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At least 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Grazer-induced changes in molecular signatures of cyanobacteria

Algal biomass production is an emerging renewable source of fuels, nutrients, manufacturing materials, and pharmaceuticals. Industrial-scale production is predominantly performed in open raceway ponds that are inexpensive to build, operate, and maintain compared to closed bioreactors. However, these open pond systems suffer from increased opportunities for biological contamination from predators, pathogens, and competitors, which result in reduced biomass quality and yields and often the complete destruction of the crop over a short period of time. Early detection of contaminants is a necessary step of integrated pest management for triggering and informing interventions to prevent crop losses. To develop a sensitive method of detection utilizing mass spectrometry (MS), we used three methods – imaging mass spectrometry (imaging MS), liquid chromatography MS/MS (LC-MS/MS) combined with molecular networking, and gas chromatography MS/MS (GC–MS/MS) – to observe and identify molecular signatures from a model predator-prey system of the heterolobosean amoeba HGG1 preying on the filamentous cyanobacterium Anabaena sp. PCC 7120. Imaging MS enabled the association of molecules with the crop, the predator, or the activity of protozoan grazing, while LC-MS/MS-based molecular networking identified a subset of the grazing-specific signals as the chlorophyll breakdown products pyropheophytin, pheophorbide A, and pyropheophorbide. Application of MS techniques to other amoebacyanobacterial predator-prey pairs allowed categorization of grazing signatures as universal or specific to the species of prey, predator, or the prey-predator pairing, indicating that MS-based techniques can distinguish crops from competitors and potentially identify predators. Finally, GCMS/MS was shown to be capable of monitoring novel volatile organic compounds (VOCs), including those predicted to be released through chlorophyll breakdown, in the headspace over algal cultures under predation. Furthermore, these results demonstrate that the combination of multiple MS technologies creates a predictive framework to identify and catalog relevant molecular signatures for informing crop protection strategies.

09 BIOMASS FUELS↗
DOE OSTI2021

Structure of a photosystem I-ferredoxin complex from a marine cyanobacterium provides insights into far-red light photoacclimation

Far-red light photoacclimation (FaRLiP) exhibited by some cyanobacteria allows these organisms to use light of the far-red region of the solar spectrum (700 to 800 nm) for photosynthesis. Part of this process includes the replacement of six photosystem I (PSI) subunits with isoforms that confer the binding of chlorophyll (Chl) f molecules that are synthesized by chlorophyll f synthase and that absorb far-red light. However, the exact sites at which Chl f molecules are bound are still challenging to determine. To aid in the identification of Chl fbinding sites, we solved the cryo-EM structure of PSI from far-red light-acclimated cells (FRLPSI) of the cyanobacterium Synechococcus sp. PCC 7335. We identified six sites that bind Chl f with high specificity, and three additional sites that are likely to bind Chl f at lower specificity. All of these binding sites are in the core antenna regions of PSI, and Chl f was not observed among the electron transport cofactors. This structural analysis also reveals both conserved and non-conserved Chl f-binding sites, the latter of which exemplify the diversity in FRL-PSI among species. We found that the FRL-PSI structure also contains a bound soluble ferredoxin, PetF1, at low occupancy, which suggests that ferredoxin binds less transiently than expected according to the canonical view of ferredoxin-binding to facilitate electron transfer. We suggest that this may result from structural changes in FRL-PSI that occur specifically during FaRLiP.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Anoxia begets anoxia: A positive feedback to the deoxygenation of temperate lakes

