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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

A haplotype‐resolved reference genome of Quercus alba sheds light on the evolutionary history of oaks

Summary White oak ( Quercus alba ) is an abundant forest tree species across eastern North America that is ecologically, culturally, and economically important. We report the first haplotype‐resolved chromosome‐scale genome assembly of Q. alba and conduct comparative analyses of genome structure and gene content against other published Fagaceae genomes. We investigate the genetic diversity of this widespread species and the phylogenetic relationships among oaks using whole genome data. Despite strongly conserved chromosome synteny and genome size across Quercus , certain gene families have undergone rapid changes in size, including defense genes. Unbiased annotation of resistance (R) genes across oaks revealed that the overall number of R genes is similar across species – as are the chromosomal locations of R gene clusters – but, gene number within clusters is more labile. We found that Q. alba has high genetic diversity, much of which predates its divergence from other oaks and likely impacts divergence time estimations. Our phylogenetic results highlight widespread phylogenetic discordance across the genus. The white oak genome represents a major new resource for studying genome diversity and evolution in Quercus . Additionally, we show that unbiased gene annotation is key to accurately assessing R gene evolution in Quercus .

Larson, Drew A. [Department of Biology Indiana Uni↗
DOE OSTI2020

Effects of nitrogen enrichment on tree carbon allocation: A global synthesis

Aim: Increased atmospheric nitrogen deposition may have profound effects on tree carbon allocation dynamics. However, a comprehensive understanding of how nitro-gen (N) enrichment influences carbon (C) allocation across plant functional processes and tree organs in individual trees remains elusive. Location: Global forest ecosystems. Time period: 1990–2018. Major taxa studied: Trees. Methods: We compiled data from 75 N addition experiments and conducted a meta-analysis to evaluate the responses of C source (photosynthesis), sinks (growth and respiration) and storage (non-structural carbohydrate concentrations) in different tree organs (foliage, above-ground wood and roots) to N enrichment. Results: N enrichment significantly enhanced C supply via photosynthesis (+39.6%, n = 128). C allocation to growth (biomass increment/production) significantly in-creased in foliage (+15.9%, n = 68) and above-ground wood (+31.8%, n = 64; bole, branch, stem and/or twig) with increasing N availability, but not in roots, whereas allocation increased in roots via increasing fine root turnover rate (+22.6%, n = 11). N fertilization significantly increased C allocation to respiration in above-ground wood (+46.6%, n = 12) and roots (+5.5%, n = 57), but not in foliage. N addition decreased non-structural carbohydrate (NSC) concentrations in foliage (-5.4%, n = 16) and roots (-5.0%, n = 21), but increased NSC in above-ground wood (+6.1%, n = 22). In addition, N enrichment effects were strongly affected by moderator variables. Main conclusions: Our results demonstrate that N addition increased C allocation to growth and respiration more strongly than C allocation to NSC storage, and increased C allocation to above-ground parts more strongly than to below-ground parts. Our results are useful for better understanding the response of tree functional processes at organ level to N enrichment. The existing data also reveal that more long-term ex-perimental studies on mature trees in tropical and boreal forests are urgently needed to provide a basis for forecasting tree responses to N enrichment at the global scale.

Li, Weibin↗
DOE OSTI2024

The Median Isn’t the Message: soil nutrient hot spots have a disproportionate influence on biogeochemical structure across years, seasons, and depths

