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DOE OSTI2025

Seeing the forest for all the trees: Mycorrhizal‐associated nutrient economies are modulated by stem density and the synchrony between overstorey and understorey communities

1. Identifying relationships between plant communities and soil characteristics is a critical step in understanding the consequences of species gains and losses in ecosystems. The mycorrhizal associated nutrient economy (MANE) hypothesis predicts that the degree to which tree species and their mycorrhizal associates affect soil properties is driven by the relative dominance of different mycorrhizal types (often measured by relative basal area). While this approach emphasizes the importance of canopy trees, it does not account for how other factors (e.g. the density and composition of understorey trees) may alter tree–soil relationships. 2. We analysed tree–soil data from an eastern deciduous forest in southern Indiana, USA that contains >29,000 georeferenced stems, including 21 species that associate with arbuscular mycorrhizal (AM) fungi and 14 that associate with ectomycorrhizal (ECM) fungi. We sampled soils (upper 5 cm) from across the plot and modelled soil characteristics to tree communities. Given differences in soil characteristics among AM-dominated and ECM-dominated neighbourhoods, we hypothesized that relationships between tree-mycorrhizal dominance and soils would be affected by both the density of stems in the plot (owing to ‘Zinke’ individual plant effects) and composition of the understorey trees (owing to ‘trait divergence effects’) 3. In support of our Zinke hypothesis, we found that the relationships between tree-mycorrhizal dominance and soil variables (soil pH, nitrification rates and carbon to nitrogen ratio) were strengthened as stand density increased. In support of the trait divergence hypothesis, we found that as the mismatch between overstorey and understorey composition increased (e.g. AM-dominated understories beneath ECM-dominated overstories and vice versa), the relationship between tree dominance and soil variables weakened. We were able to use these insights to create mycorrhizal metrics to predict soil variables that were sensitive to the structural composition of neighbourhoods. 4. Synthesis. Our results indicate that relationships between plants and soils in forests are not only shaped by dominant overstorey trees but also the density and composition of understorey trees. Thus, efforts to predict the ecosystem consequences of species gains and losses may benefit from considering these elements of forest structure and not only the basal area of the dominant trees.

MANE framework↗

DOE OSTI2022

A Mountaintop View Requires Minimal Sorting: A Faster Contour Tree Algorithm

Consider a scalar field f : M → R, where M is a triangulated simplicial mesh in R d . A level set, or contour, at value v is a connected component of f –1 (v). As v is changed, these contours change topology, merge into each other, or split. Contour trees are concise representations of f that track this contour behavior. The vertices of these trees are the critical points of f, where the gradient is zero. The edges represent changes in the topology of contours. It is a fundamental data structure in data analysis and visualization, and there is significant previous work (both theoretical and practical) on algorithms for constructing contour trees. Suppose M has n vertices, N facets, and t critical points. A classic result of Carr, Snoeyink, and Axen (2000) gives an algorithm that takes O(n log n+Nα(N)) time (where α(·) is the inverse Ackermann function). A further improvement to O(t log t + N) time was given by Chiang et al. All these algorithms involve a global sort of the critical points, a significant computational bottleneck. Unfortunately, lower bounds of Ω(t log t) also exist. We present the first algorithm that can avoid the global sort and has a refined time complexity that depends on the contour tree structure. Intuitively, if the tree is short and fat, we get significant improvements in running time. For a partition of the contour tree into a set of descending paths, P, our algorithm runs in O($\Sigma$ pϵP |p| log |p| + tα(t) + N). This is at most O(t log D + N), where D is the diameter of the contour tree. Moreover, it is O(tα(t) + N) for balanced trees, a significant improvement over the previous complexity. Our algorithm requires numerous ideas: partitioning the contour tree into join and split trees, a local growing procedure to iteratively build contour trees, and the use of heavy path decompositions for the time complexity analysis. There is a crucial use of a family of binomial heaps to maintain priorities, ensuring that any comparison made is between comparable nodes of the contour tree. We also prove lower bounds showing that the $\Sigma$ pϵP |p| log |p| complexity is inherent to computing contour trees.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

