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At least 19 records

Influence of Vegetation Canopy Architecture on Dynamics of Spatiotemporal Light Distribution and its Effect on Land-Biosphere-Atmosphere Fluxes of Energy, Carbon, and Water

The dynamic spatiotemporal distribution of light and micro climatic variables (wind speed, atmospheric CO 2 concentration, humidity, pressure, and air temperature) within the plant canopy as determined by the canopy architecture play a critical role in land-biosphere-atmosphere (LBA) photosynthetic carbon uptake, transpiratory water loss and energy partitioning. Vegetation models that include effects of sun and shade flecks, leaf temperature and energy balance partitioning between sensible and latent heat fluxes, and reduced turbulent mixing in dense vegetation canopies can accurately predict canopy performance, particularly its shaded leaves, which can constitute 80% of leaf area and contribute up to 50% of carbon update and 65% of water loss. However, current vegetation models with their bulk characterization of shaded leaves poorly represent the complex three dimensional (3D) canopy architecture are insufficient to capture the spatiotemporal dynamics of shaded leaves. Here, we propose to employ an x-ray computed tomography (XCT) imaging technique in combination with an automated, high throughput, image processing pipeline (3DArch, to be developed) to obtain an explicit 3D triangulated surface mesh of a plant canopy (Fig 1). 3DArch would provide a much needed technological jump in 3D LBA modeling where computer generated artificial 3D models suffer from lack of high resolution detailed canopy architecture parameters. The 3D canopy surface mesh output from 3DArch is coupled with an explicit 3D forward ray tracing model (fastTracer) to obtain a high resolution representation of the dynamic spatiotemporal light environment within the canopy over the course of a day (Fig 1). The results from the light attenuation model are then coupled with a process based multi-scale bio-physical canopy and leaf model of photosynthesis (PlantGro) to get fluxes of carbon, water and energy at the leaf and canopy scale, in addition to estimating whole plant carbon uptake, and water loss. Our proposed model framework would be the first of its kind to provide a breakthrough capability in the field of process-based plant modeling that bridges the key technological gap in shaded leaf modeling through explicit representation of 3D canopy architecture. Computer generated artificial 3D model canopy simulations on grasses show that the canopy light distribution does not follow an exponential behavior as assumed in most 1D vegetation models, but rather exhibits a heterogeneous behavior, with a small but significant portion of interior canopy leaves experiencing peak light levels due to sun flecks while the rest of the canopy receives substantially lower light levels. These results indicate a bias in traditional models that overestimates shaded leaf contribution towards whole canopy photosynthesis by up to 15% and underestimate transpiration by up to 12% with an associated increase in sensible heat fluxes since photosynthesis, transpiration and energy partitioning are tightly coupled processes. However, these test results need to be validated using the 3D architecture obtained from a real plant imaged in 3D using 3DArch, rather than an artificial model plant. Our proposed model framework would allow us to identify inefficiencies in canopy light distribution and prescribe optimal canopy architectures (leaf optical properties, leaf area, leaf angles, row spacing, planting density, etc.) to traditional and genetic engineering based crop breeders, for maximizing target functions such as light use efficiency, water use efficiency, drought tolerance, crop yield, crop resilience etc., with important applications in biofuel crops such as sorghum, and switchgrass. Our model can also be applied for designing optimal canopy architecture that increase surface albedo as a mitigation strategy for global warming and projections of crop yield for future food and water security under climate change.

59 BASIC BIOLOGICAL SCIENCES↗

Combining geometric-optical and spectral invariants theories for modeling canopy fluorescence anisotropy

