Energy Flux Model Research Articles

Early giant reveals faster evolution of large body size in ichthyosaurs than in cetaceans.

Body sizes of marine amniotes span six orders of magnitude, yet the factors that governed the evolution of this diversity are largely unknown. High primary production of modern oceans is considered a prerequisite for the emergence of cetacean giants, but that condition cannot explain gigantism in Triassic ichthyosaurs. We describe the new giant ichthyosaur Cymbospondylus youngorum sp. nov. with a 2-meter-long skull from the Middle Triassic Fossil Hill Fauna of Nevada, USA, underscoring rapid size evolution despite the absence of many modern primary producers. Surprisingly, the Fossil Hill Fauna rivaled the composition of modern marine mammal faunas in terms of size range, and energy-flux models suggest that Middle Triassic marine food webs were able to support several large-bodied ichthyosaurs at high trophic levels, shortly after ichthyosaur origins.

Using energy flux methods to derive a 3D ocean acoustic propagation model

The energy flux model is a direct source-to-receiver calculation that avoids the need for finding eigenvalues, but it averages out the modal interference structure as originally derived. It has been shown possible in the two-dimensional model to include the near-neighbor modal interference that resolves large-scale caustic features and shadow zones. So far limited work has been done to develop three-dimensional energy flux models for ocean acoustic propagation, but such a model may have significant computational advantages in complex environments or at high frequencies. We present current progress towards developing three-dimensional underwater acoustic propagation models that have been derived using energy flux principles. In particular we will discuss a vertical normal mode and horizontal energy flux model used to solve for the acoustic propagation in a wedge environment.

Mapping of biophysical and biochemical properties of coastal tidal wetland habitats with Landsat 8

Coastal tidal wetlands are significant and vulnerable aquatic ecosystems. Quantitative remote sensing of biophysical and biochemical properties in coastal tidal wetland habitats through the inversion of physical models has vital practical significance for monitoring ecosystem function, environmental restoration, the global carbon, and nitrogen cycles. The objectives of this research were to map leaf area index (LAI), chlorophyll content, as well as the sensible heat flux, latent heat flux, and productivity in Chongming Dongtan coastal tidal wetland habitats of China and to provide a mapping protocol of biophysical and biochemical properties in Chongming Dongtan wetland for environmental protection and restoration as well as assessment and monitoring. In order to obtain significant information for biodiversity protection and management, a method based on the Soil Canopy Observation of Photosynthesis and Energy fluxes model and lookup table approach has been developed. The results derived from our study contain the reflectance values of Scirpus mariqueter and Phragmites australis spectra are lower than those commonly found for vegetated areas. This may be caused by the dark soil background and low LAI. Moreover, as for the values of latent heat flux (between 120 and 190 W m − 2) and productivity (between 3 and 14 μmol m − 2 s − 1), mudflats are lower than vegetation. However, the values of sensible heat flux (between 140 and 170 W m − 2) of mudflats are higher than that of vegetation.

Performance of Singular Spectrum Analysis in Separating Seasonal and Fast Physiological Dynamics of Solar‐Induced Chlorophyll Fluorescence and PRI Optical Signals

AbstractHigh temporal resolution measurements of solar‐induced chlorophyll fluorescence (F) and the Photochemical Reflectance Index (PRI) encode vegetation functioning. However, these signals are modulated by time‐dependent processes. We tested the applicability of the Singular Spectrum Analysis (SSA) for disentangling fast components (physiology‐driven) and slow components (controlled by structural and biochemical properties) from PRI, far‐red F (F760), and far‐red apparent fluorescence yield (Fy∗760). The proof of concept was developed on spectral and flux time series simulated with the Soil Canopy Observation of Photochemistry and Energy fluxes (SCOPE) model. This allowed the evaluation of SSA decomposition against variables that are independent of physiology or are modified by it. Slow SSA‐decomposed components of PRI and Fy∗760 showed high correlations with the reference variables (R2 = 0.97 and 0.96, respectively). Fast SSA‐decomposed components of PRI and Fy∗760 were better related to the physiological reference variables than the original signals during periods when leaf area index (LAI) was above 1 m2 m−2. The method was also successfully applied to predict light‐use efficiency (LUE) from the fast SSA‐decomposed components of PRI (R2 = 0.70) and Fy∗760 (R2 = 0.68) when discarding data modeled with LAI < 1 m2 m−2 and short‐wave radiation Rin < 250 W m−2. The method was then tested on data acquired in a Mediterranean grassland. In this case, the fast SSA‐decomposed component of apparent LUE∗ showed a stronger correlation with the fast SSA‐decomposed component of Fy∗760 (R2 = 0.42) than with original Fy∗760 (R2 = 0.01). SSA‐based approach is a promising tool for decoupling physiological information from measurements acquired with automated proximal sensing systems.

