Assessing structural effects on PRI for stress detection in conifer forests

The retrieval of indicators of vegetation stress from remote sensing imagery is an important issue for the accurate assessment of forest decline. The Photochemical Reflectance Index (PRI) has been demonstrated as a physiological index sensitive to the epoxidation state of the xanthophyll cycle pigments and to photosynthetic efficiency, serving as a proxy for short-term changes in photosynthetic activity, stress condition, and pigment absorption, but highly affected by illumination conditions, viewing geometry and canopy structure. In this study, a diurnal airborne campaign was conducted over Pinus sylvestris and Pinus nigra forest areas with the Airborne Hyperspectral Scanner (AHS) to evaluate the effects of canopy structure on PRI when used as an indicator of stress in a conifer forest. The AHS airborne sensor was flown at two times (8:00 GMT and 12:00 GMT) over forest areas under varying field-measured stress levels, acquiring 2 m spatial resolution imagery in 80 spectral bands in the 0.43-12.5 μm spectral range. Five formulations of PRI (based on R₅₃₁ as a xanthophyll-sensitive spectral band) were calculated using different reference wavelengths, such as PRI₅₇₀ (reference band R_REF = R₅₇₀), and the PRI modifications PRI_m1 (R_REF = R₅₁₂), PRI_m2 (R_REF = R₆₀₀), PRI_m3 (R_REF = R₆₇₀), and PRI_m4 (R_REF = R₅₇₀, R₆₇₀), along with other structural indices such as NDVI, SR, OSAVI, MSAVI and MTVI2. In addition, thermal bands were used for the retrieval of the land surface temperature. A radiative transfer modeling method was conducted using the LIBERTY and INFORM models to assess the structural effects on the PRI formulations proposed, studying the sensitivity of PRI_m indices to detect stress levels while minimizing the effects caused by the conifer architecture. The PRI indices were related to stomatal conductance, xanthophyll epoxidation state (EPS) and crown temperature. The modeling analysis showed that the coefficient of variation (CV) for PRI was 50%, whereas the CV for PRIm1 (band R512 as a reference) was only 20%. Simulation and experimental results demonstrated that PRI_m1 (R_REF = R₅₁₂) was less sensitive than PRI (R_REF = R₅₇₀) to changes in Leaf Area Index (LAI) and tree densities. PRI₅₁₂ was demonstrated to be sensitive to EPS at both leaf (r² = 0.59) and canopy level (r² = 0.40), yielding superior performance than PRI₅₇₀ (r² = 0.21) at the canopy level. In addition, PRI₅₁₂ was significantly related to water stress indicators such as stomatal conductance (Gs; r² = 0.45) and water potential (Ψ; r² = 0.48), yielding better results than PRI₅₇₀ (Gs, r² = 0.21; Ψ, r² = 0.21) due to the structural effects found on the PRI₅₇₀ index at the canopy level.     

Grape quality assessment in vineyards affected by iron deficiency chlorosis using narrow-band physiological remote sensing indices

The present study investigated the use of physiological indices calculated from hyperspectral remote sensing imagery as potential indicators of wine grape quality assessment in vineyards affected by iron deficiency chlorosis. Different cv. Tempranillo/110 Richter vineyards located in northern Spain, affected and non-affected by iron chlorosis, were identified for field and airborne data collection. Airborne campaigns imaged a total of 14 study areas in both 2004 and 2005 using the AHS hyperspectral sensor, which acquired 20 spectral bands in the VIS-NIR region. Field measurements were conducted in each study site to obtain leaf and grape physiological parameters potentially linked to wine quality. Simulations carried out with the rowMCRM radiative transfer model demonstrated the feasibility of estimating leaf chlorophyll a + b (C_ab) content using TCARI/OSAVI from AHS spectral bands. In addition to traditional structural vegetation indices (NDVI) and successful canopy-level chlorophyll indices (TCARI/OSAVI), other innovative physiological indices sensitive to changes in carotenoid (Car) and anthocyanin (Anth) content in leaves were assessed from the imagery. The rowMCRM model simulations were used to evaluate canopy structural effects on these physiological indices as a function of the typical row-structured canopy variables in vineyards (LAI, crown width, row distances, C_ab content and soil background effects). Modeling results concluded that Car (Gitelson-Car2) and Anth (Gitelson-Anth) indices were highly affected by canopy structure (C_w, V_s) and soil background (ρ_s). Field measurements of grape composition and quality were used to assess potential relationships with physiological indices sensitive to foliar pigment content (C_ab, Car and Anth). NDVI and TCARI/OSAVI indices yielded lower relationships for CIRG and IMAD must quality parameters than Car and Anth physiological indices. These results suggest that the increase in carotenes and anthocyanins due to drought, thermal damage or micronutrient deficiencies is a better indicator to detect phenolic ripening difficulties for vines affected by iron chlorosis than chlorosis detection. Therefore, the potential use of physiological remote sensing indices related to carotene and anthocyanin pigments demonstrates their importance as grape quality indicators in vineyards affected by iron chlorosis.     