The spectral invariants theory ( p -theory) has received much attention in the field of quantitative remote sensing over the past few decades and has been adopted for modeling of canopy solar-induced chlorophyll fluorescence (SIF). However, the spectral invariant properties (SIP) in simple analytical formulae have not been applied for modeling canopy fluorescence anisotropy primarily because they are parameterized in terms of leaf total scattering, which precludes the differentiation between forward and backward leaf SIF emissions. In this study, we have developed the canopy-SIP SIF model by combining geometric-optical (GO) theory to account for asymmetric leaf SIF forward and backward emissions at the first-order scattering and by modeling multiple scattering based on the p-theory, thus avoiding the dependence on radiative transfer models. The applicability of the model simulations especially over 3D heterogeneous canopies was improved by incorporating canopy structure through multi-angular clumping index, and by modeling single scattering from the four components of the scene in view according to the GO approach. The results show good consistency with both the state-of-the-art SIF models and multi-angular field SIF observations over grass and chickpea canopies. Further, the coefficient of determination (R²) between the simulated SIF and field measurements was 0.75 (red) and 0.74 (far-red) for chickpea, and 0.65 (both red and far-red) for grass. The average relative error was approximately 3% for 1D homogeneous scenes when comparing the canopy-SIP SIF model simulations to the SCOPE model simulations, and around 4% for the 3D heterogeneous scene when comparing to the LESS model simulations. The results indicate that the proposed approach for separating asymmetric leaf SIF emissions is a robust way to keep a balance between satisfactory simulation accuracy and efficiency. Model simulations suggest that neglecting the leaf SIF asymmetry can lead to an underestimation of canopy red SIF by 6.3% to 42.6% for various leaf biochemical and canopy structural parameters. This study presents a simple but efficient analytical approach for canopy fluorescence modeling, with potential for large-scale canopy fluorescence simulations.

3D heterogeneous structure↗

What lies beneath: Vertical temperature heterogeneity in a Mediterranean woodland savanna

As the availability of satellite and airborne thermal infrared remote sensing (TIR-RS) data increases and their spatial, temporal, and spectral resolutions improve, researchers are finding diverse applications for TIR-RS measurements. TIR-RS is now commonly applied in regional- and continental-scale analyses, such as those focused on fire and surface energy balance. However, its application lags in plant physiology and ecology, for which a finer-scale understanding of plant canopy temperatures would be useful to elucidate plant water dynamics, for example. In particular, while methods to disaggregate TIR-RS pixels in horizontal space have advanced, possible vertical stratification of plant canopy temperature and its implications for understanding the correspondence between TIR-RS and finer-scale, field-based thermal measurements (e.g. made with a thermal camera) remain unexplored. Here, we use data from a thermal camera deployed concurrently with the recent ECOSTRESS mission to quantify vertical temperature gradients within tree canopies and temperatures of over- vs. under-story plants in a Mediterranean woodland savanna. We then leverage diverse ancillary data to maximize the geometric comparability of ECOSTRESS and thermal camera measurements, in order to assess the extent to which the two forms of thermal measurements correspond. Specifically, we ask: (1) What are the patterns of intra-canopy and over- vs. under-story vertical temperature in a Mediterranean woodland savanna?, and (2) How can vertically-resolved, but spatially-limited field-based temperature measurements be reconciled with spatially-extensive, but surface-only, temperature measurements of a space-borne remote sensor? Further, we found consistent patterns of vertical thermal heterogeneity both within tree canopies and between ecosystem over- and under-stories. The daytime difference between the top and bottom thirds of blue oak canopies was, on average, 0.48 ° C – and sometimes several times larger. Notably, canopy tops are cooler, likely associated with the under-story grass reaching daytime temperatures often exceeding over-story temperatures by 10° C. Given the consistency of the intra-canopy temperature gradients, we expected the ECOSTRESS sensor would be in better agreement with camera measurements of canopy tops than bulk canopies or canopy bottoms. However, within-canopy gradients were overwhelmed by other sources of disagreement between the measurements, in part associated with upscaling camera measurements across space. Overall, thermal camera and ECOSTRESS measurements were largely in agreement at night (pixel RMSE = 1.1°C), but they were more divergent during times of low (but >0 W/m2) and high incoming solar radiation (daytime pixel RMSE = 3.5°C).