Better revisiting chlorophyll content retrieval with varying senescent material and solar-induced chlorophyll fluorescence simulation on paddy rice during the entire growth stages

Solar-induced chlorophyll fluorescence at 760 nm (SIF) is a promising proxy of photosynthesis and can help improving plant stress monitoring. The Soil-Canopy Observation of Photochemistry and Energy fluxes (SCOPE) model combines radiative transfer and enzyme kinetics of photosynthesis and is widely used to interpret SIF at different temporal and spatial scales. In this study, growing season canopy hyperspectral reflectance between 400 nm and 900 nm was used to retrieve chlorophyll content (Cab) and leaf inclination (LIDFa) using radiative transfer models (RTMs) combined with the shuffled complex evolution-University of Arizona (SCE-UA) method. These parameters were then used to simulate diurnal and seasonal trends of SIF for paddy rice. The results showed that the accuracy of Cab retrieval was improved when the variation in senescent material (Cs) was considered, especially in the later growth stages. The SCOPE model was able to reliably interpret the diurnal cycle and seasonal trend of SIF with a correlation coefficient of 0.92 and RMSE of 0.12 w m−2 sr-1 um−1. Our results revealed that the SCOPE model provides a promising method for interpreting SIF variations but its accuracy should be evaluated in different growth stages. This will serve as a significant reference for detecting plant photosynthetic activity and physiological traits at different growth stages.

Small-scale lithospheric heterogeneity characterization using Bayesian inference and energy flux models

SUMMARYObservations from different disciplines have shown that our planet is highly heterogeneous at multiple scale lengths. Still, many seismological Earth models tend not to include any small-scale heterogeneity or lateral velocity variations, which can affect measurements and predictions based on these homogeneous models. In this study, we describe the lithospheric small-scale isotropic heterogeneity structure in terms of the intrinsic, diffusion and scattering quality factors, as well as an autocorrelation function, associated with a characteristic scale length (a) and RMS fractional velocity fluctuations (ε). To obtain this characterization, we combined a single-layer and a multilayer energy flux models with a new Bayesian inference algorithm. Our synthetic tests show that this technique can successfully retrieve the input parameter values for 1- or 2-layer models and that our Bayesian algorithm can resolve whether the data can be fitted by a single set of parameters or a range of models is required instead, even for very complex posterior probability distributions. We applied this technique to three seismic arrays in Australia: Alice Springs array (ASAR), Warramunga Array (WRA) and Pilbara Seismic Array (PSAR). Our single-layer model results suggest intrinsic and diffusion attenuation are strongest for ASAR, while scattering and total attenuation are similarly strong for ASAR and WRA. All quality factors take higher values for PSAR than for the other two arrays, implying that the structure beneath this array is less attenuating and heterogeneous than for ASAR or WRA. The multilayer model results show the crust is more heterogeneous than the lithospheric mantle for all arrays. Crustal correlation lengths and RMS velocity fluctuations for these arrays range from ∼0.2 to 1.5 km and ∼2.3 to 3.9 per cent, respectively. Parameter values for the upper mantle are not unique, with combinations of low values of the parameters (a < 2 km and ε < ∼2.5 per cent) being as likely as those with high correlation length and velocity variations (a > 5 km and ε > ∼2.5 per cent, respectively). We attribute the similarities in the attenuation and heterogeneity structure beneath ASAR and WRA to their location on the proterozoic North Australian Craton, as opposed to PSAR, which lies on the archaean West Australian Craton. Differences in the small-scale structure beneath ASAR and WRA can be ascribed to the different tectonic histories of these two regions of the same craton. Overall, our results highlight the suitability of the combination of an energy flux model and a Bayesian inference algorithm for future scattering and small-scale heterogeneity studies, since our approach allows us to obtain and compare the different quality factors, while also giving us detailed information about the trade-offs and uncertainties in the determination of the scattering parameters.

