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At least 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
NASA NTRS2013

Regional to Global Assessments of Phytoplankton Dynamics From The SeaWiFS Mission

Photosynthetic production of organic matter by microscopic oceanic phytoplankton fuels ocean ecosystems and contributes roughly half of the Earth's net primary production. For 13 years, the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) mission provided the first consistent, synoptic observations of global ocean ecosystems. Changes in the surface chlorophyll concentration, the primary biological property retrieved from SeaWiFS, have traditionally been used as a metric for phytoplankton abundance and its distribution largely reflects patterns in vertical nutrient transport. On regional to global scales, chlorophyll concentrations covary with sea surface temperature (SST) because SST changes reflect light and nutrient conditions. However, the oceanmay be too complex to be well characterized using a single index such as the chlorophyll concentration. A semi-analytical bio-optical algorithm is used to help interpret regional to global SeaWiFS chlorophyll observations from using three independent, well-validated ocean color data products; the chlorophyll a concentration, absorption by CDM and particulate backscattering. First, we show that observed long-term, global-scale trends in standard chlorophyll retrievals are likely compromised by coincident changes in CDM. Second, we partition the chlorophyll signal into a component due to phytoplankton biomass changes and a component caused by physiological adjustments in intracellular chlorophyll concentrations to changes in mixed layer light levels. We show that biomass changes dominate chlorophyll signals for the high latitude seas and where persistent vertical upwelling is known to occur, while physiological processes dominate chlorophyll variability over much of the tropical and subtropical oceans. The SeaWiFS data set demonstrates complexity in the interpretation of changes in regional to global phytoplankton distributions and illustrates limitations for the assessment of phytoplankton dynamics using chlorophyll retrievals alone.

phytoplankton↗
DOE OSTI2022

Molecular Evolution of Far-Red Light-Acclimated Photosystem II

Cyanobacteria are major contributors to global carbon fixation and primarily use visible light (400−700 nm) to drive oxygenic photosynthesis. When shifted into environments where visible light is attenuated, a small, but highly diverse and widespread number of cyanobacteria can express modified pigments and paralogous versions of photosystem subunits and phycobiliproteins that confer far-red light (FRL) absorbance (700−800 nm), a process termed far-red light photoacclimation, or FaRLiP. During FaRLiP, alternate photosystem II (PSII) subunits enable the complex to bind chlorophylls d and f, which absorb at lower energy than chlorophyll a but still support water oxidation. How the FaRLiP response arose remains poorly studied. Here, we report ancestral sequence reconstruction and structure-based molecular evolutionary studies of the FRL-specific subunits of FRL-PSII. We show that the duplications leading to the origin of two PsbA (D1) paralogs required to make chlorophyll f and to bind chlorophyll d in water-splitting FRL-PSII are likely the first to have occurred prior to the diversification of extant cyanobacteria. These duplications were followed by those leading to alternative PsbC (CP43) and PsbD (D2) subunits, occurring early during the diversification of cyanobacteria, and culminating with those leading to PsbB (CP47) and PsbH paralogs coincident with the radiation of the major groups. We show that the origin of FRL-PSII required the accumulation of a relatively small number of amino acid changes and that the ancestral FRL-PSII likely contained a chlorophyll d molecule in the electron transfer chain, two chlorophyll f molecules in the antenna subunits at equivalent positions, and three chlorophyll a molecules whose site energies were altered. The results suggest a minimal model for engineering far-red light absorbance into plant PSII for biotechnological applications.

ancestral sequence reconstruction↗
NASA NTRS2009

An Empirical Approach to Ocean Color Data: Reducing Bias and the Need for Post-Launch Radiometric Re-Calibration

