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1. Sentinel-2 Leaf Area Index Estimation for Pine Plantations in the Southeastern United States

   https://doi.org/10.3390/rs12091406  

   Cohrs, Chris W. ; Cook, Rachel L. ; Gray, Josh M. ; Albaugh, Timothy J. ( May 2020 , Remote Sensing)

   null (Ed.)

   Leaf area index (LAI) is an important biophysical indicator of forest health that is linearly related to productivity, serving as a key criterion for potential nutrient management. A single equation was produced to model surface reflectance values captured from the Sentinel-2 Multispectral Instrument (MSI) with a robust dataset of field observations of loblolly pine (Pinus taeda L.) LAI collected with a LAI-2200C plant canopy analyzer. Support vector machine (SVM)-supervised classification was used to improve the model fit by removing plots saturated with aberrant radiometric signatures that would not be captured in the association between Sentinel-2 and LAI-2200C. The resulting equation, LAI = 0.310SR − 0.098 (where SR = the simple ratio between near-infrared (NIR) and red bands), displayed good performance ( R 2 = 0.81, RMSE = 0.36) at estimating the LAI for loblolly pine within the analyzed region at a 10 m spatial resolution. Our model incorporated a high number of validation plots (n = 292) spanning from southern Virginia to northern Florida across a range of soil textures (sandy to clayey), drainage classes (well drained to very poorly drained), and site characteristics common to pine forest plantations in the southeastern United States. The training dataset included plot-level treatment metrics—silviculture intensity, genetics, and density—on which sensitivity analysis was performed to inform model fit behavior. Plot density, particularly when there were ≤618 trees per hectare, was shown to impact model performance, causing LAI estimates to be overpredicted (to a maximum of X i + 0.16). Silviculture intensity (competition control and fertilization rates) and genetics did not markedly impact the relationship between SR and LAI. Results indicate that Sentinel-2’s improved spatial resolution and temporal revisit interval provide new opportunities for managers to detect within-stand variance and improve accuracy for LAI estimation over current industry standard models. 

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2. Shrubs Compensate for Tree Leaf Area Variation and Influence Vegetation Indices in Post‐Fire Siberian Larch Forests

   https://doi.org/10.1029/2022JG007107  

   Bendavid, Nadav S. ; Alexander, Heather D. ; Davydov, Sergei P. ; Kropp, Heather ; Mack, Michelle C. ; Natali, Susan M. ; Spawn‐Lee, Seth A. ; Zimov, Nikita S. ; Loranty, Michael M. ( March 2023 , Journal of Geophysical Research: Biogeosciences)

   In post‐fire Siberian larch forests, where tree density can vary within a burn perimeter, shrubs constitute a substantial portion of the vegetation canopy. Leaf area index (LAI), defined as the one‐sided total green leaf area per unit ground surface area, is useful for characterizing variation in plant canopies. We estimated LAI with allometry for trees and tall shrubs (>0.5 and <1.5 m) across 26 sites with varying tree stem density (0.05–3.3 stems/m²) and canopy cover (4.6%–76.9%) in a uniformly‐aged mature Siberian larch forest that regenerated following a fire ∼75 years ago. We investigated relationships between tree density, tree LAI, and tall shrub LAI, and between LAI and satellite observations of Normalized Difference and Enhanced Vegetation Indices (NDVI and EVI). Across the density gradient, tree LAI increases with increasing tree density, while tall shrub LAI decreases, exhibiting no patterns in combined tree‐shrub LAI. We also found significant positive relationships between tall shrub LAI and NDVI/EVI from PlanetScope and Landsat imagery. These findings suggest that tall shrubs compensate for lower tree LAI in tree canopy gaps, forming a canopy with contiguous combined tree‐shrub LAI across the density gradient. Our findings suggest that NDVI and EVI are more sensitive to variation in tall shrub canopies than variation in tree canopies or combined tree‐shrub canopies in these ecosystems. The results improve our understanding of the relationships between forest density and tree and shrub leaf area and have implications for interpreting spatial variability in LAI, NDVI, and EVI in Siberian boreal forests.

    

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3. A new North American calibration for predicting canopy structure in deep time using epidermal phytolith morphology

   Canares, Brielle Ann ; Heath, Kit ; Torres, Juan ; Brightly, W H ; Dunn, R E ; Lowe, Alex ; Stiles, E ; Strömberg, C A ( July 2023 , Botany)