54 ENVIRONMENTAL SCIENCES↗

Seasonal decline in leaf photosynthesis in perennial switchgrass explained by sink limitations and water deficit

Leaf photosynthesis of perennial grasses usually decreases markedly from early to late summer, even when the canopy remains green and environmental conditions are favorable for photosynthesis. Understanding the physiological basis of this photosynthetic decline reveals the potential for yield improvement. We tested the association of seasonal photosynthetic decline in switchgrass (Panicum virgatum L.) with water availability by comparing plants experiencing ambient rainfall with plants in a rainfall exclusion experiment in Michigan, USA. For switchgrass exposed to ambient rainfall, daily net CO 2 assimilation ( A' net ) declined from 0.9 mol CO 2 m -2 day -1 in early summer to 0.43 mol CO 2 m -2 day -1 in late summer (53% reduction; P<0.0001). Under rainfall exclusion shelters, soil water content was 73% lower and A' net was 12% and 26% lower in July and September, respectively, compared to those of the rainfed plants. Despite these differences, the seasonal photosynthetic decline was similar in the season-long rainfall exclusion compared to the rainfed plants; A' net in switchgrass under the shelters declined from 0.85 mol CO 2 m -2 day -1 in early summer to 0.39 mol CO 2 m -2 day -1 (54% reduction; P<0.0001) in late summer. These results suggest that while water deficit limited A' net late in the season, abundant late-season rainfalls were not enough to restore A' net in the rainfed plants to early-summer values suggesting water deficit was not the sole driver of the decline. Alongside change in photosynthesis, starch in the rhizomes increased 4-fold (P<0.0001) and stabilized when leaf photosynthesis reached constant low values. Additionally, water limitation under shelters had no negative effects on the timing of rhizome starch accumulation, and rhizome starch content increased ~6-fold. These results showed that rhizomes also affect leaf photosynthesis during the growing season. Towards the end of the growing season, when vegetative growth is completed and rhizome reserves are filled, diminishing rhizome sink activity likely explained the observed photosynthetic declines in plants under both ambient and reduced water availability.

59 BASIC BIOLOGICAL SCIENCES↗

Allometric relationships and trade‐offs in 11 common M editerranean‐climate grasses

Abstract Biomass allocation in plants is the foundation for understanding dynamics in ecosystem carbon balance, species competition, and plant–environment interactions. However, existing work on plant allometry has mainly focused on trees, with fewer studies having developed allometric equations for grasses. Grasses with different life histories can vary in their carbon investment by prioritizing the growth of specific organs to survive, outcompete co‐occurring plants, and ensure population persistence. Further, because grasses are important fuels for wildfire, the lack of grass allocation data adds uncertainty to process‐based models that relate plant physiology to wildfire dynamics. To fill this gap, we conducted a greenhouse experiment with 11 common California grasses varying in photosynthetic pathway and growth form. We measured plant sizes and harvested above‐ and belowground biomass throughout the life cycle of annual species, while for the establishment stage of perennial grasses to quantify allometric relationships for leaf, stem, and root biomass, as well as plant height and canopy area. We used basal diameter as a reference measure of plant size. Overall, basal diameter is the best predictor for leaf and stem biomass, height, and canopy area. Including height as another predictor can improve model accuracy in predicting leaf and stem biomass and canopy area. Fine root biomass is a function of leaf biomass alone. Species vary in their allometric relationships, with most variation occurring for plant height, canopy area, and stem biomass. We further explored potential trade‐offs in biomass allocation across species between leaf and fine root, leaf and stem, and allocation to reproduction. Consistent with our expectation, we found that fast‐growing plants allocated a greater fraction to reproduction. Additionally, plant height and specific leaf area negatively influenced the leaf‐to‐stem ratio. However, contrary to our hypothesis, there were no differences in root‐to‐leaf ratio between perennial and annual or C 4 and C 3 plants. Our study provides species‐specific and functional‐type‐specific allometry equations for both above‐ and belowground organs of 11 common California grass species, enabling nondestructive biomass assessment in California grasslands. These allometric relationships and trade‐offs in carbon allocation across species can improve ecosystem model predictions of grassland species interactions and environmental responses through differences in morphology.