A new empirical approach is developed for ocean color remote sensing. Called the Empirical Satellite Radiance-In situ Data (ESRID) algorithm, the approach uses relationships between satellite water-leaving radiances and in situ data after full processing, i.e., at Level-3, to improve estimates of surface variables while relaxing requirements on post-launch radiometric re-calibration. The approach is evaluated using SeaWiFS chlorophyll, which is the longest time series of the most widely used ocean color geophysical product. The results suggest that ESRID 1) drastically reduces the bias of ocean chlorophyll, most impressively in coastal regions, 2) modestly improves the uncertainty, and 3) reduces the sensitivity of global annual median chlorophyll to changes in radiometric re-calibration. Simulated calibration errors of 1% or less produce small changes in global median chlorophyll (less than 2.7%). In contrast, the standard NASA algorithm set is highly sensitive to radiometric calibration: similar 1% calibration errors produce changes in global median chlorophyll up to nearly 25%. We show that 0.1% radiometric calibration error (about 1% in water-leaving radiance) is needed to prevent radiometric calibration errors from changing global annual median chlorophyll more than the maximum interannual variability observed in the SeaWiFS 9-year record (+/- 3%), using the standard method. This is much more stringent than the goal for SeaWiFS of 5% uncertainty for water leaving radiance. The results suggest ocean color programs might consider less emphasis of expensive efforts to improve post-launch radiometric re-calibration in favor of increased efforts to characterize in situ observations of ocean surface geophysical products. Although the results here are focused on chlorophyll, in principle the approach described by ESRID can be applied to any surface variable potentially observable by visible remote sensing.

Gregg, Watson W.↗
NASA NTRS2013

Algorithm Development for Predicting Biodiversity Based on Phytoplankton Absorption

Ocean color remote sensing has provided the scientific community with unprecedented global coverage of chlorophyll a, an indicator of phytoplankton biomass. Together, satellite-derived chlorophyll a and knowledge of Phytoplankton Functional Types (PFTs) will improve our limited understanding of marine ecosystem responses to physiochemical climate drivers involved in carbon cycle dynamics and linkages. Using cruise data from the Gulf of Maine and the Middle Atlantic Bight (N 269 pairs of HPLC and phytoplankton absorption samples), two modeling approaches were utilized to predict phytoplankton absorption and pigments. Algorithm I predicts the chlorophyll-specific absorption coefficient (a*(sub ph) (m(exp 2) mg chl a(exp - 1)) using inputs of temperature, light, and chlorophyll a. Modeled r(exp 2) values (400700 nm) ranged from 0.79 to 0.99 when compared to in situ observations with approximately 25 percent lower r(exp 2) values in the UV region. Algorithm II-a utilizes matrix inversion analysis to predict a(sub ph)(m(exp -1), 400700 nm) and r(exp 2) values ranged from 0.89 to 0.99. The prediction of phytoplankton pigments with Algorithm II-b produced r(exp 2) values that ranged from 0.40 to 0.93. When used in combination, Algorithm I, and Algorithm II-a are able to use satellite products of SST, PAR, and chlorophyll a (Algorithm I) to predict pigment concentrations and ratios to describe the phytoplankton community. The results of this study demonstrate that the spatial variation in modeled pigment ratios differ significantly from the 10-year SeaWiFS average chlorophyll a data set. Contiguous observations of chlorophyll a and phytoplankton biodiversity will elucidate ecosystem responses with unprecedented complexity.

phytoplankton↗
NASA NTRS1988

Non-destructive plant health sensing using absorption spectroscopy

The sensor group of the 1988 EGM 4001 class, working on NASA's Controlled Ecological Life Support Systems (CELSS) project, investigated many different plant health indicators and the technologies used to test them. The project selected by the group was to measure chlorophyll levels using absorption spectroscopy. The spectrometer measures the amount of chlorophyll in a leaf by measuring the intensity of light of a specific wavelength that is passed through a leaf. The three wavelengths of light being used corresponded to the near-IR absorption peaks of chlorophyll a, chlorophyll b, and chlorophyll-free structures. Experimentation showed that the sensor is indeed measuring levels of chlorophyll a and b and their changes before the human eye can see any changes. The detector clamp causes little damage to the leaf and will give fairly accurate readings on similar locations on a leaf, freeing the clamp from having to remain on the same spot of a leaf for all measurements. External light affects the readings only slightly so that measurements may be taken in light or dark environments. Future designs and experimentation will concentrate on reducing the size of the sensor and adapting it to a wider range of plants.