Modelling PRI for water stress detection using radiative transfer models

This paper presents a methodology for water stress detection in crop canopies using a radiative transfer modelling approach and the Photochemical Reflectance Index (PRI). Airborne imagery was acquired with a 6-band multispectral camera yielding 15 cm spatial resolution and 10 nm FWHM over 3 crops comprising two tree-structured orchards and a corn field. The methodology is based on the PRI as a water stress indicator, and a radiative transfer modelling approach to simulate PRI baselines for non-stress conditions as a function of leaf structure, chlorophyll concentration (Cab), and canopy leaf area index (LAI). The simulation work demonstrates that canopy PRI is affected by structural parameters such as LAI, Cab, leaf structure, background effects, viewing angle and sun position. The modelling work accounts for such leaf biochemical and canopy structural inputs to simulate the PRI-based water stress thresholds for non-stress conditions. Water stress levels are quantified by comparing the image-derived PRI and the simulated non-stress PRI (sPRI) obtained through radiative transfer. PRI simulation was conducted using the coupled PROSPECT-SAILH models for the corn field, and the PROSPECT leaf model coupled with FLIGHT 3D radiative transfer model for the olive and peach orchards. Results obtained confirm that PRI is a pre-visual indicator of water stress, yielding good relationships for the three crops studied with canopy temperature, an indicator of stomatal conductance (r² = 0.65 for olive, r² = 0.8 for peach, and r² = 0.72 for maize). PRI values of deficit irrigation treatments in olive and peach were consistently higher than the modelled PRI for the study sites, yielding relationships with water potential (r² = 0.84) that enabled the identification of stressed crowns accounting for within-field LAI and Cab variability. The methodology presented here for water stress detection is based on the visible part of the spectrum, and therefore it has important implications for remote sensing applications in agriculture. This method may be a better alternative to using the thermal region, which has limitations to acquire operationally high spatial resolution thermal imagery.     

Detecting water stress effects on fruit quality in orchards with time-series PRI airborne imagery

A methodology for the assessment of fruit quality in crops subjected to different irrigation regimes is presented. High spatial resolution multispectral and thermal airborne imagery were used to monitor crown temperature and the Photochemical Reflectance Index (PRI) over three commercial orchards comprising peach, nectarine and orange fruit trees during 2008. Irrigation regimes included sustained and regulated deficit irrigation strategies, leading to high variability of fruit quality at harvest. Stem water potential was used to monitor individual tree water status on each study site. Leaf samples were collected for destructive sampling of xanthophyll pigments to assess the relationship between the xanthophyll epoxidation state (EPS) and PRI at leaf and airborne-canopy level. At harvest, fruit size, Total Soluble Solids (TSS) and Tritatable Acidity (TA) were measured to characterize fruit quality. A statistically significant relationship between EPS and PRI was found at the leaf (r² = 0.81) and canopy level (r² = 0.41). Airborne-derived crown PRI calculated from the imagery acquired during the fruit growth was related to the ratio of the total soluble solids normalized by the tritatable acidity (TSS/TA), an indicator of fruit quality measured on the same trees, yielding a coefficient of determination of r² = 0.50. The relationship between the integral of PRI time-series and TSS/TA yielded a coefficient of determination of r² = 0.72 (peach) and r² = 0.61 (nectarines). On the contrary, the relation between TSS/TA and the time-series of crown thermal imagery was very weak (r² = 0.21 and 0.25 respectively). These results suggest that a physiological remote sensing indicator related to photosynthesis, such as PRI, is more appropriate for fruit quality assessment than crown temperature, the established method of water stress detection, which is more related to crown transpiration. A radiative transfer modelling study was conducted to assess the potential validity of this methodology for fruit quality assessment when using medium spatial resolution imagery. The analysis shows important effects of soil and shadows on the PRI vs EPS relationship used for fruit quality assessment if non-pure crown reflectance was extracted from the imagery.     