SCOPE 2.0: a model to simulate vegetated land surface fluxes and satellite signals

Abstract. The Soil Canopy Observation of Photosynthesis and Energy fluxes (SCOPE) model aims at linking satellite observations in the visible, infrared, and thermal domains with land surface processes in a physically based manner, and quantifying the microclimate in vegetation canopies. It simulates radiative transfer in the soil, leaves, and vegetation canopies, as well as photosynthesis and non-radiative heat dissipation through convection and mechanical turbulence. Since the first publication 12 years ago, SCOPE has been applied in remote sensing studies of solar-induced chlorophyll fluorescence (SIF), energy balance fluxes, gross primary production (GPP), and directional thermal signals. Here, we present a thoroughly revised version, SCOPE 2.0, which features a number of new elements: (1) it enables the definition of layers consisting of leaves with different properties, thus enabling the simulation of vegetation with an understorey or with a vertical gradient in leaf chlorophyll concentration; (2) it enables the simulation of soil reflectance; (3) it includes the simulation of leaf and canopy reflectance changes induced by the xanthophyll cycle; and (4) the computation speed has been reduced by 90 % compared to earlier versions due to a fundamental optimization of the model. These new features improve the capability of the model to represent complex canopies and to explore the response of remote sensing signals to vegetation physiology. The improvements in computational efficiency make it possible to use SCOPE 2.0 routinely for the simulation of satellite data and land surface fluxes. It also strengthens the operability for the numerical retrieval of land surface products from satellite or airborne data.

Modelling sun-induced fluorescence for improved evaluation of forest carbon flux (GPP): Case study of tropical deciduous forest, India

Reliable estimation of forest carbon fluxes in space and time is a major challenge. Sun-Induced Chlorophyll Fluorescence (SIF) has been found closely linked to vegetation photosynthetic activity. But the application of SIF for direct estimation of Gross Primary Productivity (GPP) is not well investigated. In this study, we demonstrate the estimation of GPP for tropical deciduous forests located in North Western Himalayan Foothills in India using simulated SIF and fluorescence quantum yield (ФF) through a modified Light Use Efficiency (LUEf) model. SIF simulated using Soil Canopy Observation, Photochemistry, and Energy fluxes (SCOPE) model provided the estimate of Photosynthetically Active Radiation (PAR) intercepted by the canopy foliage and ФF. ФF, measured through the Pulse-Amplitude Modulated (PAM) fluorometer quantifies the emission rate of SIF per unit of the absorbed photon. The integration of these factors into the proposed LUEf model offered real-time photosynthetic efficiency and improved the estimate of GPP of the deciduous forest. The results show that GPP estimated from SIF (SIFTOC) was closely related to GPPEddy with R2 = 0.91 (p<0.05) with RMSE= 29.24 gC m−2 month−1 than GPP estimated from LUE model (R2=0. 79, p<0.05) and RMSE = 96.25 gC m−2 month−1). GPPMODIS underestimated the GPP with a non-significant correlation to GPPEddy for all the months with R2=0. 36 (p<0.05) and RMSE = 188.96 gC m−2 month−1. The results obtained are promising and the proposed model can be used for estimating carbon fluxes of forests over a larger spatial scale using satellite-derived SIF.

