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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.

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At least 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Non-invasive measurement of leaf water content and pressure–volume curves using terahertz radiation

In this paper we describe a non-invasive method of measuring leaf water content using THz radiation and combine this with psychrometry for determination of leaf pressure–volume relationships. In contrast to prior investigations using THz radiation to measure plant water status, the reported method exploits the differential absorption characteristic of THz radiation at multiple frequencies within plant leaves to determine absolute water content in real-time. By combining the THz system with a psychrometer, pressure–volume curves were generated in a completely automated fashion for the determination of leaf tissue water relations parameters including water potential at turgor loss, osmotic potential at full turgor and the relative water content at the turgor loss point. This novel methodology provides for repeated, non-destructive measurement of leaf water content and greatly increased efficiency in generation of leaf PV curves by reducing user handling time.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Stomata in-sight: Integrating live confocal microscopy with leaf gas exchange and environmental control

Stomatal anatomy (aperture area, length, and width) influences leaf-level physiology traits including conductance to water vapor. Stomatal anatomy can be visualized in situ by microscopy, but the difficulty of regulating the atmospheric environment of a microscope stage means that the conditions under which imaging is done are rarely physiologically relevant. Alternatively, leaf gas exchange instruments that measure gas fluxes reflect stomatal anatomical characteristics in aggregate, but the relative strengths of anatomical traits to control water use (e.g. size vs density) cannot be firmly established. To reconcile the microscopic stomatal characteristics with leaf-level gas exchange, we describe a tool that combines laser scanning confocal microscopy, gas exchange instruments, and machine-learning image analysis to simultaneously observe anatomical characteristics of many (>40) stomata alongside leaf-level traits like photosynthesis, transpiration, and stomatal conductance. We demonstrate how the tool has the resolution capable of quantifying aperture sizes and variability in maize (Zea mays) leaves under 5 steady-state light/pCO 2 treatments while tightly controlling other environmental variables like relative humidity and temperature. A model used to calculate stomatal conductance from measured apertures and stomatal density accurately matched stomatal conductance measured by gas exchange. This technical advancement will provide insight on how stomatal anatomy and function trade off to influence stomatal conductance and leaf-level water use efficiency.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Leaf water potential, Feb2016-May2016, PA-SLZ, PA-PNM, PA-BCI: Panama

This data package contains leaf water potential data from the Barro Colorado Island (BCI), Parque Natural Metropolitano (PNM), and Bosque Protector San Lorenzo (SLZ) NGEE Tropics field sites in Panama. Pre-dawn and diurnal leaf water potential were measured on a monthly basis from February to May 2016 at SLZ and PNM. Data from BCI are only available for the month of March. This data was collected as part of the 2016 El Niño-Southern Oscillation (ENSO) campaign. Included in the attached zip file are data and metadata folders. The single data file "2016ENSO_Panama_LWP" has been provided in both Excel and CSV formats for usability purposes. The metadata file "Metadata_description_2016_ENSO_Panama" provides protocols, site descriptions, equipment information, and more, and has been provided in .docx and PDF file formats. See related datasets (existing and future) for further sample details, leaf spectra, leaf mass area (LMA), gas exchange and leaf chemistry data. VERSION 2 update. The identification of a species from the PNM site has been corrected as follows: the identification of the tree initially identified as Pseudosamanea guachapele (ALBIED) has been revised to Albizia adinocephala (ALBIAD). The updated data package includes revised data, metadata and protocol documents updated to reflect this change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Leaf temperature raw data, 2015 - 2017, at Manaus, Brazil

This data package contains raw leaf surface temperature data from the NGEE Tropics K34 tower site on a plateau near Manaus, Brazil, including automated and manually collected time series data on leaf surface temperature (thermocouples, IR radiometer, thermocamera). Leaf surface temperature (LST) was determined throughout diurnal periods using individual type T thermocouples (Omega Engineering) on 8 individual leaves of a single tree. Mature leaves at the same height and general area near the tower were selected. LST measurements were taken every 15 s and recorded on a field portable self-powered data logger (OM-CP-OCTTEMP-A, Omega Engineering). Measurements were stopped in the case of a storm or rain which can remove the attached thermocouple wires from the leaf due to large wind-driven branch movements. Included in the attached zip file are six folders: three with LST data in Excel and CSV file formats from both the K34 and B34 towers, one folder with data logger configuration programs that were used for data collection, a fifth folder with PDF files of manuals for instruments used and a final folder with two Excel metadata files. See dataset references for associated metadata package. This dataset replaces the leaf surface temperature data of two retired packages, http://dx.doi.org/10.15486/ngt/1507764 and http://dx.doi.org/10.15486/ngt/1507767

