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At least 1,261 records · Page 70

Theoretical Insights into Reaction-Induced Transformation and Tuning of Catalytic Behavior in Heterogenous Catalysis

Reaction-induced transformations in heterogenous catalysis represent diverse phenomena that challenge traditional views of static catalyst surfaces. From surface adsorbate dynamics, atomic rearrangements, to composition and phase transitions, these processes reveal the profound differences between idealized model systems under ultrahigh vacuum and the complex, evolving interfaces that govern real catalytic behaviors under reaction conditions. Here, this perspective reviews recent theoretical efforts to provide atomic-level mechanistic insights into significant reaction-induced transformations and their impact on catalytic activity and selectivity. It underscores the need for an integrated framework that combines predictive simulations with operando characterization to uncover active sites and mechanisms under realistic operating conditions. Achieving this requires accelerating existing simulations to fully capture diverse reaction-induced surface dynamics, enabling scalable and accurate modeling of catalysts as condition-dependent, dynamically evolving systems. Such approaches are critical to bridge the gap between theory and practice, offering a pathway to more impactful and predictive catalyst design.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Plant‐Induced Changes Mediate Belowground Carbon Cycling in an Experimentally Warmed Peatland

Warming and elevated atmospheric CO 2 profoundly impact peatland ecosystems, particularly through changes in plant species composition. Plants regulate the initial input of organic compounds to peatland belowground systems, controlling the availability of electron donors and electron acceptors that fuel microbially mediated organic matter decomposition to CO 2 and CH 4 . However, explicit links between porewater CO 2 and CH 4 dynamics and plant-derived chemical compounds remain relatively undefined. In a whole ecosystem warming experiment, we investigated how warming affects plant leaf chemical composition and species assemblages, and how the alteration of leaf-derived organic compounds supplied to the subsurface impacts belowground CO 2 and CH 4 production. While earlier studies at our site found no temperature-dependent changes in CH 4 production pathways, our extended timeseries has revealed increased acetoclastic methanogenesis at higher temperatures in certain peat depths, correlated with elevated porewater phenolics. These changes appear driven by the observed increased plant productivity and altered vegetation inputs, which accelerate decomposition and fuel CH 4 production through enhanced substrate availability. In conclusion, we observed warming-induced changes in molecular composition both between and within plant species, suggesting that plant-mediated controls on belowground carbon processing are more complex than previously recognized.

Wilson, Rachel M. [Florida State Univ., Tallahasse↗

Depth-dependent valence stratification driven by oxygen redox in lithium-rich layered oxide

Abstract Lithium-rich nickel-manganese-cobalt (LirNMC) layered material is a promising cathode for lithium-ion batteries thanks to its large energy density enabled by coexisting cation and anion redox activities. It however suffers from a voltage decay upon cycling, urging for an in-depth understanding of the particle-level structure and chemical complexity. In this work, we investigate the Li 1.2 Ni 0.13 Mn 0.54 Co 0.13 O 2 particles morphologically, compositionally, and chemically in three-dimensions. While the composition is generally uniform throughout the particle, the charging induces a strong depth dependency in transition metal valence. Such a valence stratification phenomenon is attributed to the nature of oxygen redox which is very likely mostly associated with Mn. The depth-dependent chemistry could be modulated by the particles’ core-multi-shell morphology, suggesting a structural-chemical interplay. These findings highlight the possibility of introducing a chemical gradient to address the oxygen-loss-induced voltage fade in LirNMC layered materials.

25 ENERGY STORAGE↗

Molecular-ink route to 13.0% efficient low-bandgap CuIn(S,Se) 2 and 14.7% efficient Cu(In,Ga)(S,Se) 2 solar cells

A stable dimethyl sulfoxide (DMSO)-based ink containing a copper–thiourea–chloride complex and an indium–DMSO–chloride complex leads to 13.0% efficient CuIn(S,Se)2 (CIS) solar cells, which is a record for solution processed CIS. The formation of these complexes was found critical to control oxidation states and loss of metals during processing and to tailor the final composition of the absorber.

