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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

SALT3-NIR: Taking the Open-source Type Ia Supernova Model to Longer Wavelengths for Next-generation Cosmological Measurements

Abstract A large fraction of Type Ia supernova (SN Ia) observations over the next decade will be in the near-infrared (NIR), at wavelengths beyond the reach of the current standard light-curve model for SN Ia cosmology, SALT3 (∼2800–8700 Å central filter wavelength). To harness this new SN Ia sample and reduce future light-curve standardization systematic uncertainties, we train SALT3 at NIR wavelengths (SALT3-NIR) up to 2 μ m with the open-source model-training software SALTshaker , which can easily accommodate future observations. Using simulated data, we show that the training process constrains the NIR model to ∼2%–3% across the phase range (−20 to 50 days). We find that Hubble residual (HR) scatter is smaller using the NIR alone or optical+NIR compared to optical alone, by up to ∼30% depending on filter choice (95% confidence). There is significant correlation between NIR light-curve stretch measurements and luminosity, with stretch and color corrections often improving HR scatter by up to ∼20%. For SN Ia observations expected from the Roman Space Telescope, SALT3-NIR increases the amount of usable data in the SALT framework by ∼20% at redshift z ≲ 0.4 and by ∼50% at z ≲ 0.15. The SALT3-NIR model is part of the open-source SNCosmo and SNANA SN Ia cosmology packages.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1972

Thermal characteristics of the moon.

The papers describe earth-based and in situ surface measurements of the thermal characteristics of lunar-type materials. A geophysical interpretation of the thermal history of the moon is given. Microwave emission from the moon and radar mapping of lunar surface roughness are studied. Lunar thermal aspects from Surveyor data, lunar surface temperatures from Apollo 11 data, the development of an in situ thermal conductivity measurement for the lunar heat flow experiment, and the Apollo 15 lunar heat flow measurement are reviewed. Thermal properties of granulated materials, thermal property measurements on lunar material returned by Apollo 11 and 12 missions, and thermal characteristics of lunar surface roughness are discussed. Individual items are abstracted in this issue.

Lucas, J. W.↗
DOE OSTI2021

Simulations With the Marine Biogeochemistry Library (MARBL)

Abstract The Marine Biogeochemistry Library (MARBL) is a prognostic ocean biogeochemistry model that simulates marine ecosystem dynamics and the coupled cycles of carbon, nitrogen, phosphorus, iron, silicon, and oxygen. MARBL is a component of the Community Earth System Model (CESM); it supports flexible ecosystem configuration of multiple phytoplankton and zooplankton functional types; it is also portable, designed to interface with multiple ocean circulation models. Here, we present scientific documentation of MARBL, describe its configuration in CESM2 experiments included in the Coupled Model Intercomparison Project version 6 (CMIP6), and evaluate its performance against a number of observational data sets. The model simulates present‐day air‐sea CO 2 flux and many aspects of the carbon cycle in good agreement with observations. However, the simulated integrated uptake of anthropogenic CO 2 is weak, which we link to poor thermocline ventilation, a feature evident in simulated chlorofluorocarbon distributions. This also contributes to larger‐than‐observed oxygen minimum zones. Moreover, radiocarbon distributions show that the simulated circulation in the deep North Pacific is extremely sluggish, yielding extensive oxygen depletion and nutrient trapping at depth. Surface macronutrient biases are generally positive at low latitudes and negative at high latitudes. CESM2 simulates globally integrated net primary production (NPP) of 48 Pg C yr −1 and particulate export flux at 100 m of 7.1 Pg C yr −1 . The impacts of climate change include an increase in globally integrated NPP, but substantial declines in the North Atlantic. Particulate export is projected to decline globally, attributable to decreasing export efficiency associated with changes in phytoplankton community composition.

Meteorology & Atmospheric Sciences↗
DOE OSTI2024

The Effects of Threshold Voltage and Number of Fins per Transistor on the TID Response of GF 12LP Technology

This abstract presents a comprehensive analysis of total ionizing dose (TID) response in GlobalFoundries’ 12LP 12nm bulk FinFET technology using 10keV X-rays. Devices with higher threshold voltages (VTs) demonstrated lower increases in off-state leakage current (IDS,OFF) post-irradiation, highlighting the mitigating role of high VT in TID response. Our data shows that transistors with fewer fins exhibit superior TID resistance, implying lower susceptibility to radiation effects. Our study also probed two bias conditions, "Gate-On" and "Pass-Gate," with the former displaying more severe TID degradation. Interestingly, p-type devices displayed negligible degradation, underscoring their inherent resilience to TID effects. Additionally, medium thick n-type devices echoed the fin-count-dependent TID response observed in other transistor types, further strengthening our findings. These results underscore the importance of strategic transistor selection and design for enhancing the TID resilience of future CMOS FinFET architectures, particularly critical in radiation-intense environments.