A new instrument for passive remote sensing: 2. Measurement of leaf and canopy reflectance changes at 531 nm and their relationship with photosynthesis and chlorophyll fluorescence

A previously described passive remote sensing fluorimeter (see companion paper) was modified to detect changes in the reflectance of vegetation. The utility of this remote sensing technique to measure the Physiological Reflectance Index (PRI) is shown at both leaf level under laboratory conditions and at the canopy level in the field. PRI, defined as the relative changes in reflectance at 531 nm with respect to those at 570 nm (PRI=R531−R570/R531+R570), is related to xanthophyll-related, dynamic changes of non-photochemical quenching of chlorophyll fluorescence. The robustness of this relationship by simultaneous remote sensing of PRI and chlorophyll fluorescence is strengthened. At the leaf level, the existence of two kinetically distinct components of PRI is shown. A fast (within seconds) component that is partly attributed to ΔpH induced chloroplast shrinkage, and a slow (within minutes), main component that is related to xanthophyll de-epoxidation, as demonstrated by its disappearance in the presence of DTT. Overall, PRI correlated better with non-photochemical quenching of chlorophyll fluorescence (NPQ) than with any other measured parameter, including the photochemical efficiency of PSII. Finally, at the canopy level and under field conditions, it is shown that PRI can be a useful tool for remote sensing of water stress in grapevines.     

Angular sensitivity analysis of vegetation indices derived from CHRIS/PROBA data

View angle effects present in spectral vegetation indices can either be regarded as an added source of uncertainty for variable retrieval or as a source of additional information, enhancing the variable retrieval; however, the magnitude of these angular effects remains for most indices unknown or unquantified. We use the ESA-mission CHRIS-PROBA (Compact High Resolution Imaging Spectrometer onboard the Project for On-board Autonomy) providing spaceborne imaging spectrometer and multiangular data to assess the reflectance anisotropy of broadband as well as recently developed narrowband indices. Multiangular variability of Hemispherical Directional Reflectance Factor (HDRF) is a prime factor determining the indices´ angular response. Two contrasting structural vegetation types, pine forest and meadow, were selected to study the effect of reflectance anisotropy on the angular response. Calculated indices were standardized and statistically evaluated for their varying HDRF. Additionally we employ a coupled radiative transfer model (PROSPECT/FLIGHT) to quantify and substantiate the findings beyond an incidental case study. Nearly all tested indices manifested a prominent anisotropic behaviour. Apart from the conventional broadband greenness indices [e.g. Simple Ratio Index (SRI), Normalized Difference Vegetation Index (NDVI)], light use efficiency and leaf pigment indices [e.g. Structure Insensitive Pigment Index (SIPI), Photochemical Reflectance Index (PRI) and Anthocyanin Reflectance Index (ARI)] did express significant different angular responses depending on the vegetation type. Following the quantification of the impact, we conclude that the angular-dependent fraction of non-photosynthetic material is of critical importance shaping the angular signature of these VIs. This work highlights the influence of viewing geometry and surface reflectance anisotropy, particularly when using light use efficiency and leaf pigment indices.     

Optimum pixel size for hyperspectral studies of ecosystem function in southern California chaparral and grassland

Hyperspectral remotely sensed data are useful for studying ecosystem processes and patterns. However, spatial characterization of such remotely sensed images is needed to optimize sampling procedures and address scaling issues. We have investigated spatial scaling in ground-based and airborne hyperspectral data for canopy- to watershed-level ecosystem studies of southern California chaparral and grassland vegetation. Three optical reflectance indices, namely, Normalized Difference Vegetation Index (NDVI), Water Band Index (WBI) and Photochemical Reflectance Index (PRI) were used as indicators of biomass, plant water content and photosynthetic activity, respectively. Two geostatistical procedures, the semivariogram and local variance, were used for the spatial scaling analysis of these indices. The results indicate that a pixel size of 6 m or less would be optimal for studying functional properties of southern California grassland and chaparral ecosystems using hyperspectral remote sensing. These results provide a guide for selecting the spatial resolution of future airborne and satellite-based hyperspectral sensors.     