14 SOLAR ENERGY↗

Wildfire impact on soil microbiome life history traits and roles in ecosystem carbon cycling

Abstract Wildfires, which are increasing in frequency and severity with climate change, reduce soil microbial biomass and alter microbial community composition and function. The soil microbiome plays a vital role in carbon (C) and nitrogen (N) cycling, but its complexity makes it challenging to predict post-wildfire soil microbial dynamics and resulting impacts on ecosystem biogeochemistry. The application of biogeochemically relevant conceptual trait-based frameworks to the soil microbiome can distill this complexity, enabling enhanced predictability of soil microbiome recovery following wildfire and subsequent impacts to biogeochemical cycles. Conceptual frameworks that have direct links to soil C and N cycling have been developed for the soil microbiome; the Y-A-S framework overviews soil microbiome life history strategies that have tradeoffs with one another and others have proposed frameworks specific to wildfire. Here, we aimed to delineate post-wildfire changes of bacterial traits in western US coniferous forests to inform how severe wildfire influences soil microbiome recovery and resultant biogeochemical cycling. We utilized a comprehensive metagenome-assembled genome catalog from post-wildfire soils representing 1 to 11 years following low- and high-severity burning to identify traits that enable the persistence of microbial taxa in burned soils and influence ecosystem C and N cycling. We found that high-severity wildfire initially selects for fast growers and, up to a decade post-fire, taxa that invest in genes for acquiring diverse resources from the external environment, which in combination could increase soil C losses. This work begins to disentangle how climate change–induced shifts in wildfire behavior might alter microbially mediated soil biogeochemical cycling.

Nelson, Amelia R.↗

CosmicEmu, Version 2.0

The CosmicEmu implements a Gaussian process emulation scheme to predict the dark matter and dark matter + neutrino power spectra over a range of physical parameters that describe the composition and evolution of the Universe. The procedure can produce thousands of spectra per second, much faster than the complex n-body simulations used to produce the training set, which can take weeks per simulation. The training simulations, their design, and the general scheme is described in Lawrence et al. (2010), Heitmann et al. (2014), Heitmann et al. (2016), and an upcoming paper.

Lawrence, Earl↗

Exome resequencing and GWAS for growth, ecophysiology, and chemical and metabolomic composition of wood of Populus trichocarpa

Populus trichocarpa is an important forest tree species for the generation of lignocellulosic ethanol. Understanding the genomic basis of biomass production and chemical composition of wood is fundamental in supporting genetic improvement programs. Considerable variation has been observed in this species for complex traits related to growth, phenology, ecophysiology and wood chemistry. Those traits are influenced by both polygenic control and environmental effects, and their genome architecture and regulation are only partially understood. Genome wide association studies (GWAS) represent an approach to advance that aim using thousands of single nucleotide polymorphisms (SNPs). Genotyping using exome capture methodologies represent an efficient approach to identify specific functional regions of genomes underlying phenotypic variation. We identified 813 K SNPs, which were utilized for genotyping 461 P. trichocarpa clones, representing 101 provenances collected from Oregon and Washington, and established in California. A GWAS performed on 20 traits, considering single SNP-marker tests identified a variable number of significant SNPs ( p -value < 6.1479E-8) in association with diameter, height, leaf carbon and nitrogen contents, and δ 15 N. The number of significant SNPs ranged from 2 to 220 per trait. Additionally, multiple-marker analyses by sliding-windows tests detected between 6 and 192 significant windows for the analyzed traits. The significant SNPs resided within genes that encode proteins belonging to different functional classes as such protein synthesis, energy/metabolism and DNA/RNA metabolism, among others. SNP-markers within genes associated with traits of importance for biomass production were detected. They contribute to characterize the genomic architecture of P. trichocarpa biomass required to support the development and application of marker breeding technologies.

09 BIOMASS FUELS↗

Imaging theory of structured pump-probe microscopy

With sub-micron spatial resolution and femtosecond temporal resolution, pump probe microscopy provides a powerful spectroscopic probe of complex electronic environments in bulk and nanoscale materials. However, the electronic structure of many materials systems are governed by compositional and morphological heterogeneities on length scales that lie below the diffraction limit. We have recently demonstrated Structured Pump Probe Microscopy (SPPM), which employs a patterned pump excitation field to provide spectroscopic interrogation of sub-diffraction limited sample volumes. Herein, we develop the imaging theory of SPPM in two dimensions to accompany the previously published experimental methodology. We show that regardless of pump and probe wavelengths, a nearly two-fold reduction in spectroscopic probe volume can be achieved. We also examine the limitations of the approach, with a detailed discussion of ringing in the point spread function that can reduce imaging performance.

