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At least 937 records · Page 52

Insights into Slip-Rate Time Functions, Rupture Parameter Correlations, and Ground Motions from Validated Multicycle Earthquake Ruptures

Earthquake strong-motion predictions using kinematic source modeling require knowledge of the slip-rate functions (SRFs) along the rupture and their distinct characteristics in asperities, background (off-asperity) areas and near the surface. Here, in this study we analyzed SRFs from well-validated, self-consistent, and fully dynamic rupture models from earthquake cycles obeying a rate-and-state friction law, from our companion study (Galvez et al., 2021). The shapes of SRFs in asperities are well described by the regularized Yoffe function (RYF), which has only two parameters: rise time T r and smoothing time T s , which control the generation of long- and short-period ground motions, respectively. In background areas, we demonstrate that, in addition to the primary rupture, multiple secondary ruptures may also nucleate from rupture heterogeneities related to asperities, resulting in SRFs with multiple peaks. Because it is impossible to fit a multiple-peak SRF by the single-peak RYF, we describe SRFs in background areas in an effective way by fitting their amplitude spectra with the RYF spectra. Such spectrally effective RYFs capture salient aspects of seismic-wave generation and can be used in rupture generators for strong motion prediction. We found that small T s values correlate with small characteristic weakening distances, large peak slip rates (PSRs), and large rupture velocities. T r values are larger in background areas and smaller in asperities. Within the shallow aseismic zone, T s values approximately quadruple whereas T r values approximately double. Because of this dominant T s increase, PSR values decrease in the near-surface zone. These features indicate that the generation of strong motions by the near-surface portions of the rupture is negligible in the studied scenarios.

Geosciences↗

Magnetic Nanoparticle Extraction of Lithium from Produced Waters - CRADA 483 (Final Report)

The demand for lithium in the energy production industry is expected to increase sharply, development of simple and cost-effective techniques for lithium production and recovery from various lithium sources is essential. In this project, core/shell magnetic nanoparticles were successfully designed to selectively extract lithium from aqueous lithium sources as an extension of Pacific Northwest National Laboratory’s magnetic nanofluid extraction technology. The core/shell magnetic nanoparticles are composed of manganese oxide-based lithium ion sieve shells, which allow selective lithium uptake from brines with multiple coexisting ions, over iron oxide cores, which can respond to external magnetic fields for effective recovery and reuse of adsorbents from a liquid. The synthesized lithium ion-sieves and core/shell magnetic nanoparticles were characterized using several techniques to reveal their crystallinity and morphology. The lithium uptake properties of the lithium ion-sieves and core/shell magnetic nanoparticles were evaluated in terms of lithium adsorption capacity, removal percentage, selectivity, and cycling performance in simulated and natural brines. Magnetic properties of the core/shell magnetic nanoparticles were tested by measuring magnetic saturation, and magnetic response of colloidal solutions containing the core/shell magnetic nanoparticles was tested with permanent magnets.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Increased Arctic NO3− Availability as a Hydrogeomorphic Consequence of Permafrost Degradation and Landscape Drying

Climate-driven permafrost thaw alters the strongly coupled carbon and nitrogen cycles within the Arctic tundra, influencing the availability of limiting nutrients including nitrate (NO3−). Researchers have identified two primary mechanisms that increase nitrogen and NO3− availability within permafrost soils: (1) the ‘frozen feast’, where previously frozen organic material becomes available as it thaws, and (2) ‘shrubification’, where expansion of nitrogen-fixing shrubs promotes increased soil nitrogen. Through the synthesis of original and previously published observational data, and the application of multiple geospatial approaches, this study investigates and highlights a third mechanism that increases NO3− availability: the hydrogeomorphic evolution of polygonal permafrost landscapes. Permafrost thaw drives changes in microtopography, increasing the drainage of topographic highs, thus increasing oxic conditions that promote NO3− production and accumulation. We extrapolate relationships between NO3− and soil moisture in elevated topographic features within our study area and the broader Alaskan Coastal Plain and investigate potential changes in NO3− availability in response to possible hydrogeomorphic evolution scenarios of permafrost landscapes. These approximations indicate that such changes could increase Arctic tundra NO3− availability by ~250–1000%. Thus, hydrogeomorphic changes that accompany continued permafrost degradation in polygonal permafrost landscapes will substantially increase soil pore water NO3− availability and boost future fertilization and productivity in the Arctic.