   Degree of canopy cover is linked to transpiration, carbon cycling and primary productivity of an ecosystem. In modern ecology, canopy structure is often quantified as Leaf Area Index (LAI), which is the amount of overstory leaf coverage relative to ground area. Although a key aspect of vegetation, the degree of canopy cover has proven difficult to reconstruct in deep time. One method, Reconstructed Leaf Area Index (rLAI), was developed to infer canopy structure using the relationship between non-grass leaf epidermal phytolith (plant biosilica) morphology, and leaf coverage in modern forests. This method leverages the observed correlation between epidermal phytolith size, shape (margin undulation), and light availability. When more light is available in a canopy, epidermal phytoliths tend to be smaller and less undulate, whereas less light availability is linked to larger and more undulate epidermal phytoliths. However, the calibration set used to develop this method was compiled from field sites and samples from localities in Costa Rica and it remains unclear how applicable it is to temperate North American fossil sites due to lack of data from relevant vegetation types and taxonomic differences between plant communities in the Neotropics vs. mid-latitude North America. For example, preliminary results measuring rLAI in phytolith assemblages from the Miocene of the North American Great Plains have yielded surprisingly high degrees of canopy density despite containing high relative abundances of open-habitat grasses. To test whether vegetational and taxonomic differences impact the calibration set, we constructed a new North American calibration using 24 quadrats from six sites, representing reasonable modern analogs for Miocene vegetation in eastern North America. Specifically, we sampled in Bennett Springs State Park in Lebanon, MO; Mark Twain National Forest in Rolla, MO; Tellico in Franklin, NC and Congaree National Park in Hopkins, SC. All sites include a range of canopy covers and vegetation types, from oak savannas and oak woodlands to mixed hardwood forests, pine savannas, and old growth bottomland forests. From each quadrat, we collected a soil sample and took hemispherical photos of the local canopy. From modern soil samples, biosilica was extracted in the lab, yielding phytolith assemblages which were scanned for epidermal phytoliths using a compound microscope. Recovered epidermal phytoliths size and margin undulation were measured and assemblage averages were used to predict measured LAI at each quadrat. Hemispherical photographs were processed using the software Gap Light Analyzer to obtain LAI values. We hypothesize there will be a linear relationship between actual LAI and LAI calculated from epidermal phytolith morphology, but its relationship will differ from that found in South America. Results will be used to reevaluate canopy coverage in sites within the Great Plains Miocene as well as applied to Pacific Northwest Miocene sites, both to understand changes to vegetation during global climatic events in their respective regions. 

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4. Using structure to model function: incorporating canopy structure improves estimates of ecosystem carbon flux in arctic dry heath tundra

   https://doi.org/10.1088/1748-9326/acceb6  

   Min, Elizabeth ; Naeem, Shahid ; Gough, Laura ; McLaren, Jennie R. ; Rowe, Rebecca J. ; Rastetter, Edward ; Boelman, Natalie ; Griffin, Kevin L. ( May 2023 , Environmental Research Letters)

   Most tundra carbon flux modeling relies on leaf area index (LAI), generally estimated from measurements of canopy greenness using the normalized difference vegetation index (NDVI), to estimate the direction and magnitude of fluxes. However, due to the relative sparseness and low stature of tundra canopies, such models do not explicitly consider the influence of variation in tundra canopy structure on carbon flux estimates. Structure from motion (SFM), a photogrammetric method for deriving three-dimensional (3D) structure from digital imagery, is a non-destructive method for estimating both fine-scale canopy structure and LAI. To understand how variation in 3D canopy structure affects ecosystem carbon fluxes in Arctic tundra, we adapted an existing NDVI-based tundra carbon flux model to include variation in SFM-derived canopy structure and its interaction with incoming sunlight to cast shadows on canopies. Our study system consisted of replicate plots of dry heath tundra that had been subjected to three herbivore exclosure treatments (an exclosure-free control [CT], large mammals exclosure), and a large and small mammal exclosure [ExLS]), providing the range of 3D canopy structures employed in our study. We found that foliage within the more structurally complex surface of CT canopies received significantly less light over the course of the day than canopies within both exclosure treatments. This was especially during morning and evening hours, and was reflected in modeled rates of net ecosystem exchange (NEE) and gross primary productivity (GPP). We found that in the ExLS treatment, SFM-derived estimates of GPP were significantly lower and NEE significantly higher than those based on LAI alone. Our results demonstrate that the structure of even simple tundra vegetation canopies can have significant impacts on tundra carbon fluxes and thus need to be accounted for.

    

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5. Quantifying water-use efficiency in plant canopies with varying leaf angle and density distribution

   https://doi.org/10.1093/aob/mcae018  

   Ponce_de_León, María A ; Bailey, Brian N ( February 2024 , Annals of Botany)

   Variation in architectural traits related to the spatial and angular distribution of leaf area can have considerable impacts on canopy-scale fluxes contributing to water-use efficiency (WUE). These architectural traits are frequent targets for crop improvement and for improving the understanding and predictions of net ecosystem carbon and water fluxes.

   A three-dimensional, leaf-resolving model along with a range of virtually generated hypothetical canopies were used to quantify interactions between canopy structure and WUE by examining its response to variation of leaf inclination independent of leaf azimuth, canopy heterogeneity, vegetation density and physiological parameters.

   Overall, increasing leaf area index (LAI), increasing the daily-averaged fraction of leaf area projected in the sun direction (Gavg) via the leaf inclination or azimuth distribution and increasing homogeneity had a similar effect on canopy-scale daily fluxes contributing to WUE. Increasing any of these parameters tended to increase daily light interception, increase daily net photosynthesis at low LAI and decrease it at high LAI, increase daily transpiration and decrease WUE. Isolated spherical crowns could decrease photosynthesis by ~60 % but increase daily WUE ≤130 % relative to a homogeneous canopy with equivalent leaf area density. There was no observed optimum in daily canopy WUE as LAI, leaf angle distribution or heterogeneity was varied. However, when the canopy was dense, a more vertical leaf angle distribution could increase both photosynthesis and WUE simultaneously.

   Variation in leaf angle and density distributions can have a substantial impact on canopy-level carbon and water fluxes, with potential trade-offs between the two. These traits might therefore be viable target traits for increasing or maintaining crop productivity while using less water, and for improvement of simplified models. Increasing canopy density or decreasing canopy heterogeneity increases the impact of leaf angle on WUE and its dependent processes.

    

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