Assessing Forest Level Response to the Death of a Dominant Tree within a Premontane Tropical Rainforest

Small-scale treefall gaps are among the most important forms of forest disturbance in tropical forests. These gaps expose surrounding trees to more light, promoting rapid growth of understory plants. However, the effects of such small-scale disturbances on the distribution of plant water use across tree canopy levels are less known. To address this, we explored plant transpiration response to the death of a large emergent tree, Mortoniodendron anisophyllum Standl. & Steyerm (DBH > 220 cm; height ~40 m). Three suppressed, four mid-story, and two subdominant trees were selected within a 50 × 44 m premontane tropical forest plot at the Texas A&M Soltis Center for Research and Education located in Costa Rica. We compared water use rates of the selected trees before (2015) and after (2019) the tree gap using thermal dissipation sap flow sensors. Hemispherical photography indicated a 40% increase in gap fraction as a result of changes in canopy structure after the treefall gap. Micrometeorological differences (e.g., air temperature, relative humidity, and vapor pressure deficit (VPD)) could not explain the observed trends. Rather, light penetration, as measured by sensors within the canopy, increased significantly in 2019. One year after the tree fell, the water usage of trees across all canopy levels increased modestly (15%). Moreover, average water usage by understory trees increased by 36%, possibly as a result of the treefall gap, exceeding even that of overstory trees. These observations suggest the possible reallocation of water use between overstory and understory trees in response to the emergent tree death. With increasing global temperatures and shifting rainfall patterns increasing the likelihood of tree mortality in tropical forests, there is a greater need to enhance our understanding of treefall disturbances that have the potential to redistribute resources within forests.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2018

Revealing the causes and temporal distribution of tree mortality in Central Amazonia

Tree mortality is a critical process in forest ecosystems, as it influences floristic composition, structure, dynamics, carbon storage, and forest nutrient cycling. However, the mechanisms behind tree death in tropical regions are still poorly characterized. This lack of information is mainly because tree mortality data come from long-interval inventories and studies that measured tree death seasonally are scarce. Here in this study, we offer novel insights into the power of fine temporal scale observations and we use a natural history approach to understand the processes and mechanism of tree mortality. We monitored tree mortality every month during one year, in 10 ha of terra-firme forest. To determine the pathways of mortality, we considered the state of the tree at the start of the investigation and the pre and post-mortem characteristics. From November 2010 to October 2011, 67 out of 5808 trees died. Despite the 2010 drought, mortality was highly correlated with monthly rainfall (r = 0.85). In total, six pathways of mortality were assessed. Storms were the main cause of mortality, killing 45% of all dead trees, followed by Biotic/abiotic factors accounting for 30% of tree mortality. The high mortality registered in the rainy season was mostly (78%) due to healthy trees dying uprooted or snapped. Lastly, we would benefit from studies that assess mortality on a monthly basis and in combination with quantitative long-term data, we can substantially improve our understanding of the mechanisms behind tree death in the tropics.

2010 drought↗

DOE OSTI2025

Mapping tree height in complex terrain of northern China using ultra-high-resolution images