54 ENVIRONMENTAL SCIENCES↗

Can improved canopy light transmission ameliorate loss of photosynthetic efficiency in the shade? An investigation of natural variation in Sorghum bicolor

Abstract Previous studies have found that maximum quantum yield of CO2 assimilation (Φ CO2,max,app) declines in lower canopies of maize and miscanthus, a maladaptive response to self-shading. These observations were limited to single genotypes, leaving it unclear whether the maladaptive shade response is a general property of this C4 grass tribe, the Andropogoneae. We explored the generality of this maladaptation by testing the hypothesis that erect leaf forms (erectophiles), which allow more light into the lower canopy, suffer less of a decline in photosynthetic efficiency than drooping leaf (planophile) forms. On average, Φ CO2,max,app declined 27% in lower canopy leaves across 35 accessions, but the decline was over twice as great in planophiles than in erectophiles. The loss of photosynthetic efficiency involved a decoupling between electron transport and assimilation. This was not associated with increased bundle sheath leakage, based on 13C measurements. In both planophiles and erectophiles, shaded leaves had greater leaf absorptivity and lower activities of key C4 enzymes than sun leaves. The erectophile form is considered more productive because it allows a more effective distribution of light through the canopy to support photosynthesis. We show that in sorghum, it provides a second benefit, maintenance of higher Φ CO2,max,app to support efficient use of that light resource.

54 ENVIRONMENTAL SCIENCES↗

AmeriFlux AR-Rom Romano Mar Chiquita BA

This is the AmeriFlux version of the carbon flux data for the site AR-Rom Romano Mar Chiquita BA. Site Description - The site was at Mar Chiquita coastal lagoon, located in the southeast of Buenos Aires province, Argentina, in an agricultural establishment (“Antonio Romano S. A.”), whose main activity was cattle production. A flux tower was settled within the raised high marsh approximately 6 km from the sea and 2 km from a lagoon. The water body showed two hydrographic areas with marine and inland influence regulated by the sea tides and rainfall respectively. There were sandy dunes occupied by open vegetation composed of grasses and herb species. Physiognomy surrounding the measurement site was the characteristic evergreen grassy landscape with an average canopy height of 0.7 m and little phenological variation throughout the year.

Gassmann, Maria Isabel↗

California annual grass phenology and allometry influence ecosystem dynamics and fire regime in a vegetation demography model

Grass-dominated ecosystems cover wide areas of the land surface yet have received far less attention from the Earth System Model (ESM) community. This limits model projections of ecosystem dynamics in response to global change and coupled vegetation–climate dynamics. We used the Functionally Assembled Terrestrial Ecosystem Simulator (FATES), a dynamic vegetation demography model, to determine ecosystem sensitivity to alternate, observed grass allometries and biophysical traits, and evaluated model performance in capturing California C 3 annual grasslands structure and fire regimes. Grass allometry, leaf physiology, plant phenology, and plant mortality all drove the seasonal variation in matter and energy exchange and fire dynamics in California annual grasslands. Allometry influenced grassland structure and function mainly through canopy architecture-mediated space and light competition instead of through carbon partitioning strategy. Regional variation in grassland annual burned area was driven by variation in ecosystem productivity. Our study advances the modeling of grassy ecosystems in ESMs by establishing the importance of grass allometry and plant phenology and mortality in driving C 3 annual grassland seasonal dynamics and fire regime. The calibrated annual grass allometry and biophysical traits presented can be applied in future studies to project climate–vegetation–fire feedbacks in annual grass-dominant ecosystems under global change.

54 ENVIRONMENTAL SCIENCES↗

The extent of multiallelic, co‐editing of LIGULELESS1 in highly polyploid sugarcane tunes leaf inclination angle and enables selection of the ideotype for biomass yield

Summary Sugarcane ( Saccharum spp. hybrid) is a prime feedstock for commercial production of biofuel and table sugar. Optimizing canopy architecture for improved light capture has great potential for elevating biomass yield. LIGULELESS1 ( LG1 ) is involved in leaf ligule and auricle development in grasses. Here, we report CRISPR/Cas9‐mediated co‐mutagenesis of up to 40 copies/alleles of the putative LG1 in highly polyploid sugarcane (2 n = 100–120, x = 10–12). Next generation sequencing revealed co‐editing frequencies of 7.4%–100% of the LG1 reads in 16 of the 78 transgenic lines. LG1 mutations resulted in a tuneable leaf angle phenotype that became more upright as co‐editing frequency increased. Three lines with loss of function frequencies of ~12%, ~53% and ~95% of lg1 were selected following a randomized greenhouse trial and grown in replicated, multi‐row field plots. The co‐edited LG1 mutations were stably maintained in vegetative progenies and the extent of co‐editing remained constant in field tested lines L26 and L35. Next generation sequencing confirmed the absence of potential off targets. The leaf inclination angle corresponded to light transmission into the canopy and tiller number. Line L35 displaying loss of function in ~12% of the lg1 NGS reads exhibited an 18% increase in dry biomass yield supported by a 56% decrease in leaf inclination angle, a 31% increase in tiller number, and a 25% increase in internode number. The scalable co‐editing of LG1 in highly polyploid sugarcane allows fine‐tuning of leaf inclination angle, enabling the selection of the ideotype for biomass yield.

