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At least 145 records · Page 8

Differences in urban plant community compositions across an urban-rural gradient in Knoxville, TN

Urban forests, or vegetation in areas under heavy human influence, provide many ecosystem services to urban residents such as localized cooling via evapotranspiration, shade, filtering of air pollution, and the associated health benefits of natural spaces. In order to quantify the magnitude of localized cooling by trees growing in varying levels of urbanization (based on % impervious surfaces, e.g., buildings, pavement), urban forest species composition, tree size, and tree density must be characterized. As a part of Oak Ridge National Laboratory’s (ORNL) urban forest temperature study, we conducted tree censuses in five Knoxville city parks where ORNL meteorological stations are deployed. Moreover, we measured every woody plant ≥ 5 cm diameter at breast height (DBH) within a 50 m radius of each site’s meteorological station for its DBH and species identification. When possible, individuals were identified down to species. Certain genera (Quercus spp., Carya spp., Pinus spp.) were identified down to genera in interest of time. Individual and total site basal area were calculated from measured DBH data. Results show notable differences in urban plant community compositions and total woody plant basal area across sites, with more urban sites closer to downtown (West View and SEEED) having lower tree basal area than the more suburban sites (West Hills, Cumberland Estates, and Victor Ashe). We identified 54 species across all sites, with West Hills and Victor Ashe having the highest species diversity. Our results show differences in forest compositions and sizes across Knoxville, which are currently informing ORNL’s evapotranspiration estimates for each site. Data Summary: Census data for West Hills (WH), Cumberland Estates (CE), Victor Ashe (VA), West View (WV), and Socially Equal Energy Efficient Development or SEEED (SD) urban forests in Knoxville, TN, USA, including tree size based on diameter at breast height (DBH; 1.3 m), species identification (Latin and common names), and basal area per stem (BA=π×[.5*DBH]^2). Field data are summarized in this file: “Community_Composition_Data.CSV”. Site-specific data detailing each site’s coordinates, number of stems measured at DBH, average tree DBH, α-diversity (number of species present), and total site basal area (sum of individual basal areas per site) are in this file: “Site_Comparisons.CSV”.

Warren, Jeffrey [ORNL] (ORCID:0000000206804697)↗

Mycorrhizal associations of temperate forest seedlings mediate rhizodeposition, but not soil carbon storage, under elevated nitrogen availability

Abstract Tree‐mycorrhizal associations are associated with patterns in nitrogen (N) availability and soil organic matter storage; however, we still lack a mechanistic understanding of what tree and fungal traits drive these patterns and how they will respond to global changes in soil N availability. To address this knowledge gap, we investigated how arbuscular mycorrhizal (AM)‐ and ectomycorrhizal (EcM)‐associated seedlings alter rhizodeposition in response to increased seedling inorganic N acquisition. We grew four species each of EcM and AM seedlings from forests of the eastern United States in a continuously 13 C‐labeled atmosphere within an environmentally controlled chamber and subjected to three levels of 15 N‐labeled fertilizer. We traced seedling 15 N uptake from, and 13 C‐labeled inputs (net rhizodeposition) into, root‐excluded or ‐included soil over a 5‐month growing season. N uptake by seedlings was positively related to rhizodeposition for EcM‐ but not AM‐associated seedlings in root‐included soils. Despite this contrast in rhizodeposition, there was no difference in soil C storage between mycorrhizal types over the course of the experiment. Instead root‐inclusive soils lost C, while root‐exclusive soils gained C. Our findings suggest that mycorrhizal associations mediate tree belowground C investment in response to inorganic N availability, but these differences do not affect C storage. Continued soil warming and N deposition under global change will increase soil inorganic N availability and our seedling results indicate this could lead to greater belowground C investment by EcM‐associated trees. This potential for less efficient N uptake by EcM‐trees could contribute to AM‐tree success and a shift toward more AM‐dominated temperate forests.

