PBL height from random forest, random forest classifier and lightGBM ML models.
PBL height from random forest, random forest classifier and lightGBM ML models.
LightGBM ML models↗
SEARCH · Search NASA
Results for “FORESTS”
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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Mapping of Taiga Forest Units Using AirSar Data and/or Optical Data, and Retrieval of Forest Parameters
A maximum a posteriori Bayesian Classifier is used to perform a supervised classification of multifrequency, polariemtric, airborne, SAR obserations of boreal forests from the Bonanza Creek Experimental Forest, near Fairbanks, AK, into six Categories.
Taiga↗
Experimental warming advances phenology of groundlayer plants at the boreal‐temperate forest ecotone
Premise of the Study Changes to plant phenology have been linked to warmer temperatures caused by climate change. Despite the importance of the groundlayer to community and forest dynamics, few warming experiments have focused on herbaceous plant and shrub phenology. Methods Using a field study in Minnesota, United States, we investigated phenological responses of 16 species to warming over five growing seasons (2009–2013) at two sites, under two canopy covers, and in three levels of simultaneous above‐ and belowground warming: ambient temperature, ambient +1.7°C and ambient +3.4°C. We tested whether warming led to earlier phenology throughout the growing season and whether responses varied among species and years and depended on canopy cover. Key Results Warming extended the growing season between 11–30 days, primarily through earlier leaf unfolding. Leaf senescence was delayed for about half of the species. Warming advanced flowering across species, especially those flowering in August, with modest impacts on fruit maturation for two species. Importantly, warming caused more than half of the species to either converge or diverge phenologically in relation to each other, suggesting that future warmed climate conditions will alter phenological relationships of the groundlayer. Warm springs elicited a stronger advance of leaf unfolding compared to cool spring years. Several species advanced leaf unfolding (in response to warming) more in the closed canopy compared to the open. Conclusions Climate warming will extend the growing season of groundlayer species in the boreal‐temperate forest ecotone and alter the synchrony of their phenology.
Rice, Karen E.↗
Redox Fluctuations Control the Coupled Cycling of Iron and Carbon in Tropical Forest Soils
In this paper, oscillating redox conditions are a common feature of humid tropical forest soils, driven by an ample supply and dynamics of reductants, high moisture, microbial oxygen consumption, and finely textured clays that limit diffusion. However, the net result of variable soil redox regimes on iron (Fe) mineral dynamics and associated carbon (C) forms and fluxes is poorly understood in tropical soils. Using a 44-day redox incubation experiment with humid tropical forest soils from Puerto Rico, we examined patterns in Fe and C transformations under four redox regimes: static anoxic, "flux 4-day" (4d oxic, 4d anoxic), "flux 8-day" (8d oxic, 4d anoxic) and static oxic. Prolonged anoxia promoted reductive dissolution of Fe-oxides, and led to an increase in soluble Fe(II) and amorphous Fe oxide pools. Preferential dissolution of the less-crystalline Fe pool was evident immediately following a shift in bulk redox status (oxic to anoxic), and coincided with increased dissolved organic C, presumably due to acidification or direct release of organic matter (OM) from dissolving Fe(III) mineral phases. The average nominal oxidation state of water-soluble C was lowest under persistent anoxic conditions, suggesting that more reduced organic compounds were metabolically unavailable for microbial consumption under reducing conditions. Anoxic soil compounds had high H/C values (and were similar to lignin-like compounds) whereas oxic soil compounds had higher O/C values, akin to tannin- and cellulose-like components. Cumulative respiration derived from native soil organic C was highest in static oxic soils. These results show how Fe minerals and Fe-OM interactions in tropical soils are highly sensitive to variable redox effects. Shifting soil oxygen availability rapidly impacted exchanges between mineral-sorbed and aqueous C pools, increased the dissolved organic C pool under anoxic conditions implying that the periodicity of low-redox events may control the fate of C in wet tropical soils.