Abstract Soil nutrient distribution is heterogeneous in space and time, potentially altering nutrient acquisition by trees and microorganisms. Ecologists have distinguished “hot spots” (HSs) as areas with enhanced and sustained rates of nutrient fluxes relative to the surrounding soil matrix. We evaluated the spatial and temporal patterns in nutrient flux HSs in two mixed-conifer forest soils by repeatedly sampling the soil solution at the same spatial locations (horizontally and vertically) over multiple seasons and years using ion exchange resins incubated in situ. The climate of these forests is Mediterranean, with intense fall rains occurring following summers with little precipitation, and highly variable winter snowfall. Hot spots formed most often for NO 3 − and Na + . Although nutrient HSs often occurred in the same spatial location multiple times, HSs persisted more often for PO 4 3− NH 4 + , and NO 3 − , and were more transient for Ca 2+ , Mg 2+ , and Na + . Sampling year (annual precipitation ranged from 558 to 1223 mm) impacted the occurrence of HSs for most nutrients, but season was only significant for PO 4 3− , NH 4 + , NO 3 − , and Na + , with HSs forming more often after fall rains than after spring snowmelt. The frequency of HSs significantly decreased with soil depth for all nutrients, forming most commonly immediately below the surficial organic horizon. Although HSs accounted for less than 17% of the sampling volume, they were responsible for 56–88% of PO 4 3− , NH 4 + , and NO 3 − resin fluxes. Our results suggest that macronutrient HSs have a disproportional contribution to soil biogeochemical structure, with implications for vegetation nutrient acquisition strategies and biogeochemical models. Graphical abstract

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Impact of prescribed fire on soil microbial communities in a Southern Appalachian Forest clear-cut

Escalating wildfire frequency and severity, exacerbated by shifting climate patterns, pose significant ecological and economic challenges. Prescribed burns, a common forest management tool, aim to mitigate wildfire risks and protect biodiversity. Nevertheless, understanding the impact of prescribed burns on soil and microbial communities in temperate mixed forests, considering temporal dynamics and slash fuel types, remains crucial. Our study, conducted at the University of Tennessee Forest Resources AgResearch and Education Center in Oak Ridge, TN, employed controlled burns across various treatments, and the findings indicate that low-intensity prescribed burns have none or minimal short-term effects on soil parameters but may alter soil nutrient concentrations, as evidenced by significant changes in porewater acetate, formate, and nitrate concentrations. These burns also induce shifts in microbial community structure and diversity, with Proteobacteria and Acidobacteria increasing significantly post-fire, possibly aiding soil recovery. In contrast, Verrucomicrobia showed a notable decrease over time, and other specific microbial taxa correlated with soil pH, porewater nitrate, ammonium , and phosphate concentrations. Our research contributes to understanding the intricate relationships between prescribed fire, soil dynamics, and microbial responses in temperate mixed forests in the Southern Appalachian Region, which is valuable for informed land management practices in the face of evolving environmental challenges.

Microbiology↗
DOE OSTI2022

Effects of trunk injection with emamectin benzoate on arthropod diversity

Abstract BACKGROUND Pine wood nematode is a major plant quarantine object in the world. Trunk injection is an effective method for controlling pests that cause disease. To evaluate the ecological safety of trunk injection with emamectin benzoates in forests of Pinus massoniana , the community diversity and community composition of soil arthropods and flying insects (Hymenoptera) were studied at different stages of trunk injection. RESULTS The dominant taxonomic groups of soil arthropods were Collembola (30.80%), Insecta (26.42%), and Arachnida (23.84%). The taxonomic groups of flying insects (Hymenoptera) were Ichneumonidae (48.94%), Formicidae (14.10%), and Braconidae (8.44%). Trunk injection with emamectin benzoate has no significant effect on the community diversity indices of total soil arthropods and flying insects (Hymenoptera). However, it has a significant effect on the community diversity indices of detritivores for soil arthropods. It changed the community composition of soil arthropods but did not impact the community composition of flying insects (Hymenoptera). Redundancy analysis of arthropod community structure and environmental variables showed that total potassium, residual of green leaf, and residual of litter leaf have a significant impact on the community structure of soil arthropods, and total phosphorus, total nitrogen, water content, organic matter, and total potassium have a significant impact on the community structure of flying insects (Hymenoptera). CONCLUSION Trunk injection with emamectin benzoate is safe for the ecological environment. This study provides a new insight into the field for the prevention and control of pine wood nematode disease, which is of great significance to forest management and pest control. © 2022 Society of Chemical Industry.