Fitch, Amelia A.↗

Multivariate environmental and trait-based controls of transpiration in the Central Amazon Rainforest

Tropical forest tree mortality is increasing due to more severe droughts, yet our understanding of how tree traits and life strategies are linked to drought stress has been limited by measurement scarcity. The BIONTE (BIOmass and NuTrient Experiment) near Manaus, Brazil hosts one of the world’s largest sap flow installations, with sensors in 90 canopy trees across a wood density gradient monitored since June 2022. The 2023 El Niño drought provided a unique opportunity to evaluate how water availability impacts tree transpiration. An interpretable machine learning framework was used to study the complex interactions between transpiration and multiple environmental variables such as soil water availability and vapor pressure deficit (VPD), and how these interactions vary with wood density and individual trees. We found varying responses of transpiration from different trees during the El Niño drought. Transpiration generally increased with temperature, with stronger effects in wetter areas and in trees with low to medium wood density. However, this response was modulated by stomatal sensitivity to VPD, which constrained transpiration under high atmospheric demand, particularly in intermediate-moisture area. The inflection in transpiration rate at high temperatures (>32°C) underscores the role of stomatal and hydraulic regulation in limiting water loss and protecting trees from excessive evaporative demand. Analysis of soil water contribution to transpiration revealed unimodal patterns in wetter area, with peak contributions near 0.45 cm 3 cm -3 of surface soil water and declining or flat responses beyond that threshold, suggesting a shift from water- to energy-limited transpiration. In contrast, drier areas exhibited limited transpiration sensitivity to soil water conditions and minimal trait-based variation in VPD responses, indicating supply-limited conditions. Despite higher wood density trees being generally more resilient, this study shows diverse tree drought resilience, prompting further investigation into the specific traits and dynamics between environmental variables in regulating transpiration and other physiological processes in trees.

Drought↗

Getting allometry right at the Oak Ridge free‐air CO 2 enrichment experiment: Old problems and new opportunities for global change experiments

Societal Impact Statement Free‐air CO 2 enrichment (FACE) experiments provide essential data on forest responses to increasing atmospheric CO 2 for evaluations of climate change impacts on humanity. Understanding and reducing the uncertainty in the experimental results is critical to ensure scientific and public confidence in the models and policy initiatives that derive therefrom. One source of uncertainty is the estimation of tree biomass using mathematical relationships between biomass and easily obtained and non‐destructive measurements (allometry). We evaluated the robustness of the allometric relationships established at the beginning of a FACE experiment and discuss the challenges and opportunities for the new generation of FACE experiments. Summary Long‐term field experiments to elucidate forest responses to rising atmospheric CO 2 concentration require allometric equations to estimate tree biomass from non‐destructive measurements of tree size. We analyzed whether the allometric equations established at the beginning of a free‐air CO 2 enrichment (FACE) experiment in a Liquidambar styraciflua plantation were still valid at the end of the 12 year experiment. Aboveground woody biomass was initially predicted by an equation that included bole diameter, taper, and height, assuming that including taper and height as predictors would accommodate changes in tree structure that might occur over time and in response to elevated CO 2 . At the conclusion of the FACE experiment, we harvested 23 trees, measured dimensions and dry mass of boles and branches, and extracted and measured the woody root mass of 10 trees. Although 10 of the harvested trees were larger than the trees used to establish the allometric relationship, measured aboveground woody biomass was well predicted by the original allometry. The initial linear equation between bole basal area and woody root biomass underestimated final root biomass by 28%, but root biomass was just 21% of total wood mass, and errors in aboveground and belowground estimates were offsetting. The allometry established at the beginning of the experiment provided valid predictions of tree biomass throughout the experiment. New allometric approaches using terrestrial laser scanning should reduce an important source of uncertainty in decade‐long forest experiments and in assessments of centuries‐long forest biomass accretion used in evaluating carbon offsets and climate mitigation.

59 BASIC BIOLOGICAL SCIENCES↗

FORESTR: Finding, Organizing, Representing, Explaining, Summarizing, and Thinning Random forests

Random forests have become popular models used for data driven predictions. As a result, random forests are currently used or being considered for high-consequence mission applications in national security, such as the prediction of yield from optical signals and malware detection. While random forests may provide accurate predictions, the complexity of the algorithm causes a lack of interpretability. Random forests are an ensemble of regression or decision trees. Individual regression and decision trees are interpretable, but ensembles are inherently difficult to interpret due to the compilation of many models. We aim to increase the interpretability of random forests by finding patterns in the ensemble of trees that can be used to “thin” (or remove) trees. As a starting point, in this report, we develop a new distance metric for quantifying the similarity between trees based on their topologies (i.e., shapes). We base the metric on a novel distance metric for graphs that is a proper mathematical distance, is invariant to transformations, has registration between graphs, and computes topological evolutions between graphs. We use the tree distance metric to compute tree statistics such as a “mean tree” and to identify clusters of trees. We apply the developed methodology to a toy dataset and a mission relevant product inspection dataset to demonstrate how the metric can provide insight into random forests. Furthermore, we discuss the limitations of the approach and ideas for future research into how the metric could be used as a thinning tool to develop less complex models.