54 ENVIRONMENTAL SCIENCES↗

ABF Past Accomplishments - TEA/LCA

The Integrated Analysis task in the Agile BioFoundry (ABF) conducts techno-economic analysis (TEA) and life cycle assessment (LCA) to quantify the economics and environmental impacts of bioprocesses under development. The team from Argonne National Laboratory (ANL) and the National Renewable Energy Laboratory (NREL) develops TEA and LCA models of selected compound targets and hosts of interest to the ABF in an effort to provide an analysis-based foundation to the R&D. To date, the Integrated Analysis task has performed process modeling and analyses on multiple pairings of bioproducts and hosts, centered around major metabolic "beachheads" and "exemplar" molecules chosen for each of the metabolic pathways of interest. This presentation provides an overview of the approach used for TEA and LCA in the ABF and of the progress, outcomes, and impacts of TEA and LCA to support ABF goals, with a focus towards developing bio-based products that are both environmentally and economically viable.

BIOMASS FUELS,INORGANIC, ORGANIC, PHYSICAL, AND AN↗

Predicting Initial Trans-Membrane Pressure for Optimized Operations in UF Unit Using Random Forest

With the growing scarcity of freshwater, innovative process design mechanisms like Reverse Osmosis (RO) are increasingly gaining attention among water treatment utilities to address the rising demand. Ensuring reliable water production necessitates efficient resource utilization, minimizing downtime in (ultra-filtration) UF systems. Recent advancements in machine learning (ML) have enabled the development of accurate data-driven models for Model Predictive Control (MPC), often requiring minimal prior knowledge of underlying physical processes. In this study, we present predictive regression models based on Random Forest (RF) and Auto-Regressive (AR) approaches to forecast the initial Trans-Membrane Pressure (TMP) for each filtration cycle in data generated by Direct Potable Reuse (DPR) systems. The proposed RF-based model demonstrates superior performance compared to baseline methods, including historical mean, Last Observation Carried Forward (LOCF), and naïve AR models, across various forecasting horizons in terms of root mean square error (RMSE) metric. To evaluate how different classes of process variables contribute to TMP dynamics over time, we examine the feature importance of independent covariates across multiple forecast horizons. This analysis provides insight into the temporal relevance of operational and sensor-derived features, guiding control and monitoring strategies. Additionally, the impact of hyperparameter tuning on TMP prediction performance is studied for both direct and recursive RF modelling approaches across increasing forecast horizons. Accurate prediction of initial TMP is critical for optimizing RO operations, as it enables the development of robust modelling frameworks by accurately estimating membrane fouling trends, thereby enhancing process efficiency and long-term reliability. The demonstrated efficacy of the RF-based approach highlights its potential as a tool for real-time decision-making in water treatment systems, paving the way for advanced process optimization and sustainable water resource management.

Mukherjee, Subrata [ORNL] (ORCID:0000000309930338)↗

Role of Wadsley Defects and Cation Disorder to Enhance MoNb 12 O 33 Diffusion

Wadsley-Roth (WR) niobates have emerged as high-rate anode materials that can combine rapid ionic diffusion with good electronic conductivity. WR compounds have been defect-enhanced by limited annealing, however, such materials often contain multiple types of defects. In particular, both Wadsley defects (variable block size) and transition metal disorder have the potential to modify transport rates, however the corresponding effects are not well understood mechanistically. Here, MoNb 12 O 33 (MNO) was calcined at two different temperatures to compare a defect-rich condition (MNO-800) with a proximal order-rich condition (MNO-900) as assessed through XRD, XANES, EXAFS, and STEM characterizations. Galvanostatically cycled lithium half cells of MNO-800 exhibited additional capacity (307 mAhg −1 at 0.1C, 4.66% higher) and improved high-rate capacity of 200 mAhg −1 at 10C. ICI-based overpotential analysis identified solid state diffusion as the dominant rate limiting process where MNO-800 correspondingly exhibited ∼3X faster capacity-weighted diffusivity. A machine-learning interatomic potential was trained to density functional theory and then applied with molecular dynamics (MLIP-MD) to examine the possible roles of Wadsley defects and transition metal disorder. For both defect-types, Li was found to populate and activate fast diffusion paths from window sites at lower extents of lithiation as compared to the order-rich model.

defect↗

Modulating Li + and Polysulfide Solvation with Low-Density Moderately Solvating Electrolytes for Lithium–Sulfur Batteries

