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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 217 records · Page 12

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NASA NTRS2009

Modeling Bird Migration under Climate Change: A Mechanistic Approach

How will migrating birds respond to changes in the environment under climate change? What are the implications for migratory success under the various accelerated climate change scenarios as forecast by the Intergovernmental Panel on Climate Change? How will reductions or increased variability in the number or quality of wetland stop-over sites affect migratory bird species? The answers to these questions have important ramifications for conservation biology and wildlife management. Here, we describe the use of continental scale simulation modeling to explore how spatio-temporal changes along migratory flyways affect en-route migration success. We use an individually based, biophysical, mechanistic, bird migration model to simulate the movement of shorebirds in North America as a tool to study how such factors as drought and wetland loss may impact migratory success and modify migration patterns. Our model is driven by remote sensing and climate data and incorporates important landscape variables. The energy budget components of the model include resting, foraging, and flight, but presently predation is ignored. Results/Conclusions We illustrate our model by studying the spring migration of sandpipers through the Great Plains to their Arctic breeding grounds. Why many species of shorebirds have shown significant declines remains a puzzle. Shorebirds are sensitive to stop-over quality and spacing because of their need for frequent refueling stops and their opportunistic feeding patterns. We predict bird "hydrographs that is, stop-over frequency with latitude, that are in agreement with the literature. Mean stop-over durations predicted from our model for nominal cases also are consistent with the limited, but available data. For the shorebird species simulated, our model predicts that shorebirds exhibit significant plasticity and are able to shift their migration patterns in response to changing drought conditions. However, the question remains as to whether this behavior can be maintained over increasing and sustained environmental change. Also, the problem is much more complex than described by the current processes captured in our model. We have taken some important and interesting steps, and our model does demonstrate how local scale information about individual stop-over sites can be linked into the migratory flyway as a whole. We are incorporating additional, species specific, mechanistic processes to better reflect different climate change scenarios

Smith, James A.↗

DOE OSTI2026

TES: Modelling Microbes to Predict Post-Fire Carbon Cycling in the Boreal Forest across Burn Severities (Exploratory Proposal)

Wildfires in boreal ecosystems represent a globally significant ecological process that is expected to be sensitive to changing climate as well as forest management strategies, but is currently insufficiently understood and represented in models. We sought to determine whether linking belowground microbial community composition, size, and activity to aboveground properties of burn severity and plant community composition (upland jack pine and upland spruce) would allow us to better model post-fire soil CO 2 fluxes using the Carbon, Organisms, Rhizosphere and Protection in the Soil Environment (CORPSE) model. We used an integrated modelling experimental approach, with mechanistic laboratory experiments designed to inform models.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2014

How Do Various Maize Crop Models Vary in Their Responses to Climate Change Factors?

Potential consequences of climate change on crop production can be studied using mechanistic crop simulation models. While a broad variety of maize simulation models exist, it is not known whether different models diverge on grain yield responses to changes in climatic factors, or whether they agree in their general trends related to phenology, growth, and yield. With the goal of analyzing the sensitivity of simulated yields to changes in temperature and atmospheric carbon dioxide concentrations [CO2], we present the largest maize crop model intercomparison to date, including 23 different models. These models were evaluated for four locations representing a wide range of maize production conditions in the world: Lusignan (France), Ames (USA), Rio Verde (Brazil) and Morogoro (Tanzania). While individual models differed considerably in absolute yield simulation at the four sites, an ensemble of a minimum number of models was able to simulate absolute yields accurately at the four sites even with low data for calibration, thus suggesting that using an ensemble of models has merit. Temperature increase had strong negative influence on modeled yield response of roughly -0.5 Mg ha(sup 1) per degC. Doubling [CO2] from 360 to 720 lmol mol 1 increased grain yield by 7.5% on average across models and the sites. That would therefore make temperature the main factor altering maize yields at the end of this century. Furthermore, there was a large uncertainty in the yield response to [CO2] among models. Model responses to temperature and [CO2] did not differ whether models were simulated with low calibration information or, simulated with high level of calibration information.

carbon dioxide↗

DOE OSTI2025

A comparison of surrogate constitutive models for viscoplastic creep simulation of HT-9 steel

