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Review of the Third Conference of the Imaging Mass Spectrometry Society (IMSS 3): Accounts of a Hybrid Virtual and In-Person Meeting and the State and Future of the Field
The third annual conference of the Imaging Mass Spectrometry Society (IMSS3) was held October 3–6, 2021 in a hybrid format that included virtual and in-person attendance (Colorado Springs, CO). In this work, we highlight many of the methods and applications presented, the state of the field, and some insights into the emerging areas in the field of imaging mass spectrometry. We also reflect upon the processes behind planning a hybrid conference and discuss the successes and challenges of the event in retrospect.
Accounting for Changes in Radiation Improves the Ability of SIF to Track Water Stress-Induced Losses in Summer GPP in a Temperate Deciduous Forest
Global observations of solar-induced chlorophyll fluorescence (SIF) are available from multiple satellite platforms, and SIF is increasingly used as a proxy for photosynthetic activity and ecosystem productivity. Because the relationship between SIF and gross primary productivity (GPP) depends on a variety of factors including ecosystem type and environmental conditions, it is necessary to study SIF observations across various spatiotemporal scales and ecosystems. To explore how SIF signals relate to productivity over a temperate deciduous forest, we deployed a PhotoSpec spectrometer system at the University of Michigan Biological Station AmeriFlux site (US-UMB) in the northern Lower Peninsula of Michigan during the 2018 and 2019 growing seasons. We found that SIF correlated with GPP across diurnal and seasonal cycles (R 2 = 0.61 and 0.64 for 90-min- and daily-averaged data), but that SIF signals were more strongly related to downwelling radiation than GPP (R 2 = 0.91 for daily-averaged data). The dependence of SIF on radiation obscured the impact of intraseasonal drought in the SIF timeseries, but drought stress was apparent as a decrease in relative SIF, which exhibited a stronger correlation with GPP (R 2 = 0.56) than other remotely sensed data over the drought period. These results highlight the potential of SIF for detecting stress-induced losses in forest productivity. Additionally, we found that the red:far-red SIF ratio did not exhibit a response to water stress-induced losses in productivity, but was largely driven by seasonal and interannual changes in canopy structure, as well as by synoptic changes in downwelling radiation.
The Importance of Accounting for Landscape Position When Investigating Grasslands: A Multidisciplinary Characterisation of a California Coastal Grassland
Abstract Grasslands are one of the most common land‐cover types, providing important ecosystem services globally, yet few studies have examined grassland critical‐zone functioning throughout hillslopes. This study characterised a coastal grassland over a small hillslope at Point Reyes National Seashore, California, using multidisciplinary techniques, combining remotely‐sensed, geophysical, plant, and soil measurements. Clustering techniques delineated the study area into four landscape zones, up‐, mid‐, and down‐slope, and a bordering riparian ecotone, which had distinct environmental properties that varied spatially across the site, with depth, and time. Soil moisture increased with depth and down slope towards a bordering riparian zone, and co‐varied with soil CO 2 flux rates both spatially and temporally. This highlighted three distinct controls of soil moisture on soil respiration: CO 2 fluxes were inhibited by high moisture content in the down‐slope during the wet winter months, and converged across landscape positions in the dry summer months, while also displaying post‐rain pulses. The normalised difference vegetation index (NDVI) ranged from 0.32 (September)–0.80 (April) and correlated positively with soil moisture and aboveground biomass, moving down slope. Yet, NDVI, aboveground biomass, and soil moisture were not correlated to soil organic carbon (SOC) content (0.4%–4.5%), which was highest in the mid‐slope. The SOC content may instead be linked to shifts in dominant grassland species and their rhizosphere properties with landscape position. This multidisciplinary characterisation highlighted significant heterogeneity in grassland properties with landscape position, and demonstrated an approach that could be used to characterise other critical‐zone environments on hillslopes.
Alpine permafrost could account for a quarter of thawed carbon based on Plio-Pleistocene paleoclimate analogue
Estimates of the permafrost-climate feedback vary in magnitude and sign, partly because permafrost carbon stability in warmer-than-present conditions is not well constrained. Here we use a Plio-Pleistocene lacustrine reconstruction of mean annual air temperature (MAAT) from the Tibetan Plateau, the largest alpine permafrost region on the Earth, to constrain past and future changes in permafrost carbon storage. Clumped isotope-temperatures (Δ 47 -T) indicate warmer MAAT (~1.2 °C) prior to 2.7 Ma, and support a permafrost-free environment on the northern Tibetan Plateau in a warmer-than-present climate. Δ 47 -T indicate ~8.1 °C cooling from 2.7 Ma, coincident with Northern Hemisphere glacial intensification. Combined with climate models and global permafrost distribution, these results indicate, under conditions similar to mid-Pliocene Warm period (3.3–3.0 Ma), ~60% of alpine permafrost containing ~85 petagrams of carbon may be vulnerable to thawing compared to ~20% of circumarctic permafrost. This estimate highlights ~25% of permafrost carbon and the permafrost-climate feedback could originate in alpine areas.