Tree height is a key parameter for estimating forest biomass and carbon sequestration. In recent years, notable progress has been made in mapping tree height using satellite imagery. However, existing tree height products show low accuracy in mountainous and complex terrains, and few studies typically addressed tree height estimations in mountain areas. This study examines the Mentougou district of Beijing, China, characterized by complex terrain and mountainous landscapes. We analyzed two methods for estimating tree height: one using only spectral features and another combining spectral features with topographic factors (elevation, slope, aspect). We used 3-m resolution PlanetScope 8-band multispectral imagery, with 710 field-measured individual tree heights averaged to obtain 471 pixel-level tree height values as ground-truth, to develop tree height prediction models using eXtreme Gradient Boosting (XGBoost), Random Forest (RF), and Gradient Boosting Machine (GBM) models. The results show that the XGBoost model consistently presented the highest accuracy for both methods evaluated. Specifically, the XGBoost model that combined spectral data with elevation and slope variables with an R² of 0.75 and an RMSE of 2.69 m. Using the XGBoost model, we generated the tree height map for the Mentougou area at 3 m resolution, showing tree heights ranging from 0.5 to 30.4 m, and the model’s prediction error standard deviations ranged from 2.50 to 4.71 m, indicating reliable performance across varied terrain. Additionally, we compared and evaluated the global tree height products, identifying limitations in the accuracy within complex terrains. This study demonstrates the potential for accurately predicting tree heights by combining high-resolution multispectral satellites with a terrain factor modeling approach.

Complex terrain↗

DOE OSTI2015

Dynamic Event Tree advancements and control logic improvements

The RAVEN code has been under development at the Idaho National Laboratory since 2012. Its main goal is to create a multi-purpose platform for the deploying of all the capabilities needed for Probabilistic Risk Assessment, uncertainty quantification, data mining analysis and optimization studies. RAVEN is currently equipped with three different sampling categories: Forward samplers (Monte Carlo, Latin Hyper Cube, Stratified, Grid Sampler, Factorials, etc.), Adaptive Samplers (Limit Surface search, Adaptive Polynomial Chaos, etc.) and Dynamic Event Tree (DET) samplers (Deterministic and Adaptive Dynamic Event Trees). The main subject of this document is to report the activities that have been done in order to: start the migration of the RAVEN/RELAP-7 control logic system into MOOSE, and develop advanced dynamic sampling capabilities based on the Dynamic Event Tree approach. In order to provide to all MOOSE-based applications a control logic capability, in this Fiscal Year an initial migration activity has been initiated, moving the control logic system, designed for RELAP-7 by the RAVEN team, into the MOOSE framework. In this document, a brief explanation of what has been done is going to be reported. The second and most important subject of this report is about the development of a Dynamic Event Tree (DET) sampler named “Hybrid Dynamic Event Tree” (HDET) and its Adaptive variant “Adaptive Hybrid Dynamic Event Tree” (AHDET). As other authors have already reported, among the different types of uncertainties, it is possible to discern two principle types: aleatory and epistemic uncertainties. The classical Dynamic Event Tree is in charge of treating the first class (aleatory) uncertainties; the dependence of the probabilistic risk assessment and analysis on the epistemic uncertainties are treated by an initial Monte Carlo sampling (MCDET). From each Monte Carlo sample, a DET analysis is run (in total, N trees). The Monte Carlo employs a pre-sampling of the input space characterized by epistemic uncertainties. The consequent Dynamic Event Tree performs the exploration of the aleatory space. In the RAVEN code, a more general approach has been developed, not limiting the exploration of the epistemic space through a Monte Carlo method but using all the forward sampling strategies RAVEN currently employs. The user can combine a Latin Hyper Cube, Grid, Stratified and Monte Carlo sampling in order to explore the epistemic space, without any limitation. From this pre-sampling, the Dynamic Event Tree sampler starts its aleatory space exploration. As reported by the authors, the Dynamic Event Tree is a good fit to develop a goal-oriented sampling strategy. The DET is used to drive a Limit Surface search. The methodology that has been developed by the authors last year, performs a Limit Surface search in the aleatory space only. This report documents how this approach has been extended in order to consider the epistemic space interacting with the Hybrid Dynamic Event Tree methodology.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS2014

An Efficient, Multi-Layered Crown Delineation Algorithm for Mapping Individual Tree Structure Across Multiple Ecosystems

