Search NASA⌕ Search

SEARCH · Search NASA

Results for “leaf quantity”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 19 records

Canopy Structure Exhibits Linear and Nonlinear Links to Biome‐Level Maximum Light Use Efficiency

Maximum light use efficiency (ε max ) represents a plant's capacity to convert light into carbon during photosynthesis. Although prior studies have explored ε max variations between sunlit and shaded leaves or its temporal ties to canopy structure, the spatial relationship between biome-level ε max (ε biome ) and biome structure remains poorly understood. We analysed data from 320 eddy covariance sites (~855 site-years) with satellite-derived near-infrared reflectance of vegetation (NIRv) and leaf area index (LAI). We introduced NIRvN (NIRv/LAI) to isolate architectural effects from leaf quantity. Site-level ε max was calculated and aggregated by biome to derive ε biome . Results show ε biome rises nonlinearly with NIRv and LAI, saturating at high LAI, with crops and tropical evergreen forests deviating from this trend. Conversely, ε biome decreases linearly with increasing NIRvN, indicating that biomes with greater NIR scattering efficiency exhibit lower ε biome . These results enhance understanding of structural influences on carbon uptake across global biomes.

54 ENVIRONMENTAL SCIENCES↗

Monitoring leaf phenology in moist tropical forests by applying a superpixel-based deep learning method to time-series images of tree canopies

Tropical leaf phenology-particularly its variability at the tree-crown scale-dominates the seasonality of carbon and water fluxes. However, given enormous species diversity, accurate means of monitoring leaf phenology in tropical forests is still lacking. Time series of the Green Chromatic Coordinate (GCC) metric derived from tower-based red-green-blue (RGB) phenocams have been widely used to monitor leaf phenology in temperate forests, but its application in the tropics remains problematic. To improve monitoring of tropical phenology, we explored the use of a deep learning model (i.e. superpixel-based Residual Networks 50, SP-ResNet50) to automatically differentiate leaves from non-leaves in phenocam images and to derive leaf fraction at the tree-crown scale. To evaluate our model, we used a year of data from six phenocams in two contrasting forests in Panama. Here, we first built a comprehensive library of leaf and non-leaf pixels across various acquisition times, exposure conditions and specific phenocams. We then divided this library into training and testing components. We evaluated the model at three levels: 1) superpixel level with a testing set, 2) crown level by comparing the model-derived leaf fractions with those derived using image-specific supervised classification, and 3) temporally using all daily images to assess the diurnal stability of the model-derived leaf fraction. Finally, we compared the model-derived leaf fraction phenology with leaf phenology derived from GCC. Our results show that: 1) the SP-ResNet50 model accurately differentiates leaves from non-leaves (overall accuracy of 93%) and is robust across all three levels of evaluations; 2) the model accurately quantifies leaf fraction phenology across tree-crowns and forest ecosystems; and 3) the combined use of leaf fraction and GCC helps infer the timing of leaf emergence, maturation and senescence, critical information for modeling photosynthetic seasonality of tropical forests. Collectively, this study offers an improved means for automated tropical phenology monitoring using phenocams.

54 ENVIRONMENTAL SCIENCES↗

Synergy between optical and microwave remote sensing to derive soil and vegetation parameters from MAC Europe 1991 Experiment

The ability of remote sensing for monitoring vegetation density and soil moisture for agricultural applications is extensively studied. In optical bands, vegetation indices (NDVI, WDVI) in visible and near infrared reflectances are related to biophysical quantities as the leaf area index, the biomass. In active microwave bands, the quantitative assessment of crop parameters and soil moisture over agricultural areas by radar multiconfiguration algorithms remains prospective. Furthermore the main results are mostly validated on small test sites, but have still to be demonstrated in an operational way at a regional scale. In this study, a large data set of radar backscattering has been achieved at a regional scale on a French pilot watershed, the Orgeval, along two growing seasons in 1988 and 1989 (mainly wheat and corn). The radar backscattering was provided by the airborne scatterometer ERASME, designed at CRPE, (C and X bands and HH and VV polarizations). Empirical relationships to estimate water crop and soil moisture over wheat in CHH band under actual field conditions and at a watershed scale are investigated. Therefore, the algorithms developed in CHH band are applied for mapping the surface conditions over wheat fields using the AIRSAR and TMS images collected during the MAC EUROPE 1991 experiment. The synergy between optical and microwave bands is analyzed.

