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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 667 records · Page 37
All sourcesNASA NTRSDOE OSTI
NASA NTRS1999

The Isothermal Dendritic Growth Experiment (IDGE)

The Isothermal Dendritic Growth Experiment (IDGE) constituted a series of three NASA-supported microgravity experiments, all of which flew aboard the space shuttle, Columbia. This experimental space flight series was designed and operated to grow and record dendrite solidification in the absence of gravity-induced convective heat transfer, and thereby produce a wealth of benchmark-quality data for testing solidification scaling laws. The data and analysis performed on the dendritic growth speed and tip size in Succinontrie (SCN) demonstrates that although the theory yields predictions that are reasonably in agreement with experiment, there are significant discrepancies. However, some of these discrepancies can be explained by accurately describing the diffusion of heat. The key finding involves recognition that the actual three-dimensional shape of dendrites includes time-dependent side-branching and a tip region that is not a paraboloid of revolution. Thus, the role of heat transfer in dendritic growth is validated, with the caveat that a more realistic model of the dendrite then a paraboloid is needed to account for heat flow in an experimentally observed dendrite. We are currently conducting additional analysis to further confirm and demonstrate these conclusions. The data and analyses for the growth selection physics remain much less definitive. From the first flight, the data indicated that the selection parameter, sigma*, is not exactly a constant, but exhibits a slight dependence on the supercooling. Additional data from the second flight are being examined to investigate the selection of a unique dendrite speed, tip size and shape. The IDGE flight series is now complete. We are currently completing analyses and moving towards final data archiving. It is gratifying to see that the IDGE published results and archived data sets are being used actively by other scientists and engineers. In addition, we are also pleased to report that the techniques and IDGE hardware system that the authors developed with NASA, are being currently employed on both designated flight experiments, like EDSE, and on flight definition experiments, like TDSE.

Glicksman, Martin E.↗
NASA NTRS2011

What Dominates the Coronal Emission Spectrum During the Cycle of Impulsive Heating and Cooling?

The smoking gun of small-scale, impulsive events heating the solar corona is expected to be the presence of a hot ( > 5 MK) plasma component. Evidence for this has been scarce, but has gradually begun to accumulate due to recent studies designed to constrain the high temperature part of the emission measure distribution. However, the detected hot component is often weaker than models predict and this is due in part to the common modeling assumption that the ionization balance remains in equilibrium. The launch of the latest generation of space-based observing instrumentation aboard Hinode and the Solar Dynamics Observatory (SDO) has brought the matter of the ionization state of the plasma firmly to the forefront. It is timely to consider exactly what emission current instruments would detect when observing a corona heated impulsively on small-scales by nanoflares. Only after we understand the full effects of nonequilibrium ionization can we draw meaningful conclusions about the plasma that is (or is not) present. We have therefore performed a series of hydrodynamic simulations for a variety of different nanoflare properties and initial conditions. Our study has led to several key conclusions. 1. Deviations from equilibrium are greatest for short-duration nanoflares at low initial coronal densities. 2. Hot emission lines are the most affected and are suppressed sometimes to the point of being invisible. 3. The emission detected in all of the SDO-AIA channels is generally dominated by warm, over-dense, cooling plasma. 4. It is difficult not to create coronal loops that emit strongly at 1.5 MK and in the range 2 to 5 MK, which are the most commonly observed kind, for a broad range of nanoflare scenarios. 5. The Fe XV (284.16 ) emission in most of our models is about 10 times brighter than the Ca XVII (192.82 ) emission, consistent with observations. Our overarching conclusion is that small-scale, impulsive heating inducing a nonequilibrium ionization state leads to predictions for observable quantities that are entirely consistent with what is actually observed.