54 ENVIRONMENTAL SCIENCES↗
Real-time imaging of self-organization and mechanical competition in carbon nanotube forest growth [Real-time environmental TEM investigation of self-organization and mechanical competition in carbon nanotube forest growth]
Here, the properties of carbon nanotube (CNT) networks and analogous materials comprising filamentary nanostructures are governed by the intrinsic filament properties and their hierarchical organization and interconnection. As a result, direct knowledge of the collective dynamics of CNT synthesis and self-organization is essential to engineering improved CNT materials for applications such as membranes and thermal interfaces. Here, we use real-time environmental transmission electron microscopy (E-TEM) to observe nucleation and self-organization of CNTs into vertically aligned forests. Upon introduction of the carbon source, we observe a large scatter in the onset of nucleation of individual CNTs and the ensuing growth rates. Experiments performed at different temperatures and catalyst particle densities show the critical role of CNT density on the dynamics of self-organization; low-density CNT nucleation results in the CNTs becoming pinned to the substrate and forming random networks, whereas higher density CNT nucleation results in self-organization of the CNTs into bundles that are oriented perpendicular to the substrate. We also find that mechanical coupling between growing CNTs alters their growth trajectory and shape, causing significant deformations, buckling, and defects in the CNT walls. Therefore, it appears that CNT–CNT coupling not only is critical for self-organization but also directly influences CNT quality and likely the resulting properties of the forest. As a result, our findings show that control of the time-distributed kinetics of CNT nucleation and bundle formation are critical to manufacturing well-organized CNT assemblies and that E-TEM can be a powerful tool to investigate the mesoscale dynamics of CNT networks.
77 NANOSCIENCE AND NANOTECHNOLOGY↗
Listening to the Forest: An Artificial Neural Network‐Based Model of Carbon Uptake at Harvard Forest
Abstract The terrestrial biosphere strongly modulates atmospheric CO 2 mixing ratios, whose inexorable rise propels anthropogenic climate change. Modeling and mechanistically understanding C uptake by the terrestrial biosphere are thus of broad societal concerns. Yet despite considerable progress, scaling up point observations to landscape and larger scales continues to frustrate analyses of the anthropogenically perturbed global C cycle. While that up‐scaling is our overarching motivation, here we focus on one of its elements, modeling C uptake at a given site. We devise a novel artificial neural network (ANN)‐based model of C uptake at Harvard Forest that combines locally observed and remotely sensed variables. Most of our model predictors are those used by an established ecosystem C uptake model, the Vegetation Photosynthesis and Respiration Model (VPRM), easing comparisons. To those, we add observed cumulative antecedent precipitation and soil temperature. We find that model errors are much larger in winter, indicating that better understanding and modeling of respiration will likely discernibly improve model performance. Comparing the ANN and VPRM results reveals errors attributed to unrealistic treatment of temperature in the VPRM formulation, indicating that better representation of temperature dependencies is also likely to enhance model skill. By judiciously comparing VPRM and ANN errors we thus overcome ANNs' notoriety for concealing the mechanisms underlying their predictive skills. We demonstrate their ability to identify outstanding ecosystem science knowledge gaps and particularly fruitful corresponding model development directions, improving site specific and up‐scaling flux modeling and understanding of the climate impacts of the northern forest.
Eshel, Gidon↗
Quantifying mean, variability, and uncertainty in indoor radon exposure in Pennsylvania using random forest and quantile regression forest models
Radon is a naturally occurring radioactive gas that poses a serious health risk as the primary cause of lung cancer in non-smokers. Despite the well-known adverse association with health outcomes, current radon exposure assessments are limited to county-level or average-level estimates, which fail to capture regional variability. This study uses Machine Learning models, including Random Forest (RF) and Quantile Regression Forest (QRF), to estimate the indoor radon concentrations at the ZCTA (Zip code tabulation area)-level and characterize uncertainties in model estimates. Incorporating geological, meteorological, and building-specific data, the models aim to improve radon risk assessment by capturing mean exposure, variability, and extreme concentration levels. Processed radon test data (n = 718,111) were analyzed using average, variability, and quantile prediction methods. Models that estimate the average radon exposure at the ZCTA-level can yield promising model-fit results, but they do not capture the underlying variability of indoor radon exposure within a ZCTA. We utilize volatility analyses to identify characteristics indicative of high variability of indoor radon exposure. We also show that a QRF model can be used to estimate upper quantiles of residential radon exposure, thereby uncovering localized areas of elevated exposure that were not apparent in mean estimates. The results highlighted the need for a deep characterization of exposure risk and show that regions with moderate average exposure levels could still harbor extreme outliers with implications for evaluating health risks. Utilizing multiple radon exposure models allows for a deeper characterization of radon risk within a geographic area and can better identify high-risk areas. The results from this study provide a foundation for developing mitigation strategies and examining associations between radon exposure and health outcomes at fine scales. Future research should extend the geographic scope and incorporate additional environmental risk factors to establish a comprehensive framework for risk assessment.