97 MATHEMATICS AND COMPUTING↗

PANDORA: A Parallel Dendrogram Construction Algorithm for Single Linkage Clustering on GPU

This paper introduces Pandora, a parallel algorithm for computing dendrograms, the hierarchical cluster trees for single linkage clustering (SLC). Current parallel approaches construct dendrograms by partitioning a minimum spanning tree and removing edges. However, they struggle with skewed, hard-to-parallelize real-world dendrograms. Consequently, computing dendrograms is the sequential bottleneck in HDBSCAN*[21], a popular SLC variant. Pandora uses recursive tree contraction to address this limitation. Pandora contracts nodes to construct progressively smaller trees. It computes the smallest contracted dendrogram and expands it by inserting contracted edges. This recursive strategy is highly parallel, skew-independent, work-optimal, and well-suited for GPUs and multicores. We develop a performance portable implementation of Pandora in Kokkos[31] and evaluate its performance on multicore CPUs and multi-vendor GPUs (e.g., Nvidia, AMD) for dendrogram construction in HDBSCAN*. Multithreaded Pandora is 2.2x faster than the current best-multithreaded implementation. Our GPU version achieves 6-20x speedup on AMD GPUs and 10-37x on NVIDIA GPUs over multithreaded Pandora. Pandora removes HDBSCAN*’s sequential bottleneck, greatly boosting efficiency, particularly with GPUs.

Sao, Piyush↗

Terrestrial laser scanning data (Levels 0 and 1) for Pasoh, Malaysia, Sep 2024

This data package contains data from terrestrial laser scanning (TLS) at the Pasoh Forest Reserve, Malaysia. The Pasoh Forest Reserve is a facility of the Forest Research Institute Malaysia, and contains evergreen lowland dipterocarp forest. The Next-Generation Ecosystem Experiments Tropics (NGEE-Tropics) study areas at Pasoh were established to study how different species respond to climatic variation and soil water availability. Two study areas were chosen representing different topography and species. The TLS data archived here were collected to provide detailed, three-dimensional information about forest structure. Specifically, data were collected to allow tree-level characterization of woody structure and leaf area for 12 focal trees with FloraPulse and sap flux sensors, facilitating estimation of woody biomass and leaf area to allow upscaling of water content and transpiration data to the tree-level. Scan positions were not selected to provide consistent data for non-focal trees with the study areas. This data package contains the following data: - High-level files document further details of the campaign and data package: 1_CampaignSummary.csv provides details about the campaign and study site, 2_ScanAreasDetail.csv provides details about each separate scan area (groups of scans post-processed into a single point cloud), 3_TerrestrialLidarSensor.csv provides further technical details about the Riegl VZ-400i TLS sensor, TLS_CSV_dd.csv is a CSV Data Dictionary providing information about the fields in CSV files following the ESS-DIVE CSV File Formatting Guidelines Reporting Format, TLS_flmd.csv is a File Level Metadata file providing information about each file in the data package following the ESS-DIVE File Level Metadata Reporting Format, and README.txt is a text file describing the overall project and file structure. - Level 0 data are the raw data (.PROJ folders) as recorded by the Riegl VZ-400i TLS instrument before scan co-registration and post-processing with the Riegl's proprietary RiSCAN PRO software, which requires a license. - Level 1 data contain post-processed, co-registered data from each scan area. The "PointClouds" folder for each scan area contains a .las file with 1 cm resolution point cloud data exported from RiSCAN PRO. These are the main files likely to be of interest to most users and can be further processed with any software capable of manipulating .las files (e.g. Python, R CloudCompare). The "Project Information" folder contains log files from post-processing in RiSCAN PRO that may be of interest to users who want to see detailed records of post-processing, including all PDF reports generated by RiSCAN PRO. The "ScanPositions" folder contains information about the final position of all TLS scans, after post-processing, in multiple formats. The file ScanPositions_*.csv provides final geo-referenced scan positions, and the file SOP_backup_*.csv can be used in RiSCAN PRO to restore the co-registered scan positions if users wish to re-process raw data (Level 0 .PROJ folders) with RiSCAN PRO software (e.g., subsample to a different resolution, exclude a certain scan position, or apply different filters on reflectance or deviation values) without redoing time-consuming co-registration steps.