Bradshaw, Stephen J.↗
NASA NTRS2018

GEOS S2S-2_1: The GMAO High Resolution Seasonal Prediction System

A new version of the coupled modeling and analysis system used to produce near real time subseasonal to seasonal forecasts was recently released by the NASA/Goddard Global Modeling and Assimilation Office. The new version runs at higher atmospheric resolution than the previous, (approximately 1/2 degree globally), contains a substantially improved model description of the cryosphere, and includes additional interactive earth system model components (aerosol model). In addition, the Ocean data assimilation system has been replaced with a Local Ensemble Transform Kalman Filter, and now includes the assimilation of along-track sea surface height. Here will describe the new system, along with the plans for the future (GEOS S2S-3_0) which will include a higher resolution ocean model and more interactive earth system model components (interactive vegetation, biomass burning from fires). We will also present results from a series of retrospective seasonal forecasts. Results show significant improvements in surface temperatures over much of the northern hemisphere and a much improved prediction of sea ice extent in both hemispheres. Analysis of the ensemble spread shows improvements relative to the previous system, including generally better reliability. The precipitation forecast skill is comparable to previous S2S systems, and the only tradeoff is an increased "double ITCZ", which is expected as we go to higher atmospheric resolution.

Molod, Andrea↗
NASA NTRS2002

A Stochastic Model of Space-Time Variability of Tropical Rainfall: I. Statistics of Spatial Averages

Global maps of rainfall are of great importance in connection with modeling of the earth s climate. Comparison between the maps of rainfall predicted by computer-generated climate models with observation provides a sensitive test for these models. To make such a comparison, one typically needs the total precipitation amount over a large area, which could be hundreds of kilometers in size over extended periods of time of order days or months. This presents a difficult problem since rain varies greatly from place to place as well as in time. Remote sensing methods using ground radar or satellites detect rain over a large area by essentially taking a series of snapshots at infrequent intervals and indirectly deriving the average rain intensity within a collection of pixels , usually several kilometers in size. They measure area average of rain at a particular instant. Rain gauges, on the other hand, record rain accumulation continuously in time but only over a very small area tens of centimeters across, say, the size of a dinner plate. They measure only a time average at a single location. In making use of either method one needs to fill in the gaps in the observation - either the gaps in the area covered or the gaps in time of observation. This involves using statistical models to obtain information about the rain that is missed from what is actually detected. This paper investigates such a statistical model and validates it with rain data collected over the tropical Western Pacific from ship borne radars during TOGA COARE (Tropical Oceans Global Atmosphere Coupled Ocean-Atmosphere Response Experiment). The model incorporates a number of commonly observed features of rain. While rain varies rapidly with location and time, the variability diminishes when averaged over larger areas or longer periods of time. Moreover, rain is patchy in nature - at any instant on the average only a certain fraction of the observed pixels contain rain. The fraction of area covered by rain decreases, as the size of a pixel becomes smaller. This means that within what looks like a patch of rainy area in a coarse resolution view with larger pixel size, one finds clusters of rainy and dry patches when viewed on a finer scale. The model makes definite predictions about how these and other related statistics depend on the pixel size. These predictions were found to agree well with data. In a subsequent second part of the work we plan to test the model with rain gauge data collected during the TRMM (Tropical Rainfall Measuring Mission) ground validation campaign.

Kundu, Prasun K.↗
NASA NTRSDate not supplied

Initial Testing the Exploration Extravehicular Mobility Unit (xEMU) in Lunar Environment Simulation at the Neutral Buoyancy Lab (NBL) in 2022

Understanding how to effectively train for Extravehicular Activities (EVAs) for Artemis missions is critical. Tasked by the new Extravehicular Activity and Human Surface Mobility Program(EHP), a team of stakeholders from engineering and flight operations worked together to test the Exploration Extravehicular Mobility (xEMU) in the Neutral Buoyancy Lab(NBL) simulating the lunar environment. The NBL is a pool in which astronauts are typically trained to complete simulated International Space Station (ISS) EVA tasks in a neutral weigh-out. The overall focus for this test series was evaluating how well the NBL could be used as an effective simulated environment for Artemis lunar EVAs. New NBL support hardware was manufactured to support this test series and update the interfaces to be more representative of xEMU hardware such as a new NBL Portable Life Support System(PLSS)mock-up and umbilical, lights and cameras, and display and control unit (DCU).To simulate the 1/6th-gravity (1/6-g) environment, extra weights were added around the suit to create an accurate center of gravity representation. The Partial Gravity Weigh-out Stand (PGWS) predicted where and how much weight would be required for the 1/6th-G simulation and predicted the center of gravity placement. After the weigh-out attempt was completed, the suited participant would complete a set of directed tasks such as kneeling, object pick-up, and walking to evaluate the weigh-out. To create the lunar environment, sand, boulders, and ramps were added to the pool floor. If time allowed after weigh-out was determined acceptable, the flight operations team would direct the suited participants to complete simulated Artemis EVA tasks using flight-like tools and tool cart. The team also evaluated turning out the overhead lights in the NBL for a portion of some of the test runs and using a solar simulator to create amore realistic lunar south pole lighting environment. The test series completed one unmanned test and nine manned tests. With four of the tests, dual xEMU suited operations were completed with subjects in both the small and large xEMU sizes. Overall, the NBL was able to create an acceptable lunar landscape and ability to have two subjects work side by side in pressurized xEMUs which currently cannot be achieved in other test environments. Achieving a stable 1/6th-G lunar weigh-out and clear, consistent dual suit communications was a challenge for this series. Future work is planned to continue to improve this simulation environment.