PRI assessment of long-term changes in carotenoids/chlorophyll ratio and short-term changes in de-epoxidation state of the xanthophyll cycle

The Photochemical Reflectance Index (PRI), an index based on leaf reflectance at 531 nm, has been found suitable for tracking variations in photosynthetic activity from leaf to ecosystem levels. This suitability has been attributed to PRI correlation with xanthophyll interconversion and photosynthetic radiation-use efficiency. However, other pigments and factors may be involved in such relationships. We studied the relationship between PRI and xanthophylls and other carotenoids in saplings of two widely distributed evergreen species (Scots pine and Holm oak) submitted to experimentally changing light conditions in a field experiment. PRI was strongly correlated with the de-epoxidation state of xanthophylls (DEPS, an expression of the relative concentration of the three xanthophyll cycle pigments), but also with carotenoids/chlorophyll ratio and β-carotene/chlorophyll ratio in both species. However, following momentary decreases in light due to clouds, PRI changed following the DEPS changes, while the carotenoids/chlorophyll ratio remained constant. The results show that PRI was able to reveal short-term changes in de-epoxidation state, i.e. the signal of xanthophyll interconversion, but it also tracked long-term changes in carotenoids/chlorophyll. Carotenoids other than xanthophylls, e.g. β-carotene, are also related to photoprotective processes, thus also making PRI effective as a measure of changes in photosynthetic light-use efficiency in response to stress on a long-term level.     

The Photochemical Reflectance Index (PRI) as a water-stress index

Measurements of leaf reflectance in two narrow wavelength bands centred around 531 and 570 nm were carried out during withering of two contrasting functional and structural plant types: Chenopodium quinoa (Willd.) and Arbutus unedo (L.). The Photochemical Reflectance Index (PRI)=( R 531 - R 570 )/ ( R 531 + R 570 ) was calculated. The results showed that PRI could be used as a reliable water-stress index. However, some limits to the use of PRI have to be emphasized, e.g. the wilting of leaves during dry periods. If such limits are under control, PRI could be a non-destructive and low cost method for assessing plant water status.     

Linking physiological responses,chlorophyll fluorescence and hyperspectral imagery to detect salinity stress using the physiological reflectance index in the coastal shrub,Myrica cerifera

Measurements of physiology, chlorophyll fluorescence and hyperspectral reflectance were used to detect salinity stress in the evergreen coastal shrub, Myrica cerifera on Hog Island, Virginia. Two experimental sites were used in our study, the oceanside of a M. cerifera thicket, which is exposed to sea spray, and the protected, leeside of the thicket. Using the physiological reflectance index (PRI), we were able to detect stress at both the canopy and landscape level. Monthly variations in stomatal conductance, photosynthesis, and relative water content indicated a strong summer drought response that was not apparent in chlorophyll fluorescence or in the water band index (WBI) derived from canopy and airborne reflectance measurements. In contrast, there were significant differences in both physiological measurements and tissue chlorides between the two sites used in the study, indicating salinity stress. This was reflected in measurements of PRI. There was a positive relationship between PRI measured at the canopy-level and light-adapted fluorescence (ΔF/F′_m; r² = 0.69). PRI was significantly lower on the oceanside of the Myrica cerifera thicket. PRI was not significantly related to NDVI (r² = 0.01) at the canopy-level and only weakly related (r² = 0.04) at the landscape-level, suggesting that the indices are independent. The chlorophyll index (CI) did not show any significant changes between the two sites. Frequency histograms of pixels sampled from airborne hyperspectral imagery revealed that the distribution of PRI was shifted to the right on the backside of the thicket relative to the oceanside and there was a significant difference between sites. These results suggest that PRI may be used for early identification of salt-stress and to identify areas across the landscape where community structure may change due to sea-level rise.     

Monitoring yield and fruit quality parameters in open-canopy tree crops under water stress. Implications for ASTER