Lee, Heechan [ORNL]↗
New Particle Formation and Growth in an Isoprene-Dominated Ozark Forest: From Sub-5 nm to CCN-Active Sizes
Particle Investigations at a Northern Ozarks Tower: NOx, Oxidant, Isoprene Research (PINOT-NOIR) were conducted in a Missouri forest dominated by isoprene emissions, from May to October 2012. This study presents results of new particle formation (NPF) and the growth of new particles to cloud condensation nuclei (CCN)-active sizes (~100 nm) observed from this field campaign. The measured sub-5 nm particles were up to ~20000 cm-3 during a typical NPF event. Nucleation rates J1 were relatively high (11.0±10.6 cm-3s-1), and one order of magnitude higher than formation rates of 5 nm particles (J5). Sub-5 nm particle events were observed on 64% of the measurement days, with a high preference in biogenic volatile organic compounds (BVOCs)- and SO2-poor northwesterly (90%) air masses than in BVOCs-rich southerly air masses (13%). About 80% of sub-5 nm particle events led to the further growth. While high temperatures and high aerosol loadings in the southerly air masses were not favorable for nucleation, high BVOCs in the southerly air masses facilitated the growth of new particles to CCN-active sizes. In overall, 0.4-9.4% of the sub-5 nm particles grew to CCN-active sizes within a NPF event. During a regional NPF event period that took place consecutively over several days, concentrations of CCN size particles increased by a factor of 5 in average. This enhanced production of CCN particles from new particles was commonly observed during all 13 regional NPF events observed during the campaign.
cloud condensation nuclei, isoprene, BVOC↗
Paraburkholderia solitsugae sp. nov. and Paraburkholderia elongata sp. nov., phenolic acid-degrading bacteria isolated from forest soil and emended description of Paraburkholderia madseniana
Two bacterial strains, 1N T and 5N T , were isolated from hemlock forest soil using a soluble organic matter enrichment. Cells of 1N T (0.65×1.85 µm) and 5N T (0.6×1.85 µm) are Gram-stain-negative, aerobic, motile, non-sporulating and exist as single rods, diplobacilli or in chains of varying length. During growth in dilute media (≤0.1× tryptic soy broth; TSB), cells are primarily motile with flagella. At higher concentrations (≥0.3× TSB), cells of both strains increasingly form non-motile chains, and cells of 5N T elongate (0.57×~7 µm) and form especially long filaments. Optimum growth of 1N T and 5N T occurred at 25–30 °C, pH 6.5–7.0 and <0.5% salinity. Results of comparative chemotaxonomic, genomic and phylogenetic analyses revealed that 1N T and 5N T were distinct from one another and their closest related type strains: Paraburkholderia madseniana RP11 T , Paraburkholderia aspalathi LMG 27731 T and Paraburkholderia caffeinilytica CF1 T . The genomes of 1N T and 5N T had an average nucleotide identity (91.6 and 91.3%) and in silico DNA–DNA hybridization values (45.8%±2.6 and 45.5%±2.5) and differed in functional gene content from their closest related type strains. The composition of fatty acids and patterns of substrate use, including the catabolism of phenolic acids, also differentiated strains 1N T and 5N T from each other and their closest relatives. The only ubiquinone present in strains 1N T and 5N T was Q-8. The major cellular fatty acids were C 16 : 0 , 3OH-C 16 : 0 , C 17 : 0 cyclo, C 19 : 0 cyclo ω8 c and summed features 2 (3OH-C 14 : 0 / C 16 : 1 iso I), 3 (C 16 : 1 ω6 c /ω7 c ) and 8 (C 18 : 1 ω7 c /ω6 c ). A third bacterium, strain RL16-012-BIC-B, was isolated from soil associated with shallow roots and was determined to be a strain of P. madseniana (ANI, 98.8%; 16S rRNA gene similarity, 100%). Characterizations of strain RL16-012-BIC-B (DSM 110723=LMG 31706) led to proposed emendments to the species description of P. madseniana . Our polyphasic approach demonstrated that strains 1N T and 5N T represent novel species from the genus Paraburkholderia for which the names Paraburkholderia solitsugae sp. nov. (type strain 1N T =DSM 110721 T =LMG 31704 T ) and Paraburkholderia elongata sp. nov. (type strain 5N T =DSM 110722 T =LMG 31705 T ) are proposed.