spacesuit↗
NASA NTRSDate not supplied

Initial Testing of the Exploration Extravehicular Mobility Unit (xEMU) in Lunar Environment Simulation at the Neutral Buoyancy Lab (NBL) in 2022

Understanding how to effectively train for Extravehicular Activities (EVAs) for Artemis missions is critical. Tasked by the new Extravehicular Activity and Human Surface Mobility Program(EHP), a team of stakeholders from engineering and flight operations worked together to test the Exploration Extravehicular Mobility (xEMU) in the Neutral Buoyancy Lab(NBL) simulating the lunar environment. The NBL is a pool in which astronauts are typically trained to complete simulated International Space Station (ISS) EVA tasks in a neutral weigh-out. The overall focus for this test series was evaluating how well the NBL could be used as an effective simulated environment for Artemis lunar EVAs. New NBL support hardware was manufactured to support this test series and update the interfaces to be more representative of xEMU hardware such as a new NBL Portable Life Support System(PLSS)mock-up and umbilical, lights and cameras, and display and control unit (DCU).To simulate the 1/6th-gravity (1/6-g) environment, extra weights were added around the suit to create an accurate center of gravity representation. The Partial Gravity Weigh-out Stand (PGWS) predicted where and how much weight would be required for the 1/6th-G simulation and predicted the center of gravity placement. After the weigh-out attempt was completed, the suited participant would complete a set of directed tasks such as kneeling, object pick-up, and walking to evaluate the weigh-out. To create the lunar environment, sand, boulders, and ramps were added to the pool floor. If time allowed after weigh-out was determined acceptable, the flight operations team would direct the suited participants to complete simulated Artemis EVA tasks using flight-like tools and tool cart. The team also evaluated turning out the overhead lights in the NBL for a portion of some of the test runs and using a solar simulator to create amore realistic lunar south pole lighting environment. The test series completed one unmanned test and nine manned tests. With four of the tests, dual xEMU suited operations were completed with subjects in both the small and large xEMU sizes. Overall, the NBL was able to create an acceptable lunar landscape and ability to have two subjects work side by side in pressurized xEMUs which currently cannot be achieved in other test environments. Achieving a stable 1/6th-G lunar weigh-out and clear, consistent dual suit communications was a challenge for this series. Future work is planned to continue to improve this simulation environment.

spacesuit↗
DOE OSTI2026

Bridge Connectivity Dictates Spin Interactions and Triplet Pair Dynamics in Intramolecular Singlet Fission

Electron spin plays a critical role in determining the structure, dynamics, and reactivities of molecular excited states, including multiexciton processes such as singlet fission. These systems exhibit triplet pair states whose excited state dynamics can be widely tuned through molecular engineering. For example, the electronic coupling between covalently linked chromophores can be readily modulated using chemical bridges to control proximity, quantum interference, or resonance effects. However, less is known about how spin coupling interactions are impacted by chromophore architecture, and how this influences triplet pair recombination dynamics. Here, in this study, we investigate the role of bridge connectivity and chromophore identity in modulating interchromophore exchange and dipolar coupling interactions for a series of pentacene and tetracene dimers bridged by alternant hydrocarbons (phenylene, naphthalene, anthracene). Using both time-resolved electron paramagnetic resonance and transient absorption spectroscopy, we find that the boundedness and recombination pathways of the triplet pair spins are highly sensitive to molecular architecture and chromophore-specific magnetic dipolar interactions. Notably, nominally ferromagnetic and antiferromagnetic eigenstates result in distinct spin state orderings, consistent with predictions from quantum interference-based graphical models. These findings establish new design principles for tuning spin dynamics in iSF materials, with implications for photonic and quantum information applications.