Deriving individual tree information from discrete return, small footprint LiDAR data may improve forest above ground biomass estimates, and provide tree-level information that is important in many ecological studies. Several crown delineation algorithms have been developed to extract individual tree information from LiDAR point clouds or rasterized canopy height models (CHM), but many of these algorithms have difficulty discriminating between overlapping crowns, and also may fail to detect understory trees. Our approach uses a watershed based delineation of a CHM, which is subsequently refined using the LiDAR point cloud. Individual tree detection was validated with stem mapped field data from the Smithsonian Environmental Research Center (SERC), Maryland, and on a plot and stand level through comparisons of stem density and basal area to delineated metrics at both SERC and a study area in the Sierra Nevada, California. For individual tree detection, the algorithm correctly identified 70% of dominant trees, 58% of co-dominant trees, 35% of intermediate trees and 21% of suppressed trees at SERC. The algorithm had difficulty distinguishing between crowns of small, dense understory trees of approximately the same height. Delineated crown volume alone explained 53% and 84% of the variability in basal area at the SERC and Sierra Nevada sites, respectively. The algorithm produced crown area distributions comparable to diameter at breast height (DBH) size class distributions observed in the field in both study sites. The algorithm detected understory crowns better in the conifer-dominated Sierra Nevada site than in the closed-canopy deciduous site in Maryland. The ability for the algorithm to reproduce both accurate tree size distributions and individual crown geometries in two dissimilar and complex forests suggests great promise for applicability to a wide range of forest systems.

LiDAR↗

DOE OSTI2015

Quest for Orthologs Entails Quest for Tree of Life: In Search of the Gene Stream

Quest for Orthologs (QfO) is a community effort with the goal to improve and benchmark orthology predictions. As quality assessment assumes prior knowledge on species phylogenies, we investigated the congruency between existing species trees by comparing the relationships of 147 QfO reference organisms from six Tree of Life (ToL)/species tree projects: The National Center for Biotechnology Information (NCBI) taxonomy, Opentree of Life, the sequenced species/species ToL, the 16S ribosomal RNA (rRNA) database, and trees published by Ciccarelli et al. (Ciccarelli FD, et al. 2006. Toward automatic reconstruction of a highly resolved tree of life. Science 311:1283–1287) and by Huerta-Cepas et al. (Huerta-Cepas J, Marcet-Houben M, Gabaldon T. 2014. A nested phylogenetic reconstruction approach provides scalable resolution in the eukaryotic Tree Of Life. PeerJ PrePrints 2:223) Our study reveals that each species tree suggests a different phylogeny: 87 of the 146 (60%) possible splits of a dichotomous and rooted tree are congruent, while all other splits are incongruent in at least one of the species trees. Topological differences are observed not only at deep speciation events, but also within younger clades, such as Hominidae, Rodentia, Laurasiatheria, or rosids. The evolutionary relationships of 27 archaea and bacteria are highly inconsistent. By assessing 458,108 gene trees from 65 genomes, we show that consistent species topologies are more often supported by gene phylogenies than contradicting ones. The largest concordant species tree includes 77 of the QfO reference organisms at the most. Results are summarized in the form of a consensus ToL (http://swisstree.vital-it.ch/species_tree) that can serve different benchmarking purposes.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2015

Fog as a source of nitrogen for redwood trees: evidence from fluxes and stable isotopes