54 ENVIRONMENTAL SCIENCES↗

Terrestrial laser scanning data (Levels 0 and 1) from Urban Biogeochemistry Pilot Project sites, Knoxville, Tennessee, Jul 2024 - Jul 2025

This data package contains data from terrestrial laser scanning (TLS) at five urban park sites in Knoxville, Tennessee, USA. All parks include open-grown and/or closed-canopy trees and mixed nearby land use. These study sites were established as part of the Urban Biogeochemistry Pilot Project, which has an overall goal of better understanding how hydrobiogeochemical cycling is altered within the human environment. These five sites represent a gradient of urbanization, and were instrumented to understand hydrological and biogeochemical cycling (e.g., soil moisture, soil physical properties and biogeochemistry, tree transpiration, species type). The TLS data archived here were collected to provide detailed, three-dimensional information about forest structure. Specifically, data were collected to allow tree- and stand-level characterization of woody structure and leaf area. TLS scans were placed to capture the area around trees with sap flow sensors, and as much of a 50 m radius area around the meteorological station as possible given site property limits. Derived products will allow upscaling of water content and transpiration data. This data package contains the following data: - High-level files document further details of the campaign and data package: 1_CampaignSummary.csv provides details about the campaign and study site, 2_ScanAreasDetail.csv provides details about each separate scan area (groups of scans post-processed into a single point cloud), 3_TerrestrialLidarSensor.csv provides further technical details about the Riegl VZ-400i TLS sensor, TLS_CSV_dd.csv is a CSV Data Dictionary providing information about the fields in CSV files following the ESS-DIVE CSV File Formatting Guidelines Reporting Format, TLS_flmd.csv is a File Level Metadata file providing information about each file in the data package following the ESS-DIVE File Level Metadata Reporting Format, and README.txt is a text file describing the overall project and file structure. - Level 0 data are the raw data (.PROJ folders) as recorded by the Riegl VZ-400i TLS instrument before scan co-registration and post-processing with the Riegl's proprietary RiSCAN PRO software, which requires a license. - Level 1 data contain post-processed, co-registered data from each scan area. The "PointClouds" folder for each scan area contains a .las file with 1 cm resolution point cloud data exported from RiSCAN PRO. These are the main files likely to be of interest to most users and can be further processed with any software capable of manipulating .las files (e.g. Python, R CloudCompare). The "Project Information" folder contains log files from post-processing in RiSCAN PRO that may be of interest to users who want to see detailed records of post-processing, including all PDF reports generated by RiSCAN PRO. The "ScanPositions" folder contains information about the final position of all TLS scans, after post-processing, in multiple formats. The file ScanPositions_*.csv provides final geo-referenced scan positions, and the file SOP_backup_*.csv can be used in RiSCAN PRO to restore the co-registered scan positions if users wish to re-process raw data (Level 0 .PROJ folders) with RiSCAN PRO software (e.g., subsample to a different resolution, exclude a certain scan position, or apply different filters on reflectance or deviation values) without redoing time-consuming co-registration steps.

54 ENVIRONMENTAL SCIENCES↗

Dynamic ecosystem assembly and escaping the “fire trap” in the tropics: insights from FATES_15.0.0