He, Guiying [City Univ. of New York (CUNY), NY (Un↗
DOE OSTI2026

Stoichiometrically-informed symbolic regression for extracting chemical reaction mechanisms from data

A data-driven computational method is introduced to extract chemical reaction mechanisms from time series chemical concentration data. It is realized through the use of dynamic symbolic regression in which a sparse analytical form for a dynamical system is discoverable from the underlying data. We specifically develop the stoichiometrically-informed symbolic regression (SISR) method to address a standing challenge in complex chemical reaction networks: given a time-series dataset of concentrations of several components, what is the mechanism and the associated rate constants? SISR finds the optimal mechanism, kinetic equations and rate constants by combining differential optimization with a genetic optimization approach that searches a symbolic space of possible reaction mechanisms. Use of SISR in several paradigmatic examples spanning linear and nonlinear reaction schemes results in excellent agreement between true and predicted mechanisms, including when the method is applied to noisy data. The advantages of a stoichiometrically-informed approach such as SISR to address reaction discovery is illustrated through comparison with the use of generic state-of-the-art data-driven approaches.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Entropy-Assisted Quality Pattern Identification in Finance

Short-term patterns in financial time series form the cornerstone of many algorithmic trading strategies, yet extracting these patterns reliably from noisy market data remains a formidable challenge. In this paper, we propose an entropy-assisted framework for identifying high-quality, non-overlapping patterns that exhibit consistent behavior over time. We ground our approach in the premise that historical patterns, when accurately clustered and pruned, can yield substantial predictive power for short-term price movements. To achieve this, we incorporate an entropy-based measure as a proxy for information gain: patterns that lead to high one-sided movements in historical data yet retain low local entropy are more “informative” in signaling future market direction. Compared to conventional clustering techniques such as K-means and Gaussian Mixture Models (GMMs), which often yield biased or unbalanced groupings, our approach emphasizes balance over a forced visual boundary, ensuring that quality patterns are not lost due to over-segmentation. By emphasizing both predictive purity (low local entropy) and historical profitability, our method achieves a balanced representation of Buy and Sell patterns, making it better suited for short-term algorithmic trading strategies. This paper offers an in-depth illustration of our entropy-assisted framework through two case studies on Gold vs. USD and GBPUSD. While these examples demonstrate the method’s potential for extracting high-quality patterns, they do not constitute an exhaustive survey of all possible asset classes.

Physics↗
NASA NTRS1981

Spatial and Temporal scales of time-averaged 700 MB height anomalies

The monthly and seasonal forecasting technique is based to a large extent on the extrapolation of trends in the positions of the centers of time averaged geopotential height anomalies. The complete forecasted height pattern is subsequently drawn around the forecasted anomaly centers. The efficacy of this technique was tested and time series of observed monthly mean and 5 day mean 700 mb geopotential heights were examined. Autocorrelation statistics are generated to document the tendency for persistence of anomalies. These statistics are compared to a red noise hypothesis to check for evidence of possible preferred time scales of persistence. Space-time spectral analyses at middle latitudes are checked for evidence of periodicities which could be associated with predictable month-to-month trends. A local measure of the average spatial scale of anomalies is devised for guidance in the completion of the anomaly pattern around the forecasted centers.

Gutzler, D.↗
NASA NTRS1991

Micro-mechanical analysis of damage growth and fracture in discontinuous fiber reinforced metal matrix composites

An experimental verification is presented for a new two parameter fracture model based on the equivalent remote biaxial stresses (ERBS). A detailed comparison is made between the new theory and the constant K(sub IC) approach of linear elastic fracture mechanics (LEFM). Fracture is predicted through a failure curve representing the change in a variable fracture toughness K(sub IC) with the ERBS ratio B(sub E). The nonsingular term (T) in the series expansion of the near crack-tip transverse stress is included in the model. Experimental results for polymethyl methacrylate (PPMA) show that the theory can account for the effects of geometry on fracture toughness as well as indicate the initiation of crack branching. It is shown that the new criterion predicts failure for PMMA with a 95 percent confidence zone which is nearly three times smaller than that of the LEFM K(sub IC) approach.