42 ENGINEERING↗
DOE OSTI2024

Detecting Anomalous Images in Astronomical Datasets

Abstract Environmental and instrumental conditions can cause anomalies in astronomical images, which can potentially bias all kinds of measurements if not excluded. Detection of the anomalous images is usually done by human eyes, which is slow and sometimes not accurate. This is an important issue in weak lensing studies, particularly in the era of large-scale galaxy surveys, in which image qualities are crucial for the success of galaxy shape measurements. In this work we present two automatic methods for detecting anomalous images in astronomical data sets. The anomalous features can be divided into two types: one is associated with the source images, and the other appears on the background. Our first method, called the entropy method, utilizes the randomness of the orientation distribution of the source shapes and the background gradients to quantify the likelihood of an exposure being anomalous. Our second method involves training a neural network (autoencoder) to detect anomalies. We evaluate the effectiveness of the entropy method on the Canada–France–Hawaii Telescope Lensing Survey (CFHTLenS) and Dark Energy Camera Legacy Survey (DECaLS DR3) data. In CFHTLenS, with 1171 exposures, the entropy method outperforms human inspection by detecting 12 of the 13 anomalous exposures found during human inspection and uncovering 10 new ones. In DECaLS DR3, with 17112 exposures, the entropy method detects a significant number of anomalous exposures while keeping a low false-positive rate. We find that although the neural network performs relatively well in detecting source anomalies, its current performance is not as good as the entropy method.

Astronomy & Astrophysics↗
DOE OSTI2023

Photo-zSNthesis: Converting Type Ia Supernova Lightcurves to Redshift Estimates via Deep Learning

Abstract Upcoming photometric surveys will discover tens of thousands of Type Ia supernovae (SNe Ia), vastly outpacing the capacity of our spectroscopic resources. In order to maximize the scientific return of these observations in the absence of spectroscopic information, we must accurately extract key parameters, such as SN redshifts, with photometric information alone. We present Photo- z SNthesis, a convolutional neural network-based method for predicting full redshift probability distributions from multi-band supernova lightcurves, tested on both simulated Sloan Digital Sky Survey (SDSS) and Vera C. Rubin Legacy Survey of Space and Time data as well as observed SDSS SNe. We show major improvements over predictions from existing methods on both simulations and real observations as well as minimal redshift-dependent bias, which is a challenge due to selection effects, e.g., Malmquist bias. Specifically, we show a 61× improvement in prediction bias 〈Δ z 〉 on PLAsTiCC simulations and 5× improvement on real SDSS data compared to results from a widely used photometric redshift estimator, LCFIT+Z. The PDFs produced by this method are well constrained and will maximize the cosmological constraining power of photometric SNe Ia samples.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

COVID ‐19 outcomes in patients with cancer: Findings from the University of California health system database

Abstract Background The interaction between cancer diagnoses and COVID‐19 infection and outcomes is unclear. We leveraged a state‐wide, multi‐institutional database to assess cancer‐related risk factors for poor COVID‐19 outcomes. Methods We conducted a retrospective cohort study using the University of California Health COVID Research Dataset, which includes electronic health data of patients tested for severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) at 17 California medical centers. We identified adults tested for SARS‐CoV‐2 from 2/1/2020–12/31/2020 and selected a cohort of patients with cancer. We obtained demographic, clinical, cancer type, and antineoplastic therapy data. The primary outcome was hospitalization within 30d after the first positive SARS‐CoV‐2 test. Secondary outcomes were SARS‐CoV‐2 positivity and severe COVID‐19 (intensive care, mechanical ventilation, or death within 30d after the first positive test). We used multivariable logistic regression to identify cancer‐related factors associated with outcomes. Results We identified 409,462 patients undergoing SARS‐CoV‐2 testing. Of 49,918 patients with cancer, 1781 (3.6%) tested positive. Patients with cancer were less likely to test positive (RR 0.70, 95% CI: 0.67–0.74, p < 0.001). Among the 1781 SARS‐CoV‐2‐positive patients with cancer, BCR/ABL‐negative myeloproliferative neoplasms (RR 2.15, 95% CI: 1.25–3.41, p = 0.007), venetoclax (RR 2.96, 95% CI: 1.14–5.66, p = 0.028), and methotrexate (RR 2.72, 95% CI: 1.10–5.19, p = 0.032) were associated with greater hospitalization risk. Cancer and therapy types were not associated with severe COVID‐19. Conclusions In this large, diverse cohort, cancer was associated with a decreased risk of SARS‐CoV‐2 positivity. Patients with BCR/ABL‐negative myeloproliferative neoplasm or receiving methotrexate or venetoclax may be at increased risk of hospitalization following SARS‐CoV‐2 infection. Mechanistic and comparative studies are needed to validate findings.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Deep Multimodal Networks for M-type Star Classification with Paired Spectrum and Photometric Image