47 OTHER INSTRUMENTATION↗

Atmosphere Effects in Laser Powder Bed Fusion: A Review

The use of components fabricated by laser powder bed fusion (LPBF) requires the development of processing parameters that can produce high-quality material. Manipulating the most commonly identified critical build parameters (e.g., laser power, laser scan speed, and layer thickness) on LPBF equipment can generate acceptable parts for established materials and moderately intricate part geometries. The need to fabricate increasingly complex parts from unique materials drives the limited research into LPBF process control using underutilized parameters, such as atmosphere composition and pressure. As presented in this review, manipulating atmosphere composition and pressure in laser beam welding has been shown to expand processing windows and produce higher-quality welds. The similarities between laser beam welding and laser-based AM processes suggest that this atmosphere control research could be effectively adapted for LPBF, an area that has not been widely explored. Tailoring this research for LPBF has significant potential to reveal novel processing regimes. This review presents the current state of the art in atmosphere research for laser beam welding and LPBF, with a focus on studies exploring cover gas composition and pressure, and concludes with an outlook on future LPBF atmosphere control systems.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

MOCVD growth of Si-doped α-(AlGa) 2 O 3 on m-plane α-Al 2 O 3 substrates

We reported the growth of (AlGa) 2 O 3 layers on ($10\overline{10}$) α-Al 2 O 3 substrates using cold-wall metalorganic chemical vapor deposition, and the electrical characterization of Si-doped (AlGa) 2 O 3 layers. In the Ga 2 O 3 growth, the α phase was dominant at low growth temperature, achieving the growth rate of 2.4 μm h –1 at 650 °C. Sheet resistance and electrical conductivity of the Ga 2 O 3 layers with a Si concentration of 3 × 10 20 cm –3 were 1 × 10 4 Ω/square and 8.3 S cm –1 , respectively, at the measurement temperature of 500 °C. The Al composition in the (AlGa) 2 O 3 layers was controlled from 0% to 74%. In our initial attempts, we obtained electrically conductive α-(AlGa) 2 O 3 layers by Si doping (2 × 10 –9 S cm –1 in the sample with an Al composition of 56%). Finally, hybrid functional calculations suggest the conductivities are limited by compensation of Si through cation vacancy complexes, and not by the significant amounts of co-incorporated C and N that are predicted to be electrically passivated by hydrogen.

36 MATERIALS SCIENCE↗

CosmicEmu, Version 2.0

The CosmicEmu implements a Gaussian process emulation scheme to predict the dark matter and dark matter + neutrino power spectra over a range of physical parameters that describe the composition and evolution of the Universe. The procedure can produce thousands of spectra per second, much faster than the complex n-body simulations used to produce the training set, which can take weeks per simulation. The training simulations, their design, and the general scheme is described in Lawrence et al. (2010), Heitmann et al. (2014), Heitmann et al. (2016), and an upcoming paper.

Lawrence, Earl↗

Experiments and numerical modeling of surrogate droplet combustion for a 93 octane gasoline calibration fuel

Gasoline is the world’s most prolific liquid transportation fuel for ground transportation vehicles. Yet, a fundamental understanding of its burning characteristics is still lacking. Complicating this matter is the highly multicomponent nature of gasoline (comprised of hundreds of chemical species) and the seasonable variability of its composition due to variations in the crude oil feedstocks used in refining. The need to bring order to this complex problem has led to development of calibration fuels (Tier II in presented study) which on average will provide repeatable metrics that replicate performance of refined gasoline for various engine designs. This study presents results of experiments using the configuration of an isolated droplet to study the combustion dynamics of calibration fuel and three different surrogates (S4, S5, S6) for the calibration fuel. Droplet burning is under microgravity conditions, where gas transport is determined entirely by fuel evaporation in order to promote spherical symmetry in the burning process. The initial droplet diameters ranged between 0.55 mm and 0.60 mm. The droplets were spark-ignited and their burning histories were recorded by digital video cameras to obtain quantitative data. For each fuel, the evolutions of droplet, flame, and soot-shell diameters were measured to calculate the burn rates, flame-droplet diameter ratios (FSR) and soot-droplet diameter ratios. Additionally, a detailed numerical modeling is presented. This simulation includes multicomponent phase equilibrium, unsteady gas and liquid transport, radiative heat transfer, internal liquid diffusion and detailed combustion chemistry of different fuels during their burning process. Experiment results show that the calibration fuel and surrogates have a close burn rates and FSR, and S5 presents a relatively similar results with calibration fuel. Predictions from the numerical simulation using the surrogate are compared with experiment measurements, which showed a good agreement with the experiment results, including the droplet burning rate and FSR.