Abstract. Fire is a fundamental part of the Earth system, with impacts on vegetation structure, biomass, and community composition, the latter mediated in part via key fire-tolerance traits, such as bark thickness. Due to anthropogenic climate change and land use pressure, fire regimes are changing across the world, and fire risk has already increased across much of the tropics. Projecting the impacts of these changes at global scales requires that we capture the selective force of fire on vegetation distribution through vegetation functional traits and size structure. We have adapted the fire behavior and effects module, SPITFIRE (SPread and InTensity of FIRE), for use with the Functionally Assembled Terrestrial Ecosystem Simulator (FATES), a size-structured vegetation demographic model. We test how climate, fire regime, and fire-tolerance plant traits interact to determine the biogeography of tropical forests and grasslands. We assign different fire-tolerance strategies based on crown, leaf, and bark characteristics, which are key observed fire-tolerance traits across woody plants. For these simulations, three types of vegetation compete for resources: a fire-vulnerable tree with thin bark, a vulnerable deep crown, and fire-intolerant foliage; a fire-tolerant tree with thick bark, a thin crown, and fire-tolerant foliage; and a fire-promoting C4 grass. We explore the model sensitivity to a critical parameter governing fuel moisture and show that drier fuels promote increased burning, an expansion of area for grass and fire-tolerant trees, and a reduction of area for fire-vulnerable trees. This conversion to lower biomass or grass areas with increased fuel drying results in increased fire-burned area and its effects, which could feed back to local climate variables. Simulated size-based fire mortality for trees less than 20 cm in diameter and those with fire-vulnerable traits is higher than that for larger and/or fire-tolerant trees, in agreement with observations. Fire-disturbed forests demonstrate reasonable productivity and capture observed patterns of aboveground biomass in areas dominated by natural vegetation for the recent historical period but have a large bias in less disturbed areas. Though the model predicts a greater extent of burned fraction than observed in areas with grass dominance, the resulting biogeography of fire-tolerant, thick-bark trees and fire-vulnerable, thin-bark trees corresponds to observations across the tropics. In areas with more than 2500 mm of precipitation, simulated fire frequency and burned area are low, with fire intensities below 150 kW m−1, consistent with observed understory fire behavior across the Amazon. Areas drier than this demonstrate fire intensities consistent with those measured in savannas and grasslands, with high values up to 4000 kW m−1. The results support a positive grass–fire feedback across the region and suggest that forests which have existed without frequent burning may be vulnerable at higher fire intensities, which is of greater concern under intensifying climate and land use pressures. The ability of FATES to capture the connection between fire disturbance and plant fire-tolerance strategies in determining biogeography provides a useful tool for assessing the vulnerability and resilience of these critical carbon storage areas under changing conditions across the tropics.

54 ENVIRONMENTAL SCIENCES↗

OrthoPhyl—streamlining large-scale, orthology-based phylogenomic studies of bacteria at broad evolutionary scales

Abstract There are a staggering number of publicly available bacterial genome sequences (at writing, 2.0 million assemblies in NCBI's GenBank alone), and the deposition rate continues to increase. This wealth of data begs for phylogenetic analyses to place these sequences within an evolutionary context. A phylogenetic placement not only aids in taxonomic classification but informs the evolution of novel phenotypes, targets of selection, and horizontal gene transfer. Building trees from multi-gene codon alignments is a laborious task that requires bioinformatic expertise, rigorous curation of orthologs, and heavy computation. Compounding the problem is the lack of tools that can streamline these processes for building trees from large-scale genomic data. Here we present OrthoPhyl, which takes bacterial genome assemblies and reconstructs trees from whole genome codon alignments. The analysis pipeline can analyze an arbitrarily large number of input genomes (>1200 tested here) by identifying a diversity-spanning subset of assemblies and using these genomes to build gene models to infer orthologs in the full dataset. To illustrate the versatility of OrthoPhyl, we show three use cases: E. coli/Shigella, Brucella/Ochrobactrum and the order Rickettsiales. We compare trees generated with OrthoPhyl to trees generated with kSNP3 and GToTree along with published trees using alternative methods. We show that OrthoPhyl trees are consistent with other methods while incorporating more data, allowing for greater numbers of input genomes, and more flexibility of analysis.