59 BASIC BIOLOGICAL SCIENCES↗

Characterizing Turbulence at a Forest Edge: Comparing Sub-Filter Scale Turbulence Models in Simulations of Flow over a Canopy

In wildfires, atmospheric turbulence plays a major role in the transfer of turbulent kinetic energy. Understanding how turbulence feeds back into a dynamical system is important, down to the varying small scales of fuel structures (i.e. pine needles, grass). Large eddy simulations (LES) are a common way of numerically representing turbulence. The Smagorinsky model (1963) serves as one of the most studied sub-grid scale representations in LES. In this investigation, the Smagorinsky model was implemented in HIGRAD/FIRETEC, LANL’s coupled fire-atmosphere model. This study was motivated by the need to quantitatively investigate the vorticity budget equation in HIGRAD/FIRETEC. The Smagorinsky turbulent kinetic energy (TKE) was compared to FIRETEC’s 1.5-order TKE eddy-viscosity subgrid-scale model, known as the Linn turbulence model. This was done in simulations of flow over flat terrain with a homogeneous, cuboidal canopy in the center of the domain. Examinations of the modeled vertical TKE profile and turbulent statistics at the leading edge, and throughout the canopy, show that the Smagorinsky model provides comparable results to that of the original closure model posed in FIRETEC.

58 GEOSCIENCES↗

Convergent Hydraulic Redistribution and Groundwater Access Supported Facilitative Dependency Between Trees and Grasses in a Semi‐Arid Environment

Abstract Hydraulic redistribution is the transport of water from wet to dry soil layers, upward or downward, through plant roots. Often in savanna and woodland ecosystems, deep‐rooted trees, and shallow‐rooted grasses coexist. The degree to which these different species compete for or share soil‐water derived from precipitation or groundwater, as well as how these interactions are altered by hydraulic redistribution, is unknown. We use a multilayer canopy model and field observations to examine how the presence of deep, but tree‐root accessible, groundwater impacts seasonal patterns of hydraulic redistribution, and interaction between coexisting vegetation species in a semiarid riparian woodland (US‐CMW). Based on the simulation, trees absorb moisture at the water table (∼10 m depth) and release it in the shallow soil depth (0–3 m) during the dry pre‐monsoon season. We observed the occurrence of a new convergent hydraulic redistribution pattern during the monsoon season, where moisture is transported from both the near‐surface (0–0.5 m) and the water table to intermediate soil layers (1–5 m) through tree roots. We found that hydraulic redistribution demonstrates a growth facilitation effect at this site, supporting 49% of growing season tree transpiration and 14% of the grass transpiration. Compared to a similarly structured upland savanna without accessible groundwater, the riparian site shows an increased amount of hydraulically redistributed water and more facilitative water use between coexisting grasses and trees. These results shed light on the linkage between accessible groundwater and the role of hydraulic redistribution on the interaction between deep‐rooted and shallow‐rooted vegetation.

Lee, E.↗

DUET - Distribution of Understory using Elliptical Transport: A mechanistic model of leaf litter and herbaceous spatial distribution based on tree canopy structure

Heterogeneity in surface fuels produced by overstory trees and understory vegetation is a major driver of fire behavior and ecosystem dynamics. Previous attempts at predicting tree leaf and needle litter accumulation over time have been constrained in scope to probabilistic models that consider a limited number of key factors influencing tree litter dispersal patterns and decomposition processes. Here we present a mechanistic model for estimating variation in surface fuels called the Distribution of Understory using Elliptical Transport (DUET). DUET uses a pre-generated voxelated canopy array and distributes the leaf litter from the trees in an elliptical shape based on tree species characteristics, wind data, and location-specific features. DUET then calculates grass growth between trees and around the litter patterns and sets moisture levels based on relative humidity. In this study, we use DUET to simulate spatial distributions of leaf litter and illustrate model sensitivity to several parameters, providing inputs for testing fuel spatial heterogeneity impacts on fire behavior using process-based models.