Work on water stress detection at tree and orchard levels using a high-spatial airborne thermal sensor is presented, showing its connection with yield and some fruit quality indicators in olive and peach commercial orchards under different irrigation regimes. Two airborne campaigns were conducted with the Airborne Hyperspectral Scanner (AHS) over olive and peach orchards located in Córdoba, southern Spain. The AHS sensor was flown at three different times on 25 July 2004 and 16 July 2005, collecting 2 m spatial resolution imagery in 80 spectral bands in the 0.43-12.5 μm spectral range. Thermal bands were assessed for the retrieval of land surface temperature using the split-window algorithm and TES (Temperature-Emissivity-Separation) method, separating pure crowns from shadows and sunlit soil pixels using the reflectance bands. Stem water potential and stomatal conductance were measured on selected trees at the time of airborne flights over the orchards. Tree fruit yield and quality parameters such as oil, weight and water content (for the olive trees), and fruit volume and weight (for the peach trees) were obtained at harvest and through laboratory analysis. Relationships between airborne-estimated crown temperature minus air temperature and stem water potential yielded r² = 0.5 (12:30 GMT) at the olive tree level, and r² = 0.81 (9:00 GMT) at the treatment level in peach trees. These results demonstrate that water stress can be detected at the crown level even under the usual water management conditions of commercial orchards. Regressions of yield and fruit quality against remote sensing estimates of crown temperature as an indicator of water stress, yielded r² = 0.95 (olive fruit water content) and r² = 0.94 (peach fruit mean diameter). These results suggest that high-spatial remote sensing thermal imagery has potential as an indicator of some fruit quality parameters for crop field segmentation and irrigation management purposes. A simulation study using ASTER spectral bands and aggregated pixels for stress detection as a function of irrigation level was conducted in order to study the applicability of medium resolution thermal sensors for the global monitoring of open-canopy tree crops. The determination coefficients obtained between the ASTER-simulated canopy temperature minus air temperature and stem water potential yielded r² = 0.58 (12:30 GMT) for olive trees, suggesting the potential for extrapolating these methods to ASTER satellite for global monitoring of open tree canopies.     

NDVI responses to the forest canopy and floor from spring to summer observed by airborne spectrometer in eastern Siberia

A popular method of satellite-based monitoring of the photosynthetic potential of vegetation is to calculate the normalised difference vegetation index (NDVI) from measurements of the red (RED) and near-infrared (NIR) bands. Enormous amounts of vegetation information have been obtained over continental to global areas based on NDVI derived from NOAA-AVHRR, Terra/Aqua-MODIS, and SPOT-VEGETATION satellite observations. In eastern Siberia, where sparse boreal forests are dominant, the lack of landscape-scale canopy-reflectance observations impedes interpretation of how NDVI seasonality is controlled by the forest canopy and floor status. We discuss the NDVI of the canopy and floor separately based on airborne spectral reflectance measurements and simultaneous airborne land surface images acquired around Yakutsk, Siberia, using a hedgehopping aircraft from spring to summer 2000. The aerial land surface images (4402 scenes) were visually classified into four types according to the forest condition: no-green canopy and snow floor (Type 1), green canopy and snow floor (Type 2), no-green canopy and no-snow floor (Type 3), and green canopy and no-snow floor (Type 4). The spectral reflectance from 350 to 1200 nm was then calculated for these four types. Type 1 had almost no difference in reflectance between the RED and NIR bands, and the resultant NDVI was slightly negative (− 0.03). Although Type 2 showed a significant difference between the two bands because of canopy greenness, the resultant NDVI was rather low (0.17) because of high reflection from the snow cover on the floor. In Type 3, the significant difference between the two bands was mainly caused by the greenness of the floor, and the NDVI was relatively high (0.45). The NDVI for Type 4 was the highest (0.75) among the four types. The contributions of reflectance from the forest canopy and floor to the total reflectance were tested with a forest radiative transfer model. The reflectance difference between NIR and RED bands (NIR − RED) of Type 4 (15.6%) was approximately double the differences of Type 2 (7.0%) and of Type 3 (7.9%), suggesting half-and-half contributions of forest canopy greenness and floor greenness to the total greenness. The result also suggested that the satellite-derived NDVI in the larch forest around Yakutsk reaches 85% of the maximum NDVI owing to the forest floor greenness, and only the other 15% of the increase in NDVI should be attributed to the canopy foliation. These results quantitatively reveal that the NDVI depends considerably on forest floor greenness and snow cover in addition to canopy greenness in the case of relatively sparse forest in Siberia.     