Abstract Traditional stellar classification methods include spectral and photometric classification separately. Although satisfactory results can be achieved, the accuracy could be improved. In this paper, we pioneer a novel approach to deeply fuse the spectra and photometric images of the sources in an advanced multimodal network to enhance the model’s discriminatory ability. We use Transformer as the fusion module and apply a spectrum–image contrastive loss function to enhance the consistency of the spectrum and photometric image of the same source in two different feature spaces. We perform M-type stellar subtype classification on two data sets with high and low signal-to-noise ratio (S/N) spectra and corresponding photometric images, and the F1-score achieves 95.65% and 90.84%, respectively. In our experiments, we prove that our model effectively utilizes the information from photometric images and is more accurate than advanced spectrum and photometric image classifiers. Our contributions can be summarized as follows: (1) We propose an innovative idea for stellar classification that allows the model to simultaneously consider information from spectra and photometric images. (2) We discover the challenge of fusing low-S/N spectra and photometric images in the Transformer and provide a solution. (3) The effectiveness of Transformer for spectral classification is discussed for the first time and will inspire more Transformer-based spectral classification models.

Astronomy & Astrophysics↗
NASA NTRS1982

Modelling of photodegradation in solar cell modules of substrate and superstrate design made with ethylene-vinyl acetate as pottant material

A computer model which simulates, in principle, the chemical changes in the photooxidation of hydrocarbons using as input data a set of elementary reactions, corresponding kinetic rate data and appropriate initial conditions was developed. The Model was refined and exploited to examine more closely the photooxidation and photostabilization of a hydrocarbon polymer. The results lead to the following observations. (1) The time to failure, tau sub f (chosen as the level of 5% C-H bond oxidation which is within the range anticipated for marked change in mechanical properties) varies as the inverse square root of the light intensity. However, tau sub f is almost unaffected by both the photoinitiator type and concentration. (2) The time to failure decreases with the rate of abstraction of C-H by peroxy radicals but increases with the rate of bimolecular radical termination controlled by diffusion. (3) Of the various stabilization mechanisms considered, the trapping of peroxy radicals is distinctly the most effective, although the concommitant decomposition of hydroperoxide is also desirable.

Somersall, A. C.↗
DOE OSTI2022

Retracted: Monitoring Hatchery Broodstock Composition and Genetic Variation of Spring/Summer Chinook Salmon in the Columbia River Basin with Multigeneration Pedigrees

Abstract Hatchery production of Chinook Salmon Oncorhynchus tshawytscha in the Columbia River basin comprises most of the anadromous salmonid production in this region. Hatchery facilities and programs serve to mitigate for impacts to salmonids due to the construction and operation of hydropower dams and habitat impacts from development in addition to the conservation and restoration of natural populations. A genetic method referred to as parentage-based tagging (PBT) enables highly reliable detection of hatchery-origin fish and inference of multigeneration pedigrees. This study compiles 11 years of PBT data from nearly 125,000 interior stream-type Chinook Salmon from 24 spawning hatcheries located in tributaries of the mid- and upper Columbia River as well as the Salmon, Clearwater, and Grande Ronde River subbasins. Multigenerational pedigrees allowed investigation of the proportion of natural- and hatchery-origin broodstock (pNOB and pHOB, respectively) for each hatchery and enumeration of the scale of production between segregated and integrated programs. We then compared how pHOB and the scale of production influenced the number of stray fish observed, genetic diversity, relatedness, and age-class compositions within broodstocks. Over 91.0% of hatchery broodstock could be assigned back to their parents, and there was an overall rate of less than 1.0% of broodstock that were unintentionally incorporated into nonnatal hatchery programs. We evaluated 14 segregated programs with 0.0–10.0% pNOB, 7 intermediate programs (10.1–50.0% pNOB), and 3 integrated programs (>50.0% pNOB). There was no correlation between the scale of production or pNOB with the level of genetic diversity, but as production size increased, so did the effective number of breeders. This study demonstrates the utility of PBT as a monitoring tool for hatchery broodstocks, and results suggest that segregated and integrated programs have tradeoffs that generally align with their intended broodstock management purpose of providing fish for harvest and/or fish for supplementation or reintroduction.