Abstract Declining oxygen concentrations in the deep waters of lakes worldwide pose a pressing environmental and societal challenge. Existing theory suggests that low deep‐water dissolved oxygen (DO) concentrations could trigger a positive feedback through which anoxia (i.e., very low DO) during a given summer begets increasingly severe occurrences of anoxia in following summers. Specifically, anoxic conditions can promote nutrient release from sediments, thereby stimulating phytoplankton growth, and subsequent phytoplankton decomposition can fuel heterotrophic respiration, resulting in increased spatial extent and duration of anoxia. However, while the individual relationships in this feedback are well established, to our knowledge, there has not been a systematic analysis within or across lakes that simultaneously demonstrates all of the mechanisms necessary to produce a positive feedback that reinforces anoxia. Here, we compiled data from 656 widespread temperate lakes and reservoirs to analyze the proposed anoxia begets anoxia feedback. Lakes in the dataset span a broad range of surface area (1–126,909 ha), maximum depth (6–370 m), and morphometry, with a median time‐series duration of 30 years at each lake. Using linear mixed models, we found support for each of the positive feedback relationships between anoxia, phosphorus concentrations, chlorophyll a concentrations, and oxygen demand across the 656‐lake dataset. Likewise, we found further support for these relationships by analyzing time‐series data from individual lakes. Our results indicate that the strength of these feedback relationships may vary with lake‐specific characteristics: For example, we found that surface phosphorus concentrations were more positively associated with chlorophyll a in high‐phosphorus lakes, and oxygen demand had a stronger influence on the extent of anoxia in deep lakes. Taken together, these results support the existence of a positive feedback that could magnify the effects of climate change and other anthropogenic pressures driving the development of anoxia in lakes around the world.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Light regulation of light-harvesting antenna size substantially enhances photosynthetic efficiency and biomass yield in green algae

One of the major factors limiting biomass productivity in algae is the low thermodynamic efficiency of photosynthesis. The greatest thermodynamic inefficiencies in photosynthesis occur during the conversion of light into chemical energy. At full sunlight the light-harvesting antenna captures photons at a rate nearly 10 times faster than the rate-limiting step in photosynthetic electron transport. Excess captured energy is dissipated by non-productive pathways including the production of reactive oxygen species. Substantial improvements in photosynthetic efficiency have been achieved by reducing the optical cross-section of the light-harvesting antenna by selectively reducing chlorophyll b levels and peripheral light-harvesting complex subunits. Smaller light-harvesting antenna, however, may not exhibit optimal photosynthetic performance in low or fluctuating light environments. Additionally, we describe a translational control system to dynamically adjust light-harvesting antenna sizes for enhanced photosynthetic performance. Furthermore, by expressing a chlorophyllide a oxygenase (CAO) gene having a 5' mRNA extension encoding a Nab1 translational repressor binding site in a CAO knockout line it was possible to continuously alter chlorophyll b levels and correspondingly light-harvesting antenna sizes by light-activated Nab1 repression of CAO expression as a function of growth light intensity. Significantly, algae having light-regulated antenna sizes had substantially higher photosynthetic rates and two-fold greater biomass productivity than the parental wild-type strains as well as near wild-type ability to carry out state transitions and non-photochemical quenching. These results have broad implications for enhanced algae and plant biomass productivity.

09 BIOMASS FUELS↗
DOE OSTI2022

Integration of physiologically relevant photosynthetic energy flows into whole genome models of light‐driven metabolism

SUMMARY Characterizing photosynthetic productivity is necessary to understand the ecological contributions and biotechnology potential of plants, algae, and cyanobacteria. Light capture efficiency and photophysiology have long been characterized by measurements of chlorophyll fluorescence dynamics. However, these investigations typically do not consider the metabolic network downstream of light harvesting. By contrast, genome‐scale metabolic models capture species‐specific metabolic capabilities but have yet to incorporate the rapid regulation of the light harvesting apparatus. Here, we combine chlorophyll fluorescence parameters defining photosynthetic and non‐photosynthetic yield of absorbed light energy with a metabolic model of the pennate diatom Phaeodactylum tricornutum. This integration increases the model predictive accuracy regarding growth rate, intracellular oxygen production and consumption, and metabolic pathway usage. Through the quantification of excess electron transport, we uncover the sequential activation of non‐radiative energy dissipation processes, cross‐compartment electron shuttling, and non‐photochemical quenching as the rapid photoacclimation strategy in P. tricornutum. Interestingly, the photon absorption thresholds that trigger the transition between these mechanisms were consistent at low and high incident photon fluxes. We use this understanding to explore engineering strategies for rerouting cellular resources and excess light energy towards bioproducts in silico . Overall, we present a methodology for incorporating a common, informative data type into computational models of light‐driven metabolism and show its utilization within the design–build–test–learn cycle for engineering of photosynthetic organisms.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Molecular diversity and evolution of far-red light-acclimated photosystem I