54 ENVIRONMENTAL SCIENCES↗

Bridging the Flux Gap: Sap Flow Measurements Reveal Species-Specific Patterns of Water Use in a Tallgrass Prairie

Woody encroachment, the process through which woody plants (trees and shrubs) replace grasses and wildflowers in grassland ecosystems, is occurring globally. Because woody plants use water differently (e.g., rates, soil depths of uptake, and time periods of activity) than grasses, woody encroachment could potentially change the water cycle in grasslands. In order to understand how grassland water use might change with ongoing woody encroachment, we measured continuous rates of water loss in common plant species in a North American grassland. Furthermore, we found that the main encroaching shrub in this grassland used more water over time than grasses or wildflowers. Additionally, this shrub and grasses used a large amount of water at night compared to wildflowers. Finally, we found that different weather conditions had different impacts on how water was used by woody plants, grasses, and wildflowers. We suggest that woody encroachment might reduce the amount of water stored in grasslands, which could alter the composition of grassland plants in the future.

54 ENVIRONMENTAL SCIENCES↗

Miscanthus: An Environmental Choice for Marginal Lands

Miscanthus x giganteus, or Giant Miscanthus, is a tall, perennial grass originally from Asia. It is considered a sterile hybrid that has been bred to not produce viable seeds. Instead, rhizomes are planted to establish the crop. Here, the rhizome is an underground modified stem mass that puts out shoots and roots supporting new growth each year. This perennial crop takes two to three years to reach maturity, but established stands can reach upwards of 12 ft. tall with a very thick canopy (Pyter, 2007). Miscanthus has shown potential for high dry matter yields compared to other biomass crops, which could in turn lead to more efficient land use especially when applied to a bioenergy and bioproduct supply chain. In one study, switchgrass (Panicum virgatum) yielded 10.3 Mg/ha of biomass on average, while miscanthus yielded 22.4 Mg/ha (Heaton et al., 2004). Additionally, miscanthus production has been associated with many environmental benefits, including benefits to water quality, nutrient load removal, soil stabilization, and soil health (Bhardwaj et al., 2011; Hussain et al., 2019). Many of the possible practical and environmental benefits that are associated with miscanthus production may be attractive to stakeholders who are interested in alternative land use options, particularly in areas considered to be marginal in productivity.

54 ENVIRONMENTAL SCIENCES↗

CHESS 2025: Leaf Area Index (LAI) for meadow, shrub, tree, and understory vegetation