Goree, James G.↗
NASA NTRS1993

Solar flux forecasting using mutual information with an optimal delay

Solar flux F(sub 10.7) directly affects the atmospheric density, thereby changing the lifetime and prediction of satellite orbits. For this reason, accurate forecasting of F(sub 10.7) is crucial for orbit determination of spacecraft. Our attempts to model and forecast F(sub 10.7) uncovered highly entangled dynamics. We concluded that the general lack of predictability in solar activity arises from its nonlinear nature. Nonlinear dynamics allow us to predict F(sub 10.7) more accurately than is possible using stochastic methods for time scales shorter than a characteristic horizon, and with about the same accuracy as using stochastic techniques when the forecasted data exceed this horizon. The forecast horizon is a function of two dynamical invariants: the attractor dimension and the Lyapunov exponent. In recent years, estimation of the attractor dimension reconstructed from a time series has become an important tool in data analysis. In calculating the invariants of the system, the first necessary step is the reconstruction of the attractor for the system from the time-delayed values of the time series. The choice of the time delay is critical for this reconstruction. For an infinite amount of noise-free data, the time delay can, in principle, be chosen almost arbitrarily. However, the quality of the phase portraits produced using the time-delay technique is determined by the value chosen for the delay time. Fraser and Swinney have shown that a good choice for this time delay is the one suggested by Shaw, which uses the first local minimum of the mutual information rather than the autocorrelation function to determine the time delay. This paper presents a refinement of this criterion and applies the refined technique to solar flux data to produce a forecast of the solar activity.

Ashrafi, S.↗
NASA NTRS2006

Aircraft Cabin Turbulence Warning Experiment

New turbulence prediction technology offers the potential for advance warning of impending turbulence encounters, thereby allowing necessary cabin preparation time prior to the encounter. The amount of time required for passengers and flight attendants to be securely seated (that is, seated with seat belts fastened) currently is not known. To determine secured seating-based warning times, a consortium of aircraft safety organizations have conducted an experiment involving a series of timed secured seating trials. This demonstrative experiment, conducted on October 1, 2, and 3, 2002, used a full-scale B-747 wide-body aircraft simulator, human passenger subjects, and supporting staff from six airlines. Active line-qualified flight attendants from three airlines participated in the trials. Definitive results have been obtained to provide secured seating-based warning times for the developers of turbulence warning technology

Bogue, Rodney K.↗
NASA NTRS2012

A Generalized Timeline Representation, Services, and Interface for Automating Space Mission Operations

Numerous automated and semi-automated planning & scheduling systems have been developed for space applications. Most of these systems are model-based in that they encode domain knowledge necessary to predict spacecraft state and resources based on initial conditions and a proposed activity plan. The spacecraft state and resources as often modeled as a series of timelines, with a timeline or set of timelines to represent a state or resource key in the operations of the spacecraft. In this paper, we first describe a basic timeline representation that can represent a set of state, resource, timing, and transition constraints. We describe a number of planning and scheduling systems designed for space applications (and in many cases deployed for use of ongoing missions) and describe how they do and do not map onto this timeline model.

Chien, Steve A.↗
NASA NTRS2024

Southern California Water Resources: Using NASA Earth Observations to Monitor Seagrass Extent and Water Quality Parameters in Southern California

Eelgrass (Zostera marina) is a species of submerged aquatic vegetation found in shallow bays and estuaries with soft seafloors. Eelgrass is recognized for providing ecosystem benefits, such as carbon sequestration, sediment stabilization, water clarification, and fish and wildlife habitats. However, eelgrass is impacted by both marine and terrestrial threats associated with climate change. In this project, we worked with the Southern California Coastal Water Research Project, the National Oceanic and Atmospheric Administration’s National Marine Fisheries Service, and the State of California San Diego Regional Water Quality Control Board to investigate water quality parameters (i.e., chlorophyll-a concentration, sea surface temperature, and turbidity) associated with eelgrass in Newport Bay and Mission Bay, California. The team used Landsat 8 Operational Land Imager and Thermal Infrared Sensor, Landsat 9 Operational Land Imager-2 and Thermal Infrared Sensor-2, Sentinel-2 MultiSpectral Instrument, and ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station land surface temperature and cloud mask to create a time series of these water quality parameters from 2019–2023. We found that the parameters followed cyclical, seasonal patterns with turbidity and sea surface temperature peaking in the summer. We did not find that the parameters had changed significantly over longer time periods. These results will be used in a model developed by the Southern California Coastal Water Research Project to assess eelgrass ecosystem health and predict ecosystem occupancy in the future.