Guo, Songtao↗

Superior Capacitive Energy-Storage Performance in Pb-Free Relaxors with a Simple Chemical Composition

Chemical design of lead-free relaxors with simultaneously high energy density (W rec ) and high efficiency (η) for capacitive energy-storage has been a big challenge for advanced electronic systems. The current situation indicates that realizing such superior energy-storage properties requires highly complex chemical components. Herein, we demonstrate that, via local structure design, an ultrahigh W rec of 10.1 J/cm 3 , concurrent with a high η of 90%, as well as excellent thermal and frequency stabilities can be achieved in a relaxor with a very simple chemical composition. By introducing 6s 2 lone pair stereochemical active Bi into the classical BaTiO 3 ferroelectric to generate a mismatch between A- and B-site polar displacements, a relaxor state with strong local polar fluctuations can be formed. Through advanced atomic-resolution displacement mapping and 3D reconstructing the nanoscale structure from neutron/X-ray total scattering, it is revealed that the localized Bi enhances the polar length largely at several perovskite unit cells and disrupts the long-range coherent Ti polar displacements, resulting in a slush-like structure with extremely small size polar clusters and strong local polar fluctuations. This favorable relaxor state exhibits substantially enhanced polarization, and minimized hysteresis at a high breakdown strength. This work offers a feasible avenue to chemically design new relaxors with a simple composition for high-performance capacitive energy-storage.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Energy-resolved neutron imaging and diffraction including grain orientation mapping using event camera technology

Time-of-flight neutron diffraction and energy-resolved imaging each provide unique perspectives into material properties. Neutron diffraction is useful for assessing microstructural parameters such as phase composition, texture, and dislocation densities, though it typically provides averaged data over the sampled volume. Energy-resolved imaging, on the other hand, offers both spatial and spectral information by detecting Bragg edges and neutron absorption resonances, which enables detailed mapping of microstructure and isotopic composition. When combined, these techniques have the potential to enrich our understanding of material behavior across different scales, enhancing our understanding of complex materials. Traditionally, these modalities are conducted on separate instruments, which is time-consuming and poses challenges for data integration. Here, we report the integration of the LumaCam, an event-mode energy-resolved neutron imaging camera with the HIPPO time-of-flight diffractometer at LANSCE. This integration enables simultaneous diffraction and imaging across the full spectrum, with analysis optimized for diffraction and Bragg-edge imaging in the thermal range (0.45–10 Å) and resonance imaging in the epithermal range (0.5–3000 eV), facilitating comprehensive multi-modal analysis. We demonstrate its capabilities through case studies, including spatial mapping of grain orientations in a steel sample and accurate thickness estimations for irregular samples including a depleted uranium cylinder and a natural silver-containing mineral specimen. The combined setup enhances real-time sample alignment and provides comprehensive data for crystal structure, texture, and isotopic composition analysis. This approach opens new possibilities for advanced applications in nuclear engineering, archaeology, and materials science.

36 MATERIALS SCIENCE↗

Anhydrous vs Hydrated f-Element Acetate Polymers Dictated by the Stoichiometry of Protic Acidic/Basic Azole Mixtures