Bledsoe, Jim↗
NASA NTRS2001

Observations of Ocean Primary Productivity Using MODIS

Measuring the magnitude and variability of oceanic net primary productivity (NPP) represents a key advancement toward our understanding of the dynamics of marine ecosystems and the role of the ocean in the global carbon cycle. MODIS observations make two new contributions in addition to continuing the bio-optical time series begun with Orbview-2's SeaWiFS sensor. First, MODIS provides weekly estimates of global ocean net primary productivity on weekly and annual time periods, and annual empirical estimates of carbon export production. Second, MODIS provides additional insight into the spatial and temporal variations in photosynthetic efficiency through the direct measurements of solar-stimulated chlorophyll fluorescence. The two different weekly productivity indexes (first developed by Behrenfeld & Falkowski and by Yoder, Ryan and Howard) are used to derive daily productivity as a function of chlorophyll biomass, incident daily surface irradiance, temperature, euphotic depth, and mixed layer depth. Comparisons between these two estimates using both SeaWiFS and MODIS data show significant model differences in spatial distribution after allowance for the different integration depths. Both estimates are strongly dependence on the accuracy of the chlorophyll determination. In addition, an empirical approach is taken on annual scales to estimate global NPP and export production. Estimates of solar stimulated fluorescence efficiency from chlorophyll have been shown to be inversely related to photosynthetic efficiency by Abbott and co-workers. MODIS provides the first global estimates of oceanic chlorophyll fluorescence, providing an important proof of concept. MODIS observations are revealing spatial patterns of fluorescence efficiency which show expected variations with phytoplankton photo-physiological parameters as measured during in-situ surveys. This has opened the way for research into utilizing this information to improve our understanding of oceanic NPP variability. Deriving the ocean bio-optical properties places severe demands on instrument performance (especially band to band precision) and atmospheric correction. Improvements in MODIS instrument characterization and calibration over the first 16 mission months have greatly improved the accuracy of the chlorophyll input fields and FLH, and therefore the estimates of NPP and fluorescence efficiency. Annual estimates now show the oceanic NPP accounts for 40-50% of the global total NPP, with significant interannual variations related to large scale ocean processes. Spatial variations in ocean NPP, and exported production, have significant effects on exchange of CO2 between the ocean and atmosphere. Further work is underway to improve both the primary productivity model functions, and to refine our understanding of the relationships between fluorescence efficiency and NPP estimates. We expect that the MODIS instruments will prove extremely useful in assessing the time dependencies of oceanic carbon uptake and effects of iron enrichment, within the global carbon cycle.

Esaias, Wayne E.↗
DOE OSTI2021

Airborne hyperspectral imaging of nitrogen deficiency on crop traits and yield of maize by machine learning and radiative transfer modeling