59 BASIC BIOLOGICAL SCIENCES↗

Sap Velocity Data for East River Watershed Sites (2023-2025)

This dataset includes sap velocity measurements for aspen (populus tremuloides), fir (abies lasiocarpa), spruce (Engelmann spruce) and lodgepole pine (pinus contorta) trees at nine sites in the East River Watershed near Gothic, CO. This dataset was generated following a similar method as a previous dataset (Dataset. doi:10.15485/1647654) but was conducted at different sites in the area and now includes lodgepole pine. Site selection was done to explicitly improve understanding of topographic controls of tree water use. The data collection began in June 2023 and we provide data until December 2025 - though data collection is ongoing. The sap flux data were collected using ICT SFM1 sensors and are presented in both units of cm h^-1 and as kg h^-1 by multiplying the sap flux by the sapwood area of the tree. All sap flow data has been been corrected using estimates of wounding diameter, water content of wood and sap wood depth. We also provide a normalized sap velocity estimate by subtracting each measurement from that trees' annual minimum and dividing by that trees' annual maximum. This provides data for each tree and year on a 0-1 scale. This data entry contains one CSV file that includes all available sap flow data. The timestamps are provided in local time as year, day of year and hour and each measurement contains an associated latitude, longitude and site number which can be used to identify trees in a given stand. Each species is given a numeric value as: 1= populus tremuloides, 2=Engelmann spruce, 3=abies lasiocarpa and 4=pinus contorta.

abies↗

Testing mechanisms of how mycorrhizal associations affect forest soil carbon and nitrogen cycling (Final Technical Report)

Trees are in a symbiotic partnership with mycorrhizal fungi in which they provide the fungi with carbon from photosynthesis and the fungi provide the trees with nutrients and water. In temperate forests, the vast majority of trees form symbioses with one of two types of mycorrhizal fungi—arbuscular mycorrhizal (AM) fungi or ectomycorrhizal (EcM) fungi. These fungi differ in their morphology, hyphal length, and nutrient acquisition strategies. Many studies have found systematic differences in soil organic matter and nitrogen availability between forest stands dominated by AM-associating trees versus EcM-associating trees. For instance, there is a larger proportion of organic matter that is mineral-associated, more available nitrogen, and lower soil carbon to nitrogen ratios in AM forest stands relative to EcM forests stands. However, the mechanisms driving these patterns are not known, which complicates our ability to model soil organic matter dynamics in forested ecosystems. The main objective of this research was to understand the degree to which the observed differences in soil C and N dynamics between AM and EcM dominated forests are driven by tree traits like litter decomposability and root exudation versus mycorrhizal fungal nutrient acquisition strategies. We investigated these mechanisms using observations and targeted experiments and incorporated this knowledge into a process-based soil organic matter model. The observational studies compared the importance of leaf litter decomposability versus fungal identity on soil organic matter processes. We found that often fungal identity and traits were more important drivers of soil organic matter patterns than leaf litter decomposability. We ran two novel experiments: 1) a growth chamber experiment across four EcM and four AM tree species using a 13 C-labeled atmosphere to trace seedling-derived C into hyphae, the rhizosphere, and soil; and 2) an in situ decomposition experiment of six different 13 C and 15 N labeled litters that ranged in decomposability incubated across a gradient of EcM dominance at three sites that capture important variation in climate, soils, and forest species composition. In the first experiment, we found no significant differences of seedling mycorrhizal association on soil carbon sequestration over a growing season, but we did find that mycorrhizal association affected rhizodeposition with EcM-associating seedlings depositing more carbon in response to increased nitrogen availability. The decomposition experiment is still ongoing, but thus far, we have found slower litter decomposition in only one of three EcM-dominated forests which suggests that differences between AM- and EcM-dominated forests depend on the environmental context and identity of the EcM fungi. Lastly, we explicitly incorporated mycorrhizal processes into the Carbon, Organisms, Rhizosphere, and Protection in the Soil Environment (CORPSE) model creating Myco-CORPSE. By including the different nutrient acquisition strategies of AM and EcM fungi, we explored the conditions under which EcM fungi can slow decomposition rates and lead to greater soil organic carbon accumulation compared to AM fungi. We found that the effect of EcM fungi was highly context dependent and that EcM fungi decreased decomposition in colder forests with recalcitrant litter inputs and when they produced oxidases and necromass-degrading enzymes. Our research highlights the importance of fungal nutrient acquisition in driving soil organic matter patterns and the need to move beyond the AM-EcM dichotomy to consider the identity and traits of the specific fungi participating in the symbiosis. Overall, this research has resulted in six, peer-reviewed published papers in journals such as Global Change Biology, Ecology (2), Soil Biology and Biochemistry, and Ecosystems (2). There are at least two more papers in progress on this research including one that was recently submitted to Global Change Biology.