The need to acclimate to different environmental conditions is central to the evolution of cyanobacteria. Far-red light (FRL) photoacclimation, or FaRLiP, is an acclimation mechanism that enables certain cyanobacteria to use FRL to drive photosynthesis. During this process, a well-defined gene cluster is upregulated, resulting in changes to the photosystems that allow them to absorb FRL to perform photochemistry. Because FaRLiP is widespread, and because it exemplifies cyanobacterial adaptation mechanisms in nature, it is of interest to understand its molecular evolution. Here, we performed a phylogenetic analysis of the photosystem I subunits encoded in the FaRLiP gene cluster and analyzed the available structural data to predict ancestral characteristics of FRL-absorbing photosystem I. The analysis suggests that FRL-specific photosystem I subunits arose relatively late during the evolution of cyanobacteria when compared with some of the FRL-specific subunits of photosystem II, and that the order Nodosilineales, which include strains like Halomicronema hongdechloris and Synechococcus sp. PCC 7335, could have obtained FaRLiP via horizontal gene transfer. We show that the ancestral form of FRL-absorbing photosystem I contained three chlorophyll f-binding sites in the PsaB2 subunit, and a rotated chlorophyll a molecule in the A0B site of the electron transfer chain. Along with our previous study of photosystem II expressed during FaRLiP, these studies describe the molecular evolution of the photosystem complexes encoded by the FaRLiP gene cluster.

ancestral sequence reconstruction↗
DOE OSTI2024

Monitoring water quality in the lower Kansas River using remote sensing

Abstract We demonstrate how to combine remote sensing data from satellite imagery (Sentinel‐2) with in situ water quality gauging (USGS Super Gages and the Gybe hyperspectral radiometer) to create spatially dense maps of water quality parameters (chlorophyll‐a concentration, turbidity, and nitrate plus nitrite concentration) along the lower Kansas River. The water quality maps are created using locally tuned models of the target water quality parameters, and this study describes the steps used to design, calibrate, and validate the empirical correlations. Water quality parameters such as chlorophyll‐a concentration are correlated with well‐studied absorption and scattering features in the visible spectrum (roughly 400–700 nm). Nutrients (such as nitrate plus nitrite concentration) lack strong absorption features in the visible spectrum, and in those cases we describe a novel surrogate data modeling approach that identifies overlapping water parcels between the in situ gauging and the remote sensing imagery. Measurements from the overlapping water parcels yield excellent correlations () for the target water quality parameters for limited windows of time (or limited sections of river reaches). Examples are provided illustrating how the water quality maps can be used to track river inputs from ungauged sources (such as creeks), or reveal the mixing patterns at the confluences.

Tufillaro, Nicholas↗
DOE OSTI2024

Lattice light-sheet microscopy allows for super-resolution imaging of receptors in leaf tissue