Horn, Rebekah L.↗
DOE OSTI2023

Multigeneration Pedigrees to Monitor Hatchery Broodstock Composition and Genetic Variation of Spring/Summer Chinook Salmon in the Columbia River Basin

Abstract Hatchery production of Chinook Salmon Oncorhynchus tshawytscha in the Columbia River basin comprises most of the anadromous salmonid production in this region. Hatchery facilities and programs serve to mitigate for impacts to salmonids due to the construction and operation of hydropower dams and habitat impacts from development in addition to the conservation and restoration of natural populations. A genetic method referred to as parentage-based tagging (PBT) enables highly reliable detection of hatchery-origin fish and inference of multigeneration pedigrees. This study compiles 11 years of PBT data from nearly 125,000 interior stream-type Chinook Salmon from 24 spawning hatcheries located on tributaries of the mid- and upper Columbia River and in the Salmon, Clearwater, and Grande Ronde River subbasins. Multigenerational pedigrees allowed for investigation of the proportions of natural- and hatchery-origin broodstock (pNOB and pHOB, respectively) for each hatchery and enumeration of the scale of production between segregated and integrated programs. We then compared how pHOB and the scale of production influenced the number of stray fish observed, genetic diversity, relatedness, and age-class compositions within broodstocks. Over 91.0% of hatchery broodstock could be assigned back to their parents, and overall less than 1.0% of broodstock consisted of fish that were unintentionally incorporated into nonnatal hatchery programs. We evaluated 11 segregated programs with 0.0–10.0% pNOB, 9 intermediate programs (10.1–50.0% pNOB), and 3 integrated programs (>50.0% pNOB). There was no correlation between the scale of production or pNOB with the level of genetic diversity, but as production size increased, so did the effective number of breeders. This study demonstrates the utility of PBT as a monitoring tool for hatchery broodstocks, and results suggest that segregated and integrated programs have tradeoffs that generally align with their intended broodstock management purpose of providing fish for harvest and/or fish for supplementation or reintroduction.

Horn, Rebekah L.↗
DOE OSTI2021

The effects of varying colour–luminosity relations on Type Ia supernova science

ABSTRACT The success of Type Ia supernova (SN Ia) distance standardization for cosmology relies on a single global linear relationship between their peak luminosity and colour, the β parameter. However, there are several pieces of evidence and physical reasons to believe that this relation is not universal and may change within different subgroups, or even among individual objects. In this work, we allow β to vary among subpopulations with different observed properties in the cosmological fits. Although the inferred cosmological parameters are consistent with previous studies that assume a single colour–luminosity relation, we find that the SN data favour non-universal distributions of β when split according to SN colour and/or host-galaxy mass. For galaxy mass, we obtain a β-step relation in which low β values occur in more massive galaxies, a trend that can be explained by differing dust reddening laws for two types of environments. For colour, we find that bluer/redder SNe Ia are consistent with a lower/larger β. This trend is explained with β being a combination of a low intrinsic colour–luminosity relation dominant in bluer SNe and a higher extrinsic reddening relation dominant at redder colours. The host-galaxy mass-step correction always provides better distance calibration, regardless of the multiple β approaches, and we suggest that it may come from a difference in intrinsic colour–luminosity properties of SNe Ia in two types of environments. Additionally, we find that blue SNe in low-mass environments are better standard candles than the others.