Ouyang, Xianheng↗
DOE OSTI2025

Observations and modeling reveal that heatwaves reduce photosynthesis, plant carbon reserves, and net carbon uptake

Heatwaves threaten ecosystem carbon balances, yet the mechanisms driving short-term carbon flux responses remain poorly understood. Here, integrating high-frequency eddy covariance (EC) data from 140 global flux tower sites (872 site-years) with detailed process-based modeling, we examine ecosystem responses during and immediately after heatwaves. We show that heatwaves caused a −40% (range [−29%, −128%]) reduction in net ecosystem productivity (NEP) compared to pre-heatwave values, with this reduction persisting over the following two weeks (−38% range [+3%, −154%]). We attributed NEP decreases to photosynthesis decreases more than to ecosystem respiration (RE) increases. Forest sites had greater NEP decreases during heatwaves than non-forest sites, but remained carbon sinks afterwards, indicating resilience. Our modeling analysis of extreme heatwaves at selected EC sites shows that decreased photosynthesis, increased maintenance respiration, and decreased plant non-structural carbon reserves during heatwaves drive carbon cycle changes that persist for weeks. Consistent with phenocam observations, we modeled a reduction in leaf area index caused by reduced non-structural carbon reserves, leading to early leaf senescence and longer-term impacts. Ongoing increases in heatwaves are therefore likely to reduce NEP across a range of ecosystems, exacerbating carbon cycle feedback.

carbon cycle↗
DOE OSTI2022

AmeriFlux FLUXNET-1F US-UMd UMBS Disturbance

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-UMd UMBS Disturbance. This is the FLUXNET version of the carbon flux data for the site US-UMd UMBS Disturbance produced by applying the standard ONEFlux (1F) software. Site Description - The UMBS Disturbance site is an artificial disturbance site that has recently been created as part of the Forest Accelerate Succession ExperimenT (FASET). In Spring 2008, every aspen and birch tree (>6,700, ~35% canopy LAI), the dominant early successional trees, were girdled over 39 ha of the FASET treatment plot to stimulate a disturbance that will move the forest into a later successional stage, dominated by maples, oaks, and white pine. This treatment caused aspen and birch mortality within 2 - 3 years. As a result of the changed canopy structure, there is a divergence in net ecosystem exchange between the control plot (enhanced carbon uptake) and the treatment plot (reduced carbon uptake).

Classen, Aimee↗
DOE OSTI2026

Data for The Value of Reversible Carbon Storage in a Zero-Emissions World

Atmospheric carbon dioxide removal (CDR) is required to stabilize global temperature. CDR can be achieved via ecosystem-based approaches that are cost-effective but reversible (e.g., soil and forest management) or by more durable but expensive approaches (e.g., direct air capture coupled with geologic storage). Here, we examine trade-offs between these approaches, focusing on timing, climate impacts, and cost. We simulated reversible carbon accrual for a range of CDR contract structures using a general minimalist model of ecosystem carbon cycling, and parameterized it to simulate US agricultural soil management─specifically cover cropping─as a case study. We then quantified the resulting impact on atmospheric carbon and global temperature using a climate model emulator. We find that maintaining a patchwork of reversible CDR projects by replacing lapsed projects with new projects can reduce warming by 22–195 μ°C in 2100 and that the magnitude of this cooling effect depends on how effectively the patchwork is maintained. Long-term maintenance of reversible CDR projects requires institutional stability that cannot be guaranteed over multiple decades. Consequently, effective CDR ultimately requires replacing reversible projects with durable projects. To address this problem, we modeled the cost of replacing reversible agricultural soil CDR with geologic CDR. We found that using reversible CDR as a bridge to durable CDR is potentially more cost-effective as a global cooling strategy (0.20–0.81 billion USD per μ°C avoided) than perpetual maintenance of reversible CDR (0.32–1.31 billion USD per μ°C avoided) or an immediate transition to durable CDR (1.37–2.19 billion USD per μ°C avoided). However, we emphasize that institutional commitments to maintain reversible CDR projects cannot be guaranteed. Reliance on reversible CDR as a bridge to durable CDR therefore carries an unknown amount of risk and will only function if efforts to maintain reversible CDR are robust.