Lithium–sulfur (Li–S) batteries show great promise as the next-generation rechargeable batteries, yet they still suffer from polysulfide shuttling and interphasial instability. Electrolyte, as the medium for ion transport and sulfur conversion, plays a crucial role in overcoming these challenges. Here, we introduce a moderately solvating electrolyte (MSE) based on low-density, low-viscosity, and nonfluorinated ether co-solvents that balances polysulfide suppression, Li metal stabilization, and redox kinetics. Through multiple solvent–solvent and solvent-ion interactions, the optimized MSE weakens Li + -solvent pairing while strengthening cation–anion interactions, thereby lowering the desolvation barrier and promoting the formation of a favorable solid–electrolyte interphase (SEI). Meanwhile, MSE limits the polysulfide dissolution but improves the accessibility of active material through better wettability and tailored solvation environment, leading to an altered sulfur deposition mechanism with β – α conversion. This approach enables a stable cycling of high-mass loading Li–S cells (> 3.5 mg cm -2 ) at both room temperature and 45 °C (where shuttling and side reactions are severer), and demonstrates a pouch cell with lean electrolyte content (4.5 µL mg s -1 ). This work highlights a practical route to develop high-performance electrolyte for Li–S cells and provides mechanistic insights into their operation.

25 ENERGY STORAGE↗

Species-Specific Shifts in Diurnal Sap Velocity Dynamics and Hysteretic Behavior of Ecophysiological Variables During the 2015–2016 El Niño Event in the Amazon Forest

Current climate change scenarios indicate warmer temperatures and the potential for more extreme droughts in the tropics, such that a mechanistic understanding of the water cycle from individual trees to landscapes is needed to adequately predict future changes in forest structure and function. In this study, we contrasted physiological responses of tropical trees during a normal dry season with the extreme dry season due to the 2015–2016 El Niño-Southern Oscillation (ENSO) event. We quantified high resolution temporal dynamics of sap velocity (V s ), stomatal conductance (g s ) and leaf water potential (Ψ L ) of multiple canopy trees, and their correlations with leaf temperature (T leaf ) and environmental conditions [direct solar radiation, air temperature (T air ) and vapor pressure deficit (VPD)]. The experiment leveraged canopy access towers to measure adjacent trees at the ZF2 and Tapajós tropical forest research (near the cities of Manaus and Santarém). The temporal difference between the peak of g s (late morning) and the peak of VPD (early afternoon) is one of the major regulators of sap velocity hysteresis patterns. Sap velocity displayed species-specific diurnal hysteresis patterns reflected by changes in T leaf . In the morning, T leaf and sap velocity displayed a sigmoidal relationship. In the afternoon, stomatal conductance declined as T leaf approached a daily peak, allowing Ψ L to begin recovery, while sap velocity declined with an exponential relationship with Tleaf. In Manaus, hysteresis indices of the variables T leaf -T air and Ψ L -T leaf were calculated for different species and a significant difference (p < 0.01, α = 0.05) was observed when the 2015 dry season (ENSO period) was compared with the 2017 dry season (“control scenario”). In some days during the 2015 ENSO event, T leaf approached 40°C for all studied species and the differences between T leaf and T air reached as high at 8°C (average difference: 1.65 ± 1.07°C). Generally, T leaf was higher than T air during the middle morning to early afternoon, and lower than T air during the early morning, late afternoon and night. Our results support the hypothesis that partial stomatal closure allows for a recovery in Ψ L during the afternoon period giving an observed counterclockwise hysteresis pattern between Ψ L and T leaf .

54 ENVIRONMENTAL SCIENCES↗

Accelerated Stress Testing of Perovskite Photovoltaic Modules: Differentiating Degradation Modes with Electroluminescence Imaging

Herein, electroluminescence (EL) and thermal imaging are used to examine p–i–n metal halide perovskite (MHP) photovoltaic (PV) mini-modules (MA0.6FA0.4PbI3, 20 cells, 78 cm2) before and after indoor-accelerated stress testing or outdoor deployment. Distinct spatial patterns in the EL images emerge, which depend on the external stress conditions experienced by the mini-module. Imaging results highlight a distribution of dark speckle features that dominate after UV stress, attributed to widespread interfacial contact degradation. Lateral intensity gradients across cells dominate after thermal cycling (TC) stress, attributed to current crowding near scribe defects. While current–voltage analysis alone does not give full insight on the degradation process, this study shows that distinct degradation modes can be further defined by multimodal electro-optical imaging (i.e., EL combined with photoluminescence and dark lock-in thermography). Neither UV exposure nor TC-accelerated stress testing alone replicates the same degradation signatures observed after outdoor deployment, suggesting that multiple degradation modes occur under concurrent stressors outdoors. Finally, spatial characterization of degradation modes in MHP PV mini-modules before and after accelerated stress testing lays the groundwork for developing targeted accelerated stress testing procedures through comparison with outdoor aging.