Taconet, O.↗

Mineral-Associated Organic Matter Concentration Beneath Northern Temperate Trees Varies by Mycorrhizal Type and Leaf Habit

Mycorrhizal fungi are important drivers of soil organic matter dynamics, but it can be difficult to isolate the effects of the fungi themselves from covarying traits of their host trees. For example, many trees with an evergreen leaf habit associate with ectomycorrhizal (ECM) fungi, while many deciduous tree species associate with arbuscular mycorrhizal (AM) fungi. Because leaf habit influences the quantity and quality of organic matter inputs to soil, it is often an important factor in soil carbon and nitrogen dynamics, and thus can mask the effects of mycorrhizal fungi on soil organic matter processes. We evaluated how tree mycorrhizal associations and leaf habit separately influence the amount and composition of mineral-associated organic matter (MAOM) and particulate organic matter (POM) in forest soils in New Hampshire and Vermont, USA. We measured carbon (C) and nitrogen (N) concentrations and C/N ratios of three soil density fractions beneath six tree species that vary in mycorrhizal association and leaf habit. We found lower concentrations of MAOM C and N beneath evergreen vs. deciduous trees, but only for tree species associating with AM fungi. Further, MAOM C/N was higher beneath evergreen trees and beneath trees with ECM fungi rather than AM fungi. Furthermore, these results add to the growing body of support for mycorrhizal fungi as mediators of soil organic matter dynamics, suggesting that the MAOM fraction is more sensitive to leaf habit beneath AM-associated versus ECM-associated trees. Because MAOM decomposition is thought to be less responsive than POM decomposition to changes in soil temperature and moisture, differences in the tendency of AM- and ECM-dominated forests to support MAOM formation and persistence may lead to systematic differences in the response of these forest types to ongoing climate change.

54 ENVIRONMENTAL SCIENCES↗

Radar measurement of forested areas during OTTER

To test a forest ecosystem model in the OTTER (Oregon ecosystem research) project, it is desirable to find forest canopy parameters via radar remote sensing measurements. Conventionally, forest biomass, along with quantities such as the leaf area index, drive the model. It is shown that the radar backscatter is not uniquely related to biomass. A sensitivity study is carried out using a forward scattering model to determine the variation of radar cross section as a function of several forest parameters. The results are used to find suitable quantities to recover via radar experiments. A parameter estimation scheme is developed to calculate some preliminary statistical properties of the forest.

Moghaddam, M.↗

Effective Interpolation of Incomplete Satellite-Derived Leaf-Area Index Time Series for the Continental United States

Many earth science modeling applications employ continuous input data fields derived from satellite data. Environmental factors, sensor limitations and algorithmic constraints lead to data products of inherently variable quality. This necessitates interpolation of one form or another in order to produce high quality input fields free of missing data. The present research tests several interpolation techniques as applied to satellite-derived leaf area index, an important quantity in many global climate and ecological models. The study evaluates and applies a variety of interpolation techniques for the Moderate Resolution Imaging Spectroradiometer (MODIS) Leaf-Area Index Product over the time period 2001-2006 for a region containing the conterminous United States. Results indicate that the accuracy of an individual interpolation technique depends upon the underlying land cover. Spatial interpolation provides better results in forested areas, while temporal interpolation performs more effectively over non-forest cover types. Combination of spatial and temporal approaches offers superior interpolative capabilities to any single method, and in fact, generation of continuous data fields requires a hybrid approach such as this.

Jasinski, Michael F.↗

Calculated sensitivities of several optical radiometric indices for vegetation canopies

The present study employs a radiative transfer model for a vegetation canopy to compute several quantities used in remote sensing applications and to determine the sensitivity of these radiometric quantities to several of the important problem parameters. Attention is given to the ratio of near IR to visible reflected intensities in the nadir direction, the ratio of the fraction of incident energy reflected in the near IR to that in the visible, the normalized difference between the near IR and visible nadir-reflected intensities, and the visible intensity transmitted in a given downward direction. A realistic radiative transfer model is proposed for calculating these radiometric quantities. With these models, the sensitivity of the reflected and transmitted quantities to various canopy and illumination conditions are then determined. The sensitivity of the calculated quantities are presented as a function of the leaf area index of the canopy, and, for the reflected quantities, also as a function of the fraction of visible light absorbed in the canopy.