A novel two-step method for winter wheat-leaf chlorophyll content estimation using a hyperspectral vegetation index

Remote sensing estimation of leaf chlorophyll content is of importance to crop nutrition diagnosis and yield assessment, yet the feasibility and stability of such estimation has not been assessed thoroughly for mixed pixels. This study analyses the influence of spectral mixing on leaf chlorophyll content estimation using canopy spectra simulated by the PROSAIL model and the spectral linear mixture concept. It is observed that the accuracy of leaf chlorophyll content estimation would be degraded for mixed pixels using the well-accepted approach of the combination of transformed chlorophyll absorption index (TCARI) and optimized soil-adjusted vegetation index (OSAVI). A two-step method was thus developed for winter wheat chlorophyll content estimation by taking into consideration the fractional vegetation cover using a look-up-table approach. The two methods were validated using ground spectra, airborne hyperspectral data and leaf chlorophyll content measured the same time over experimental winter wheat fields. Using the two-step method, the leaf chlorophyll content of the open canopy was estimated from the airborne hyperspectral imagery with a root mean square error of 5.18 μg cm^?2, which is an improvement of about 8.9% relative to the accuracy obtained using the TCARI/OSAVI ratio directly. This implies that the method proposed in this study has great potential for hyperspectral applications in agricultural management, particularly for applications before crop canopy closure.     

Retrieval of leaf chlorophyll content in field crops using narrow-band indices: effects of leaf area index and leaf mean tilt angle

Reliable estimation of leaf chlorophyll-a and -b content (chl-a + b) at canopy scales is essential for monitoring vegetation productivity, physiological stress, and nutrient availability. To achieve this, narrow-band vegetation indices (VIs) derived from imaging spectroscopy data are commonly used. However, VIs are affected by canopy structures other than chl-a + b, such as leaf area index (LAI) and leaf mean tilt angle (MTA). In this study, we evaluated the performance of 58 VIs reported in the literature to be chl-a + b-sensitive against a unique measured set of species-specific leaf angles for six crop species in southern Finland. We created a large simulated canopy reflectance database (100,000 canopy configurations) using the physically based PROSAIL (coupling of PROSPECT and SAIL (Scattering by Arbitrarily Inclined Leaves) radiative transfer models) model. The performance of model-simulated indices was compared against airborne AISA Eagle II imaging spectroradiometer data and field-measured chl-a + b, LAI, and MTA values. In general, LAI had a positive effect on the strength of the correlation between chl-a + b and VIs while MTA had a negative effect in both measured and simulated data. Three indices (REIP (red edge inflection point), TCARI (transformed chlorophyll absorption ratio index)/OSAVI (optimized soil-adjusted vegetation index), and CTR6 (Carter indices)) showed strong correlations with chl-a + b and similar performance in model-simulated and measured data set. However, only two (TCARI/OSAVI and CTR6) were independent from LAI and MTA. We consider these two indices robust proxies of crop leaf chl-a + b.     

Reflectance assessment of seasonal and annual changes in biomass and CO2 uptake of a Mediterranean shrubland submitted to experimental warming and drought

We aimed to evaluate how the remote sensing vegetation indices NDVI and PRI responded to seasonal and annual changes in an early successional stage Mediterranean coastal shrubland canopy that was submitted to experimental warming and drought simulating predicted climate change for the next decades. These conditions were obtained by using a new non-intrusive methodological approach that increases the temperature and prolongs the drought period by using roofs that automatically cover the vegetation after the sunset or when it rains. On average, warming increased air temperature by 0.7 °C and soil temperature by 1.6 °C, and the drought treatment reduced soil moisture by 22%. We measured spectral reflectance at the canopy level and at the individual plant level seasonally during 4 years. Shrubland NDVI tracked the community development and activity. In control and warming treatments, NDVI increased with the years while it did not change in the drought treatment. There was a good relationship between NDVI and both community and individual plant biomass. NDVI also decreased in summer seasons when some species dry or decolour. The NDVI of E. multiflora plant individuals was lower in autumn and winter than in the other seasons, likely because of flowering. Shrubland PRI decreased only in winter, similarly to the PRI of the most dominant species, G. alypum. At this community scale, NDVI was better related than PRI to photosynthetic activity, probably because photosynthetic fluxes followed canopy seasonal greening in this complex canopy, which includes brevideciduous, annual and evergreen species and variable morphologies and canopy coverage. PRI followed the seasonal variations in photosynthetic rates in E. multiflora and detected the decreased photosynthetic rates of drought treatment. However, PRI did not track the photosynthetic rates of G. alypum plants which have lower LAIs than E. multiflora. In this community, which is in its early successional stages, NDVI was able to track biomass, and indirectly, CO₂ uptake changes, likely because LAI values did not saturate NDVI. Thus, NDVI appears as a valid tool for remote tracking of this community development. PRI was less adequate for photosynthetic assessment of this community especially for its lower LAI canopies. PRI usefulness was also species-dependent and could also be affected by flowering. These results will help to improve the interpretation of remote sensing information on the structure and physiological status of these Mediterranean shrublands, and to gain better insight on ecological and environmental controls on their ecosystem carbon dioxide exchange. They also show the possibility of assessing the impacts of climate change on shrubland communities.     