A defining feature of the redwood forest in coastal California is the presence of fog in the summer months, a time when there is typically little rainfall. Our goal was to determine the role of summer fog in canopy transformation of nitrogen, nitrogen uptake by trees and photosynthesis within a coastal redwood forest ecosystem. We measured horizontal and vertical inputs of nitrogen, the isotopic composition of nitrogen in a variety of atmospheric sources (summer fog, winter rain and throughfall throughout the year), nitrogen pools (soil solution) and plant tissue (roots and foliage), as well as rates of photosynthesis and nitrogen uptake by trees. Throughfall nitrogen fluxes were greater at the forest edge compared to the interior both within the canopy (sampled 10m above-ground) and onto the forest floor (sampled 1m above-ground; P <0.05). Similarly, soil solution $\mathrm{NO^{-}_{3}}$ and total inorganic nitrogen were greater at the forest edge compared to the interior ( P =0.0014 and 0.009, respectively). Whereas natural abundance δ 15 NO 3 values were not significantly different between winter rain (measured as bulk precipitation) and summer fog water (average δ 15 N=-1.2±0.68 0/00), δ 15 NH 4 values were significantly greater in fog water (11.4±2.7 0/00) compared to rain (1.2±0.9 0/00). We found no difference in δ 15 N in roots from forest edge trees compared to interior trees. In contrast, nitrogen concentrations and δ 15 N in foliage from forest edge trees were significantly greater compared to interior trees ( P <0.0001), suggesting that the leaves of forest edge trees may be obtaining a greater proportion of their nitrogen from fog compared to those of the interior trees. Natural abundance 13 C of leaf sugars and rates of photosynthesis were significantly higher at the forest edge compared to the interior during the fog season ( P <0.05), but not different between locations in the rain season ( P >0.05). Nitrification in the forest floor, rather than the canopy, is the primary source of $\mathrm{NO^{-}_{3}}$ in these soils throughout the year. Synthesis. Finally, summer fog provides nitrogen directly and indirectly to redwood trees, especially those at the forest edge, and affects the physiologic function of redwood trees. Summer fog provides nitrogen directly and indirectly to redwood trees, especially those at the forest edge, and affects the physiologic function of redwood trees.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2018

Tree cover shows strong sensitivity to precipitation variability across the global tropics

Abstract Aim Vegetation is sensitive to mean annual precipitation (MAP), but the sensitivity of vegetation to precipitation variability (PV) is less clear. Tropical ecosystems are likely to experience increased PV in the future. Here we assessed the importance, magnitude and mechanism of PV effects on tree cover in the context of covarying environmental drivers such as fire, temperature and soil properties. Location Tropical land. Time period 2000–2010. Major taxa studied Trees. Methods We compiled climate, soil and remotely‐sensed tree cover data over tropical land. We then comprehensively assessed the contribution of PV at different time‐scales to tropical tree cover variations and estimated the sensitivity of tree cover to PV changes by conducting rolling‐window regression and variance decomposition analyses. We further adopted a mechanistic modelling approach to test whether water competition between trees and grasses can explain the observed effect of PV. Results We find that PV contributes 33–56% to the total explained spatial variation (65–79%) in tree cover. The contribution of PV depends on MAP and is highest under intermediate MAP (500–1,500 mm). Tree cover generally increases with rainy day frequency and wet season length but shows mixed responses to inter‐annual PV. Based on the estimated sensitivity, tropical tree cover can decrease by 3–5% overall and by up to 20% in Amazonia under a 20% decrease in rainy days. Mechanistic modelling analysis reproduced the continental differences in tree cover along an MAP gradient. Main conclusions Under intermediate rainfall regimes (500–1,500 mm), PV can be a more important determinant of tropical tree cover than conventionally proposed drivers such as MAP and fire. The effect of PV likely results from the sensitivity of tree–grass competition to the temporal distribution of water resources. These results show that climate variability can strongly shape the biosphere.

Xu, Xiangtao↗

DOE OSTI2013

Distribution of radioactive Cesium in trees and effect of decontamination of forest contaminated by the Fukushima nuclear accident