Carbon↗
DOE OSTI2022

Damage Detection and Electrical Performance Impact of Flat-Flexible Circuits

Flat-flexible circuits or ‘flex circuits’ have varied applications in electronics and in explosive detonation systems. They pose advantages over conventional coaxial cables in their ability to fit into small mechanical envelopes and routings. A typical flex circuit is composed of a laminated assembly of multiple layers of conductor and dielectric materials. Copper, because of its high electrical conductivity, is one of the primary materials used in flex circuit conductors. The conductor must maintain structural integrity and electrical continuity when the flexible circuit is bent during processing or to fit an application envelope. Under some strain conditions a cable may have degraded electrical performance even though visible damage may not be evident. Dislocation density can increase by mechanisms such as dislocation forest hardening, where gliding dislocations in primary slip planes get pinned at obstacles and form Frank-Read sources. Dislocation density increases within the conductor layers may impact electrical resistivity but would not necessarily result in visible mechanical failure. In some detonation applications, such as for building implosion for demolition, the time for signal transmission and voltage used for firing detonators can be critical. If the resistance in a single flex cable within a building demolition array is too high, the resultant demolition shape may be asymmetric, leading to unplanned damage to nearby structures and potential hazards to public safety. This study will apply non-destructive evaluation techniques to evaluate the detectability of damage accumulation in flat, flexible copper-conductor cables and discuss potential implications to their practical use.

42 ENGINEERING↗
DOE OSTI2020

Implications from Monitoring Gopher Tortoises at Two Spatial Scales

A problem that conservation biologists face is how to monitor species, given both resource limitations and the inherent challenges of assessing long-term demographic processes. We assessed gopher tortoise (Gopherus polyphemus) abundance at a landscape scale and at the scale of 3 local populations within the Conecuh National Forest (CNF).USA between 1991 and 2017. Landscape-level data were collected 26 from line transect distance sampling arranged uniformly across the CNF and collected during a single season (2011); data for local populations were generated from long-term mark-recapture of individuals at three sites selected based on prior knowledge of high density at each. At a landscape scale, we estimated 5,242 (95% CI = 3,538-7,768) tortoises occurred across the approximately 34,000-ha forest, yielding a density of 0.14-0.32 tortoises/ ha. These low densities across the landscape suggest that, on average, management activities across the property have not allowed tortoise populations to retain social structure needed for long-term persistence. The three local populations, however, contained 25-60 individuals and densities of 1.9–6.9 tortoises/ha. Over the study period, populations at two sites were stable and the third experienced significant population growth. Mean annual survival of individuals was 0.89 and invariant across size classes. Altogether, line transect distance sampling is important for assessing landscape-scale abundance of tortoises but may fail to detect local clusters of high-density sites important for population persistence. Our mark-recapture efforts at the local scale revealed that small populations on these high-density sites can exhibit long-term stability or growth even though they do not meet current established criteria for viability. Improved models that incorporate immigration and emigration and better reflect dynamics of peripheral populations would assist in determining how such populations best contribute to species recovery and regional conservation targets.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Benchmarking and parameter sensitivity of physiological and vegetation dynamics using the Functionally Assembled Terrestrial Ecosystem Simulator (FATES) at Barro Colorado Island, Panama