Shultis, J. K.↗

Cyclic variations in nitrogen uptake rate of soybean plants: ammonium as a nitrogen source

When NO3- is the sole nitrogen source in flowing solution culture, the net rate of nitrogen uptake by nonnodulated soybean (Glycine max L. Merr. cv Ransom) plants cycles between maxima and minima with a periodicity of oscillation that corresponds with the interval of leaf emergence. Since soybean plants accumulate similar quantities of nitrogen when either NH4+ or NO3- is the sole source in solution culture controlled at pH 6.0, an experiment was conducted to determine if the oscillations in net rate of nitrogen uptake also occur when NH4+ is the nitrogen source. During a 21-day period of vegetative development, net uptake of NH4+ was measured daily by ion chromatography as depletion of NH4+ from a replenished nutrient solution containing 1.0 millimolar NH4+. The net rate of NH4+ uptake oscillated with a periodicity that was similar to the interval of leaf emergence. Instances of negative net rates of uptake indicate that the transition between maxima and minima involved changes in influx and efflux components of net NH4+ uptake.

NASA Discipline Life Support Systems↗

Environmental controls on the light use efficiency of terrestrial gross primary production

Abstract Gross primary production (GPP) by terrestrial ecosystems is a key quantity in the global carbon cycle. The instantaneous controls of leaf‐level photosynthesis are well established, but there is still no consensus on the mechanisms by which canopy‐level GPP depends on spatial and temporal variation in the environment. The standard model of photosynthesis provides a robust mechanistic representation for C 3 species; however, additional assumptions are required to “scale up” from leaf to canopy. As a consequence, competing models make inconsistent predictions about how GPP will respond to continuing environmental change. This problem is addressed here by means of an empirical analysis of the light use efficiency (LUE) of GPP inferred from eddy covariance carbon dioxide flux measurements, in situ measurements of photosynthetically active radiation (PAR), and remotely sensed estimates of the fraction of PAR (fAPAR) absorbed by the vegetation canopy. Focusing on LUE allows potential drivers of GPP to be separated from its overriding dependence on light. GPP data from over 100 sites, collated over 20 years and located in a range of biomes and climate zones, were extracted from the FLUXNET2015 database and combined with remotely sensed fAPAR data to estimate daily LUE. Daytime air temperature, vapor pressure deficit, diffuse fraction of solar radiation, and soil moisture were shown to be salient predictors of LUE in a generalized linear mixed‐effects model. The same model design was fitted to site‐based LUE estimates generated by 16 terrestrial ecosystem models. The published models showed wide variation in the shape, the strength, and even the sign of the environmental effects on modeled LUE. These findings highlight important model deficiencies and suggest a need to progress beyond simple “goodness of fit” comparisons of inferred and predicted carbon fluxes toward an approach focused on the functional responses of the underlying dependencies.

54 ENVIRONMENTAL SCIENCES↗

Plant biochemistry influences tropospheric ozone formation, destruction, deposition, and response

Tropospheric ozone (O 3 ) is among the most damaging air pollutant to plants. Plants alter the atmospheric O 3 concentration in two distinct ways: (i) by the emission of volatile organic compounds (VOCs) that are precursors of O 3 ; and (ii) by dry deposition, which includes diffusion of O 3 into vegetation through stomata and destruction by nonstomatal pathways. Isoprene, monoterpenes, and higher terpenoids are emitted by plants in quantities that alter tropospheric O 3 . Deposition of O 3 into vegetation is related to stomatal conductance, leaf structural traits, and the detoxification capacity of the apoplast. The biochemical fate of O 3 once it enters leaves and reacts with aqueous surfaces is largely unknown, but new techniques for the tracking and identification of initial products have the potential to open the black box.

59 BASIC BIOLOGICAL SCIENCES↗

Conserved genetic mechanisms for biotic stress in sorghum (Final report)

Developing durable disease resistance for biofuel crops is crucial, particularly as the range of biofuel crop production expands and pathogens of other plant species evolve to cause diseases of bioenergy feedstocks. Setosphaeria species are significant pathogens of the Andropogonae, and S. turcica can infect both maize and sorghum. Sorghum leaf blight (SLB), caused by S. turcica, is widespread and can decrease grain yields up to 50%, reduce forage quantity and quality, and predispose plants to other diseases, such as anthracnose. Our overall objective was to gain a systems-level understanding of the pathosystem by leveraging natural genetic variation, host specificity of the pathogen, and transcriptome analysis to improve biotic stress resistance in sorghum. We proposed three specific goals: 1) Identify sorghum alleles conferring resistance to S. turcica using natural genetic variation. 2) Characterize genes associated with biotic stress response in sorghum. 3) Identify fungal genes responsible for host specificity.