54 ENVIRONMENTAL SCIENCES↗

Canopy structure modulates the sensitivity of subalpine forest stands to interannual snowpack and precipitation variability

A declining spring snowpack is expected to have widespread effects on montane and subalpine forests in western North America and across the globe. The way that tree water demands respond to this change will have important impacts on forest health and downstream water subsidies. Here, we present data from a network of sap velocity sensors and xylem water isotope measurements from three common tree species (Picea engelmannii, Abies lasiocarpa and Populus tremuloides) across a hillslope transect in a subalpine watershed in the Upper Colorado River basin. We use these data to compare tree- and stand-level responses to the historically high spring snowpack but low summer rainfall of 2019 against the low spring snowpack but high summer rainfall amounts of 2021 and 2022. From the sap velocity data, we found that only 40 % of the trees showed an increase in cumulative transpiration in response to the large snowpack year (2019), illustrating the absence of a common response to interannual spring snowpack variability. The trees that increased water use during the year with the large spring snowpack were all found in dense canopy stands – irrespective of species – while trees in open-canopy stands were more reliant on summer rains and, thus, more active during the years with modest snow and higher summer rain amounts. Using the sap velocity data along with supporting measurements of soil moisture and snow depth, we propose three mechanisms that lead to stand density modulating the tree-level response to changing seasonality of precipitation: Topographically mediated convergence zones have consistent access to recharge from snowmelt which supports denser stands with high water demands that are more reliant and sensitive to changing snow. Interception of summer rain in dense stands reduces the throughfall of summer rain to surface soils, limiting the sensitivity of the dense stands to changes in summer rain. Shading in dense stands allows the snowpack to persist deeper into the growing season, providing high local reliance on snow during the fore-summer (early-summer) drought period. Combining data generated from natural gradients in stand density, like this experiment, with results from controlled forest-thinning experiments can be used to develop a better understanding of the responses of forested ecosystems to futures with reduced spring snowpack.

54 ENVIRONMENTAL SCIENCES↗

Local carbon reserves are insufficient for phloem terpene induction during drought in Pinus edulis in response to bark beetle–associated fungi

Stomatal closure during drought inhibits carbon uptake and may reduce a tree's defensive capacity. Limited carbon availability during drought may increase a tree's mortality risk, particularly if drought constrains trees' capacity to rapidly produce defenses during biotic attack. We parameterized a new model of conifer defense using physiological data on carbon reserves and chemical defenses before and after a simulated bark beetle attack in mature Pinus edulis under experimental drought. Attack was simulated using inoculations with a consistent bluestain fungus (Ophiostoma sp.) of Ips confusus, the main bark beetle colonizing this tree, to induce a defensive response. Trees with more carbon reserves produced more defenses but measured phloem carbon reserves only accounted for c. 23% of the induced defensive response. Our model predicted universal mortality if local reserves alone supported defense production, suggesting substantial remobilization and transport of stored resin or carbon reserves to the inoculation site. Our results show that de novo terpene synthesis represents only a fraction of the total measured phloem terpenes in P. edulis following fungal inoculation. Without direct attribution of phloem terpene concentrations to available carbon, many studies may be overestimating the scale and importance of de novo terpene synthesis in a tree's induced defense response.

59 BASIC BIOLOGICAL SCIENCES↗

Poplar: a phylogenomics pipeline

Motivation Generating phylogenomic trees from the genomic data is essential in understanding biological systems. Each step of this complex process has received extensive attention and has been significantly streamlined over the years. Given the public availability of data, obtaining genomes for a wide selection of species is straightforward. However, analyzing that data to generate a phylogenomic tree is a multistep process with legitimate scientific and technical challenges, often requiring a significant input from a domain-area scientist. Results We present Poplar, a new, streamlined computational pipeline, to address the computational logistical issues that arise when constructing the phylogenomic trees. It provides a framework that runs state-of-the-art software for essential steps in the phylogenomic pipeline, beginning from a genome with or without an annotation, and resulting in a species tree. Running Poplar requires no external databases. In the execution, it enables parallelism for execution for clusters and cloud computing. The trees generated by Poplar match closely with state-of-the-art published trees. The usage and performance of Poplar is far simpler and quicker than manually running a phylogenomic pipeline. Availability and implementation Freely available on GitHub at https://github.com/sandialabs/poplar. Implemented using Python and supported on Linux.