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Diurnal leaf water potential on four tree species, San Lorenzo, Panama, 2020

This data package contains pre-dawn and diurnal leaf water potential (LWP) measured on four trees at the STRI San Lorenzo crane site between January and March 2020. These data were collected from four of the core trees instrumented for sap flux (Guatteria dumetorum, Miconia minutiflora, Terminalia amazonia,Vochysia ferruginea), with measurements made on a single tree on each day. For each tree, leaf samples were harvested from fully sunlit, top of canopy positions pre-dawn (06:00 local time), and then hourly for the subsequent 12 hours. Leaf water potential was measured on 6 - 10 leaves from each time point. Harvested leaves were stored in a cool humid bag in the dark for no more than 40 minutes before LWP was measured. These data were collected as part of a 2020 dry season campaign led by Brookhaven National Laboratory (BNL). Refer to related datasets for further sample details, and paired leaf mass area (LMA), survey gas exchange, and leaf chemistry data. The files included in this data package are in .csv format, and include one data file and three metadata files.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Identification of Colletotrichum aenigma as the new causal agent of leaf blight disease on Aucuba japonica Thunb., and screenings of effective fungicides for its sustainable management

Aucuba japonica Thunb is an evergreen woody ornamental plant with significant economic and ecological values. It also produces aucubin, showing a variety of biological activities. It is widely planted in the southwest region of China, including karst landscape areas in Guizhou Province. In January 2022, a serious leaf blight disease was observed on the leaves of A. japonica in the outdoor gardens of Guizhou University, Guiyang, Guizhou, China. The causal agent was identified as Colletotrichum aenigma through amplification and sequencing of the internal transcribed spacer (ITS) region, translation of the chitin synthase ( CHS ) and actin ( ACT ) genes, and morphological characterizations. Koch’s postulates were confirmed by its pathogenicity on healthy leaves, including re-isolation and identification. To our knowledge, this is the first report of C. aenigma causing leaf blight on A. japonica worldwide. To identify pathogen characteristics that could be utilized for future disease management, the effects of temperature and light on mycelial growth, conidia production, and conidial germination, and the effects of humidity on conidial germination were studied. Optimal temperatures for mycelial growth of C. aenigma BY827 were 25–30°C, while 15°C and 35°C were favorable for conidia production. Concurrently, alternating 10-h light and 14-h dark, proved to be beneficial for mycelial growth and conidial germination. Additionally, conidial germination was enhanced at 90% humidity. In vitro screenings of ten chemical pesticides to assess their efficacy in suppressing C. aenigma representative strain BY827. Among them, difenoconazole showed the best inhibition rate, with an EC 50 (concentration for 50% of maximal effect) value of 0.0148 μg/ml. Subsequently, field experiment results showed that difenoconazole had the highest control efficiency on A. japonica leaf blight (the decreasing rate of disease incidence and decreasing rate of disease index were 44.60 and 47.75%, respectively). Interestingly, we discovered that C. aenigma BY827 may develop resistance to mancozeb, which is not reported yet among Colletotrichum spp. strains. In conclusion, our study provided new insights into the causal agent of A. japonica leaf blight, and the effective fungicides evaluated provided an important basis and potential resource for the sustainable control of A. japonica leaf blight caused by C. aenigma in the field.

Fan, Ruidong↗
DOE OSTI2024

Leaf functional traits highlight phenotypic variation of two tree species in the urban environment