09 BIOMASS FUELS↗

Conserved genetic mechanisms for biotic stress in sorghum (Final Report)

Developing durable disease resistance for biofuel crops is crucial, particularly as the range of biofuel crop production expands and pathogens of other plant species evolve to cause diseases of bioenergy feedstocks. Setosphaeria species are significant pathogens of the Andropogonae, and S. turcica can infect both maize and sorghum. Sorghum leaf blight (SLB), caused by S. turcica, is widespread and can decrease grain yields up to 50%, reduce forage quantity and quality, and predispose plants to other diseases, such as anthracnose. Our overall objective was to gain a systems-level understanding of the pathosystem by leveraging natural genetic variation, host specificity of the pathogen, and transcriptome analysis to improve biotic stress resistance in sorghum. We proposed three specific goals: 1) Identify sorghum alleles conferring resistance to S. turcica using natural genetic variation. 2) Characterize genes associated with biotic stress response in sorghum. 3) Identify fungal genes responsible for host specificity.

09 BIOMASS FUELS↗

A scattering model for forested area

A forested area is modeled as a volume of randomly oriented and distributed disc-shaped, or needle-shaped leaves shading a distribution of branches modeled as randomly oriented finite-length, dielectric cylinders above an irregular soil surface. Since the radii of branches have a wide range of sizes, the model only requires the length of a branch to be large compared with its radius which may be any size relative to the incident wavelength. In addition, the model also assumes the thickness of a disc-shaped leaf or the radius of a needle-shaped leaf is much smaller than the electromagnetic wavelength. The scattering phase matrices for disc, needle, and cylinder are developed in terms of the scattering amplitudes of the corresponding fields which are computed by the forward scattering theorem. These quantities along with the Kirchoff scattering model for a randomly rough surface are used in the standard radiative transfer formulation to compute the backscattering coefficient. Numerical illustrations for the backscattering coefficient are given as a function of the shading factor, incidence angle, leaf orientation distribution, branch orientation distribution, and the number density of leaves. Also illustrated are the properties of the extinction coefficient as a function of leaf and branch orientation distributions. Comparisons are made with measured backscattering coefficients from forested areas reported in the literature.

Karam, M. A.↗

Evidence for widespread thermal acclimation of canopy photosynthesis

Plants acclimate to temperature by adjusting their photosynthetic capacity over weeks to months. However, most evidence for photosynthetic acclimation derives from leaf-scale experiments. Here we address the scarcity of evidence for canopy-scale photosynthetic acclimation by examining the correlation between maximum photosynthetic rates (A max,2,000 ) and growth temperature $(\overline{T_{air}})$ across a range of concurrent temperatures and canopy foliage quantity, using data from >200 eddy covariance sites. We detect widespread thermal acclimation of canopy-scale photosynthesis, demonstrated by enhanced A max,2,000 under higher $\overline{T_{air}}$, across flux sites with adequate water availability. A 14-day period is identified as the most relevant timescale for acclimation across all sites, with a range of 12-25 days for different plant functional types. The mean apparent thermal acclimation rate across all ecosystems is 0.41 (-0.38-1.04 for 5th-95th percentile range) µmol m -2 s -1 °C -1 , with croplands showing the largest acclimation rates and grasslands the lowest. Incorporating an optimality-based prediction of leaf photosynthetic capacities into a biochemical photosynthesis model is shown to improve the representation of thermal acclimation. Our results underscore the critical need for enhanced understanding and modelling of canopy-scale photosynthetic capacity to accurately predict plant responses to warmer growing seasons.

59 BASIC BIOLOGICAL SCIENCES↗

Canopy architecture of a walnut orchard

A detailed dataset describing the canopy geometry of a walnut orchard was acquired to support testing and comparison of the predictions of canopy microwave and optical inversion models. Measured canopy properties included the quantity, size, and orientation of stems, leaves, and fruit. Eight trees receiving 100 percent of estimated potential evapotranspiration water use and eight trees receiving 33 percent of potential water use were measured. The vertical distributions of stem, leaf, and fruit properties are presented with respect to irrigation treatment. Zenith and probability distributions for stems and leaf normals are presented. These data show that, after two years of reduced irrigation, the trees receiving only 33 percent of their potential water requirement had reduced fruit yields, lower leaf area index, and altered allocation of biomass within the canopy.