This dataset contains Leaf Area Index (LAI) measurements made as part of the Colorado Headwaters Ecological Spectroscopy Study (CHESS) during June and July of 2025. Data were collected in the Upper Gunnison Basin, Colorado, across three study domains: the Upper East River (CRBU), Almont Triangle (ALMO), and the Upper Taylor Basin (UPTA). Field observations of LAI were collected within 72 hours of airborne data collection by the National Ecological Observatory Network’s Aerial Observation Platform (NEON AOP). The NEON AOP collected waveform LiDAR (Light Detection and Ranging) and imaging spectrometer data in 426 spectral bands from the visible to shortwave infrared. LAI measurements were collected using the LICOR LAI-2200C Plant Canopy Analyzer following protocols outlined in the instrument manual (LI-COR 2019). Sampling targeted four distinct vegetation types: meadows, shrubs, trees, and aspen forest understory. We have archived data separately by site type because different field methods were used for each. At meadow sites, measurements were made at the four corners of 1m x 1m plots, with the instrument moving inward toward the center of the plot. At shrub sites, we measured the canopies of individual shrubs. At tree sites, we made measurements within a 10m x 10m subplot centered around a focal tree, with 30 observations taken on a regular grid. At aspen understory sites, we measured overstory trees following the tree protocol and understory herbaceous vegetation following the meadow protocol. All measurements included above-canopy (A) and below-canopy (B) readings, with specific protocols for scattering correction measurements in direct-sun conditions. Data were processed using the R package `rlai` (Worsham 2025). This package includes functions to calculate LAI, gap fraction, apparent clumping factor (Ω), scattering correction, and other canopy metrics. Package contents: Full file descriptions appear in ‘flmd.csv’. Files named according to the convention ‘lai_*_summary_data_cleaned.csv’ contain summary values of LAI, apparent clumping factor (Ωapp), and scattering correction factors for each site. These are the analysis-ready products that most data users will work with. Files named ‘lai_*_metadata_cleaned.csv’ contain additional site-level observations made during field collection. We have also archived intermediate and supplementary data for users who wish to check our processing approach or apply alternative methods. ‘raw_lai_2200C.zip’ contains the raw files as read from the LI-COR instrument, with no processing applied, in TXT format. The zip archive contains subdirectories by site type, which are further subdivided by sampling area. Filenames correspond to the sampling site number. ‘intermediate_results.zip’ contains detailed output from the processing routines, in JSON format. The zip archive contains subdirectories by site type; filenames correspond to the sampling site number. ‘scattering_correction_logs.zip’ contains logfiles from the implementation of Kobayashi et al.'s (2013) scattering correction algorithm. The logfiles report values of several parameters at each iteration of the algorithm, as the model converges toward a stable solution. They are intended for users who want to verify scattering correction performance. The zip archive contains subdirectories by site type; filenames correspond to the sampling site number. ‘spot_checks.csv’ reports LAI and other values for a small number of files processed with LI-COR FV2200 software (LI-COR 2013) using the same control parameters as in our R-based approach. Additional metadata are provided in a data dictionary describing column names and definitions (dd.csv), and in a file-level metadata file (flmd.csv). All zip files can be expanded with common archive utilities. TXT, CSV, and JSON files can be ingested into R or Python computing environments or read in common text editor utilities. Geospatial information: Geospatial data for mapping measurement site locations are in the files CHESS_polygons_lai_UTM.geojson, CHESS_polygons_shrub_UTM.geojson, and CHESS_polygons_meadow_UTM.geojson in the companion geospatial package for the 2025 CHESS campaign, ‘CHESS 2025: Location data for field observations and sampling’ (Henderson et al., 2026). CHESS Project Description: The Colorado Headwaters Ecological Spectroscopy Study (CHESS) comprised a multi-week airborne remote sensing and field observation campaign in the Upper Gunnison Basin, Colorado, conducted in June and July of 2025. Airborne remote sensing was conducted by the National Ecological Observatory Network Airborne Observation Platform (NEON AOP), concurrent with a field campaign run by the Rocky Mountain Biological Laboratory (RMBL), the Lawrence Berkeley National Laboratory (LBNL) and SLAC National Accelerator Laboratory Watershed Function Science Focus Area (SFA), and NASA-JPL (Jet Propulsion Laboratory) Earth Surface Mineral Dust Source Investigation (EMIT) program. Between June 10 and July 18, 2025, the NEON AOP flight team collected high-resolution aerial imaging spectroscopy and Light Detection and Ranging (LiDAR) data over three domains: the Upper East River (CRBU), Almont Triangle (ALMO), and the Upper Taylor Basin (UPTA). In coordination with the flights, a field campaign acquired ground-truth observations, including observations of vegetation composition, foliar traits, forest demography, and subsurface properties in 18 core sampling areas within the domains. Additional surface water observations were taken at over 380 point locations. All CHESS campaign datasets can be found within the CHESS ESS-DIVE data portal: https://data.ess-dive.lbl.gov/portals/chess. Funding Acknowledgement: Field and remote-sensing data acquisition was performed under a grant from the National Aeronautics and Space Administration (80NSSC24K1005). This work was also supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231. * Todorov and Worsham are co–first authors.