Continuing our investigations of ionic liquid (IL) based routes to a library of f-element/soft donor complexes which could be studied crystallographically, we have explored the dissolution of f-element salts in protic imidazole-based ILs containing only soft donors at high temperatures to drive off volatiles, including water and carboxylic or mineral acids. Here we present our results, reacting acidic and basic azoles in 1:3 or 1:1 stoichiometric compositions at elevated temperature, followed by saturation with Nd(OAc) 3 ·xH 2 O or Ce(OAc) 3 ·xH 2 O, which led to 13 new metal–acetate polymeric complexes identified by single-crystal X-ray diffraction. We found that the diversity in coordination modes of the simple acetate ligand that interfere with substitution of the softer N donors led to several readily crystallizable complexes forming two distinct groups with respect to f-element interaction with the ionic liquid precursors. When the acidic/basic azole ratio was 1:3, acetate and a neutral basic azole were found to be coordinated to the metal centers but no water, although in one case (2) water was observed in the secondary coordination sphere: [Ce(μ 2 -OAc) 3 (C 1 im)] n (1, C 1 im = 1-methylimidazole), [Nd(μ 2 -(OAc) 3 (C 1 im)] n ·nH 2 O (2), [Ce(μ 2 -OAc) 3 (C 2 im)] n (3, C 2 im = 1-ethylimidazole), [Ln(μ 2 -OAc) 3 DMF] n (Ln = Nd (4), Ce (5); dimethylformamide (DMF) was substituted for the azole mixture), and [Nd(μ 2 -OAc) 3 (C 4 im)] n (6, C 4 im = 1-butylimidazole). However, when the stoichiometric ratio was 1:1, water was always observed coordinated to the metal ions with the acidic azole included in the structure as a solvate or cocrystal, despite a higher reaction temperature: [Nd(μ 2 -OAc) 3 (OH 2 )] n ·n(1,2,3-Taz) (7, 1,2,3-Taz = 1,2,3-triazole), [Ln(μ 2 -OAc) 3 (OH 2 )] n ·n(4,5-DCim) (Ln = Nd (8), Ce (9), 4,5-DCim = 4,5-dicyanoimidazole), [Ln(μ 2 -OAc) 3 (OH 2 )] n ·n(3,5-diNH 2 -1,2,4-Taz) (Ln = Nd (10), Ce (11), 3,5-diNH 2 -1,2,4-Taz = 3,5-diamino-1,2,4-triazole), [Ce(μ 2 -OAc) 3 (OH 2 )] n ·n(3-NH 2 -1,2,4-Taz) (12, 3-NH 2 -1,2,4-Taz = 3-amino-1,2,4-triazole), and [Nd(μ 2 -OAc) 3 (OH 2 )] n ·n(5-NH 2 -Tz) (13, 5-NH2-Tz = 5-aminotetrazole). All of the compounds retain the Ln:OAc– ratio of 1:3 and form 1D polymeric chains; however, they exhibit a variety of coordination modes affecting the degree of chain condensation. The isolation of both hydrated and anhydrous products revealed different abilities of the investigated soft N-donors to compete with O-donors finding their place in the coordination sphere of the lanthanide or in the crystal lattice.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

MXene Reinforced Thermosetting Composite for Lightning Strike Protection of Carbon Fiber Reinforced Polymer

Ti 3 C 2 – a member of the MXenes (2D transition metal carbides and nitrides) family, is investigated as an effective filler to improve the electrical, mechanical, and thermal properties of divinylbenzene (DVB) thermosetting resin. Consequently, its performance as a lightning strike protection (LSP) coating for carbon fiber reinforced polymer (CFRP) is evaluated. Polyaniline (PANI) – dodecylbenzene sulfonic acid (DBSA) complex is used to cure the DVB resin. The synergic effect of MXenes (with surface that is negatively charged) with polyaniline (positive charge) shows electrostatic bonding and improved electrical conductivity in the composite. We also find that the addition of MXenes at 2 wt% into the PANI-DVB composite shows ≈139%, 10%, and 9% improvement in electrical conductivity, flexural strength, and flexural modulus, respectively, compared to the neat PANI-DVB composite. The composites are investigated using various material characterization techniques including Fourier transforms infrared spectroscopy, thermogravimetric analysis, differential scanning calorimetry, and scanning electron microscopy. Furthermore, MXenes-DVB is utilized to create a conductive thermosetting coating on top of a CFRP substrate and tested against a lightning strike of 100 kA. CFRP with MXenes-DVB coating reduced the surface damage from 40.61 cm 2 (reference CFRP panel) to 13.29 cm 2 (CFRP coated with MXenes-DVB).