Plant functional traits determine vegetation responses to environmental variation, but variation in trait values is large, even within a single site. Likewise, uncertainty in how these traits map to Earth system feedbacks is large. We use a vegetation demographic model (VDM), the Functionally Assembled Terrestrial Ecosystem Simulator (FATES), to explore parameter sensitivity of model predictions, and comparison to observations, at a tropical forest site: Barro Colorado Island in Panama. We define a single 12-dimensional distribution of plant trait variation, derived primarily from observations in Panama, and define plant functional types (PFTs) as random draws from this distribution. We compare several model ensembles, where individual ensemble members vary only in the plant traits that define PFTs, and separate ensembles differ from each other based on either model structural assumptions or non-trait, ecosystem-level parameters, which include (a) the number of competing PFTs present in any simulation and (b) parameters that govern disturbance and height-based light competition. While single-PFT simulations are roughly consistent with observations of productivity at Barro Colorado Island, increasing the number of competing PFTs strongly shifts model predictions towards higher productivity and biomass forests. Different ecosystem variables show greater sensitivity than others to the number of competing PFTs, with the predictions that are most dominated by large trees, such as biomass, being the most sensitive. Changing disturbance and height-sorting parameters, i.e., the rules of competitive trait filtering, shifts regimes of dominance or coexistence between early- and late-successional PFTs in the model. Increases to the extent or severity of disturbance, or to the degree of determinism in height-based light competition, all act to shift the community towards early-successional PFTs. In turn, these shifts in competitive outcomes alter predictions of ecosystem states and fluxes, with more early-successional-dominated forests having lower biomass. It is thus crucial to differentiate between plant traits, which are under competitive pressure in VDMs, from those model parameters that are not and to better understand the relationships between these two types of model parameters to quantify sources of uncertainty in VDMs.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Wildland Fires in the Subtropical Hill Forests of Southeastern Bangladesh

The first ever comprehensive study on wildland fires in Bangladesh is carried out to develop a fire prevention and prediction method. The major causes of huge wildland fires (88%) in the subtropical Chittagong Hill forest (43% of total) of southern Bangladesh are reported as shifting cultivation, grazing and unauthorized settlement. We used satellite hotspot (HS) data from 2003 to 2021 (a total of 54,669 HSs) to clarify the spatio-temporal structure of wildland fires. Fire weather conditions were analyzed using various weather data and synoptic-scale weather maps at different air levels. Fires concentrated from March through April or a transitional period from the dry season, caused by the Asian winter monsoon, to the wet season, due to the Asian summer monsoon. Fire occurrence depended on dry conditions and pre-monsoon showers and their timing. The difference in 925 hPa heights of high and low pressure systems may be attributed to the different types of the Asian winter and summer monsoons. The average maximum air temperature and incident shortwave solar energy in April were the highest and strongest, contributing fire-prone weather conditions. Based on the analysis, a fire prevention and prediction method will be developed, and this report may also facilitate the establishment of future CO 2 reduction measures for Bangladesh.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Alternating salt and freshwater floods of coastal soils impact soil structure, hydraulic properties, and oxygen dynamics

Coastal soils are increasingly impacted by hydrologic intensification in the form of rising sea level and flooding from storm surges and precipitation. Alternating saltwater (SW) and freshwater (FW) exposure has the potential to disperse colloids, which can lead to disintegration of soil structure, clogging of pore spaces, and reduction in ecologically and biogeochemically important functions like infiltration or gas exchange. To investigate how hydrologic intensification affects soil structure and oxygen dynamics, we conducted a series of laboratory-based flood simulations. Intact soil cores of the A and B horizons (22 total) from the toe slope of an upland coastal forest along the western shore of Chesapeake Bay. We subjected the cores to 24 h of saturation with either FW or alternating brackish SW and FW, with a 24-h draining event in between flood events. Oxygen diffusion into soil during draining was reduced by up to 30% for soils flooded alternating SW-FW compared to soils flooded only with FW. We attributed the reduced oxygen diffusion to clogging of smaller pores by colloids, with colloid redistribution observed as an increase in specific surface area down the core profile of up to 59%. After three SW-FW floods (six floods total), there were significant changes in pore size distribution, significant redistribution of colloids, and the A horizon became sodic. We concluded that a small number of SW flooding events can induce a measurable change in soil physical properties that directly impacts the biogeochemical dynamics.