SIFT: Modeling Solar-Induced Chlorophyll Fluorescence Over Sloping Terrain

Solar-induced chlorophyll fluorescence (SIF) is found well correlated with gross primary productivity (GPP) and a good indicator of vegetation status. However, the influence of topography on SIF has not been studied, and SIF models with topographic consideration are needed to analyze this influence. Unfortunately, apart from computationally expensive 3-D models, current SIF models cannot work with sloping terrain. An efficient 1-D SIF model with topographic consideration (SIFT) is proposed in this study based on the well-known Soil Canopy Observation, Photochemistry and Energy fluxes (SCOPE) model. The evaluation of SIFT, by comparing with the 3-D Discrete Anisotropic Radiative Transfer (DART) model, demonstrates that it has high accuracy. This study also demonstrates that ignoring topography induces significant errors (exceeding 125% for a 60° slope) in canopy SIF simulations. The conclusion that the topography is an important factor for SIF and the proposed SIFT model will benefit those who are interested in SIF simulations and applications.

Analyzing Daily Estimation of Forest Gross Primary Production Based on Harmonized Landsat-8 and Sentinel-2 Product Using SCOPE Process-Based Model

Vegetation top-of-canopy reflectance contains valuable information for estimating vegetation biochemical and structural properties, and canopy photosynthesis (gross primary production (GPP)). Satellite images allow studying temporal variations in vegetation properties and photosynthesis. The National Aeronautics and Space Administration (NASA) has produced a harmonized Landsat-8 and Sentinel-2 (HLS) data set to improve temporal coverage. In this study, we aimed to explore the potential and investigate the information content of the HLS data set using the Soil Canopy Observation of Photosynthesis and Energy fluxes (SCOPE) model to retrieve the temporal variations in vegetation properties, followed by the GPP simulations during the 2016 growing season of an evergreen Norway spruce dominated forest stand. We optimized the optical radiative transfer routine of the SCOPE model to retrieve vegetation properties such as leaf area index and leaf chlorophyll, water, and dry matter contents. The results indicated percentage differences less than 30% between the retrieved and measured vegetation properties. Additionally, we compared the retrievals from HLS data with those from hyperspectral airborne data for the same site, showing that HLS data preserve a considerable amount of information about the vegetation properties. Time series of vegetation properties, retrieved from HLS data, served as the SCOPE inputs for the time series of GPP simulations. The SCOPE model reproduced the temporal cycle of local flux tower measurements of GPP, as indicated by the high Nash–Sutcliffe efficiency value (&gt;0.5). However, GPP simulations did not significantly change when we ran the SCOPE model with constant vegetation properties during the growing season. This might be attributed to the low variability in the vegetation properties of the evergreen forest stand within a vegetation season. We further observed that the temporal variation in maximum carboxylation capacity had a pronounced effect on GPP simulations. We focused on an evergreen forest stand. Further studies should investigate the potential of HLS data across different forest types, such as deciduous stand.

Physical model inversion of the green spectral region to track assimilation rate in almond trees with an airborne nano-hyperspectral imager

Significant advances toward the remote sensing of photosynthetic activity have been achieved in the last decades, including sensor design and radiative transfer model (RTM) development. Nevertheless, finding methods to accurately quantify carbon assimilation across species and spatial scales remains a challenge. Most methods are either empirical and not transferable across scales or can only be applied if highly complex input data are available. Under stress, the photosynthetic rate is limited by the maximum carboxylation rate (Vcmax), which is determined by the leaf biochemistry and the environmental conditions. Vcmax has been connected to plant photoprotective mechanisms, photosynthetic activity and chlorophyll fluorescence emission. Recent RTM developments such as the Soil-Canopy Observation of Photosynthesis and Energy fluxes (SCOPE) model allow the simulation of the sun-induced chlorophyll fluorescence (SIF) and Vcmax effects on the canopy spectrum. This development provides an approach to retrieve Vcmax through RTM model inversion and track assimilation rate. In this study we explore SIF, narrow-band indices and RTM inversion to track changes in photosynthetic efficiency as a function of vegetation stress. We use hyperspectral imagery acquired over an almond orchard under different management strategies which affected the assimilation rates measured in the field. Vcmax used as an indicator of assimilation was retrieved through SCOPE model inversion from pure-tree crown hyperspectral data. The relationships between field-measured assimilation rates and Vcmax retrieved from model inversion were higher (r2 = 0.7–0.8) than when SIF was used alone (r2 = 0.5–0.6) or when traditional vegetation indices were used (r2 = 0.3–0.5). The method was proved successful when applied to two independent datasets acquired at two different dates throughout the season, ensuring its robustness and transferability. When applied to both dates simultaneously, the results showed a unique significant trend between the assimilation measured in the field and Vcmax derived using SCOPE (r2 = 0.56, p < 0.001). This work demonstrates that tracking assimilation in almond trees is feasible using hyperspectral imagery linked to radiative transfer-photosynthesis models.