Mechanistic microstructure-informed constitutive models for the mechanical response of polycrystals are a cornerstone of computational materials science. However, as these models become increasingly more complex – often involving coupled differential equations describing the effect of specific deformation modes – their associated computational costs can become prohibitive, particularly in optimization or uncertainty quantification tasks that require numerous model evaluations. To address this challenge, surrogate constitutive models that balance accuracy and computational efficiency are highly desirable. Data-driven surrogate models, that learn the constitutive relation directly from data, have emerged as a promising solution. In this work, we develop two local surrogate models for the viscoplastic response of a steel: a piecewise response surface method and a mixture of experts model. These surrogates are designed to adapt to complex material behavior, which may vary with material parameters or operating conditions. The surrogate constitutive models are applied to creep simulations of HT-9 steel, an alloy of considerable interest to the nuclear energy sector due to its high tolerance to radiation damage, using training data generated from viscoplastic self-consistent (VPSC) simulations. In conclusion, we define a set of test metrics to numerically assess the accuracy of our surrogate models for predicting viscoplastic material behavior, and show that the mixture of experts model outperforms the piecewise response surface method in terms of accuracy.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Challenges in quantifying unparameterized spatial uncertainties in deep geologic repositories for nuclear waste

Spatially heterogeneous uncertainties are prevalent in geophysical modeling applications, such as probabilistic post-closure performance assessment (PA) of deep geologic repositories for nuclear waste. Such uncertainties are often highly influential to model outputs, so it is desirable to identify the most important mechanisms by which they influence model predictions. However, these uncertainties are often unparameterized in the sense that there is no set of parameters that can be specified to yield a particular realization of the uncertainty. Additionally, the uncertainty is not intrinsically endowed with a parameterization that captures a realization’s mechanistic influence on model outputs. Therefore, in this work we present a novel methodology to develop and assess a set of proxy variables that aim to represent this influence. We show how they can be computed, downselected, and incorporated into the construction of statistical surrogate models mapping model inputs to outputs. We present our methodology in the context of a motivating application problem in deep geologic repository PA and discuss the challenges in capturing the effects of these spatial heterogeneities in uncertainty analyses.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

NASA NTRS1991

Creep and stress relaxation modeling of polycrystalline ceramic fibers

A variety of high performance polycrystalline ceramic fibers are currently being considered as reinforcement for high temperature ceramic matrix composites. However, under mechanical loading above 800 C, these fibers display creep-related instabilities which can result in detrimental changes in composite dimensions, strength, and internal stress distributions. As a first step toward understanding these effects, this study examines the validity of mechanistic-based empirical model which describes primary stage tensile creep and stress relaxation of polycrystalline ceramic fibers as independent functions of time, temperature, and applied stress or strain. To verify these functional dependencies, a simple bend test is used to measure stress relaxation for four types of commercial ceramic fibers for which direct tensile creep data are available. These fibers include both nonoxide (SCS-6, Nicalon) and oxide (PRD-166, FP) compositions. The results of the bend stress relaxation (BSR) test not only confirm the stress, time, and temperature dependencies predicted by the model but also allow measurement of model empirical parameters for the four fiber types. In addition, comparison of model predictions and BSR test results with the literature tensile creep data show good agreement, supporting both the predictive capability of the model and the use of the BSR test as a simple method for parameter determination for other fibers.

Dicarlo, James A.↗

DOE OSTI2026

Assessing shellfish water exposure to fecal bacteria pollution in Salish Sea: three-dimensional modeling and implications for monitoring

Fecal bacteria (FB) contamination poses significant risks to shellfish safety and management in coastal and estuarine waters. Despite extensive pollution identification and correction efforts, FB contamination in shellfish-growing areas persists in the Salish Sea, highlighting the need to identify overlooked sources and better understand FB transport from riverine and shoreline inputs to shellfish beds. To address this, a high-resolution three-dimensional hydrodynamic model coupled with FB kinetics was developed and applied to a case study site in Salish Sea—Portage Bay—to simulate freshwater plume circulation, flushing dynamics, and bacterial transport. Daily FB loading from the major freshwater inflow—Nooksack River was generated by both linear interpolation and integrating a machine learning approach (XGBoost), trained on historical hydrological and meteorological data. The model successfully reproduced both the magnitude and seasonal variation of FB concentrations in Portage Bay for the year of 2021, demonstrating that simplified FB kinetics with first-order decay due to mortality was effective in this dynamic coastal environment with short flushing time. Model results identified the Nooksack River as the dominant far-field FB source, while scenario simulations showed that near-field coastal stormwater outfalls elevated local FB levels following rainfall, particularly under low-flow conditions. The XGBoost prediction provided comparable or superior accuracy to linear interpolation, particularly during periods of missing observational data, by capturing short-term variability and event-driven loading more effectively. Integrating data-driven riverine FB inputs with mechanistic coastal numerical modeling provides a robust framework for operational forecasting of shellfish bed exposure risk and supports adaptive monitoring and management of shellfish growing areas in the Salish Sea and similar coastal systems.