Accounting for access and inequality
Access to modern energy sources is essential for sustainable development and human well-being. A recent study uses a bottom-up model to show how the existing inequalities in energy access persists until 2050 under different socioeconomic and policy scenarios.
The long road to ignition: An eyewitness account
This paper reviews the many twists and turns in the long journey that culminated in ignition in late 2022 using the laser heated indirect-drive approach to imploding DT filled targets at the National Ignition Facility (NIF), located at the Lawrence Livermore National Laboratory (LLNL). We describe the early origins of the Laser Program at LLNL and key developments such as the paradigm shifting birth of high energy density physics (HEDP) studies with lasers, changes in choice of laser wavelength, and the development of key diagnostics and computer codes. Fulfilling the requirements of the multi-faceted Nova Technical Contract was a necessary condition for the approval of the NIF, but more importantly, the end of the Cold War and the cessation of nuclear testing were key catalysts in that approval, along with the ready-and-waiting field of HEDP. The inherent flexibility of the field of laser driven inertial confinement fusion played a fundamental role in achieving success at the NIF. We describe how the ultimately successful ignition target design evolved from the original “point design” target, through the lessons of experiment. All key aspects of that original design changed: The capsule's materials and size were changed; the hohlraum's materials, size, laser entrance hole size, and gas fills were also all changed, as were the laser pulse shapes that go along with all those changes. The philosophy to globally optimize performance for stability (by raising the adiabat and thus lowering the implosion convergence) was also key, as was progress in target fabrication, and in increasing NIF's energy output. The persistence of the research staff and the steadfast backing of our supporters were also necessary elements in this success. We gratefully acknowledge seven decades of researcher endeavors and four decades of the dedicated efforts of many hundreds of personnel across the globe who have participated in NIF construction, operation, target fabrication, diagnostic, and theoretical advances that have culminated in ignition.
National population mapping from sparse survey data: A hierarchical Bayesian modeling framework to account for uncertainty
Population estimates are critical for government services, development projects, and public health campaigns. Such data are typically obtained through a national population and housing census. However, population estimates can quickly become inaccurate in localized areas, particularly where migration or displacement has occurred. Some conflict-affected and resource-poor countries have not conducted a census in over 10 y. We developed a hierarchical Bayesian model to estimate population numbers in small areas based on enumeration data from sample areas and nationwide information about administrative boundaries, building locations, settlement types, and other factors related to population density. We demonstrated this model by estimating population sizes in every 10- m grid cell in Nigeria with national coverage. These gridded population estimates and areal population totals derived from them are accompanied by estimates of uncertainty based on Bayesian posterior probabilities. The model had an overall error rate of 67 people per hectare (mean of absolute residuals) or 43% (using scaled residuals) for predictions in out-of-sample survey areas (approximately 3 ha each), with increased precision expected for aggregated population totals in larger areas. This statistical approach represents a significant step toward estimating populations at high resolution with national coverage in the absence of a complete and recent census, while also providing reliable estimates of uncertainty to support informed decision making.
Overlooked branch turnover creates a widespread bias in forest carbon accounting
Most measurements and models of forest carbon cycling neglect the carbon flux associated with the turnover of branch biomass, a physiological process quantified for other organs (fine roots, leaves, and stems). Synthesizing data from boreal, temperate, and tropical forests (184,815 trees), we found that including branch turnover increased empirical estimates of aboveground wood production by 16% (equivalent to 1.9 Pg Cy −1 globally), of similar magnitude to the observed global forest carbon sinks. In addition, reallocating carbon to branch turnover in model simulations reduced stem wood biomass, a long-lasting carbon storage, by 7 to 17%. This prevailing neglect of branch turnover suggests widespread biases in carbon flux estimates across global datasets and model simulations. Branch litterfall, sometimes used as a proxy for branch turnover, ignores carbon lost from attached dead branches, underestimating branch C turnover by 38% in a pine forest. Modifications to field measurement protocols and existing models are needed to allow a more realistic partitioning of wood production and forest carbon storage.
Review of Candidate Techniques for Material Accountancy Measurements in Electrochemical Separations Facilities
Not provided.
Exploratory vs solution-seeking big data: Discussion for “Experiences with big data: Accounts from a data scientist’s perspective”
Abstract not provided.