Koning, Elizabeth [Sandia National Laboratories (S↗

Comparative genomics and stable isotope analysis reveal the saprotrophic-pathogenic lifestyle of a neotropical fungus

In terrestrial forested ecosystems, fungi may interact with trees in at least three distinct ways: (i) associated with roots as symbionts; (ii) as pathogens in roots, trunks, leaves, flowers, and fruits; or (iii) decomposing dead tree tissues on soil or even on dead tissues in living trees. Distinguishing the latter two nutrition modes is rather difficult in Hymenochaetaceae (Basidiomycota) species. Herein, we have used an integrative approach of comparative genomics, stable isotopes, host tree association, and bioclimatic data to investigate the lifestyle ecology of the scarcely known neotropical genus Phellinotus, focusing on the unique species Phellinotus piptadeniae. This species is strongly associated with living Piptadenia gonoacantha (Fabaceae) trees in the Atlantic Forest domain on a relatively high precipitation gradient. Phylogenomics resolved P. piptadeniae in a clade that also includes both plant pathogens and typical wood saprotrophs. Furthermore, both genome-predicted Carbohydrate-Active Enzymes (CAZy) and stable isotopes (δ 13 C and δ 15 N) revealed a rather flexible lifestyle for the species. Altogether, our findings suggest that P. piptadeniae has been undergoing a pathotrophic specialization in a particular tree species while maintaining all the metabolic repertoire of a wood saprothroph.

59 BASIC BIOLOGICAL SCIENCES↗

Roles for epigenetics in wood formation and stress response intrees–from basic biology to forest management

Annual model and crop species have been the subject of most epigenetic studies for plants. In contrast to annuals, forest trees persist on natural landscapes and experience environmental variation within and across seasons, years, and decades or even centuries. Most forest trees species are undomesticated and typically grown on variable landscapes with no irrigation or application of agricultural chemicals. Forest trees must thus rely on their inherent ability to alter growth and physiology to mitigate the effects of changing abiotic and biotic stressors. Like other plants, trees have mechanisms encoded in their genomic DNA sequence that can respond directly to stress events such as drought or heat. Hypothetically, it would be highly advantageous to join these mechanisms with a dynamic “memory” of past exposure to stress. It is now well established that annual model and crop plants can establish epigenetic-based memory of stress events that support more rapid and robust response to stress in the future. Here, evidence is discussed for epigenetic regulation and “memory” in two fundamental biological processes in trees, wood formation and abiotic stress response. Wood formation is an ideal trait for epigenetic research in trees, as wood formation is highly responsive to environmental conditions and includes multiple rapid developmental changes as cells adopt distinct fates within complex tissues. This is followed by a discussion of research needs that would provide the foundation for new epigenetic applications for forestry.

Groover, Andrew↗

Hydraulic redistribution supplies a major water subsidy and improves water status of understory species in a longleaf pine ecosystem

Hydraulic redistribution (HR) is a common phenomenon in water-limited ecosystems; however, it remains unclear how the volume of water transported via HR compares to other components of the hydrologic budget and how HR influences water availability for understory plant communities. In this study, we investigate the absolute and relative magnitude of HR on a forest water budget and identify potential impacts of this water subsidy to understory plant communities. We scaled tree-level estimates of transpiration and HR of three common tree species naturally occurring in a longleaf pine woodland with plot-level measurements of basal area to determine their magnitude at the stand scale. We trenched plots containing understory vegetation but devoid of mature trees and their connected roots to exclude HR subsidies to understory plant species. We analysed soil water isotopes and assessed leaf water potential (Ψ L ) in trenched and control plots to determine if HR results in mixing of water among soil strata and improves understory plant moisture status. Water inputs from HR were equivalent to >30% of total rainfall for the site during the observation period and ~40% of total tree water uptake, depending on species. A stable isotope mixing model confirmed that soil water within HR-exposed plots was more similar to groundwater, whereas soil water within trenched plots was more similar to precipitation. Exclusion of HR via trenching decreased soil moisture and pre-dawn Ψ L for all understory species. These three lines of evidence suggest that HR from overstory trees redistributes a sizable portion of water from deeper to shallower soil profiles and that this water subsidy enhances understory plant water status.

54 ENVIRONMENTAL SCIENCES↗