14 SOLAR ENERGY↗

Whole core analysis of the single-fluid double-zone thorium molten salt reactor (SD-TMSR)

The SD-TMSR (2,250 MW th ) is a Single-fluid Double-zone Thorium-based Molten Salt Reactor. The active core of the SD-TMSR is divided into the inner zone (486 fuel tubes) and the outer zone (522 fuel tubes) to improve the Th-U3 breeding performance. This work adopted the SERPENT-2 Monte Carlo code to analyze the whole core model of the SD-TMSR. Built-in SERPENT-2 capabilities simulated online reprocessing and refueling and calculated the multiplication factor and Breeding Ratio (BR). We found that the molten salt Temperature Coefficient of Reactivity ( α T ) was negative for initial and equilibrium states. This study investigated the variation of the multiplication factor, BR, and build-up of important nuclides in the core as a function of burnup. Under online reprocessing and refueling, we studied the variation of the reactivity during 60 years of reactor operation. Additionally, the neutron spectrum shift during the reactor operation was calculated. Finally, these simulations determined the appropriate 232 Th and 233 U feed rates for maintaining criticality and enabled analysis of the overall SD-TMSR fuel cycle performance.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Defect formation and microstructure tuning via proton irradiation to control electrochemical and phase reversibility in layered battery materials

The reversibility of phase transformation influences the functionality of electrode materials in batteries. In many battery materials, nanosized grains favor phase reversibility but at the cost of cyclability due to aggravated side reactions with the electrolyte. Here, in this study, we present a novel approach to enhance the phase transformation reversibility of layered oxide cathodes, exemplified by Na 2/3 Fe 1/2 Mn 1/2 O 2 through proton irradiation. In addition to forming defects, proton irradiation at sufficiently high doses can subdivide single grains into multiple nanodomains without physically rupturing them. Hence, the single grains of the material assume a pseudo-secondary particle nature without reducing the overall grain size. Preserving the grain size is advantageous, as it reduces side reactions, which is not possible with conventional grain size reduction methods. While chemical transformations and defect formation induced through proton irradiation can influence the stability of battery materials, it is expected that structural reorganization due to cycling-induced phase transformation will be contained within these nanodomains. Such confinement of phase transformation is potentially responsible for enhancing the reversibility of layered oxide materials in our study. Thus, our study suggests that grain subdivision could become an effective microstructure tuning strategy for managing electrochemical cycling-induced phase changes in battery electrodes.

25 ENERGY STORAGE↗

Fundamental Behavior of ENSO Phase Locking

El Niño–Southern Oscillation (ENSO) events tend to peak at the end of the calendar year, a phenomenon called ENSO phase locking. This phase locking is a fundamental ENSO property that is determined by its basic dynamics. The conceptual ENSO recharge oscillator (RO) model is adopted to examine the ENSO phase-locking behavior in terms of its peak time, strength of phase locking, and asymmetry between El Niño and La Niña events. The RO model reproduces the main phase-locking characteristics found in observations, and the results show that the phase locking of ENSO is mainly dominated by the seasonal modulation of ENSO growth/decay rate. In addition, the linear/nonlinear mechanism of ENSO phase preference/phase locking is investigated using RO model. The difference between the nonlinear phase-locking mechanism and linear phase-preference mechanism is largely smoothed out in the presence of noise forcing. Further, the impact on ENSO phase locking from annual cycle modulation of the growth/decay rate, stochastic forcing, nonlinearity, and linear frequency are examined in the RO model. The preferred month of ENSO peak time depends critically on the phase and strength of the seasonal modulation of the ENSO growth/decay rate. Furthermore, the strength of phase locking is mainly controlled by the linear growth/decay rate, the amplitude of seasonal modulation of growth/decay rate, the amplitude of noise, the SST-dependent factor of multiplicative noise, and the linear frequency. The asymmetry of the sharpness of ENSO phase locking is induced by the asymmetric effect of state-dependent noise forcing in El Niño and La Niña events.