2018 NEON and 2025 CHESS Campaigns↗

AmeriFlux FLUXNET-1F CA-SF2 Saskatchewan - Western Boreal, forest burned in 1989

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site CA-SF2 Saskatchewan - Western Boreal, forest burned in 1989. This is the FLUXNET version of the carbon flux data for the site CA-SF2 Saskatchewan - Western Boreal, forest burned in 1989 produced by applying the standard ONEFlux (1F) software. Site Description - Amiro_et_al_2006, AFM/136:...The 1989 burn site (F89) was northeast of Prince Albert National Park, Saskatchewan, with the humancaused fire covering 13,500 ha. Parts of the area had been logged prior to the fire, and slash residues would have been burned in some locations. Parts of the area were aerially seeded with jack pine seeds in the winter of 1990. The present tree canopy was composed of balsam poplar (Populus balsamifera L.), jack pine, trembling aspen, and birch (Betula papyrifera Marsh.) and prior to the fire, the stand consisted of these same species aswell asblack spruce.Deadsnags of black spruce and jack pinewere still standing, althoughmost had fallen over and formed a leaningmix of dry, dead tree boles. The understory vegetation consisted mostly of black spruce saplings, saplings of the tree overstory species, bearberry, blueberry (Vaccinium myrtilloides Michx.), raspberry (Rubus idaeus L.), rose (Rosa acicularis Lindl.), bunchberry (Cornus canadensis L.), and reed grass (Calamagrostis canadensis (Michx.) Nutt.).

Amiro, Brian↗

Contrasting Carbon–Water–Energy Dynamics in Perennial and Annual Bioenergy Agroecosystems Using Eddy Covariance and Interpretable Machine Learning

Understanding how agroecosystems respond to environmental variability is fundamental to predicting productivity and sustainability under a changing climate. We analyzed 55 site-years of high-frequency eddy covariance observations from five agroecosystems—two perennial grasses (miscanthus and switchgrass), two annual rotation systems (maize–soybean and sorghum–soybean), and a restored native prairie—to examine ecosystem-scale carbon, water, and energy fluxes. Using an interpretable machine-learning framework with regression tree ensembles, Shapley Additive Explanations, and Accumulated Local Effects, we quantified how environmental and temporal factors regulate gross primary productivity (GPP), evapotranspiration (ET), water-use efficiency, and the Bowen ratio. Perennials exhibited stronger physiological buffering and maintained fluxes across a broader range of temperature and moisture conditions, reflecting deeper rooting and persistent canopy cover. Annuals, in contrast, showed greater short-term variability and stronger coupling to atmospheric demand, with GPP and ET declining rapidly under low humidity or soil moisture. Differences in temperature sensitivity of Bowen ratio further revealed that perennials sustained proportionally greater sensible heat flux under cool conditions, whereas annuals exhibited constrained energy exchange when evaporative demand was low. Together, these results demonstrate that crop life cycle and canopy structure are fundamental determinants of ecosystem-scale carbon–water–energy coupling. By integrating long-term flux observations with interpretable machine learning, this study identifies the environmental drivers that shape agroecosystem function and highlights how conversion from annual to perennial feedstocks can enhance climatic resilience and alter land–atmosphere energy feedbacks. These findings provide a data-driven basis for improving crop and Earth-system models and for guiding bioenergy landscape design under future climate scenarios.

Accumulated Local Effects↗

High Vapor Pressure Deficit Decreases the Productivity and Water Use Efficiency of Rain‐Induced Pulses in Semiarid Ecosystems

Abstract Intermittent rain events drive dynamic pulses of carbon and water exchange in many arid and semiarid ecosystems. Although soil moisture is known to control these pulses, the effect of atmospheric dryness on pulses is not well documented. Here we hypothesized that vapor pressure deficit ( VPD ) modulates net ecosystem production ( NEP ) and ecosystem‐scale water use efficiency ( WUE ) during pulse events due to its effects on canopy stomatal conductance and evapotranspiration. We quantified relationships between VPD and carbon and water exchange during growing season rain events and tested their generality across four semiarid flux sites with varied vegetation in the southwest United States. Across grassland, shrubland, and savanna sites, we found that high VPD during pulses suppressed ecosystem photosynthesis and surface conductance to a greater degree than respiration or evapotranspiration, particularly when soil moisture was high. Thus, periods of high VPD were associated with a 13–64% reduction in NEP and an 11–25% decrease in WUE , relative to moderate VPD conditions. Sites dominated by shrubs with the C3 photosynthetic pathway were more sensitive to VPD than sites dominated by C4 grasses. We found that a 1 kPa increase in VPD reduced the average NEP of pulse events by 13–56%, which illustrates the potential for projected increases in atmospheric demand to reduce the net productivity of semiarid ecosystems.

Roby, Matthew C.↗