Urbanization is transforming landscapes globally, altering environmental conditions that affect ecosystem functioning, particularly in urban areas where trees are crucial for regulating microclimates, improving air quality, and sustaining biodiversity. This study investigates the environmental differences and tree leaf structure and morphology in urban and suburban sites in the Chicago Metropolitan Region. The leaf functional traits of Norway Maple and Little − leaved Linden were studied in three locations in the summer of 2023: an urban park (University of Illinois Chicago, Chicago, IL), a suburban park (Morton Arboretum, Lisle, IL), and a suburban residential site (Lombard, IL). The urban site had higher daytime and nighttime air, and land surface temperatures compared to the suburban sites with significant fluctuations observed across the sites. Cumulative growing degree days, a measure of potential photosynthetically active days, were also higher in the urban park than in the suburban sites between March and August. Norway Maple trees growing in the urban site displayed higher specific leaf area (SLA) and lower leaf dry matter content (LDMC) than in the suburban sites, resulting in thinner leaves. Similarly, Little−leaved Linden trees in the suburban residential site displayed higher SLA and lower LDMC than those in the suburban park. The values of gas exchange traits − namely photosynthetic assimilation, transpiration rates, and stomatal conductance − of Norway Maple were higher at the urban site compared to suburban sites as temperatures increased during the summer. Norway Maple gas exchange values decreased as the growing season progressed, as expected by ontogeny. In contrast, Little−leaved Linden maintained similar leaf gas exchange values throughout the growing season. Both species in the urban site exhibited lower instantaneous water use efficiency and reduced LDMC, suggesting greater water loss in response to elevated temperatures compared to suburban park and residential sites. Comparisons with existing global trait databases emphasize the need for localized data to accurately capture site−specific responses. Although some traits aligned with database values, others deviated significantly, underscoring the importance of comprehensive, site−specific datasets for robust ecosystem modeling and management strategies.

Cho, Ahram↗
DOE OSTI2024

Genetically correlated leaf tensile and morphological traits are driven by growing season length in a widespread perennial grass

Leaf tensile resistance, a leaf's ability to withstand pulling forces, is an important determinant of plant ecological strategies. One potential driver of leaf tensile resistance is growing season length. When growing seasons are long, strong leaves, which often require more time and resources to construct than weak leaves, may be more advantageous than when growing seasons are short. Growing season length and other ecological conditions may also impact the morphological traits that underlie leaf tensile resistance.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Correlational selection and genetic architecture shape the evolution of the leaf economics spectrum in a perennial grass

The generality of the worldwide leaf economics spectrum (LES) has made it a pillar of trait-based ecological research. Yet, few studies have examined the processes shaping the evolution of the LES within species, in part, because most species occupy only a small portion of the LES. Here, to address this gap, we took advantage of the distinct leaf economics strategies present in different ecotypes of the phenotypically diverse perennial grass Panicum virgatum (switchgrass) to generate a genetic mapping population, which we planted in common gardens at three sites spanning 12 degrees of latitude in the central United States. With this genetic mapping population, we evaluated two potentially interacting causes of LES evolution: 1) genetic architecture, where multiple traits are influenced by either the same gene (pleiotropy) or by genes in close physical proximity (genetic linkage), and 2) correlational selection, where selection acts on traits in combination rather than in isolation. We found that shared genetic architecture influenced covariation between photosynthetic rate (A MASS ) and leaf nitrogen (N MASS ) and between A MASS and leaf mass per area (LMA). We also found that correlational selection favored the trait combinations predicted by the LES (e.g., high LMA with low N MASS or low LMA with high N MASS ) and disfavored other, mismatched trait combinations at two of the three sites. Together, these results demonstrate how the evolution of an integrated LES within species can arise from multiple evolutionary causes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

The leaf economics spectrum of triploid and tetraploid C 4 grass Miscanthus x giganteus

Abstract The leaf economics spectrum (LES) describes multivariate correlations in leaf structural, physiological and chemical traits, originally based on diverse C 3 species grown under natural ecosystems. However, the specific contribution of C 4 species to the global LES is studied less widely. C 4 species have a CO 2 concentrating mechanism which drives high rates of photosynthesis and improves resource use efficiency, thus potentially pushing them towards the edge of the LES. Here, we measured foliage morphology, structure, photosynthesis, and nutrient content for hundreds of genotypes of the C 4 grass Miscanthus × giganteus grown in two common gardens over two seasons. We show substantial trait variations across M .× giganteus genotypes and robust genotypic trait relationships. Compared to the global LES, M .× giganteus genotypes had higher photosynthetic rates, lower stomatal conductance, and less nitrogen content, indicating greater water and photosynthetic nitrogen use efficiency in the C 4 species. Additionally, tetraploid genotypes produced thicker leaves with greater leaf mass per area and lower leaf density than triploid genotypes. By expanding the LES relationships across C 3 species to include C 4 crops, these findings highlight that M .× giganteus occupies the boundary of the global LES and suggest the potential for ploidy to alter LES traits.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Reproductive and leaf litterfall fluxes in forest ecosystem sites globally (1950-2022)