Nitrogen is an essential nutrient that directly affects plant photosynthesis, crop yield, and biomass production for bioenergy crops, but excessive application of nitrogen fertilizers can cause environmental degradation. To achieve sustainable nitrogen fertilizer management for precision agriculture, there is an urgent need for nondestructive and high spatial resolution monitoring of crop nitrogen and its allocation to photosynthetic proteins as that changes over time. Here, we used visible to shortwave infrared (400–2400 nm) airborne hyperspectral imaging with high spatial (0.5 m) and spectral (3–5 nm) resolutions to accurately estimate critical crop traits, i.e., nitrogen, chlorophyll, and photosynthetic capacity (CO 2 -saturated photosynthesis rate, V max,27 ), at leaf and canopy scales, and to assess nitrogen deficiency on crop yield. We conducted three airborne campaigns over a maize (Zea mays L.) field during the growing season of 2019. Physically based soil-canopy Radiative Transfer Modeling (RTM) and data-driven approaches i.e. Partial-Least Squares Regression (PLSR) were used to retrieve crop traits from hyperspectral reflectance, with ground truth of leaf nitrogen, chlorophyll, V max,27 , Leaf Area Index (LAI), and harvested grain yield. To improve computational efficiency of RTMs, Random Forest (RF) was used to mimic RTM simulations to generate machine learning surrogate models RTM-RF. The results show that prior knowledge of soil background and leaf angle distribution can significantly reduce the ill-posed RTM retrieval. RTM-RF achieved a high accuracy to predict leaf chlorophyll content (R 2 = 0.73) and LAI (R 2 = 0.75). Meanwhile, PLSR exhibited better accuracy to predict leaf chlorophyll content (R 2 = 0.79), nitrogen concentration (R 2 = 0.83), nitrogen content (R 2 = 0.77), and V max,27 (R 2 = 0.69) but required measured traits for model training. We also found that canopy structure signals can enhance the use of spectral data to predict nitrogen related photosynthetic traits, as combining RTM-RF LAI and PLSR leaf traits well predicted canopy-level traits (leaf traits × LAI) including canopy chlorophyll (R 2 = 0.80), nitrogen (R 2 = 0.85) and V max,27 (R 2 = 0.82). Compared to leaf traits, we further found that canopy-level photosynthetic traits, particularly canopy V max,27 , have higher correlation with maize grain yield. This study highlights the potential for synergistic use of process-based and data-driven approaches of hyperspectral imaging to quantify crop traits that facilitate precision agricultural management to secure food and bioenergy production.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1972

Radiometric ocean color surveys through a scattering atmosphere

A series of aircraft flights has been initiated to measure the spectral reflectance of ocean waters containing various concentrations of chlorophyll. The results of both the theoretical and experimental investigations indicate that satellite-borne radiometers can sense ocean color. However, the accuracy to which the chlorophyll concentration can be measured appears to be 0.1 to 0.4 mg/cu m depending upon solar zenith angles. These accuracies are less than desired by many of the oceanographers and an effort is being made to improve the quality of the chlorophyll concentration determination. Further measurements will be made in areas with higher chlorophyll concentration in order to better understand the relationship between chlorophyll concentration and ocean color. Also the effects of high water turbidity will be investigated.

Curran, R. J.↗
NASA NTRS1982

Water Raman normalization of airborne laser fluorosensor measurements - A computer model study

The technique for normalizing airborne lidar measurements of chlorophyll fluoresence by the water Raman scattering signal is investigated for laser-excitation wavelengths of 480 and 532 nm using a semianalytic Monte Carlo methodology (SALMON). The signal-integration depth for chlorophyll fluorescence Z(90,F), is found to be insensitive to excitation wavelength and ranges from a maximum of 4.5 m in clearest waters to less than 1 m at a chlorophyll concentration of 20 microgram/liter. For excitation at 532 nm, the signal-integration depth for Raman scattering, Z(90,R), is comparable to Z(90,F). For excitation at 480 nm, Z(90,R) is four times as large as Z(90,F) in clearest waters but nearly equivalent at chlorophyll concentrations greater than 2-3 microgram/liter. Absolute signal levels are stronger with excitation at 480 nm than with excitation at 532 nm, but this advantage must be weighed against potential ambiguities resulting from different integration depths for the fluorescence and Raman scattering signals in clearer waters. To the precision of the simulations, Raman normalization produces effectively linear response to chlorophyll concentration for both excitation wavelengths.