Plant leaf tissues are difficult to image via fluorescent microscopy, largely due to the presence of chlorophyll and other pigments that provide large background fluorescence. An advantage of Lattice Light-Sheet microscopy is its use of Bessel beams that illuminate a thin focal region of interest for microscopy, allowing for the excitation of fluorescent molecules within this region without surrounding chlorophyll-like objects outside of the region of interest. Here, we apply STORM Super-resolution techniques to observe Receptor-Like Kinases in Arabidopsis thaliana leaf cells. By applying this technique with the Lattice Light-Sheet, we can localize immune response proteins in sub-100 nm length scales and reconstruct three-dimensional locations of proteins within individual leaf cells. Using this technique, we observed the effect of the elicitors ATP and flg22, where we observed a significant degree of internalization of cognate receptors P2K1 and FLS2. We were also able to similarly observe differences in colocalization due to stimulation with these elicitors, where we observe proteins on the membrane becoming less colocalized as a result of stimulation, suggesting an immune response mechanism involving receptors internalizing via pathways distinct to the receptor. Further, these data show the Lattice Light-Sheet’s capabilities for imaging tissue with problematic background fluorescence that otherwise makes super-resolution fluorescence microscopy difficult.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Multi-site assessment of the potential of fine resolution red-edge vegetation indices for estimating gross primary production

Gross primary production (GPP) models driven by fine resolution remote sensing data characterize the spatial and temporal heterogeneities in plant photosynthesis, which is largely dependent on biome-specific maximum photosynthetic capacity. The red-edge reflectance, sensitive to leaf chlorophyll content, is a good proxy of maximum photosynthetic capacity. More importantly, studies show that the red-edge reflectance-related chlorophyll content index (CIr) multiplied by the incident photosynthetic active radiation (PAR in ) strongly correlates to GPP estimated at carbon flux towers (GPP flux ). Yet, to the best of our knowledge, there is no systematic study investigating the general relationship between fine spatial resolution CIr and GPP among biomes and the relationship between CIr and maximum photosynthetic capacity in GPP models. To provide an overview on incorporating space-borne CIr into a GPP model, we applied fine resolution Sentinel-2-derived CIr and GPP flux over 57 flux sites representative of 10 biomes. We investigated the relationship between CIr and GPP flux , and the spatio-temporal relationship between CIr and ecosystem maximum photosynthetic capacity indicated by the potential ecosystem light use efficiency (LUE pot ). We also evaluated the relationship between other five vegetation indices (VIs) and GPP flux . Results showed that the CIr multiplied by PARin has a higher agreement (R 2 > 0.5) with GPP than other VIs. A universal relationship exists between the CIr multiplied by PARin and GPP, except for forest biomes. The CIr also strongly (R 2 > 0.5) relates to the LUE pot during the peak of the growing season. The CIr has a low spatial variance (CV = 0.25) among biomes, highlighting that CIr can be a proxy of maximum photosynthetic capacity in GPP models that do not require biome-dependent coefficients. This study provides insight for incorporating CIr into GPP models and better quantifying global terrestrial photosynthesis.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Tracking seasonal variability in plant traits from spaceborne PRISMA and NEON AOP across forest types and ecoregions

Plant traits serve as critical indicators of how plants adapt to environmental changes and influence ecosystem functions. While airborne hyperspectral remote sensing effectively maps plant traits through detailed reflectance properties, it is limited by cost and scale, making large-scale and temporal studies challenging. The recently launched spaceborne hyperspectral imager, PRecursore IperSpettrale della Missione Applicativa (PRISMA), offers frequent, large scale and high-fidelity observations on a spatial resolution of 30 m and a revisit time of around 29 days, making it suitable for large-scale seasonal trait mapping. However, their potential remains largely unexplored. This study developed a multi-stage framework by leveraging the PRISMA spaceborne hyperspectral data and National Ecological Observatory Network (NEON) Airborne Observation Platform (AOP) hyperspectral data to investigate the seasonal dynamics of four key plant traits — chlorophyll content, carotenoid content, equivalent water thickness, and nitrogen content — across eleven NEON sites representing diverse forest types and ecoregions in the contiguous U.S. Our results demonstrated that PRISMA hyperspectral data can reliably track seasonal variability in plant traits, achieving overall R 2 values ranging from 0.78 to 0.88 and normalized root mean square error (NRMSE) values ranging from 5.4% to 8.4% for the four traits. Seasonal patterns revealed bell-shaped trajectories for chlorophyll and carotenoids, while equivalent water thickness decreased steadily across most sites, driven by structural changes during leaf maturation and senescence. Nitrogen content exhibited less pronounced seasonal variation but followed expected nutrient resorption patterns. Analysis of environmental drivers showed that seasonal variability is primarily controlled by solar radiation and day length in northern sites, vapor pressure in semi-arid regions, and temperature in mid-southeastern sites. Spatial variability, meanwhile, was primarily driven by soil properties, particularly during the peak growing season. However, the influence of soil variables slightly declines toward the end of the season at several sites, as climatic factors become more prominent. This study highlights the capability of PRISMA, and potentially other similar spaceborne hyperspectral data for large-scale, time-series plant trait mapping and provides valuable insights into the interactions between plant traits and environmental factors. In conclusion, these findings contribute to advancing our understanding of plant functional ecology and improving predictions of ecosystem responses to environmental changes.