54 ENVIRONMENTAL SCIENCES↗

Comparative life cycle assessment of remote potable water supply for the Department of Defense

The Department of Defense (DOD) and other agencies, including relief organizations, require potable water for remote missions around the globe. As part of recent initiative by the U.S. Federal government through Executive Order 14057, the DOD has been instructed to investigate the sustainability of operations and practices within the context of climate change. One such practice that needs to be addressed is the procurement of potable water, an essential requirement of any remote mission or location. Currently, there are three primary means of procuring potable water at remote locations: bottled water, on-site purification, or tie-in to existing, local infrastructure. The first two operations are often considered the most secure options, but have sustainability concerns. The purpose of this study is to compare the environmental impacts of bottled water procurement versus on-site treatment via a mobile Reverse Osmosis Water Purification Unit (ROWPU), which uses multiple levels of filtration to make potable water from a local source. A cradle-to-gate assessment was developed for both systems to compare different options for potable water supply. An in person inventory was paired with data taken from the Ecoinvent 3.8 database to directly compare the two systems. The two systems are compared on a 5-year timeline to analyze the environmental impact of repeated bottled water transport versus diesel generator-fueled on-site treatment. Across all impact categories, the results indicate that high energy costs of the reverse osmosis process have significantly less impact on the environment than the repetitive transport and procurement of bottled water. The results of the study have important implications for advancing sustainable operations for remote communities or temporary settlements.

54 ENVIRONMENTAL SCIENCES↗

Water effects on NH 3 -SCR over Cu-based small-pore zeolite catalysts: A review

The selective catalytic reduction (SCR) of NO x with NH 3 as the reductant over small-pore Cu-zeolite catalysts is a leading strategy for controlling emissions from diesel engines and mobile sources. While the hydrothermal stability of Cu-zeolites such as Cu-SSZ-13, Cu-SAPO-34, and Cu-SSZ-39 has been extensively studied, the multifaceted role of water vapor under operating conditions has only recently received systematic attention. Water impacts multiple aspects of SCR catalysis, including NO x conversion, N 2 O formation, Cu ion speciation, redox kinetics, and surface reactions. This review comprehensively summarizes recent advances in understanding the effect of water on NH 3 -SCR over Cu-based catalysts. For Cu-SSZ-13, water vapor induces both inhibitory and promotive effects depending on temperature, Cu loading, and Si/Al ratio by altering NH 3 adsorption, Cu mobility, and redox half-cycle kinetics. Studies have revealed that water can suppress ammonium nitrate formation at low temperatures and enhance nitrate pathways at higher temperatures. Over Cu-SAPO-34, water promotes NO conversion by improving Cu(II) reducibility and strengthening Brønsted acidity. First-principles calculations confirm that water-coordinated Cu species lower O 2 activation barriers. In Cu-SSZ-39, water was found to facilitate Cu reduction, migration, and O 2 activation, resulting in superior water tolerance and unexpected catalytic promotion. Both experimental and computational studies highlight that water vapor exerts complex, catalyst-dependent effects on NH 3 -SCR performance, underscoring the need for tailored catalyst designs that leverage beneficial water interactions while minimizing inhibitory impacts.

Ammonia selective catalytic reduction↗

Systematic Evaluation of Atmospheric Forcing, Surface Datasets, and Mesh Effects on Kilometer-Scale Land Surface and River Modeling

Earth system models are advancing toward kilometer-scale resolution to capture local climate impacts and extremes. High-resolution land and river modeling depends on multiple factors, including mesh, surface datasets, and atmospheric forcing, but their relative effects at kilometer scales remain unquantified. We evaluated five Energy Exascale Earth System Model land and river configurations over the Mid-Atlantic region using two mesh (1/8° structured versus variable-resolution unstructured mesh), two surface datasets (default versus newly developed), and three atmospheric forcings (NLDAS2, MSWX, GSWP). Evaluation against satellite, reanalysis, and in situ benchmarks across water, energy, and carbon cycles quantifies how these factors affect model performance. Forcing selection produces the largest bias reductions (12-99% across variables), followed by surface datasets (7-75%) and mesh (up to 21%). Forcing effects vary by variable, with MSWX reducing biases for snow water equivalent, evapotranspiration, albedo, temperature, and gross primary productivity, GSWP for snow cover and runoff, and NLDAS for soil moisture and streamflow. The use of newly developed surface datasets improves gross primary productivity (58% bias reduction) and evapotranspiration but increase soil moisture and albedo biases due to current modeling limitations. Variable-resolution unstructured mesh improves the simulation of small-basin streamflow through better capturing drainage networks, though mesh minimally affects other land variables. These findings provide important guidance for high-resolution modeling development and actionable science.

