spruce forest ecosystems, both at leaf and also canopy level. VIs were measured at two research plots using a ground-based high spatial/spectral resolution imaging spectroscopy technique. No significant relationship between VIs and leaf light-saturated CO2 assimilation (A(MAX)) was detected in instantaneous measurements of grassland under steady-state irradiance conditions. Once the temporal dimension and daily irradiance variation were included into the experimental setup, statistically significant changes in VIs related to tested physiological parameters were revealed. ΔPRI and Δ(R686/R630) of grassland plant leaves under dark-to-full sunlight transition in the scale of minutes were significantly related to A(MAX) (R² = 0.51). In the daily course, the variation of VIs measured in one-hour intervals correlated well with the variation of Gross Primary Production (GPP), Net Ecosystem Exchange (NEE), and LUE estimated via the eddy-covariance flux tower. Statistical results were weaker in the case of the grassland ecosystem, with the strongest statistical relation of the index R686/R630 with NEE and GPP.

Scientific and technical challenges in remote sensing of plant canopy reflectance and fluorescence.

State-of-the-art optical remote sensing of vegetation canopies is reviewed here to stimulate support from laboratory and field plant research. This overview of recent satellite spectral sensors and the methods used to retrieve remotely quantitative biophysical and biochemical characteristics of vegetation canopies shows that there have been substantial advances in optical remote sensing over the past few decades. Nevertheless, adaptation and transfer of currently available fluorometric methods aboard air- and space-borne platforms can help to eliminate errors and uncertainties in recent remote sensing data interpretation. With this perspective, red and blue-green fluorescence emission as measured in the laboratory and field is reviewed. Remotely sensed plant fluorescence signals have the potential to facilitate a better understanding of vegetation photosynthetic dynamics and primary production on a large scale. The review summarizes several scientific challenges that still need to be resolved to achieve operational fluorescence based remote sensing approaches.

Near-distance imaging spectroscopy investigating chlorophyll fluorescence and photosynthetic activity of grassland in the daily course.

Detection of grassland canopy chlorophyll fluorescence (Chl-F) conducted with an imaging spectroradiometer provided evidence of potential remote sensing estimation of steady-state Chl-F (Chl-Fs). Daily near-nadir views of extremely high spatial resolution hyperspectral images were acquired from a distance of 4 m for temperate montane grassland in the Czech Republic. Simultaneously, measurements of Chl-F and total chlorophyll content (Chla + b) were made on a single leaf at ground level were collected. A specifically designed 'shade removal' experiment revealed the influence of dynamic physiological plant processes on hyperspectral reflectance of three wavelengths: 532, 686 and 740 nm. Based on this information, the vegetation indexes R686/R630, R740/R800 and PRI calculated as (R532-R570)/(R532+R570) were tested for statistical significance with directly measured Chl-F parameters (maximum fluorescence yield, Fv/Fm; steady-state chlorophyll fluorescence, Chl-Fs and actual quantum yield, ФII). The grassland species under investigation were: Festuca rubra agg. (L.), Hieracium sp., Plantago sp., Nardus stricta (L.) and Jacea pseudophrygia (C.A. Meyer). The coefficients of determination (R2) for best-fit relationships between PRI-ФII and PRI-Chl-Fs, measured in the daily course, show a high variability of 0.23-0.78 and 0.20-0.65, respectively. Similarly, R2 for the R686/R630-ФII and R686/R630-Chl-Fs relationships varied between 0.20-0.73 and 0.41-0.70, respectively. The highest average R2 values were found between PRI and Chla + b (0.63) and R686/R630 and Chla + b (0.72). The ratio R740/R800 did not yield a statistically significant relation with Chl-F parameters.

Spectral analysis of coniferous foliage and possible links to soil chemistry: are spectral chlorophyll indices related to forest floor dissolved organic C and N?

Dissolved organic matter in soils can be predicted from forest floor C:N ratio, which in turn is related to foliar chemistry. Little is known about the linkages between foliar constituents such as chlorophylls, lignin, and cellulose and the concentrations of water-extractable forest floor dissolved organic carbon and dissolved organic nitrogen. Lignin and cellulose are not mobile in foliage and thus may be indicative of growing conditions during prior years, while chlorophylls respond more rapidly to the current physiological status of a tree and reflect nutrient availability. The aim of this study was to examine potential links among spectral foliar data, and the organic C and N of forest soils. Two coniferous species (red spruce and balsam fir) were studied in the White Mountains of New Hampshire, USA. Six trees of each species were sampled at 5 watersheds (2 in the Hubbard Brook Experimental Forest, 3 in the Bartlett Experimental Forest). We hypothesized that in a coniferous forest, chemistry of old foliage would better predict the chemical composition of the forest floor litter layer than younger foliage, which is the more physiologically active and the most likely to be captured by remote sensing of the canopy. Contrary to our expectations, chlorophyll concentration of young needles proved to be most tightly linked to soil properties, in particular water-extractable dissolved organic carbon. Spectral indices related to the chlorophyll content of needles could be used to predict variation in forest floor dissolved organic carbon and dissolved organic nitrogen. Strong correlations were found between optical spectral indices based on chlorophyll absorption and forest floor dissolved organic carbon, with higher foliage chlorophyll content corresponding to lower forest floor dissolved organic carbon. The mechanisms behind these correlations are uncertain and need further investigation. However, the direction of the linkage from soil to tree via nutrient availability is hypothesized based on negative correlations found between foliar N and forest floor dissolved organic carbon.