Microbiology↗
CMB lensing and Ly α forest cross bispectrum from DESI’s first-year quasar sample
The squeezed cross-bispectrum B κ,Ly α between the gravitational lensing in the cosmic microwave background and the 1D Ly α forest power spectrum can constrain bias parameters and break degeneracies between σ8 and other cosmological parameters. We detect B κ,Ly α with 4.8σ significance at an effective redshift z eff =2.4 using Planck PR3 lensing map and over 280,000 quasar spectra from the Dark Energy Spectroscopic Instrument’s first-year data. We test our measurement against metal contamination and foregrounds such as Galactic extinction and clusters of galaxies by deprojecting the thermal Sunyaev-Zeldovich effect. Finally, we compare our results to a tree-level perturbation theory calculation and find reasonable agreement between the model and measurement.
79 ASTRONOMY AND ASTROPHYSICS↗
Ecosystem-scale volatile organic compound fluxes during an extreme drought in a broadleaf temperate forest of the Missouri Ozarks (central USA)
Considerable amounts and varieties of biogenic volatile organic compounds (BVOCs) are exchanged between vegetation and the surrounding air. These BVOCs play key ecological and atmospheric roles that must be adequately represented for accurately modeling the coupled biosphere–atmosphere–climate earth system. One key uncertainty in existing models is the response of BVOC fluxes to an important global change process: drought. Here, we describe the diurnal and seasonal variation in isoprene, monoterpene, and methanol fluxes from a temperate forest ecosystem before, during, and after an extreme 2012 drought event in the Ozark region of the central USA. BVOC fluxes were dominated by isoprene, which attained high emission rates of up to 35.4 mg m 2 h 1 at midday. Methanol fluxes were characterized by net deposition in the morning, changing to a net emission flux through the rest of the daylight hours. Net flux of CO 2 reached its seasonal maximum approximately a month earlier than isoprenoid fluxes, which highlights the differential response of photosynthesis and isoprenoid emissions to progressing drought conditions. Nevertheless, both processes were strongly suppressed under extreme drought, although isoprene fluxes remained relatively high compared to reported fluxes from other ecosystems. Methanol exchange was less affected by drought throughout the season, confirming the complex processes driving biogenic methanol fluxes. The fraction of daytime (7–17 h) assimilated carbon released back to the atmosphere combining the three BVOCs measured was 2% of gross primary productivity (GPP) and 4.9% of net ecosystem exchange (NEE) on average for our whole measurement campaign, while exceeding 5% of GPP and 10% of NEE just before the strongest drought phase. In conclusion, the MEGANv2.1 model correctly predicted diurnal variations in fluxes driven mainly by light and temperature, although further research is needed to address model BVOC fluxes during drought events.
54 ENVIRONMENTAL SCIENCES↗
Causes of reduced leaf-level photosynthesis during strong El Niño drought in a Central Amazon forest
Not provided.