FLiES-SIF version 1.0: three-dimensional radiative transfer model for estimating solar induced fluorescence

Abstract. Global terrestrial ecosystems control the atmospheric CO2 concentration through gross primary production (GPP) and ecosystem respiration processes. Chlorophyll fluorescence is one of the energy release pathways of excess incident light in the photosynthetic process. Over the last 10 years, extensive studies have revealed that canopy-scale Sun-induced chlorophyll fluorescence (SIF), which potentially provides a direct pathway to link leaf-level photosynthesis to global GPP, can be observed from satellites. SIF is used to infer photosynthetic capacity of plant canopy; however, it is not clear how the leaf-level SIF emission contributes to the top-of-canopy directional SIF. Plant canopy radiative transfer models are useful tools to understand the mechanism of anisotropic light interactions such as scattering and absorption in plant canopies. One-dimensional (1-D) plane-parallel layer models (e.g., the Soil Canopy Observation, Photochemistry and Energy fluxes (SCOPE) model) have been widely used and are useful to understand the general mechanisms behind the temporal and seasonal variations in SIF. However, a 1-D model does not explain the complexity of the actual canopy structures. Three-dimensional models (3-D) have a potential to delineate the realistic directional canopy SIFs. Forest Light Environmental Simulator for SIF (FLiES-SIF) version 1.0 is a 3-D Monte Carlo plant canopy radiative transfer model to understand the biological and physical mechanisms behind the SIF emission from complex forest canopies. The FLiES-SIF model is coupled with leaf-level fluorescence and a physiology module so that users are able to simulate how the changes in environmental and leaf traits as well as canopy structure affect the observed SIF at the top of the canopy. The FLiES-SIF model was designed as three-dimensional model, yet the entire modules are computationally efficient: FLiES-SIF can be easily run by moderate-level personal computers with lower memory demands and public software. In this model description paper, we focused on the model formulation and simulation schemes, and showed some sensitivity analysis against several major variables such as view angle and leaf area index (LAI). The simulation results show that SIF increases with LAI then saturated at LAI&gt;2–4 depending on the spectral wavelength. The sensitivity analysis also shows that simulated SIF radiation may decrease with LAI at a higher LAI domain (LAI&gt;5). These phenomena are seen in certain Sun and view angle conditions. This type of nonlinear and nonmonotonic SIF behavior towards LAI is also related to spatial forest structure patterns. FLiES-SIF version 1.0 can be used to quantify the canopy SIF in various view angles including the contribution of multiple scattering which is the important component in the near-infrared domain. The potential use of the model is to standardize the satellite SIF by correcting the bidirectional effect. This step will contribute to the improvement of the GPP estimation accuracy through SIF.

Simulation and Verification of Vertical Heterogeneity Spectral Response of Winter Wheat Based on the mSCOPE Model.

Vertical heterogeneity of the biochemical characteristics of crop canopy is important in diagnosing and monitoring nutrition, disease, and crop yield via remote sensing. However, the research on vertical isomerism was not comprehensive. Experiments were carried out from the two levels of simulation and verification to analyze the applicability of this recently development model. Effects of winter wheat on spectrum were studied when input different structure parameters (e.g., leaf area index (LAI)) and physicochemical parameters (e.g., chlorophyll content () and water content ()) to the mSCOPE (Soil Canopy Observation, Photochemistry, and Energy fluxes) model. The maximum operating efficiency was 127.43, when the winter wheat was stratified into three layers. Meanwhile, the simulation results also proved that: the vertical profile of LAI had an influence on canopy reflectance in almost all bands; the vertical profile of mainly affected the reflectivity of visible region; the vertical profile of only affected the near-infrared reflectance. The verification results showed that the vegetation indexes (VIs) selected of different bands were strongly correlated with the parameters of the canopy. LAI, and affected VIs estimation related to LAI, and respectively. The Root Mean Square Error (RMSE) of the new-proposed was the smallest, which was 0.05. Sensitivity analysis showed that the spectrum was more sensitive to changes in upper layer parameters, which verified the rationality of mSCOPE model in explaining the law that light penetration in vertical nonuniform canopy gradually decreases with the increase of layers.