In decontamination pilot projects conducted by Japan Atomic Energy Agency (JAEA), many different techniques were tested to determine their applicability to remediate areas evacuated after the Fukushima Daiichi nuclear accident following the Great Tohoku earthquake and tsunami of March 11, 2011. In addition to buildings, roads and farmland, the forest adjacent to living areas was one of the main decontamination targets. The projects evaluated the radioactive contamination of trees and the effectiveness of decontaminating a highly contaminated evergreen forest. This forest was located 1.3 km southwest of the Fukushima Daiichi Nuclear Power Plant and is dominated by Japanese cedar trees and fir trees. As the first step, three Japanese cedar trees and three fir trees were cut down and the distributions of radioactive cesium (Cs) were measured in each. The total concentrations of {sup 134}Cs and {sup 137}Cs in the leaves and branches were about 1 MBq/kg for both cedar and fir trees, and were appreciably higher than in the bark for cedar. The concentrations in the outer part of the trunks (under the bark) were lower, on the order of 10 kBq/kg, and those in the core of the trunks were lower than 1 kBq/kg for both kinds of trees. The observation that the Cs concentrations are higher in the outer part of trees, is compatible with the assumption that radio-Cs was mostly adsorbed on the surface of trees and partly penetrated into the trunks through the bark. Evolution of air dose rates in a 100 x 60 m pasture adjacent to the forest was monitored during decontamination of the forest and of the pasture itself. The dose rates in the pasture decreased drastically after stripping contaminated topsoil from the pasture and decreased slightly more after stripping contaminated topsoil of the forest floor and pruning the trees. Cutting down and removing 84 trees in the outermost area (10- m width) of the forest also slightly decreased these dose rates. After decontamination, the residual dose rates around the highly contaminated forest were mostly attributed to radioactive Cs existing in or on trees and topsoil in the untouched forest beyond the decontaminated area. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

NASA NTRSDate not supplied

Employing NASA Earth Observations and Socioeconomic Data to Conduct Site Suitability Analyses on Residential Tree Planting Initiatives in Phoenix, Arizona

Phoenix, Arizona is the hottest large city in the United States with an average summer daytime temperature of 106°F. Temperatures in Phoenix continue to climb due to increasing global greenhouse gas concentrations and regional urbanization. The impacts of high temperatures, including heat-related illnesses and deaths, are disproportionately concentrated in low-income neighborhoods often characterized by little tree canopy, lack of green space, and insufficient access to shade. The City of Phoenix’s Office of Heat Response and Mitigation and Arizona State University’s Urban Climate Research Center, partnered with NASA DEVELOP to identify residential neighborhoods and parcels within qualified census tracts (QCTs) to be prioritized for tree planting initiatives using funding from the American Rescue Plan Act (ARPA). This project conducted analyses using NASA Earth observations, socioeconomic data from the 2019 American Community Survey, and local tree canopy and mobility data. For Earth observations, daytime land surface temperature, vegetation, and land cover were obtained from the Landsat 8 Thermal Infrared Sensor (TIRS) and Operational Land Imager (OLI). The project team incorporated these data into a heat vulnerability index (HVI) with an emphasis on tree canopy and social vulnerability to rank block groups within QCTs and focused on the resulting top 25 block group HVI scores. These top 25 most vulnerable block groups were then processed through a parcel analysis to determine the feasibility of residential tree planting based on building footprints on each parcel. Within the top 25 block groups, 2,411 parcels were analyzed, and 3,133 existing trees were identified averaging 1.3 trees per parcel with 90% of parcels having 3 trees or less. Homes with 2 trees or fewer were considered high priority for future planting efforts. Based on the City’s goals for increased tree canopy the project team determined that <10,000 additional trees would need to be planted within the most vulnerable 25 block groups. The project findings have helped initiate community engagement efforts and have contributed to the approval of tree planting funds in Phoenix.