Poole, L. R.↗
NASA NTRS1982

Analysis of high altitude remotely sensed data collected in the Nantucket Shoals experiment 4-15 May, 1981

High altitude ocean color scanner ratios of band 2 (456 to 476 nanometers) to band 4 (539 to 559 nanometers) and band 1 (418 to 438 nanometers) to band 3 (498 to 518 nanometers) had high correlation coefficient values (-0.928 and 0.891 respectively) with seven boat sampled chlorophyll a measurements. The range of chlorophyll a concentrations was small (1.7-2.58 mg/cu m.). Each ratio was used to calculate chlorophyll a values for the center pixel of each scan line on flight lines 5 and 6. The two ratios produced dissimilar chlorophyll a trends. Due to the high noise level in the scanner data, no reliable synoptic chlorophyll a map could be generated with either ratio algorithm.

Ohlhorst, C. W.↗
NASA NTRS1986

Biological consequences of a recurrent eddy off Point Conception, California

The biological effects on three different time scales (100-day mesoscale, annual, and several-year) of a mesoscale anticyclonic eddy consistently found in shipboard surveys and satellite-sensed data several hundred kilometers southwest of Point Conception, CA, are described. A detailed shipboard study of the eddy in January 1981 found a complex system of fronts in surface chlorophyll at the northern edge of the eddy; microplankton and zooplankton distributions were strongly affected by entrainment processes at the surface and, apparently, at depth. Concurrent satellite coastal zone color scanner ocean color images show agreement with the general surface characteristics of the eddy chlorophyll field but do not reflect features deeper than about 25 m, including the contribution of the deep chlorophyll maximum to the integrated chlorophyll values. Satellite data for the period October 1980 through October 1981 and shipboard data from California Cooperative Oceanic Fisheries Investigations (CalCOFI) for December 1980 to July 1981 show the continued presence of the eddy in the sea surface temperature and color field and in the distributions of surface chlorophyll and zooplankton displacement volume. A review of the CalCOFI survey results from 1949 to the present time demonstrates the recurrent nature of the eddy system on a year-to-year basis. The eddy system appears to have a significant effect on the distribution of both oceanic and nearshore organisms. Offshore transport of coastal species occurs in the form of large entrained plumes or filaments.

Haury, Loren R.↗
NASA NTRS1995

SeaWiFS Technical Report Series. Volume 29: SeaWiFS CZCS-type pigment algorithm

The Sea-viewing Wide Field-of-view Sensor (SeaWiFS) mission will provide operational ocean color that will be superior to the previous Coastal Zone Color Sensor (CZCS) proof-of-concept mission. an algorithm is needed that exploits the full functionality of SeaWiFS whilst remaining compatible in concept with algorithms used for the CZCS. This document describes the theoretical rationale of radiance band-radio methods for determining chlorophyll alpha and other important biogeochemical parameters, and their implementation for the SeaWiFS mission. Pigment interrelationships are examined to explain the success of the CZCS algorithms. In the context where chlorophyll alpha absorbs only weakly at 520 nm, the success of the 520 nm to 550 nm CZCS band ratio needs to be explained. This is explained by showing that in pigment data from a range of oceanic provinces chlorophyll alpha (absorbing at less than 490 nm), carotenoids (absorbing at greater than 460 nm), and total pigment are highly correlated. Correlations within pigment groups particularly photoprotectant and photosynthetic carotenoids are less robust. The sources of variability in optical data re examined using the NIMBUS Experiment Team (NET) bio-optical data set and bio-optical model. In both the model and NET data, the majority of the variance in the optical data is attributed to variability in pigment (chlorophyll alpha, and total particulates, with less than 5% of the variability resulting from pigment assemblage. The relationships between band ratios and chlorophyll is examined analytically, and a new formulation based on a dual hyperbolic model is suggested which gives a better calibration curve than the conventional log-log linear regression fit. The new calibration curve shows that 490:555 ratio is the best single-band ratio and is the recommended CZCS-type pigment algorithm. Using both the model and NET data, a number of multiband algorithms are developed; the best of which is an algorithm based on the 443:555 and 490:555 ratios. From model data, the form of potential algorithms for other products, such as total particulates and dissolved organic matter (DOM), are suggested.

Hooker, Stanford B.↗