Rod, Kenton A. [Pacific Northwest National Laborat↗
DOE OSTI2020

Revealing the Formation Energy–Exfoliation Energy–Structure Correlation of MAB Phases Using Machine Learning and DFT

MAB phases are popular as high-temperature materials with high damage tolerance and excellent electrical conductivity that are used to exfoliate two-dimensional (2D) transition metal borides (MBenes); a promising material for developing next- generation nanodevices. In this report, we explore the correlation between the formation energy, exfoliation energy and structural factors of MAB phases using DFT and machine learning. In order to do so, we developed three different machine learning models based on the support vector machine, deep neural network, and random forest regressor to study the stability of the MAB phases by calculating their formation energies. Furthermore, our support vector machine and deep neural network models are capable of predicting the formation energies with mean absolute errors less than 0.1 eV/atom. We demonstrated that the stability of a MAB phase for a given transition metal decreases when the A element changes from Al to Tl. The density functional theory (DFT) re- vealed that M-A and M-B bond strength strongly correlates with the stability of MAB phases. In addition, the exfoliation possibility of 2D MBenes becomes higher when the A element changes from Al to Tl due to weakening of M-A and M-B bonds.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Learning epistatic polygenic phenotypes with Boolean interactions

Detecting epistatic drivers of human phenotypes is a considerable challenge. Traditional approaches use regression to sequentially test multiplicative interaction terms involving pairs of genetic variants. For higher-order interactions and genome-wide large-scale data, this strategy is computationally intractable. Moreover, multiplicative terms used in regression modeling may not capture the form of biological interactions. Building on the Predictability, Computability, Stability (PCS) framework, we introduce the epiTree pipeline to extract higher-order interactions from genomic data using tree-based models. The epiTree pipeline first selects a set of variants derived from tissue-specific estimates of gene expression. Next, it uses iterative random forests (iRF) to search training data for candidate Boolean interactions (pairwise and higher-order). We derive significance tests for interactions, based on a stabilized likelihood ratio test, by simulating Boolean tree-structured null (no epistasis) and alternative (epistasis) distributions on hold-out test data. Finally, our pipeline computes PCS epistasis p-values that probabilisticly quantify improvement in prediction accuracy via bootstrap sampling on the test set. We validate the epiTree pipeline in two case studies using data from the UK Biobank: predicting red hair and multiple sclerosis (MS). In the case of predicting red hair, epiTree recovers known epistatic interactions surrounding MC1R and novel interactions, representing non-linearities not captured by logistic regression models. In the case of predicting MS, a more complex phenotype than red hair, epiTree rankings prioritize novel interactions surrounding HLA-DRB1 , a variant previously associated with MS in several populations. Taken together, these results highlight the potential for epiTree rankings to help reduce the design space for follow up experiments.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Bacterial community dynamics explain carbon mineralization and assimilation in soils of different land-use history