Biodiversity & Conservation↗
AVTA Federal Fleet PEV Readiness Data Logging and Characterization Study for the United States Forest Service: Caribou-Targhee National Forest
Battelle Energy Alliance, LLC, managing and operating contractor for the U.S. Department of Energy’s Idaho National Laboratory, is the lead laboratory for U.S. Department of Energy Advanced Vehicle Testing. Battelle Energy Alliance, LLC contracted with Intertek Testing Services, North America (ITSNA) to collect and evaluate data on federal fleet operations as part of the Advanced Vehicle Testing Activity’s Federal Fleet Vehicle Data Logging and Characterization study. The Advanced Vehicle Testing Activity study seeks to collect and evaluate data to validate the utilization of advanced electric drive vehicle transportation. This report focuses on the Caribou-Targhee National Forest (CTNF) fleet to identify daily operational characteristics of select vehicles and report findings on vehicle and mission characterizations to support the successful introduction of plug-in electric vehicles (PEVs) into the agencies’ fleets. Individual observations of these selected vehicles provide the basis for recommendations related to electric vehicle adoption and whether a battery electric vehicle (BEV) or plug-in hybrid electric vehicle (PHEV) (collectively plug-in electric vehicles, or PEVs) can fulfill the mission requirements. ITSNA acknowledges the support of Idaho National Laboratory and CTNF for participation in the study. ITSNA is pleased to provide this report and is encouraged by enthusiasm and support from the Forest Service and CTNF personnel.
33 ADVANCED PROPULSION SYSTEMS↗
A Preliminary Review of U.S. Forest Service Business Practices To Authorize Special Uses, Including Energy Infrastructure Projects, on National Forest System Lands
The U.S. Forest Service (USFS) Special Uses-Lands Program is in jeopardy. Although this program, authorized in Title 36, Part 251, of the U.S. Code of Federal Regulations (36 CFR Part 251), ranks among the top four revenue-generating programs for use of National Forest System (NFS) lands, along with the Timber, Minerals, and Special Uses-Recreation Programs, the Special Uses-Lands Program is in a state of neglect. Repeated cuts in funding (a decrease of 26% from fiscal years 2010 to 2014) are adversely affecting staffing and training, which in turn is affecting timely permit processing and ultimately the public’s ability to use and benefit from NFS lands. In addition, highly experienced staff with valuable institutional knowledge of the program have begun to retire. The ability of the program to function under these dire circumstances can be attributed to the dedication of Special Uses staff to the program and their commitment to the public. The initial focus of this report was to identify opportunities for improving performance of permitting and review for large energy infrastructure-related projects. However, it became clear during this analysis that these projects are generally adequately staffed and managed. This is due in large part to the availability of cost-recovery dollars and the high-profile nature of these projects. However, it also became apparent that larger issues affecting the bulk of the work of the Special Uses-Lands Program need to be addressed immediately. This report is a preliminary examination of the state of the Special Uses-Lands Program and focuses on a few key items requiring immediate attention. Further investigation through case studies is recommended to dig deeper into the Special Uses-Lands Program business process to determine the most costeffective strategies for streamlining the overall process and the metrics by which performance can be evaluated, including for the permitting and tracking of energy infrastructure projects.
29 ENERGY PLANNING, POLICY, AND ECONOMY↗
Evaluating the Performance of Random Forest and Iterative Random Forest Based Methods when Applied to Gene Expression Data
Gene-to-gene networks, such as Gene Regulatory Networks (GRN) and Predictive Expression Networks (PEN) capture relationships between genes and are beneficial for use in downstream biological analyses. There exists multiple network inference tools to produce these gene-to-gene networks from matrices of gene expression data. Random Forest-Leave One Out Prediction (RF-LOOP) is a method that has been shown to be efficient at producing these gene-to-gene networks, frequently known as GEne Network Inference with Ensemble of trees (GENIE3). Here we validate that iterative Random Forest-Leave One Out Prediction (iRF-LOOP) produces higher quality networks than GENIE3. We use both synthetic and empirical networks from the Dialogue for Reverse Engineering Assessment and Methods (DREAM) Challenges by Sage Bionetworks, as well as two additional empirical networks created from Arabidopsis thaliana and Populus trichocarpa expression data.