Environmental drivers↗
DOE OSTI2020

Real-time monitoring and prediction of water quality parameters and algae concentrations using microbial potentiometric sensor signals and machine learning tools

We report the overarching hypothesis of this study was that temporal microbial potentiometric sensor (MPS) signal patterns could be used to predict changes in commonly monitored water quality parameters by using artificial intelligence/machine learning tools. To test this hypothesis, the study first examines a proof of concept by correlating between MPS's signals and high algae concentrations in an algal cultivation pond. Then, the study expanded upon these findings and examined if multiple water quality parameters could be predicted in real surface waters, like irrigation canals. Signals generated between the MPS sensors and other water quality sensors maintained by an Arizona utility company, including algae and chlorophyll, were collected in real time at time intervals of 30 min over a period of 9 months. Data from the MPS system and data collected by the utility company were used to train the ML/AI algorithms and compare the predicted with actual water quality parameters and algae concentrations. Based on the composite signal obtained from the MPS, the ML/AI was used to predict the canal surface water's turbidity, conductivity, chlorophyll, and blue-green algae (BGA), dissolved oxygen (DO), and pH, and predicted values were compared to the measured values. Initial testing in the algal cultivation pond revealed a strong linear correlation (R 2 = 0.87) between mixed liquor suspended solids (MLSS) and the MPSs' composite signals. The Normalized Root Mean Square Error (NRMSE) between the predicted values and measured values were <6.5%, except for the DO, which was 10.45%. The results demonstrate the usefulness of MPSs to predict key surface water quality parameters through a single composite signal, when the ML/AI tools are used conjunctively to disaggregate these signal components. The maintenance-free MPS offers a novel and cost-effective approach to monitor numerous water quality parameters at once with relatively high accuracy.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Two-Dimensional Electronic Spectroscopy of the Far-Red-Light Photosystem II Reaction Center

Understanding the role of specific pigments in primary energy conversion in the photosystem II (PSII) reaction center has been impeded by the spectral overlap of its constituent pigments. When grown in far-red light, some cyanobacteria incorporate chlorophyll-f and chlorophyll-d into PSII, relieving the spectral congestion. Here we employ two-dimensional electronic spectroscopy to study PSII at 77 K from Synechococcus sp. PCC 7335 cells that were grown in far-red light (FRL-PSII). We observe the formation of a radical pair within ~3 ps that we assign to Chl D1 •– P D1 •+ . While Pheo D1 is thought to act as the primary electron acceptor in PSII from cells grown in visible light, we see no evidence of its involvement, which we attribute to its reduction by dithionite treatment in our samples. Our work demonstrates that primary charge separation occurs between Chl D1 and P D1 in FRL-PSII, suggesting that P D1 /P D2 may play an underappreciated role in PSII’s charge separation mechanism.