Soil dwelling microorganisms are key players in the terrestrial carbon cycle, driving both the degradation and stabilization of soil organic matter. Bacterial community structure and function vary with respect to land use; yet the ecological drivers of this variation remain poorly described and difficult to predict. For this work, we conducted a multi-substrate DNA-stable isotope probing experiment across cropland, old-field, and forest habitats to link carbon mineralization dynamics with the dynamics of bacterial growth and carbon assimilation. We tracked the movement of 13 C derived from five distinct carbon sources as it was assimilated into bacterial DNA over time. We show that carbon mineralization, community composition, and carbon assimilation dynamics all differed with respect to land use. We also show that microbial community dynamics affect carbon assimilation dynamics and are associated with soil DNA content. Soil DNA yield is easy to measure and may be useful in predicting microbial community dynamics linked to soil carbon cycling. Soil dwelling microorganisms are key players in the terrestrial carbon cycle, driving both the degradation and stabilization of soil organic matter. Microbial communities vary with respect to land use, but we still have an incomplete understanding of how variation in community structure links to variation in community function. DNA stable isotope probing (DNA-SIP) is a high-resolution method that can identify specific microbial taxa that assimilate carbon in situ. We conducted a large-scale multi-substrate DNA-SIP experiment to explore differences in bacterial activity across land-use regimes. We show that microbial community dynamics vary with land use, that these dynamics are linked to soil carbon cycling, and that they are associated with easily measured soil properties.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Insights into Prismatic Loop Formation in Irradiated Fe–Cr Alloys from Hypothesis-Driven Active Learning and Causal Analysis

Neutron and electron irradiation experimental studies conducted on body-centered cubic Fe and Fe–Cr alloys have established two prismatic dislocation loop populations, which have Burgers vectors of either a/2$\langle$111$\rangle$ or a$\langle$100$\rangle$. Here, the loop formation depends on factors such as dose (D), dose rate (D rt ), temperature (T), chromium content (Cr%), and other alloying elements. Hence, it is important to understand how irradiation-induced dislocation loops evolve conditional upon the loop characteristics, such as loop density (DD), average loop size d̅, and irradiation parameters (D, D rt , T, and irradiation type), which is still an active area of research. To understand these complex structure–property relationships, machine learning (ML) is employed in a three-step approach. This includes imputing missing data with a k-nearest neighbor, generating functionalized features, and assessing feature importance with random forest classification and regression. Physics-based features are incorporated in a hypothesis-driven active learning scheme to overcome data unavailability challenges. Insights obtained from ML models (i) to categorize dislocation loop types, show the highest correlation with d̅; (ii) Log(DD), obtained through mathematical formulations involving D, Cr%, d̅, and T (e.g., Log(DD) ~ D + exp(-Cr%) + 1/d̅ and log(DD) ~ D + exp(-Cr%) + 1/T). Hypothesis-driven active learning is able to predict Log(DD) in which the experimental date is not known. Causal models verify cause–effect relationships for dislocation loop classification and irradiation factors in FeCr alloys.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Towards a liana plant functional type for vegetation models

Lianas (woody climbers) are crucial components of tropical forests and they have been increasingly recognized to have profound effects on tropical forest carbon dynamics. Despite their importance, lianas' representation in vegetation models remains limited, partly due to the complexity of liana-tree dynamics and the diversity in liana life history strategies. This paper provides a comprehensive review of advances and challenges for mechanistically representing lianas in forest ecosystem models and a proposed path towards effectively representing lianas in these models. Defining a liana plant functional type is a significant challenge because of the high morphological and physiological diversity amongst liana species, and because of their structural association with trees. Here, we identify critical liana traits that likely should contribute to establishing a liana plant functional type, along with key processes to properly represent lianas in ecosystem models. Subsequently, we discuss a variety of possible liana implementation strategies with their associated strengths, limitations, computational costs and data requirements. A fundamental redesign of the tree-centric demographic vegetation models seems appropriate to accommodate the unique growth and competition strategies of lianas. We illustrate the potential of such models with a single-site case study where we disentangle putative mechanisms of liana increasing abundance. Furthermore, we underscore the critical need for comprehensive liana demographic and functional data (including long-term, physiological, and pantropical observations) for the qualitative implementation and evaluation in the proposed modeling efforts. Currently, there is a scarcity of liana data and the data that do exist have a neotropical bias. We finally introduce a new liana functional trait database that can centralize existing liana trait data, incentivize improved data gathering and thus facilitate model development and scientific analyses.

54 ENVIRONMENTAL SCIENCES↗