Ustin, Susan L.↗

Microbial community composition controls carbon flux across litter types in early phase of litter decomposition

Leaf litter decomposition is a major carbon input to soil, making it a target for increasing soil carbon storage through microbiome engineering. We expand upon previous findings to show with multiple leaf litter types that microbial composition can drive variation in carbon flow from litter decomposition and specific microbial community features are associated with synonymous patterns of carbon flow among litter types. Although plant litter type selects for different decomposer communities, within a litter type, microbial composition drives variation in the quantity of dissolved organic carbon (DOC) measured at the end of the decomposition period. Bacterial richness was negatively correlated with DOC quantity, supporting our hypothesis that across multiple litter types there are common microbial traits linked to carbon flow patterns. Variation in DOC abundance (i.e. high versus low DOC) driven by microbial composition is tentatively due to differences in bacterial metabolism of labile compounds, rather than catabolism of non-labile substrates such as lignin. The temporal asynchrony of metabolic processes across litter types may be a substantial impediment to discovering more microbial features common to synonymous patterns of carbon flow among litters. Overall, our findings support the concept that carbon flow may be programmed by manipulating microbial community composition.

59 BASIC BIOLOGICAL SCIENCES↗

Improved Modeling of Land-Atmosphere Interactions using a Coupled Version of WRF with the Land Information System

The exchange of energy and moisture between the Earth's surface and the atmospheric boundary layer plays a critical role in many hydrometeorological processes. Accurate and high-resolution representations of surface properties such as sea-surface temperature (SST), vegetation, soil temperature and moisture content, and ground fluxes are necessary to better understand the Earth-atmosphere interactions and improve numerical predictions of weather and climate phenomena. The NASA/NWS Short-term Prediction Research and Transition (SPORT) Center is currently investigating the potential benefits of assimilating high-resolution datasets derived from the NASA moderate resolution imaging spectroradiometer (MODIS) instruments using the Weather Research and Forecasting (WRF) model and the Goddard Space Flight Center Land Information System (LIS). The LIS is a software framework that integrates satellite and ground-based observational and modeled data along with multiple land surface models (LSMs) and advanced computing tools to accurately characterize land surface states and fluxes. The LIS can be run uncoupled to provide a high-resolution land surface initial condition, and can also be run in a coupled mode with WRF to integrate surface and soil quantities using any of the LSMs available in LIS. The LIS also includes the ability to optimize the initialization of surface and soil variables by tuning the spin-up time period and atmospheric forcing parameters, which cannot be done in the standard WRF. Among the datasets available from MODIS, a leaf-area index field and composite SST analysis are used to improve the lower boundary and initial conditions to the LIS/WRF coupled model over both land and water. Experiments will be conducted to measure the potential benefits from using the coupled LIS/WRF model over the Florida peninsula during May 2004. This month experienced relatively benign weather conditions, which will allow the experiments to focus on the local and mesoscale impacts of the high-resolution MODIS datasets and optimized soil and surface initial conditions. Follow-on experiments will examine the utility of such an optimized WRF configuration for more complex weather scenarios such as convective initiation. This paper will provide an overview of the experiment design and present preliminary results from selected cases in May 2004.

Case, Jonathan L.↗

Modeled economic potential for Eucalyptus spp. production for jet fuel additives in the United States

Feedstock price and availability remain a barrier to adoption of cellulosic biofuels. Eucalyptus spp., can produce an energy-dense terpene suitable for high-density synthetic hydrocarbon-type fuel (grade JP-10) production in addition to cellulosic-based feedstock for traditional jet fuels (e.g., grade Jet A) and gasoline. This study modeled economic potential for Eucalyptus to fulfill US fuel markets. Cold-tolerant Eucalyptus was simulated in an annual coppice system for maximized leaf production. Results of the lowest simulated price ($110 t -1 ) show that within 10 years, there is potential to produce 204 million L yr -1 of fuel, including 51 million L yr -1 of JP-10-type fuel, 75 million L yr -1 of Jet A type fuel, and 77 million L yr -1 of gasoline. These quantities of fuel could be valued at approximately $500 million (USD), with feedstock costs totaling approximately $100 million (USD). Longer-term markets (to 20 years) or higher priced (to $220 t -1 ) scenarios show potential for more production. Furthermore, research to determine potential for genetic improvement, delivered fuel costs, and biorefinery siting near existing infrastructure is recommended.

09 BIOMASS FUELS↗