The relationship between solar-induced fluorescence and gross primary productivity under different growth conditions: global analysis using satellite and biogeochemical model data

ABSTRACT Solar-induced fluorescence (SIF) has become a milestone for estimating terrestrial gross primary productivity (GPP) at the global scale, and therefore it is important to understand how the relationship between SIF and GPP varies with environmental stresses and canopy structures. Our study investigated the impact of environmental conditions on the relationship between SIF and GPP at the global scale based on Global Ozone Monitoring Instrument 2 (GOME-2) SIF and Max Planck Institute for Biogeochemistry (MPI-BGC) GPP. GOME-2 SIF had strong correlations with gridded GPP data at instantaneous (R 2 = 0.618, p < 0.001) and daily timescales (R 2 = 0.621, p < 0.001) across the globe in eleven major biomes. Strong linear relationships were also consistently found for nine individual biomes at the daily timescale (R 2 = 0.512–0.839, p < 0.001) but were not found for evergreen broadleaf forests (EBF) (R 2 = 0.142, p < 0.001) and closed shrublands (R 2 = 0.395, p < 0.001). Generally, high coefficients of determination (R 2 > 0.8) were mainly distributed in southern Europe, southern and central Africa, northeastern and central China, North America, India and southern Russia, and the slope had a similar spatial distribution as the coefficients of determination. The relationship between SIF and GPP varied with air temperature (T Air), vapour pressure deficit (VPD) and leaf area index (LAI). The slope of the SIF-GPP relationship had a maximal value when the air temperature ranged between approximately 10°C and 20°C, when the linear relationships between SIF and GPP were also the strongest. Our analysis based on the Soil-Canopy Observation of Photochemistry and Energy fluxes (SCOPE) model also indicated that the SIF-GPP relationship was complex and affected by T Air, VPD and LAI. Our study can improve our understanding of the functional relationship between SIF and GPP and the information contained in remotely sensed SIF.

Estimation of Seasonal Sun-Induced Fluorescence Dynamics of Indian Tropical Deciduous Forests using SCOPE and Sentinel-2 MSI

This paper presents a new approach to estimate spatial Sun-Induced Fluorescence (SIF) using the empirical relationship between simulated Canopy Chlorophyll Concentration (CCC) and simulated SIF. PROSAIL model [PROpriétésSPECTrales (PROSPECT) and Scattering by Arbitrarily Inclined Leaves (SAIL) models] was used to simulate CCC. CCC maps were generated through an Automated Radiative Transfer Model Operator (ARTMO) using the PROSAIL model and Sentinel-2 Multi-Spectral Imager (MSI) imagery. The Soil Canopy Observation, Photochemistry, and Energy fluxes (SCOPE) model was used to simulate SIF emitted at 740 nm (SIF740), at 760 nm (SIF760), and top of canopy (SIFTOC) (640-850 nm). The SCOPE model, configured with the specification of the Sentinel-2 sensor, simulates SIF within the spectrum range of 640-850 nm. A non-linear logarithmic relationship (R2>0.9, p < 0.05) was observed between simulated SIF and simulated CCC. Simulated CCC was linearly related to observed CCC with R2 0.88, 0.92 and 0.89 and RMSE = 0.04, 0.17 and 0.09 gm/m2 at p < 0.05 for summer, post-monsoon and early winter respectively. Whereas, the simulated CCC did not capture the full range of CCC variability for the post-monsoon season. Simulated SIF (SIF760) was well correlated with SIF from Orbiting Carbon Observatory-2 (OCO-2) satellite with R2 0.68, 0.73 and 0.73 (RMSE = <1 W/m2/sr/μm, p < 0.05) for the month of summer (April), pre-monsoon (May) and early winter season (November) respectively. Temporal SIFTOC effectively captured the seasonal variability associated with the phenology of deciduous tree species. Among various Sentinel-2 MSI derived VIs, Red Edge NDVI (RENDVI) exhibited maximum sensitivity with SIF (highest monthly average R2> 0.6, p < 0.05). The spatial SIF would serve as an useful link between airborne /satellite derived SIF and in-situ fluorescence measurements to understand multiscale SIF variability of terrestrial vegetation.