iRF-Loop, expression network, Populus Trichocarpa↗
Contribution from biogenic organic compounds to particle growth during the 2010 BEACHON-ROCS campaign in a Colorado temperate needleleaf forest
New particle formation (NPF) is an important atmospheric phenomenon. During an NPF event, particles first form by nucleation and then grow further in size. The growth step is crucial because it controls the number of particles that can become cloud condensation nuclei. Among various physical and chemical processes contributing to particle growth, condensation by organic vapors has been suggested as important. In order to better understand the influence of biogenic emissions on particle growth, we carried out modeling studies of NPF events during the BEACHON-ROCS (Bio–hydro–atmosphere interactions of Energy, Aerosol, Carbon, H2O, Organics & Nitrogen – Rocky Mountain Organic Carbon Study) campaign at Manitou Experimental Forest Observatory in Colorado, USA. The site is representative of the semi-arid western USA. With the latest Criegee intermediate reaction rates implemented in the chemistry scheme, the model underestimates sulfuric acid concentration by 50 %, suggesting either missing sources of atmospheric sulfuric acid or an overestimated sink term. The results emphasize the contribution from biogenic volatile organic compound emissions to particle growth by demonstrating the effects of the oxidation products of monoterpenes and 2-Methyl-3-buten-2-ol (MBO). Monoterpene oxidation products are shown to influence the nighttime particle loadings significantly, while their concentrations are insufficient to grow the particles during the day. The growth of ultrafine particles in the daytime appears to be closely related to the OH oxidation products of MBO.
54 ENVIRONMENTAL SCIENCES↗
Volatile Organic Compounds in Bankhead National Forest (AMF3). August to September, 2025
The formation of atmospheric aerosols through the transformation of volatile organic compounds (VOCs) is a fundamental process in aerosol-climate interactions, as these particles serve as cloud condensation nuclei and ultimately influence Earth’s radiative balance. However, there remains a critical need to quantify the effects of multiple coexisting VOC precursors on aerosol formation beyond the limitations of laboratory-scale studies. This research aims to advance the mechanistic understanding of secondary organic aerosol formation in the southeastern United States by investigating interactions among coexisting VOC precursors observed at the third ARM Mobile Facility located in the Bankhead National Forest. The dataset was generated from the deployment of Oak Ridge National Laboratory’s PTR-TOF 6000 X2 Proton Transfer Reaction Time-of-Flight Mass Spectrometer (PTR-ToF-MS) for the real-time, continuous monitoring of VOCs from August 21 to September 15, 2025. To minimize sampling artifacts and compound losses, the PTR-ToF-MS inlet was connected to the cabin flow line by replacing the existing Tygon tubing with 1/2-inch outer diameter perfluoroalkoxy (PFA) tubing. The instrument operated on an hourly measurement cycle consisting of 8 minutes of zero-air measurements followed by 52 minutes of ambient air sampling, with a temporal resolution of 10 seconds. The dataset includes concentrations, reported in ppb, of methanol, acetone, acetonitrile, isoprene, methyl vinyl ketone and methacrolein (MVK + MACR), monoterpenes, benzene, toluene, and catechol.
Atmospheric concentration of volatile organic comp↗
Inventory of forest and rangeland and detection of forest stress
There are no author-identified significant results in this report. Some ERTS-1 imagery has been received for each of the test sites: Black Hills, Atlanta, and Manitou. Only small portions of each site are covered and clouds have precluded capturing good imagery over the center of each site. Discoloration infestations of ponderosa pine are being located and sized on CIR transparencies. A computer program was completed from microdensitometer scans of CIR photos which maps areas of an image which are spectrally similar. Decided differences between forest types are present as well as differences between forest and other vegetative and nonvegetative land classes.
Heller, R. C.↗