Salish Sea↗

DOE OSTI2026

From Cell to System: Accelerated hpc Simulations of BESS Aging under Frequency Regulation and Arbitrage use cases

Lithium-ion battery energy storage systems (BESS) packs have emerged as a leading solution for grid-scale energy storage, enhancing resiliency and balancing load fluctuations. Yet, experimental characterization of large-format LIB packs-particularly to assess performance and degradation over hundreds of cycles - demands substantial hardware investment and multi-year testing campaigns. In this work, we couple a hierarchical, physics-based modeling framework agnostic to electrode chemistries with high-performance computing to accelerate systems level evaluation by upto two orders of magnitude. Building on the open-source liionpack platform, we implement cell, module, and pack-scale electrochemical models enriched with mechanistic aging mechanisms and deploy them on an HPC cluster to simulate 150−200kWh systems over 500 - 1,000 cycles with in days. We subject these virtual B ESS to both constant-current cycling and realistic grid service profiles spanning frequency regulation, ramp-rate support, and energy arbitrage-and quantify the resulting degradation patterns. Our results reveal that localized cell aging can induce substantial nonuniformity at module and pack levels, with service-specific cycling protocols driving distinct aging modes. This rapid, multiscale modeling approach provides a powerful design-space exploration tool for optimizing electrical architecture, control strategies, and operational schedules to prolong pack lifetime and lower total cost of ownership.

Ayalasomayajula, Surya [ORNL] (ORCID:0009000860788↗

NASA NTRS1994

Transport characteristics of a finite-difference dynamics model combined with a spectral transport model of the middle atmosphere

A three-dimensional off-line spectral transport model has been combined with a global, mechanistic, finite-difference dynamics model of the middle atmosphere in order to study transport and photochemistry in the middle atmosphere for specific, observed episodes. In this paper, the basic transport characteristics of the combined models are examined, first using steady, idealized flow fields and second using time-dependent flow fields closely related to observed atmospheric behavior. Transport conducted with the combined models is found to compare favorably with transport conducted on-line in the dynamics model, given appropriate time averaging of the flow fields and suitable choice of artificial diffusion.

Duncan, T.↗

NASA NTRS2013

Large-Scale Extratropical Weather Systems in Mars' Atmosphere

During late autumn through early spring, extratropical regions on Mars exhibit profound mean zonal equator-to-pole thermal contrasts. The imposition of this strong meridional temperature variation supports intense eastward-traveling, synoptic weather systems (i.e., transient baroclinic/barotropic waves) within Mars' extratropical atmosphere. Such disturbances grow, mature and decay within the east-west varying seasonal-mean midlatitude jet stream (i.e., the polar vortex) on the planet. Near the surface, the weather disturbances indicated large-scale spiraling "comma"-shaped dust cloud structures and scimitar-shaped dust fronts, indicative of processes associated with cyclo-/fronto-genesis. The weather systems occur during specific seasons on Mars, and in both hemispheres. The northern hemisphere (NH) disturbances are significantly more intense than their counterparts in the southern hemisphere (SH). Further, the NH weather systems and accompanying frontal waves appear to have significant impacts on the transport of tracer fields (e.g., particularly dust and to some extent water species (vapor/ice) as well). And regarding dust, frontal waves appear to be key agents in the lifting, lofting, organization and transport of this particular atmospheric aerosol. In this paper, a brief background and supporting observations of Mars' extratropical weather systems is presented. This is followed by a short review of the theory and various modeling studies (i.e., ranging from highly simplified, mechanistic and full global circulation modeling investigations) which have been pursued. Finally, a discussion of outstanding issues and questions regarding the character and nature of Mars' extratropical traveling weather systems is offered.