González-Gaitán, S. (ORCID:0000000195410317)↗
DOE OSTI2022

Hunting extreme BL Lacertae blazars with Fermi-Large Area Telescope

ABSTRACT The emission of very-high-energy (VHE) photons ($E\ \gt\ 100\ \mathrm{GeV}$) in blazars is closely connected to the production of ultra-relativistic particles and the role of these γ-ray sources as cosmic particle accelerators. This work focuses on a selection of 22 γ-ray objects from the 2BIGB catalogue of high-synchrotron-peaked sources, which are classified as blazar candidates of uncertain type in the 4FGL-DR2 catalogue. We study these sources by means of a re-analysis of the first 10 yr of γ-ray data taken with the Fermi-Large Area Telescope, including the attenuation by the extragalactic background light. Their broad-band spectral energy distributions are also evaluated, using multiwavelength archival data in the radio, optical, and X-ray bands, in terms of one-zone synchrotron-self-Compton models, adding an external Compton component when needed. Out of this analysis, we identify 17 new extreme high-synchrotron-peaked (EHSP) candidates and compare their physical parameters with those of prototypical EHSP blazars. Finally, the resulting models are used to assess their detectability by the present and future generation of ground-based Imaging Atmospheric Cherenkov Telescopes. We find two VHE candidates within the reach of the current and next generation of Cherenkov telescopes: J0847.0−2336 and J1714.0−2029.

Nievas Rosillo, M. (ORCID:0000000283219168)↗
DOE OSTI2024

Empirical Dynamic Modeling Reveals Complexity of Methane Fluxes in a Temperate Salt Marsh

Abstract Methane dynamics within salt marshes are complex because vegetation types, temperature, oscillating water levels, and changes in salinity and redox conditions influence CH 4 production, consumption, oxidation, and emissions. These non‐linear and complex interactions among variables affect the traditionally expected functional relationships and present challenges for interpreting and developing process‐based models. We employed empirical dynamic modeling (EDM) and convergent cross mapping (CCM) as a novel approach for characterizing seasonal/multiday and diurnal CH 4 dynamics by inferring causal variables, lags, and interconnections among multiple biophysical variables within a temperate salt marsh using 5 years of eddy covariance data. EDM/CCM is a nonparametric approach capable of quantifying the coupling between variables while determining time scales where variable interactions are the most relevant. We found that gross primary productivity, tidal creek dissolved oxygen, and temperature were important for seasonal/multiday dynamics (rho = 0.73–0.80), while water level was most important for diurnal dynamics during both the growing and dormancy phenoperiods (rho = 0.72 and 0.56, respectively). Lags for the top‐ranked variables (i.e., gross primary productivity, dissolved oxygen, temperature, water level) occurred between 1 and 5 weeks at the seasonal scale and 1–24 hr at the diurnal scale. The EDM had high prediction capabilities for intra‐/inter‐seasonal patterns and annual CH 4 sums but had limitations in representing large, infrequent fluxes. Results highlight the importance of non‐linearity, drivers, lag times, and interconnections among multiple biophysical variables that regulate CH 4 fluxes in tidal wetlands. This research introduces a novel approach to examining CH 4 fluxes, which will aid in evaluating current paradigms in wetlands and other ecosystems.

Environmental Sciences & Ecology↗
DOE OSTI2023

Primordial non-Gaussianity with angular correlation function: integral constraint and validation for DES

ABSTRACT Local primordial non-Gaussianity (PNG) is a promising observable of the underlying physics of inflation, characterized by $f_{\rm NL}^{\rm loc}$. We present the methodology to measure $f_{\rm NL}^{\rm loc}$ from the Dark Energy Survey (DES) data using the two-point angular correlation function (ACF) with scale-dependent bias. One of the focuses of the work is the integral constraint (IC). This condition appears when estimating the mean number density of galaxies from the data and is key in obtaining unbiased $f_{\rm NL}^{\rm loc}$ constraints. The methods are analysed for two types of simulations: ∼246 goliat-png N-body small area simulations with fNL equal to −100 and 100, and 1952 Gaussian ice-cola mocks with fNL = 0 that follow the DES angular and redshift distribution. We use the ensemble of goliat-png mocks to show the importance of the IC when measuring PNG, where we recover the fiducial values of fNL within the 1σ when including the IC. In contrast, we found a bias of ΔfNL ∼ 100 when not including it. For a DES-like scenario, we forecast a bias of ΔfNL ∼ 23, equivalent to 1.8σ, when not using the IC for a fiducial value of fNL = 100. We use the ice-cola mocks to validate our analysis in a realistic DES-like set-up finding it robust to different analysis choices: best-fitting estimator, the effect of IC, BAO damping, covariance, and scale choices. We forecast a measurement of fNL within σ(fNL) = 31 when using the DES-Y3 BAO sample, with the ACF in the 1 deg < θ < 20 deg range.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Dataset of ultralow temperature refrigeration for COVID 19 vaccine distribution solution