The photochemical reflectance index (PRI) and the remote sensing of leaf, canopy and ecosystem radiation use efficiencies: A review and meta-analysis

Traditional remote sensing techniques allow the assessment of green plant biomass, and therefore plant photosynthetic capacity. However, detecting how much of this capacity is actually realized is a more challenging goal. Is it possible to remotely assess actual carbon fluxes? Can this be done at leaf, canopy and ecosystem scales and at different temporal scales? Different approaches can be used to answer these questions. Among them, the Photochemical Reflectance Index (PRI) derived from narrow-band spectroradiometers is a spectral index increasingly being used as an indicator of photosynthetic efficiency. We examined and synthesized the scientific literature on the relationships between PRI and several ecophysiological variables across a range of plant functional types and ecosystems at the leaf, canopy and ecosystem levels and at the daily and seasonal time scales. Our analysis shows that although the strength of these relationships varied across vegetation types, levels of organization and temporal scales, in most reviewed articles PRI was a good predictor of photosynthetic efficiency or related variables with performances at least as good as the widely used NDVI as indicator of green biomass. There are possible confounding factors related to the intensity of the physiological processes linked to the PRI signals, to the structure of the canopies and to the illumination and viewing angles that warrant further studies, and it is expected that the utility of PRI will vary with the ecosystem in question due to contrasting environmental constraints, evolutionary strategies, and radiation use efficiency (RUE; the ratio between carbon uptake and light absorbed by vegetation) variability. Clearly, more research comparing ecosystem responses is warranted. Additionally, like any 2-band index that is affected by multiple factors, the interpretation of PRI can be readily confounded by multiple environmental variables, and further work is needed to understand and constrain these effects. Despite these limitations, this review shows an emerging consistency of the RUE-PRI relationship that suggests a surprising degree of functional convergence of biochemical, physiological and structural components affecting leaf, canopy and ecosystem carbon uptake efficiencies. PRI accounted for 42%, 59% and 62% of the variability of RUE at the leaf, canopy and ecosystem respective levels in unique exponential relationships for all the vegetation types studied. It seems thus that by complementing the estimations of the fraction of photosynthetically active radiation intercepted by the vegetation (FPAR), estimated with NDVI-like indices, PRI enables improved assessment of carbon fluxes in leaves, canopies and many of the ecosystems of the world from ground, airborne and satellite sensors.     

Disentangling the relationships between plant pigments and the photochemical reflectance index reveals a new approach for remote estimation of carotenoid content

The Photochemical Reflectance Index (PRI) is used as an indicator of leaf and plant canopy photosynthetic efficiency. However, the photosynthetic efficiency-PRI relationship has been shown to be inconsistent over time, likely due to changes in foliar pigment content.We measured reflectance spectra and biochemical properties from 24 leaves of two deciduous tree species and acquired pigment and reflectance data from the Leaf Optical Properties EXperiment database for an additional nine species. These data were used as inputs for the PROSPECT-5 leaf optical model. We found measurements of PRI to be significantly (p < 0.05) correlated with chlorophyll content, carotenoid content, and the carotenoid/chlorophyll ratio. However, only the PRI-carotenoid/chlorophyll ratio relationship was consistent across all analyses. Two predictive equations were derived from PROSPECT-5 simulations: a curvilinear PRI model (PRI(clm)) predicted the carotenoid/chlorophyll ratio (r² = 0.99), and a linear model using the chlorophyll index (CI(lm)) predicted chlorophyll content (r² = 0.98). Multiplying PRI(clm) with CI(lm) canceled the influence of chlorophyll content on PRI(clm) and thus allowed for prediction of carotenoid content from 11 deciduous tree species (r² = 0.83). Our results confirm that the PRI is significantly influenced by chlorophyll and carotenoid pools and demonstrate a new approach for non-destructive estimation of leaf carotenoid content using the PRI. Because variation in foliar physiological status is known to relate to leaf carotenoid content and the carotenoid/chlorophyll ratio, convolving the PRI with a chlorophyll index is likely to be useful for understanding the photosynthetic performance of deciduous vegetation across a wide range of temporal periods, ranging from daily to seasonal time scales.