Hollingsworth, Jeffery L.↗

DOE OSTI2024

EF-Hand Battle Royale: Hetero-ion Complexation in Lanmodulin

The lanmodulin (LanM) protein has emerged as an effective means for rare earth element (REE) extraction and separation from complex feedstocks without the use of organic solvents. Whereas the binding of LanM to individual REEs has been well characterized, little is known about the thermodynamics of mixed metal binding complexes (i.e., heterogeneous ion complexes), which limits the ability to accurately predict separation performance for a given metal ion mixture. In this paper, we employ the law of mass action to establish a theory of perfect cooperativity for LanM-REE complexation at the two highest-affinity binding sites. The theory is then used to derive an equation that explains the nonintuitive REE binding behavior of LanM, where separation factors for binary pairs of ions vary widely based on the ratio of ions in the aqueous phase, a phenomenon that is distinct from single-ion-binding chemical chelators. We then experimentally validate this theory and perform the first quantitative characterization of LanM complexation with heterogeneous ion pairs using resin-immobilized LanM. Importantly, the resulting homogeneous and heterogeneous constants enable accurate prediction of the equilibrium state of LanM in the presence of mixtures of up to 10 REEs, confirming that the perfect cooperativity model is an accurate mechanistic description of REE complexation by LanM. We further employ the model to simulate separation performance over a range of homogeneous and heterogeneous binding constants, revealing important insights into how mixed binding differentially impacts REE separations based on the relative positioning of the ion pairs within the lanthanide series. In addition to informing REE separation process optimization, these results provide mathematical and experimental insight into competition dynamics in other ubiquitous and medically relevant, cooperative binding proteins, such as calmodulin.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS2005

The Effect of Fiber Architecture on Matrix Cracking in Sic/sic Cmc's

Applications incorporating silicon carbide fiber reinforced silicon carbide matrix composites (CMC's) will require a wide range of fiber architectures in order to fabricate complex shape. The stress-strain response of a given SiC/SiC system for different architectures and orientations will be required in order to design and effectively life-model future components. The mechanism for non-linear stress-strain behavior in CMC's is the formation and propagation of bridged-matrix cracks throughout the composite. A considerable amount of understanding has been achieved for the stress-dependent matrix cracking behavior of SiC fiber reinforced SiC matrix systems containing melt-infiltrated Si. This presentation will outline the effect of 2D and 3D architectures and orientation on stress-dependent matrix-cracking and how this information can be used to model material behavior and serve as the starting point foe mechanistic-based life-models.

Morscher, Gregory N.↗

DOE OSTI2025

When can we detect lianas from space? Toward a mechanistic understanding of liana‐infested forest optics

Abstract Lianas, woody vines acting as structural parasites of trees, have profound effects on the composition and structure of tropical forests, impacting tree growth, mortality, and forest succession. Remote sensing could offer a powerful tool for quantifying the scale of liana infestation, provided the availability of robust detection methods. We analyze the consistency and global geographic specificity of spectral signals—reflectance across wavelengths—from liana‐infested tree crowns and forest stands, examining the underlying mechanisms of these signals. We compiled a uniquely comprehensive database, including leaf reflectance spectra from 5424 leaves, fine‐scale airborne reflectance data from 999 liana‐infested canopies, and coarse‐scale satellite reflectance data covering 775 ha of liana‐infested forest stands. To unravel the mechanisms of the liana spectral signal, we applied mechanistic radiative transfer models across scales, establishing a synthesis of the relative importance of different mechanisms, which we corroborate with field data on liana leaf chemistry and canopy structure. We find a consistent liana spectral signal at canopy and stand scales across globally distributed sites. This signature mainly arises at the canopy level due to direct effects of more horizontal leaf angles, resulting in a larger projected leaf area, and indirect effects from increased light scattering in the near and short‐wave infrared regions, linked to lianas' less costly leaf construction compared with trees on average. The existence of a consistent global spectral signal for lianas suggests that large‐scale quantification of liana infestation is feasible. However, because the traits responsible for the liana canopy‐reflectance signal are not exclusive to lianas, accurate large‐scale detection requires rigorously validated remote sensing methods. Our models highlight challenges in automated detection, such as potential misidentification due to leaf phenology, tree life history, topography, and climate, especially where the scale of liana infestation is less than a single remote sensing pixel. The observed cross‐site patterns also prompt ecological questions about lianas' adaptive similarities in optical traits across environments, indicating possible convergent evolution due to shared constraints on leaf biochemical and structural traits.