Abstract Most COVID-19 vaccines require temperature control for transportation and storage. Two types of vaccine have been developed by manufacturers (Pfizer and Moderna). Both vaccines are based on mRNA and lipid nanoparticles requiring low temperature storage. The Pfizer vaccine requires ultra-low temperature storage (−80 °C to −60 °C), while the Moderna vaccine requires −30 °C storage. However, the last stage of distribution is quite challenging, especially for rural or suburban areas, where local towns, pharmacy chains and hospitals may not have the infrastructure required to store the vaccine at the required temperature. In addition, there is limited data available to address ancillary challenges of the distribution framework for both transportation and storage stages, including safety concerns due to human exposure to large amounts of CO 2 from dry-ice sublimation, issues due to the pressure increase caused by dry-ice sublimation, and the potential issue caused by non-uniform cryogenic temperatures. As such, there is a need for test dataset to assist the development of a quick, effective, secure, and safe solution to mitigate the challenges faced by vaccine distribution logistics.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Cosmological constraints from H ii starburst galaxy, quasar angular size, and other measurements

ABSTRACT We compare the constraints from two (2019 and 2021) compilations of H ii starburst galaxy (H iiG) data and test the model independence of quasar (QSO) angular size data using six spatially flat and non-flat cosmological models. We find that the new 2021 compilation of H iiG data generally provides tighter constraints and prefers lower values of cosmological parameters than those from the 2019 H iiG data. QSO data by themselves give relatively model-independent constraints on the characteristic linear size, lm, of the QSOs within the sample. We also use Hubble parameter [H(z)], baryon acoustic oscillation (BAO), Pantheon Type Ia supernova (SN Ia) apparent magnitude (SN-Pantheon), and DES-3 yr binned SN Ia apparent magnitude (SN-DES) measurements to perform joint analyses with H iiG and QSO angular size data, since their constraints are not mutually inconsistent within the six cosmological models we study. A joint analysis of H(z), BAO, SN-Pantheon, SN-DES, QSO, and the newest compilation of H iiG data provides almost model-independent summary estimates of the Hubble constant, $H_0=69.7\pm 1.2\ \rm {km\,s^{-1}\,Mpc^{-1}}$, the non-relativistic matter density parameter, $\Omega _{\rm m_0}=0.293\pm 0.021$, and lm = 10.93 ± 0.25 pc.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Imprint of tree species mycorrhizal association on microbial‐mediated enzyme activity and stoichiometry

Abstract Understanding the effects of tree species and their mycorrhizal association on soil processes is critical for predicting the ecosystem consequences of species shifts owing to global change and forest management decisions. While it is well established that forests dominated by different mycorrhizal types can vary in how they cycle carbon (C), nitrogen (N) and phosphorus (P), the degree to which these patterns are driven by microbial‐mediated enzyme activity (EA) and ecoenzymatic stoichiometry (ES) remains elusive. Here, we synthesized the effects of mycorrhizal association on seven soil enzymes involved in microbial C, N and P acquisition and ES using data from 56 peer‐reviewed papers. We found that relative to soil in ectomycorrhizal (EcM) trees, soil in arbuscular mycorrhizal (AM) trees exhibited greater activity of some C acquisition enzymes (e.g. beta‐glucosidase; BG) and higher ecoenzymatic ratios of BG/NAG (N‐acetyl‐glucosaminidase) and BG/AP (acid phosphatase). These results supported that AM trees had rapid C and nutrient turnover rates, inorganic nutrient economics and high soil microbial C limitation. We also found evidence for an organic nutrient economy and greater soil microbial demand for nutrients in EcM trees compared to AM trees. In addition, the effect of mycorrhizal association on the activity of certain soil enzymes and enzymatic stoichiometry (i.e. BG and BG/NAG ratio) appeared to be associated with the differences in soil pH, phylogenetic group (i.e. conifers and broadleaves) and leaf habit (i.e. evergreen and deciduous) between AM and EcM trees. The results from the global meta‐analysis suggested that soil EA and ES appear to play critical roles in shaping the differences in the nutrient economy between AM and EcM tree species, but leaf morphology and soil conditions should be considered in evaluations of soil processes in forests of different mycorrhizal associations. Given that most of the studies in the database were from the temperate and subtropical regions, further research in other biomes is needed to elucidate the underlying mechanisms driving the mycorrhizal effect at the global scale. Read the free Plain Language Summary for this article on the Journal blog.

54 ENVIRONMENTAL SCIENCES↗