14 SOLAR ENERGY↗
DOE OSTI2021

Tower-Based Remote Sensing Reveals Mechanisms Behind a Two-phased Spring Transition in a Mixed-Species Boreal Forest

The boreal forest is a major contributor to the global climate system, therefore, reducing uncertainties in how the forest will respond to a changing climate is critical. One source of uncertainty is the timing and drivers of the spring transition. Remote sensing can provide important information on this transition, but persistent foliage greenness, seasonal snow cover, and a high prevalence of mixed forest stands (both deciduous and evergreen species) complicate interpretation of these signals. We collected tower-based remotely sensed data (reflectance-based vegetation indices and Solar-Induced Chlorophyll Fluorescence [SIF]), stem radius measurements, gross primary productivity, and environmental conditions in a boreal mixed forest stand. Evaluation of this data set shows a two-phased spring transition. The first phase is the reactivation of photosynthesis and transpiration in evergreens, marked by an increase in relative SIF, and is triggered by thawed stems, warm air temperatures, and increased available soil moisture. The second phase is a reduction in bulk photoprotective pigments in evergreens, marked by an increase in the Chlorophyll-Carotenoid Index. Deciduous leaf-out occurs during this phase, marked by an increase in all remotely sensed metrics. The second phase is controlled by soil thaw. Our results demonstrate that remote sensing metrics can be used to detect specific physiological changes in boreal tree species during the spring transition. The two-phased transition explains inconsistencies in remote sensing estimates of the timing and drivers of spring recovery. Our results imply that satellite-based observations will improve by using a combination of vegetation indices and SIF, along with species distribution information.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

River Geomorphology Affects Biogeochemical Responses to Hydrologic Events in a Large River Ecosystem

Shifts in the frequency and intensity of high discharge events due to climate change may have important consequences for the hydrology and biogeochemistry of rivers. However, our understanding of event-scale biogeochemical dynamics in large rivers lags that of small streams. To fill this gap, we used high-frequency sensor data collected during four consecutive summers from a main channel and backwater site of the Upper Mississippi River. We identified high discharge events and calculated event concentration-discharge responses for both physical-chemical (nitrate, turbidity, and fluorescent dissolved organic matter) and biological (chlorophyll-a and cyanobacteria) constituents using metrics of hysteresis and slope. We found a range of responses across events, particularly for nitrate. Although fluorescent dissolved organic matter (FDOM) and turbidity exhibited more consistent responses across events, contrasting hysteresis metrics indicated that FDOM was flushed to the river from more distant sources than turbidity. Biological responses (chlorophyll a and cyanobacteria) differed more between sites than physical and chemical constituents. Lastly, we found that the event characteristics best explaining concentration responses differed between sites, with event magnitude more frequently related to responses in the main channel, and antecedent wetness conditions associated with response variation in the backwater. Furthermore, our results indicate that event responses in large rivers are distinct across the diverse habitats and biogeochemical components of a large floodplain river, which has implications for local and downstream ecosystems as the climate shifts.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Enhanced Cross-Shelf Exchange by the Eddies Associated With Plume Front

Broadened width of high chlorophyll concentration band with wavy structures, patches, and filaments are often observed along the western coastal next to the Pearl River Estuary over the northern South China Sea shelf during the transition period from winter to summer monsoon. Whereas, there is no such wide band in other seasons. By using a high-resolution numerical model, we reveal that the complex structure and wider band of high coastal chlorophyll concentration results from the smaller scale eddies (about 20–50 km in diameter) associated with buoyant plume-induced salinity front and density fronts, which are roughly along the 30 and 50 m isobaths, respectively. Two trains of eddies are formed along the fronts by the baroclinic instability triggered by frequently alternating winds over the fronts during the period of monsoon transition. The influences of these two trains of eddies are extended in the cross-shelf direction by their interactions, and they can temporally enhance the cross-shelf flow and material exchange. In conclusion, they serve as an efficient pathway to link the inner shelf toward the continental slope.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Environmental Factors Associated With Fall Phytoplankton Blooms in the Northern Bering and Chukchi Seas