Environmental Sciences & Ecology↗

DOE OSTI2025

Isolation and characterization of 24 phages infecting the plant growth-promoting rhizobacterium Klebsiella sp. M5al

Bacteriophages largely impact bacterial communities via lysis, gene transfer, and metabolic reprogramming and thus are increasingly thought to alter nutrient and energy cycling across many of Earth’s ecosystems. However, there are few model systems to mechanistically and quantitatively study phage-bacteria interactions, especially in soil systems. Here, we isolated, sequenced, and genomically characterized 24 novel phages infectingKlebsiellasp. M5al, a plant growth-promoting, nonencapsulated rhizosphere-associated bacterium, and compared many of their features against all 565 sequenced, dsDNAKlebsiellaphage genomes. Taxonomic analyses revealed that theseKlebsiellaphages belong to three known phage families (Autographiviridae,Drexlerviridae, andStraboviridae) and two newly proposed phage families (CandidatusMavericviridaeand Ca.Rivulusviridae). At the phage family level, we found that core genes were often phage-centric proteins, such as structural proteins for the phage head and tail and DNA packaging proteins. In contrast, genes involved in transcription, translation, or hypothetical proteins were commonly not shared or flexible genes. Ecologically, we assessed the phages’ ubiquity in recent large-scale metagenomic datasets, which revealed they were not widespread, as well as a possible direct role in reprogramming specific metabolisms during infection by screening their genomes for phage-encoded auxiliary metabolic genes (AMGs). Even though AMGs are common in the environmental literature, only one of our phage families,Straboviridae, contained AMGs, and the types of AMGs were correlated at the genus level. Host range phenotyping revealed the phages had a wide range of infectivity, infecting between 1–14 of our 22 bacterial strain panel that included pathogenicKlebsiellaandRaoultellastrains. This indicates that not all capsule-independent Klebsiella phages have broad host ranges. Together, these isolates, with corresponding genome, AMG, and host range analyses, help build theKlebsiellamodel system for studying phage-host interactions of rhizosphere-associated bacteria.

Science & Technology - Other Topics↗

DOE OSTI2025

The effect of heat treatment on the defect evolution in LPBF 316H stainless steel

This work investigates the effect of processing and heat treatment on defect evolution and irradiation response of laser powder bed fusion (LPBF) 316H stainless steel, with comparisons to LPBF 316L and wrought 316L/316H. Using in-situ and ex-situ ion irradiations across a wide parameter space—temperature (300–675 °C), dose (0.2–25 dpa), dose rate (10 -3 –10 -5 dpa/s), and helium co-implantation (20–2500 appm)—we correlated void swelling, dislocation loop evolution, and segregation behavior with pre-irradiation microstructures (as-built, stress-relieved, solution-annealed, and cold-worked). Results show that swelling is strongly controlled by dislocation density: intermediate densities maximize swelling, while solution annealing or cold working reduce susceptibility to levels comparable to wrought alloys. Low dose rates and helium both promote cavity nucleation and lower the incubation barrier, with helium suppressing the role of dislocation density and driving swelling behavior toward wrought-like response. Loop evolution in SA LPBF 316H resembles wrought 316L but shows localized denuded zones near low-angle grain boundaries. STEM-EDS mapping further revealed Ni segregation at voids and sparse Al-rich oxides, without evidence of Ni–Si precipitates. Collectively, these findings identify dislocation density, helium content, and dose rate as the factors governing swelling in LPBF 316H and provide mechanistic datasets for model validation, supporting LAIN and the qualification of AM austenitic steels for nuclear service.

316 stainless steel↗

DOE OSTI2025

Long-term measurements of ice nucleating particles at Atmospheric Radiation Measurement (ARM) sites worldwide

Ice nucleating particles (INPs) play a critical role in cloud microphysics and precipitation formation, yet long-term, spatially extensive observational datasets remain limited. Here, we present one of the most comprehensive publicly available datasets of immersion-mode INP concentrations using a single analytical method, generated through the U.S. Department of Energy's (DOE) Atmospheric Radiation Measurement (ARM) user facility. INP filter samples have been collected across a broad range of environments – including agricultural plains, Arctic coastlines, high-elevation mountain sites, marine regions, and urban areas – via fixed observatories, mobile facility deployments, and vertically-resolved tethered balloon system operations. We describe the standardized processing and quality assurance pipeline, from filter collection and processing using the Ice Nucleation Spectrometer to final data products archived on the ARM Data Discovery portal. The dataset includes both total INP concentrations and selectively treated samples, allowing for classification of biological, organic, and inorganic INP types. It features a continuous 5-year record of INP measurements from a central U.S. site, with data collection still ongoing. Seasonal and site-specific differences in INP concentrations are illustrated through intercomparisons at −10 and −20 °C, revealing distinct regional sources and atmospheric drivers. We also outline mechanisms for researchers to access existing data, request additional sample analyses, and propose future field campaigns involving ARM INP measurements. This dataset supports a wide range of scientific applications, from observational and mechanistic studies to model development, and provides critical constraints on aerosol-cloud interactions across diverse atmospheric regimes (Creamean et al., 2024, 2020b; https://doi.org/10.5439/1770816).