36 MATERIALS SCIENCE↗

Portable and Cost-Effective Device for Reliable Detection of Counterfeit and Non-compliant Refrigerants in Diverse Applications

Counterfeit refrigerants pose significant challenges to safety, system reliability, and operational effectiveness due to their harmful contaminants or incompatible chemical compositions. Utilizing these noncompliant products can lead to reduced efficiency, equipment failures, and expensive repairs. Additionally, heightened demand for alternative refrigerants during the industry's transition has created supply gaps, enabling counterfeit products to proliferate. Accurate detection and analysis tools are therefore essential to verify refrigerant authenticity and ensure system integrity in diverse applications. This paper presents the development of a portable device designed for reliable identification and detailed analysis of refrigerant composition. By integrating precision gas sampling, controlled pressure regulation, and automated sensor technology, the device not only detects deviations from standard refrigerant properties but also provides a comprehensive composition breakdown. Pre-calibrated sensors measure the refrigerant gas to identify specific concentrations and contaminants, with an intuitive LED-based indicator system ensuring quick interpretation of results. The user-friendly interface enables operators to select refrigerant types for targeted testing, further enhancing accuracy and usability for field technicians. Comprehensive testing was conducted on mildly flammable A2L refrigerants, showcasing the device’s robustness and adaptability in analyzing composition and detecting discrepancies. The device demonstrated consistent accuracy across a range of refrigerant samples, affirming its reliability in diverse operational environments. Its design minimizes contamination risks during sampling and provides detailed composition results within 90 seconds, ensuring efficient and precise analysis. With a projected price point under $150, the proposed solution delivers affordability alongside its lightweight portability and straightforward operation. Unlike complex and costly alternatives, such as gas chromatography systems, this device provides an accessible option for technicians, customs personnel, and industry operators in need of quick and effective refrigerant verification. Compatible with both current formulations and emerging refrigerant technologies, the device addresses critical counterfeit detection needs across a range of applications. By delivering accurate composition analysis and counterfeit identification, this innovation enhances system performance, safety, and operational reliability in crucial industries.

Cheekatamarla, Praveen [ORNL] (ORCID:0000000248827↗

Predicting biomass of hyperdiverse and structurally complex central Amazonian forests - a virtual approach using extensive field data

Notice on corrigendum: This paper has a corresponding corrigendum published. Please read the corrigendum first. Old-growth forests are subject to substantial changes in structure and species composition due to the intensification of human activities, gradual climate change and extreme weather events. Trees store ca. 90 % of the total aboveground biomass (AGB) in tropical forests and precise tree biomass estimation models are crucial for management and conservation. In the central Amazon, predicting AGB at large spatial scales is a challenging task due to the heterogeneity of successional stages, high tree species diversity and inherent variations in tree allometry and architecture. We parameterized generic AGB estimation models applicable across species and a wide range of structural and compositional variation related to species sorting into height layers as well as frequent natural disturbances. We used 727 trees (diameter at breast height ≥ 5 cm) from 101 genera and at least 135 species harvested in a contiguous forest near Manaus, Brazil. Sampling from this data set we assembled six scenarios designed to span existing gradients in floristic composition and size distribution in order to select models that best predict AGB at the landscape level across successional gradients. We found that good individual tree model fits do not necessarily translate into reliable predictions of AGB at the landscape level. When predicting AGB (dry mass) over scenarios using our different models and an available pantropical model, we observed systematic biases ranging from -31 % (pantropical) to +39 %, with root-mean-square error (RMSE) values of up to 130 Mg ha -1 (pantropical). Our first and second best models had both low mean biases (0.8 and 3.9 %, respectively) and RMSE (9.4 and 18.6 Mg ha -1 ) when applied over scenarios. Predicting biomass correctly at the landscape level in hyperdiverse and structurally complex tropical forests, especially allowing good performance at the margins of data availability for model construction/calibration, requires the inclusion of predictors that express inherent variations in species architecture. The model of interest should comprise the floristic composition and size-distribution variability of the target forest, implying that even generic global or pantropical biomass estimation models can lead to strong biases. Reliable biomass assessments for the Amazon basin (i.e., secondary forests) still depend on the collection of allometric data at the local/regional scale and forest inventories including species-specific attributes, which are often unavailable or estimated imprecisely in most regions.

54 ENVIRONMENTAL SCIENCES↗