This study investigates environmental drivers of fall phytoplankton blooms in the Arctic, focusing on the northern Bering and Chukchi seas. Random Forests models were used to analyze covariates of fall phytoplankton blooms from 2013 to 2018, incorporating shipboard, remote sensing, and modeled environmental properties. Four regional models and one comprehensive all-station model considered fall as well as midsummer conditions. Midsummer properties included suspended particulate matter, chlorophyll-a, and the proportion of degraded pheophytin to chlorophyll-a used as a proxy for bloom stage. Open water duration was one of the highest ranked factors in predicting fall blooms. Open water duration also influences the stage of midsummer (July) blooms as indicated by pheophytin proportions, which in turn were the highest-ranked factor for predicting fall bloom events in the Chirikov Basin (northern Bering Sea between St. Lawrence Island and the Bering Strait) and the Chukchi Sea. Wind direction, specifically easterly winds, was an important predictor in the northern Bering Sea. Maximum wind speed ranked highly at stations located within the nutrient-poor Alaska Coastal Current in the Chukchi Sea. However, stormy days, average and maximum wind speeds generally ranked low in importance as a predictor of fall bloom events. Other parameters, including photosynthetic active radiation, modeled nutrient concentrations, mixed layer depth, and time since sea ice breakup date showed strong but regionally varying relationships with fall blooms. Altogether, results from these Random Forests models suggest that high wind events and storms in the absence of sea ice provide an incomplete narrative for initiating fall bloom events.

Gaffey, C. B. [Clark University, Worcester, MA (Un↗
DOE OSTI2020

Vibronic mixing enables ultrafast energy flow in light-harvesting complex II

Since the discovery of quantum beats in the two-dimensional electronic spectra of photosynthetic pigment-protein complexes over a decade ago, the origin and mechanistic function of these beats in photosynthetic light-harvesting has been extensively debated. The current consensus is that these long-lived oscillatory features likely result from electronic-vibrational mixing, however, it remains uncertain if such mixing significantly influences energy transport. Here, we examine the interplay between the electronic and nuclear degrees of freedom (DoF) during the excitation energy transfer (EET) dynamics of light-harvesting complex II (LHCII) with two-dimensional electronic-vibrational spectroscopy. Particularly, we show the involvement of the nuclear DoF during EET through the participation of higher-lying vibronic chlorophyll states and assign observed oscillatory features to specific EET pathways, demonstrating a significant step in mapping evolution from energy to physical space. These frequencies correspond to known vibrational modes of chlorophyll, suggesting that electronic-vibrational mixing facilitates rapid EET over moderately size energy gaps.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Structural complexity biases vegetation greenness measures

Vegetation ‘greenness’ characterized by spectral vegetation indices (VIs) is an integrative measure of vegetation leaf abundance, biochemical properties and pigment composition. Surprisingly, satellite observations reveal that several major VIs over the US Corn Belt are higher than those over the Amazon rainforest, despite the forests having a greater leaf area. This contradicting pattern underscores the pressing need to understand the underlying drivers and their impacts to prevent misinterpretations. Here we show that macroscale shadows cast by complex forest structures result in lower greenness measures compared with those cast by structurally simple and homogeneous crops. The shadow-induced contradictory pattern of VIs is inevitable because most Earth-observing satellites do not view the Earth in the solar direction and thus view shadows due to the sun–sensor geometry. The shadow impacts have important implications for the interpretation of VIs and solar-induced chlorophyll fluorescence as measures of global vegetation changes. For instance, a land-conversion process from forests to crops over the Amazon shows notable increases in VIs despite a decrease in leaf area. In conclusion, our findings highlight the importance of considering shadow impacts to accurately interpret remotely sensed VIs and solar-induced chlorophyll fluorescence for assessing global vegetation and its changes.

60 APPLIED LIFE SCIENCES↗