Forest allocation of net primary productivity (NPP) to reproduction is poorly quantified globally, despite its critical role in forest regeneration and a well-supported trade-off with allocation to growth. Although field measurements of total NPP are rare, our work finds that a proxy for reproductive carbon allocation constructed from leaf (L) and reproductive (R) litterfall fluxes, R/(R+L), is strongly correlated with R/NPP, facilitating analysis across a wide range of sites where biometric estimates of NPP are not available (R² = 0.85; Hanbury-Brown et al., 2022, Ward et al., in prep). To investigate relationships between ecosystem-scale reproductive allocation (RA) and climate, soil fertility, and stand age gradients, we conducted a literature search and synthesized 824 observations of annual average leaf and reproductive litterfall fluxes across forest sites globally. The zip file includes 1) a folder Data/ containing the litterfall data ("GlobalForestRA_data.csv") and metadata ("GlobalForestRA_metadata.doc") files. The data file includes geographic coordinates, long-term mean annual temperature and precipitation (1970-2000, extracted from WorldClim2.1), leaf and reproductive litterfall fluxes, sampling interval and protocols, forest characteristics (dominant leaf morphology, information pertaining to forest age and successional stage, and disturbance history) and soil properties (% sand, %silt, %clay, total phosphorus (P), nitrogen (N), cation exchange capacity (CEC) and pH) extracted from SoilGrids250 and from on-site measurements, where available. The metadata file contains information about each variable reported in the data file, including data sources, processing methods, and all references. The Data folder contains two additional files used to create Figure 1; these are described in greater detail in the README.2) R scripts GloalForestRA_analysis.r and GlobalForestRA_SI.r and a folder /Functions used to produce results, figures, and tables in the manuscript Ward et al. (in press)3) a README file describing how the data and R scripts can be used to reproduce statistical results, figures, and tables found in the manuscript. Ward et al. (in press)This repository can also be found at: https://github.com/r-ward/Global_Analysis_ForestRA.Ward, R.E., Zhang-Zheng, H. Aernethy, K., Adu-Bredu, S., Arroyo, L., Bailey, A. et al. (in press). Forest age rivals climate to explain reproductive allocation patterns in forest ecosystems globally. Ecology Letters. Hanbury-Brown, A.R., Ward, R.E. & Kueppers, L.M. (2022). Forest regeneration within Earth system models: current process representations and ways forward. New Phytol., 235, 20–40.Ward et al. (2025), Forest age rivals climate to explain reproductive allocation patterns in forest ecosystems globally, in prep.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Fungal mat growth and leaf colonization at the TRACE warming experiment, Mar - Aug 2024, Luquillo, Puerto Rico

This data package contains processed measurements on the growth of litter mat-forming fungi and the time to leaf colonization at the Tropical Responses to Altered Climate Experiment (TRACE). Located near the Sabana Field Research Station in Luquillo, Puerto Rico, the TRACE site is located in a mature, closed-canopy tropical rainforest within the Luquillo Experimental Forest (LEF). These data quantify fungal mat growth and the time to leaf colonization of fungi species Gymnopus johnstonii and Marasmius crinis-equi. The experiment was conducted in ambient (control) and experimentally warmed plots (4°C above ambient) during spring and summer periods to assess how litter mat-forming fungi respond to a range of environmental conditions of tropical wet forests. The data files include tables of relative fungal mat growth rates, time to leaf colonization, averages of soil temperature (°C), and number of dry days before leaf attachment. The data are stored in comma-separated values (CSV) format and viewable with any text editor, spreadsheet, or statistical software (e.g., R, Python, Excel). Associated metadata describe plot identifiers, measurement descriptions, and processing steps.

Agaric fungi↗
DOE OSTI2024

Leaf phenology data at The Morton Arboretum Forestry Plots 2019-2023

We are collecting long-term leaf phenology data at The Morton Arboretum to determine seasonal patterns of leaf production in trees. This data on leaf phenology will be integrated with other ongoing data streams to create a connection between above- and below-ground tree processes. This data package contains raw and smooth outputs from phenology data, as well as extracted phenophase dates (i.e., start, peak, and end of season): the raw and smooth outputs from the PhenoCam GUI can be found in the "leafRaw.csv" and "leafSmooth.csv" files, respectively, and the extracted phenophase dates can be found in the "leafPhenophaseDates2019-2023.csv" file. Extracted phenophase dates for evergreen species in 2023 are currently unavailable, and the files will be updated once they are extracted. Additional information on units and other file-level metadata can be found within each data file's respective data dictionary, and metadata for each of the 23 surveyed plots can be found within the "Location_metadata.csv" file. While the "leafRaw.csv" and the "leafSmooth.csv" files contain all data for all species, the "leafPhenophaseDates2019-2023.csv" file currently excludes the dates for evergreen species in 2023. Another version of the file will be added as those dates are extracted.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Identification of quantitative trait loci for sorghum leaf blight resistance