Effects of varying solar-view geometry and canopy structure on solar-induced chlorophyll fluorescence and PRI

The increasing amount of continuous time series of solar-induced fluorescence (SIF) and vegetation indices (e.g. Photochemical Reflectance Index, PRI) acquired with high temporal (sub-minute) frequencies is foreseen to allow tracking of the structural and physiological changes of vegetation in a variety of ecosystems. Coupled with observations of CO2, water, and energy fluxes from eddy covariance flux towers, these measurements can bring new insights into the remote monitoring of ecosystem functioning. However, continuously changing solar-view geometry imposes directional effects on diurnal cycles of the fluorescence radiance in the observation direction (F) and PRI, controlled by structural and biochemical vegetation properties. An improved understanding of these variations can potentially help to disentangle directional responses of vegetation from physiological ones in the continuous long-term optical measurements and, therefore, allow to deconvolve the physiological information relevant to ecosystem functioning. Moreover, this will also be useful for better interpreting and validating F and PRI satellite products (e.g., from the upcoming ESA FLEX mission).Many previous studies focused on the characterization of reflectance directionality, but only a handful of studies investigated directional effects on F and vegetation indices related to plant physiology. The aim of this study is to contribute to the understanding of red (F687) and far-red (F760) fluorescence and PRI anisotropy based on field spectroscopy data and simulations with the Soil-Canopy Observation of Photochemistry and Energy fluxes (SCOPE) model. We present an extensive dataset of multi-angular measurements of F and PRI collected at canopy level with a high-resolution instrument (FloX, JB Hyperspectral Devices UG, Germany) over different ecosystems: Mediterranean grassland, alfalfa, chickpea and rice.We found, that F760 and F687 directional responses of horizontally homogeneous canopies are characterized by higher values in the backscatter direction with a maximum in the hotspot and lower values in the forward scatter direction. The PRI exhibited similar response due to its sensitivity to sunlit-shaded canopy fractions.As confirmed by radiative transfer forward simulations, we show that in the field measurements leaf inclination distribution function controls the shape of F and PRI anisotropic response (bowl-like/dome-like shapes), while leaf area index and the ratio of leaf width to canopy height affect the magnitude and the width of the hotspot. Finally, we discuss the implications of off-nadir viewing geometry for continuous ground measurements. F observations under oblique viewing angles showed up to 67 % difference compared to nadir observations, therefore, we suggest maintaining nadir viewing geometry for continuous measurements of F and vegetation indices. Alternatively, a correction scheme should be developed and tested against multi-angular measurements to properly account for anisotropy of canopy F and PRI observations. The quantitative characterization of these effects in varying illumination geometries for different canopies that was performed in this study will also be useful for the validation of remote sensing F and PRI products at different spatial and temporal scales.

Bioconvection of Maxwell nanofluid under the influence of double diffusive Cattaneo–Christov theories over isolated rotating disk

An incompressible, MHD, bioconvective flow of Maxwell fluid is studied. The rotating isolated disk caused the fluid motion. The disk also stretches with constant rate along radial direction. Cattaneo–Christov energy and mass species flux models are adopted. Buongiorno model of nanofluid is executed in the constitutive equations along with gyrotactic microorganisms. The transformation of Von-Karman assist to obtained nonlinear system of ordinary differential equations. The final controlled equations are resolved by adopting Runge–Kutta–Fehlberg numerical procedure. Graphical illustrations of results are accounted. It is percieved that velocity field is reduced by velocity ratio parameter. themphoretic, Brownian motion and thermal relaxation time parameters enhanced thermal fields respectively. Motile organisms rate is declined due to bioconvection Peclet number.