Katya Beener↗
DOE OSTI2020

Mesh Failure Prediction Using Deep Learning Techniques

The goal of this joint effort between SRI and LLNL has been to investigate the use of state-of-the-art deep learning architectures to effectively explore the correlations between a set of mesh zone attributes and manifestations of failure in a given mesh simulation and draw useful conclusions towards a practical failure detection system. Each zone attribute is a scalar feature that is recorded separately for each zone during simulation, resulting in a multivariate time series signal for each zone. Currently, these features are used to manually decide where to apply manual relaxations so that simulations run without any failures. Our long-term vision is to build a machine learning system that is capable of reliably detecting upcoming failures and is able to apply finer-grained targeted relaxations automatically to relevant zones to avoid an expected failure.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Frontiers in divalent $f$-block chemistry

Divalent f-block chemistry has undergone rapid expansion in recent years, driven by advances in the stabilization of low-valent lanthanide and actinide complexes. Although f-elements were historically accessed in the +3 or higher oxidation states, the isolation of +2 species has revealed unusual spectroscopic signatures, distinct bonding motifs, and multiple accessible electronic configurations that influence their chemical and physical properties. These developments have generated opportunities in areas including quantum information science, molecular magnetism, catalysis, and luminescence. Computational chemistry has played a pivotal role in interpreting the electronic structure and reactivity of these systems. However, accurately modeling divalent f-block complexes remains challenging because of strong electronic correlation, multiconfigurational character, and the presence of close-in-energy competing electronic states. As experimental capabilities and theoretical methodologies continue to advance, a comprehensive assessment of divalent chemistry is both timely and needed. In this Review, we integrate experimental and theoretical perspectives to provide a systematic analysis of divalent lanthanide and actinide complexes across the f-block series. We critically assess the role of ligands in determining competing ground-state configurations (f n d 1 vs. f n+1 ) resulting in their distinct spectroscopic, magnetic, and bonding properties. Finally, we discuss emerging strategies for predictive modeling and rational design of low-valent f-block molecular systems, with potential applications ranging from dinitrogen reduction to quantum technologies.

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

PSInet: a new global water potential network

Abstract Given the pressing challenges posed by climate change, it is crucial to develop a deeper understanding of the impacts of escalating drought and heat stress on terrestrial ecosystems and the vital services they offer. Soil and plant water potential play a pivotal role in governing the dynamics of water within ecosystems and exert direct control over plant function and mortality risk during periods of ecological stress. However, existing observations of water potential suffer from significant limitations, including their sporadic and discontinuous nature, inconsistent representation of relevant spatio-temporal scales and numerous methodological challenges. These limitations hinder the comprehensive and synthetic research needed to enhance our conceptual understanding and predictive models of plant function and survival under limited moisture availability. In this article, we present PSInet (PSI—for the Greek letter Ψ used to denote water potential), a novel collaborative network of researchers and data, designed to bridge the current critical information gap in water potential data. The primary objectives of PSInet are as follows. (i) Establishing the first openly accessible global database for time series of plant and soil water potential measurements, while providing important linkages with other relevant observation networks. (ii) Fostering an inclusive and diverse collaborative environment for all scientists studying water potential in various stages of their careers. (iii) Standardizing methodologies, processing and interpretation of water potential data through the engagement of a global community of scientists, facilitated by the dissemination of standardized protocols, best practices and early career training opportunities. (iv) Facilitating the use of the PSInet database for synthesizing knowledge and addressing prominent gaps in our understanding of plants’ physiological responses to various environmental stressors. The PSInet initiative is integral to meeting the fundamental research challenge of discerning which plant species will thrive and which will be vulnerable in a world undergoing rapid warming and increasing aridification.

Forestry↗