Creamean, Jessie M. [Colorado State Univ., Fort Co↗

NASA NTRS2016

A Study of Heat Transfer and Flow Characteristics of Rising Taylor Bubbles

Practical application of flow boiling to ground- and space-based thermal management systems hinges on the ability to predict the systems heat removal capabilities under expected operating conditions. Research in this field has shown that the heat transfer coefficient within two-phase heat exchangers can be largely dependent on the experienced flow regime. This finding has inspired an effort to develop mechanistic heat transfer models for each flow pattern which are likely to outperform traditional empirical correlations. As a contribution to the effort, this work aimed to identify the heat transfer mechanisms for the slug flow regime through analysis of individual Taylor bubbles.An experimental apparatus was developed to inject single vapor Taylor bubbles into co-currently flowing liquid HFE 7100. The heat transfer was measured as the bubble rose through a 6 mm inner diameter heated tube using an infrared thermography technique. High-speed flow visualization was obtained and the bubble film thickness measured in an adiabatic section. Experiments were conducted at various liquid mass fluxes (43-200 kgm2s) and gravity levels (0.01g-1.8g) to characterize the effect of bubble drift velocityon the heat transfer mechanisms. Variable gravity testing was conducted during a NASA parabolic flight campaign.Results from the experiments showed that the drift velocity strongly affects the hydrodynamics and heat transfer of single elongated bubbles. At low gravity levels, bubbles exhibited shapes characteristic of capillary flows and the heat transfer enhancement due to the bubble was dominated by conduction through the thin film. At moderate to high gravity, traditional Taylor bubbles provided small values of enhancement within the film, but large peaks in the wake heat transfer occurred due to turbulent vortices induced by the film plunging into the trailing liquid slug. Characteristics of the wake heat transfer profiles were analyzed and related to the predicted velocity field. Results were compared and shown to agree with numerical simulations of colleagues from EPFL, Switzerland.In addition, a preliminary study was completed on the effect of a Taylor bubble passing through nucleate flow boiling, showing that the thinning thermal boundary layer within the film suppressed nucleation, thereby decreasing the heat transfer coefficient.

capillary flow↗

NASA NTRSDate not supplied

State of Wildfires

Fire is an essential component of ecosystems and acts as key driver of biogeochemical cycling with impacts on vegetation structure and composition, soil conditions, and climate feedbacks. Fire behavior and effects vary based on the types of fuel, fuel dryness, and frequency of ignition. Due to changing climate and land use patterns, fire danger is increasing in many regions globally, and fires are having increasingly devastating impacts on human health, infrastructure, and ecosystem services. Recurrent fires help to determine the distribution of trees and grasses, and overall fuel load, which inform the behavior of future fires. Process-based models can be used to capture multi-scale impacts at the forest stand-level up to the landscape level, and across minutes to centuries, but must capture variation in fire behavior and intensity as a function of the fuel and climate, from high intensity forest crown fires within boreal regions to low intensity rapid grass fires of the tropics. Fire model development demonstrates our ability to capture large scale fire influenced biogeography and vegetation distribution at the earth system scale through vegetation traits and fire feedbacks. At the individual stand scale the importance of interactions and feedbacks between above and below ground process is essential to capturing the vegetation dynamics across boreal forest systems. Improving the mechanics of including plant physiology and specifically live fuel moisture content is the next step to advancing the capability of process based models to inform fire research. Advances in the testing and creation of a mechanistic live fuel moisture model demonstrate the foundation for future live fuel dynamics research that can be informed by field and remote sensing information. Improved remote sensing, technological and modeling capabilities support a more comprehensive and cohesive fire response that will be better equipped to overcome current barriers and anticipate the new reality of fires in a warming world.

wildfires↗