Aboveground traits define differences in biomass allocation among 16 prairie species

Agrosystems, Geosciences & EnvironmentVolume 3, Issue 1 e220117 COVER IMAGE Aboveground traits define differences in biomass allocation among 16 prairie species First published: 08 October 2020 https://doi.org/10.1002/agg2.20117AboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onEmailFacebookTwitterLinked InRedditWechat Abstract On the cover: Surface energy fluxes play a crucial role in quantifying the dynamics of water and energy use efficiencies of agroecosystems. This image shows operation of flux towers to measure surface energy fluxes during the non-growing (dormant) season. These flux towers are 2 of the 10 towers that operate as a part of the Nebraska Water and Energy Flux Measurement, Modeling and Research Network (NEBFLUX) that was established by Suat Irmak. All these flux towers have been operating on an hourly basis since 2004 for various vegetation surfaces. See Kukal and Irmak: https://doi.org/10.1002/agg2.20110. Photo by Suat Irmak. Volume3, Issue12020e220117 RelatedInformation

Inversion of the fluorescence spectral information of vegetation chlorophyll based on the inverted Gaussian model

In this study, the principle, advantages, and disadvantages of the three representative chlorophyll fluorescence remote-sensing inversion algorithms standard Fraunhofer Line Discrimination(FLD), 3FLD, and improved FLD (iFLD) were compared and analyzed, and the inverted Gaussian model fluorescence inversion algorithm (IGM-FLD) was proposed. Vegetation canopy spectral data were simulated by the soil canopy observation, photochemistry, and energy flux (SCOPE) model. The analysis of the simulated and measured spectral data revealed that in contrast to the model parameters of sFLD, 3FLD, and iFLD, those of IGM-FLD have definite physical meanings. In addition, the apparent reflectance baseline of IGM-FLD was more reasonable than that of the other models. Given these properties, the fluorescence inversion accuracy of the IGM-FLD model was higher than that of the other three models. Moreover, it only required the construction of a reflectance baseline in the 680–800 nm spectral range and can simultaneously invert the fluorescence information of the O2-B and O2-A bands.

Global Sensitivity Analysis of the SCOPE Model in Sentinel-3 Bands: Thermal Domain Focus

Sentinel-3 satellite has provided simultaneous observations in the optical (visible, near infrared (NIR), shortwave infrared (SWIR)) and thermal infrared (TIR) domains since 2016, with a revisit time of 1–2 days. The high temporal resolution and spectral coverage make the data of this mission attractive for vegetation monitoring. This study explores the possibilities of using the Soil Canopy Observation, Photochemistry and Energy fluxes (SCOPE) model together with Sentinel-3 to exploit the two sensors onboard of Sentinel-3 (the ocean and land color instrument (OLCI) and sea and land surface temperature radiometer (SLSTR)) in synergy. Sobol’ variance based global sensitivity analysis (GSA) of top of atmosphere (TOA) radiance produced with a coupled SCOPE-6S model was conducted for optical bands of OLCI and SLSTR, while another GSA of SCOPE was conducted for the land surface temperature (LST) product of SLSTR. The results show that in addition to ESA level-2 Sentinel-3 products, SCOPE is able to retrieve leaf area index (LAI), leaf chlorophyll content (Cab), leaf water content (Cw), leaf senescent material (Cs), leaf inclination distribution (LAD). Leaf dry matter content (Cdm) and soil brightness, despite being important, were not confidently retrieved in some cases. GSA of LST in TIR domain showed that plant biochemical parameters—maximum carboxylation rate (Vcmax) and stomata conductance-photosynthesis slope (Ball-Berry m)—can be constrained if prior information on near-surface weather conditions is available. We conclude that the combination of optical and thermal domains facilitates the constraint of the land surface energy balance using SCOPE.