Genomic prediction of regional-scale performance in switchgrass ( Panicum virgatum ) by accounting for genotype-by-environment variation and yield surrogate traits
Switchgrass is a potential crop for bioenergy or carbon capture schemes, but further yield improvements through selective breeding are needed to encourage commercialization. To identify promising switchgrass germplasm for future breeding efforts, we conducted multisite and multitrait genomic prediction with a diversity panel of 630 genotypes from 4 switchgrass subpopulations (Gulf, Midwest, Coastal, and Texas), which were measured for spaced plant biomass yield across 10 sites. Our study focused on the use of genomic prediction to share information among traits and environments. Specifically, we evaluated the predictive ability of cross-validation (CV) schemes using only genetic data and the training set (cross-validation 1: CV1), a subset of the sites (cross-validation 2: CV2), and/or with 2 yield surrogates (flowering time and fall plant height). We found that genotype-by-environment interactions were largely due to the north–south distribution of sites. The genetic correlations between the yield surrogates and the biomass yield were generally positive (mean height r = 0.85; mean flowering time r = 0.45) and did not vary due to subpopulation or growing region (North, Middle, or South). Genomic prediction models had CV predictive abilities of –0.02 for individuals using only genetic data (CV1), but 0.55, 0.69, 0.76, 0.81, and 0.84 for individuals with biomass performance data from 1, 2, 3, 4, and 5 sites included in the training data (CV2), respectively. To simulate a resource-limited breeding program, we determined the predictive ability of models provided with the following: 1 site observation of flowering time (0.39); 1 site observation of flowering time and fall height (0.51); 1 site observation of fall height (0.52); 1 site observation of biomass (0.55); and 5 site observations of biomass yield (0.84). The ability to share information at a regional scale is very encouraging, but further research is required to accurately translate spaced plant biomass to commercial-scale sward biomass performance.
Windowing artefacts likely account for recent claimed detection of oscillating cosmic scale factor
ABSTRACT Using the Pantheon data set of Type Ia supernovae, a recent publication (R20 in this work) reports a 2σ detection of oscillations in the expansion history of the Universe. The study conducted by R20 is wholly worthwhile. However, we demonstrate that there is a $\gt 10{{\ \rm per\ cent}}$ chance of statistical fluctuations in the Pantheon data producing a false oscillatory signal larger than the oscillatory signal that R20 report. Their results are a less than 2σ detection. Applying the R20 methodology to simulated Pantheon data, we determine that these oscillations could arise due to analysis artefacts. The uneven spacing of Type Ia supernovae in redshift space and the complicated analysis method of R20 impose a structured throughput function. When analysed with the R20 prescription, about $11{{\ \rm per\ cent}}$ of artificial ΛCDM data sets produce a stronger oscillatory signal than the actual Pantheon data. Our results underscore the importance of understanding the false ‘signals’ that can be introduced by complicated data analyses.
Exaggerated Plurivory of Macrophomina phaseolina : Accounting for the Large Host Range Claim and the Shifting of Scientific Language
Macrophomina phaseolina is a plant pathogenic fungus that is frequently described as having a broad host range encompassing more than 500 species. We noticed that citations provided in support of this statement do not actually demonstrate such a broad host range. To elucidate the true documented host range of this fungus, we initiated a literature meta-analysis of 894 publications on M. phaseolina since 1913. We discovered that the first host range summaries did not require Koch's postulates or other experimental demonstrations of pathogenicity. Most of the available early host claims were based on tenuous associations between the fungus and symptoms, sometimes without reporting isolation or morphological examination in vitro. These statements apparently led to a pattern of increasingly exaggerated host range claims, without support from a primary reference, until the claim that M. phaseolina has 500 hosts became common in the early 2000s. At present, the scientific community typically requires Koch's postulates to characterize pathogenicity on a new host. Among all the available literature, we only found primary experimental evidence for M. phaseolina’s pathogenicity on 97 hosts; 74 hosts confirmed by Koch's postulates and 23 hosts with all steps from Koch's postulates completed except for recovery of the pathogen from symptomatic tissues. This study demonstrates how scientific concepts can change over time and necessitate changes to historic axioms. We propose that the hyperbole surrounding the host range of M. phaseolina has obscured an accurate depiction of its biology.
Real-time estimators for scattering observables: A full account of finite-volume errors for quantum simulation
The real-time correlators of quantum field theories can be directly probed through new approaches to simulation, such as quantum computing and tensor networks. This provides a new framework for computing scattering observables in lattice formulations of strongly interacting theories, such as lattice quantum chromodynamics. In this paper, we prove that the proposal of real-time estimators of scattering observables is universally applicable to all scattering observables of gapped quantum field theories. All finite-volume errors are exponentially suppressed, and the rate of this suppression is controlled by the regulator considered, namely, a displacement of the spectrum of the theory into the complex plane. A partial restoration of Lorentz symmetry by averaging over different boosts gives an additional suppression of finite volume errors. Our results also apply to the simulation of wave packet scattering, where a similar averaging is performed to construct the wave packets that regulate the finite volume effects. This result represents a necessary key step toward determining a broad class of scattering observables via quantum computing that are currently inaccessible via classical computing. Such observables are relevant for various applications, including hadron spectroscopy, hadron structure, and precision tests of the Standard Model. We also comment on potential applications of our results to traditional computational schemes.
Accounting for nonvanishing net-charge with unified balance functions
Not Available
Design of Thermophotovoltaic Cells for Optimal System Efficiency, Accounting for Photon Reuse from Front and Back Contacts
We develop a model showing how reflection from both the front and back contacts of thermophotovoltaic (TPV) cells affects the system efficiency. From this foundation we determine the design rules for front grids for TPV cells, and assess the consequences of those rules on cell design and system performance. We show that these design rules are different and more complex than the corresponding design rules for solar photovoltaic (PV) cells, and can lead to substantially different grid design and system performance than if the simpler solar PV design rules were used.
Improved Snow Loss Modeling Accounting for the Orientation of Modules
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