Sorghum leaf blight and northern corn leaf blight, both caused by Exserohilum turcicum {(Pass.) K. J. Leonard and Suggs [syn. Setosphaeria turcica (Luttr.) K. J. Leonard and Suggs.]}, are major diseases of sorghum [Sorghum bicolor (L.) Moench] and maize (Zea mays L.), respectively. Examining the genetic architecture of resistance in sorghum will lead to a better understanding of the relationship between resistance in sorghum and maize, which can ultimately enhance management options in both crops. In 2018 and 2019, we evaluated two sorghum recombinant inbred line (RIL) populations for resistance to E. turcicum. The BTx623 × IS3620C and BTx623 × SC155 populations consisted of 235 and 81 RILs, respectively. Resistance in both populations was moderately to highly heritable. We identified a total of six quantitative trait loci (QTL) across the two populations. Three QTL with small- to moderate-effect sizes were identified in the BTx623 × IS3620C population. Three QTL, including a large-effect QTL on chromosome three that explained 24% of the variation, were identified in the BTx623 × SC155 population. We compared the identified QTL with the position of northern corn leaf blight candidate genes and found eight candidate resistance gene orthologs that colocalize with the sorghum leaf blight QTL. There were also several nucleotide-binding leucine-rich repeat encoding genes within the candidate intervals. Understanding host resistance in multiple species furthers our understanding of the Exserohilum turcicum patho-system.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Overexpression of plasma membrane SUT1 in poplar alters lateral sucrose partitioning in stem and promotes leaf necrosis

Abstract In Populus and many other tree species, photoassimilate sucrose diffuses down a concentration gradient via symplastically connected mesophyll cells to minor vein phloem for long‐distance transport. There is no evidence for apoplastic phloem‐loading in Populus . However, plasma membrane sucrose transporters (SUT1 and SUT3) orthologous to those associated with apoplastic phloem loading are expressed in vascular tissues of poplar. While SUT3 functions in sucrose import into developing xylem, the role of SUT1 remains unclear. Here, we overexpressed PtaSUT1 in Populus tremula x P. alba to examine the effects on sucrose partitioning in transgenic plants. Overall leaf sucrose levels were similar between wild type and transgenic lines. Stem sucrose levels were not changed in bark but were significantly reduced in the adjacent xylem, suggesting hindered intercellular sucrose trafficking from the phloem to the developing xylem. Fully expanded leaves of transgenic plants deteriorated prematurely with declining photosynthesis prior to severe necrotic spotting. Necrotic spotting advanced most rapidly in the distal portion of mature leaves and was accompanied by sharp hexose increases and sharp sucrose decreases there. Leaf transcriptome profiling and network inference revealed the down‐regulation of copper proteins and elevated expression of copper microRNAs prior to noticeable leaf injury. Our results suggest ectopic expression of PtaSUT1 altered sucrose partitioning in stems with systemic effects on leaf health and copper homeostasis mediated in part by sucrose‐sensitive copper miRNAs.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Comparative analysis of thermal management systems in electric vehicles at extreme weather conditions: Case study on Nissan Leaf 2019 Plus, Chevrolet Bolt 2020 and Tesla Model 3 2020

With the surge in electric vehicle (EV) adoption and the need for extended driving ranges, optimizing energy efficiency, particularly through thermal management, is critical, especially in extreme weather. Managing the substantial energy needed for cabin climate control and battery temperature regulation can increase energy demands by over 50 %, severely limiting range. This study conducts a comparative analysis of thermal management systems (TMS) in three popular EV vehicles, 2020 Chevrolet Bolt, 2019 Nissan Leaf Plus, and 2020 Tesla Model 3, evaluating their distinct TMS configurations and performance under varied weather conditions. Using both numerical simulations and experimental data collected on a controlled test bench at Argonne National Laboratory, we assess how TMS architecture and operational modes influence energy consumption and range. A comprehensive TMS model was developed, integrating cabin and battery thermal sub-models in the Autonomie software platform, to simulate temperature fluctuations and range impacts. Cabin climate was modeled using a mono-zonal approach, while battery cell temperature distribution was estimated through a 2D nodal structure. Each vehicle's distinct TMS setup was evaluated: the Chevrolet Bolt and Tesla Model 3 use a dual evaporator vapor compression cycle with a PTC heater for the cabin and a coolant loop for battery thermal management; the Nissan Leaf Plus employs a heat pump with a PTC heater for the cabin and air-cooling for the battery. Tests conducted at ambient temperatures of 35°C, 22°C, -7°C, and -18°C reveal significant differences in energy use and range reduction across both configurations and conditions. At 35°C, the Tesla Model 3, Chevrolet Bolt, and Nissan Leaf Plus have a range reduction of 8%, 9%, and 13%, respectively, due to air conditioning. In winter, heating technology is paramount; at -7°C, the Nissan Leaf's heat pump configuration achieves a lower range reduction (19.3%) compared to the Tesla and Chevrolet Bolt PTC heaters, which reduce range by 28.3% and 31%, respectively. Further, this study provides valuable insights for automotive engineers, EV technology researchers, and thermal management system designers aiming to enhance electric vehicle performance by understanding how different weather conditions and TMS architectures impact energy consumption and driving range.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2023