Ryan Hammock↗

DOE OSTI2016

Mechanical vulnerability and resistance to snapping and uprooting for Central Amazon tree species

We report high descending winds generated by convective storms are a frequent and a major source of tree mortality disturbance events in the Amazon, affecting forest structure and diversity across a variety of scales, and more frequently observed in western and central portions of the basin. Soil texture in the Central Amazon also varies significantly with elevation along a topographic gradient, with decreasing clay content on plateaus, slopes and valleys respectively. In this study we investigated the critical turning moments ( M crit - rotational force at the moment of tree failure, an indicator of tree stability or wind resistance) of 60 trees, ranging from 19.0 to 41.1 cm in diameter at breast height ( DBH ) and located in different topographic positions, and for different species, using a cable-winch load-cell system. Our approach used torque as a measure of tree failure to the point of snapping or uprooting. This approach provides a better understanding of the mechanical forces required to topple trees in tropical forests, and will inform models of wind throw disturbance. Across the topographic positions, size controlled variation in M crit was quantified for cardeiro ( Scleronema mincranthum (Ducke) Ducke), mata-matá ( Eschweilera spp.), and a random selection of trees from 19 other species. Our analysis of M crit revealed that tree resistance to failure increased with size (DBH and ABG) and differed among species. No effects of topography or failure mode were found for the species either separately or pooled. For the random species, total variance in M crit explained by tree size metrics increased from an R 2 of 0.49 for DBH alone, to 0.68 when both DBH and stem fresh wood density (SWD) were included in a multiple regression model. This mechanistic approach allows the comparison of tree vulnerability induced by wind damage across ecosystems, and facilitates the use of forest structural information in ecosystem models that include variable resistance of trees to mortality inducing factors. Furthermore, our results indicate that observed topographic differences in wind throw vulnerability are likely due to elevational differences in wind velocities, rather than by differences in soil-related factors that might effect M crit .

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2018

Methane production and emissions in trees and forests

Forest ecosystem methane (CH 4 ) research has focused on soils, but trees are also important sources and sinks in forest CH 4 budgets. Living and dead trees transport and emit CH 4 produced in soils; living trees and dead wood emit CH 4 produced inside trees by microorganisms; and trees produce CH 4 through an abiotic photochemical process. Here, we review the state of the science on the production, consumption, transport, and emission of CH 4 by living and dead trees, and the spatial and temporal dynamics of these processes across hydrologic gradients inclusive of wetland and upland ecosystems. Emerging research demonstrates that tree CH 4 emissions can significantly increase the source strength of wetland forests, and modestly decrease the sink strength of upland forests. Scaling from stem or leaf measurements to trees or forests is limited by knowledge of the mechanisms by which trees transport soil-produced CH 4 , microbial processes produce and oxidize CH 4 inside trees, a lack of mechanistic models, the diffuse nature of forest CH 4 fluxes, complex overlap between sources and sinks, and extreme variation across individuals. Understanding the complex processes that regulate CH 4 source–sink dynamics in trees and forests requires cross-disciplinary research and new conceptual models that transcend the traditional binary classification of wetland vs upland forest.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

Effectiveness of street trees in reducing air temperature and outdoor heat exposure in Las Vegas

Urban greening and especially tree planting strategies are being widely planned and implemented to mitigate urban overheating and thermal stress in many urban areas. However, the effectiveness of these strategies depends on multiple factors, including urban morphology, environmental conditions, and tree characteristics. This study investigates the effects of street tree planting strategies on air temperature and outdoor heat exposure in Las Vegas by combining an urbanized mesoscale climate model coupled to a multi-layer street tree model (Weather Research and Forecasting-BEP-Tree; Δ x = 900 m) with a microscale pedestrian heat exposure model (Temperatures of Urban Facets for Pedestrian; Δ x = 1 m). A series of simulations are conducted for July and August 2022. Large city-wide increases of a drought tolerant tree species cool air temperature mainly during the nighttime (up to 1.5 °C), with daytime effects being limited due to leaves shedding sensible instead of latent heat as stomata close in response to high vapor pressure deficits. Increased evaporative cooling is achieved with a different tree species (double at night, and reaching 0.4 °C during the day), but water requirements increase threefold. Despite their relatively small effect on air temperature during the day, trees provide significant shade by intercepting solar radiation, reducing mean radiant temperature (up to 16 °C) and enhancing outdoor thermal comfort, a major benefit of street trees in hot arid climates. The nighttime cooling of trees and the daytime reduction of radiant loading show potential to reduce the heat-related health impacts. Our results highlight the need to evaluate the effects of street trees on a case-by-case basis.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2016