Land and River modeling↗

Estimate long-term impact on battery degradation by considering electric vehicle real-world end-use factors

Many estimates of battery capacity degradation are based on accelerated lab tests that involve charge-discharge cycles or rely on data or electrochemical modeling. These methods are reasonable for technology benchmarking but rarely consider real-world end-use factors. To address this issue, this study develops the Battery Run-down under Electric Vehicle Operation (BREVO) model. It links the driver's travel pattern to physics-based battery degradation and powertrain energy consumption models. The model simulates the impacts of charging behavior, charging rate, driving patterns, and multiple energy management modules on battery capacity degradation. It finds that, over a 10-year timespan, firstly, for a random driver situated in the New England area, daily direct-current fast charging (60 kW) could lead to up to 22% less battery capacity when compared to daily Level-1 charging (1.8 kW). Second, the battery thermal management system can delay battery degradation by approximately 0.5% in the New England area. Third, warmer ambient temperatures enhance BEV battery usage. The model indicates that the battery capacity in the Los Angeles area is 6% higher than that in the New England area. The BREVO model provides crucial information for consumers and BEV manufacturers on range anxiety, BEV battery design, and decision support of battery warranty.

25 ENERGY STORAGE↗

Simulation of the NuScale SMR and Investigation of the Effect of Load-Following on Component Lifetimes

The NuScale SMR has been modelled using the Virtual Environment for Reactor Applications (VERA) multiphysics environment and the results compared with the publicly reported data in the Design Certification Application (DCA). The results show an excellent agreement for the compared axial and radial power distributions, temperature coefficients of reactivity, boron and control rod worths, and fast neutron flux. This NuScale model is then used to investigate the effect of different operational modes on reactor components to determine how flexible load-following operation may affect control rod and reactor pressure vessel (RPV) lifetimes. The control rod degradation is confirmed to primarily affect the silver-indium-cadmium (AIC) rod tip. The degradation rate is observed to follow a non-linear function of core power level where the increase in degradation decreases with insertion depth. For the variation in core power levels expected with current load-following schemes, the total control rod degradation is found to be mild, at 5-10% of usable life per cycle for a reactor operating at <80% power. Nonetheless, this enables load following strategies to be confirmed and/or modified to ensure that control rods do not need to be replaced during the 60+ year life of the reactor. The RPV degradation was found to be almost directly proportional to the core power level and was not overly sensitive to flux shape perturbations. Future work is planned using these damage functions to optimize operation over multiple NuScale SMR units and develop strategies for prognostics and health management.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

At least it is a dry cold: the global distribution of freeze–thaw and drought stress and the traits that may impart poly-tolerance in conifers

Abstract Conifers inhabit some of the most challenging landscapes where multiple abiotic stressors (e.g., aridity, freezing temperatures) often co-occur. Physiological tolerance to multiple stressors (‘poly-tolerance’) is thought to be rare because exposure to one stress generally limits responses to another through functional trade-offs. However, the capacity to exhibit poly-tolerance may be greater when combined abiotic stressors have similar physiological impacts, such as the disruption of hydraulic function imposed by drought or freezing. Here, we reviewed empirical data in light of theoretical expectations for conifer adaptations to drought and freeze–thaw cycles with particular attention to hydraulic traits of the stem and leaf. Additionally, we examined the commonality and spatial distribution of poly-stress along indices of these combined stressors. We found that locations with the highest values of our poly-stress index (PSi) are characterized by moderate drought and moderate freeze–thaw, and most of the global conifer distribution occupies areas of moderate poly-stress. Among traits examined, we found diverse responses to the stressors. Turgor loss point did not correlate with freeze–thaw or drought stress individually, but did with the PSi, albeit inverse to what was hypothesized. Leaf mass per area was more strongly linked with drought stress than the poly-stress and not at all with freeze–thaw stress. In stems, the water potential causing 50% loss of hydraulic conductivity became more negative with increasing drought stress and poly-stress but did not correlate with freeze–thaw stress. For these traits, we identified a striking lack of coverage for substantial portions of species ranges, particularly at the upper boundaries of their respective PSis, demonstrating a critical gap in our understanding of trait prevalence and plasticity along these stress gradients. Future research should investigate traits that confer tolerance to both freeze–thaw and drought stress in a wide range of species across broad geographic scales.

54 ENVIRONMENTAL SCIENCES↗