An ecologically-constrained deep learning model for tropical leaf phenology monitoring using PlanetScope satellites

In tropical forests, leaf phenology signals leaf-on/off status and exhibits considerable variability across scales from a single tree-crown to the entire forest ecosystem. Such phenology signals importantly regulate large-scale biogeochemical cycles and regional climate. PlanetScope CubeSats data with a 3-m resolution and near-daily global coverage provide an unprecedented opportunity to monitor both fine- and ecosystem-scale phenology variability along large environmental gradients. However, a scalable method that accurately characterizes leaf phenology from PlanetScope with biophysically meaningful metrics remains lacking. Here we developed an index-guided, ecologically constrained autoencoder (IG-ECAE) method to automatically derive a deciduousness metric (i.e. percentage of tree canopies with leaf-off status within an image pixel) from PlanetScope. The IG-ECAE first estimated the reflectance spectra of leafy/leafless canopies based on their spectral indices characteristics, then used the derived reflectance spectra to guide an autoencoder deep learning method with additional ecological constraints to refine the reflectance spectra, and finally used linear spectral unmixing to estimate the relative abundance of leafless canopies (or deciduousness) per PlanetScope image pixel. We tested the IG-ECAE method at 16 tropical forest sites spanning multiple continents and a large precipitation gradient (1470-2819 mm year -1 ). Among these sites, we evaluated the PlanetScope-derived deciduousness with corresponding measures derived from WorldView-2 (n=9 sites) and local phenocams (n=9 sites). Our results show that PlanetScope-derived deciduousness agrees: 1) with that derived from WorldView-2 at the patch level (90m×90m) with r 2 =0.89 across all sites; and 2) with that derived from phenocams to quantify ecosystem-scale seasonality with r 2 ranging from 0.62-0.96. These results demonstrate the effectiveness and scalability of IG-ECAE in characterizing the wide variability in deciduousness across scales from pixels to forest ecosystems, and from a single date to the full annual cycle, indicating the potential for using high-resolution satellites to track the large-scale phenological patterns and response of tropical forests to climate change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

The Rate of Canopy Development Modulates the Link Between the Timing of Spring Leaf Emergence and Summer Moisture

Shifts in phenological timing have important implications for ecosystem processes, with spring leaf emergence as a dominant control of carbon, water, and energy cycling. Phenological events are predominantly determined by weather and climate, therefore dynamic in time and sensitive to climate feedbacks. Improving our understanding of how ecosystems respond to changes in phenological timing will enhance our ability to assess summer soil water availability, since the timing of spring leaf emergence may lead to soil moisture deficits later in the growing season. We leveraged data from five AmeriFlux towers in central and eastern United States to investigate the extent spring leaf emergence (i.e., start of spring, SoS ) influences rates at which forest canopies develop and how this impacts summer soil moisture ( θ JJA ) variability. Our results indicate that ecosystem processes, specifically gross primary production ( GPP ) and evapotranspiration ( ET ), exhibit compensatory responses to varying leaf emergence; with delayed spring-onset, the canopy developed more quickly, resulting in rapid GPP and ET increases, consistent across sites. Nonetheless, early SoS is a relatively good indicator for potential summer soil water deficits, particularly when it occurs together with meteorological conditions (i.e., lower-than-average precipitation, hot summer temperatures) that contribute to soil water deficits. When these meteorological conditions coincide with early SoS , θ JJA deficits are exacerbated. To the extent that these extreme conditions occur more frequently under future climate scenarios, the dynamics of spring phenology and hydroclimate may play an increasingly important role in portending the likelihood of summer water deficits, which are projected to become more severe.

54 ENVIRONMENTAL SCIENCES↗