Unsupervised individual tree crown detection in high-resolution satellite imagery

Rapidly and accurately detecting individual tree crowns in satellite imagery is a critical need for monitoring and characterizing forest resources. We present a two-stage semiautomated approach for detecting individual tree crowns using high spatial resolution (0.6 m) satellite imagery. First, active contours are used to recognize tree canopy areas in a normalized difference vegetation index image. Given the image areas corresponding to tree canopies, we then identify individual tree crowns as local extrema points in the Laplacian of Gaussian scale-space pyramid. The approach simultaneously detects tree crown centers and estimates tree crown sizes, parameters critical to multiple ecosystem models. As a demonstration, we used a ground validated, 0.6 m resolution QuickBird image of a sparse forest site. The two-stage approach produced a tree count estimate with an accuracy of 78% for a naturally regenerating forest with irregularly spaced trees, a success rate equivalent to or better than existing approaches. In addition, our approach detects tree canopy areas and individual tree crowns in an unsupervised manner and helps identify overlapping crowns. Furthermore, the method also demonstrates significant potential for further improvement.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2016

Comparison of tree transpiration under wet and dry canopy conditions in a Costa Rican premontane tropical forest

Spatial and temporal variation in wet canopy conditions following precipitation events can influence processes such as transpiration and photosynthesis, which can be additionally enhanced as upper canopy leaves dry more rapidly than the understory following each event. As part of a larger study aimed at improving land surface modelling of evapotranspiration processes in wet tropical forests, we compared transpiration among trees with exposed and shaded crowns under both wet and dry canopy conditions in central Costa Rica, which has an average 420 mm annual rainfall. Transpiration was estimated for 5 months using 43 sap flux sensors in eight dominant, ten midstory and eight suppressed trees in a mature forest stand surrounding a 40-m tower equipped with micrometeorological sensors. Dominant trees were 13% of the plot's trees and contributed around 76% to total transpiration at this site, whereas midstory and suppressed trees contributed 18 and 5%, respectively. After accounting for vapour pressure deficit and solar radiation, leaf wetness was a significant driver of sap flux, reducing it by as much as 28%. Under dry conditions, sap flux rates (J s ) of dominant trees were similar to midstory trees and were almost double that of suppressed trees. On wet days, all trees had similarly low J s . As expected, semi-dry conditions (dry upper canopy) led to higher J s in dominant trees than midstory, which had wetter leaves, but semi-dry conditions only reduced total stand transpiration slightly and did not change the relative proportion of transpiration from dominant and midstory. Thus, models that better capture forest stand wet–dry canopy dynamics and individual tree water use strategies are needed to improve accuracy of predictions of water recycling over tropical forests.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Tree mortality during long-term droughts is lower in structurally complex forest stands

Increasing drought frequency and severity in a warming climate threaten forest ecosystems with widespread tree deaths. Canopy structure is important in regulating tree mortality during drought, but how it functions remains controversial. Here, we show that the interplay between tree size and forest structure explains drought-induced tree mortality during the 2012-2016 California drought. Through an analysis of over one million trees, we find that tree mortality rate follows a “negative-positive-negative” piecewise relationship with tree height, and maintains a consistent negative relationship with neighborhood canopy structure (a measure of tree competition). Trees overshadowed by tall neighboring trees experienced lower mortality, likely due to reduced exposure to solar radiation load and lower water demand from evapotranspiration. Our findings demonstrate the significance of neighborhood canopy structure in influencing tree mortality and suggest that re-establishing heterogeneity in canopy structure could improve drought resiliency. Our study also indicates the potential of advances in remote-sensing technologies for silvicultural design, supporting the transition to multi-benefit forest management.

59 BASIC BIOLOGICAL SCIENCES↗