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The weathering of shale exerts an important control on the hydrochemical fluxes to river systems, thus influencing the global carbon, nutrient, and geochemical cycles. However, the quantitative understanding of shale weathering and its impact on global biogeochemical cycles remains inadequate due to the complex interplay between hydrological, biogeochemical, and physical processes. In this study, we develop a novel modeling approach to quantitatively interpret the long-term chemical weathering of shale occurring since the last glaciation period (15,000 years) leading to the present geochemical conditions. The model explicitly considers processes occurring across multiple phases and involved in the weathering, including: (i) the infiltration of meteoric water, (ii) the interactions between the water and the mineral assemblage via dissolution/precipitation reactions, (iii) the microbially-mediated oxidation of organic matter, (iv) the evolution of porosity induced by mineral reactions, and (v) the exchange of gases between the subsurface and the atmosphere. To implement and test our model, we conduct this study at a well-instrumented hillslope underlain by Mancos Shale and located at the East River study site, Western Colorado. Consistent with field observations, the model successfully reproduces the stratified weathering front, the complex spatial distribution of organic carbon, and the gaseous emissions of carbon dioxide from the subsurface. Model simulations show that aerobic respiration exerts a fundamental control on the weathering of shale. While previous studies have highlighted the diffusion of oxygen from the atmosphere as the primary mechanism for shale weathering, our model simulations demonstrate that aerobic respiration limits the propagation of oxygen in the shallow subsurface, and thereby inhibits the dissolution of pyrite at depth. Aerobic respiration is particularly favored in the top soil horizon due to the constant flux of oxygen from the atmosphere, the replenishment of fresh litter/plant-derived organic matter, and to a lesser extent the presence of fossil shale-associated organic matter. The acidic pore water generated through aerobic respiration within the shallow subsurface is transported to greater depths, where it sustains the dissolution of carbonate (dolomite in this example). Overall, our results demonstrate that the evolution of pyrite and carbonate depletion fronts are significantly different, and primarily depend on the ability of microorganisms to carry out microbial respiration and the various transport pathways of reactants controlling the mineral reactions under partially saturated conditions., This work was supported by the Watershed Function Science Focus Area project at Lawrence Berkeley National Laboratory funded by the U.S. Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231. Constructive comments of four anonymous reviewers improved the quality of the manuscript.

Serpentine minerals exert important controls on the physical properties of ultramafic rocks and have the potential to influence deformation phenomena in fault zones and to control the release of water in subducted slabs. Sheet serpentine generally, and lizardite and amesite specifically, can adopt alternative crystallographic stacking arrangements called polytypes. Polytypism has been extensively studied in fully ordered crystals, but it remains largely enigmatic in the more common semi-disordered crystals that in long-range analyses such as X-ray diffraction only exhibit random combinations of 0b and ±1/3b interlayer shifts. To date, atomic-resolution imaging to identify locally ordered polytypes has been precluded by the beam-sensitive nature of this hydrous magnesium silicate mineral. Here, we employed low-dose high-angle annular dark-field scanning transmission electron microscopy (HAADF-STEM) to study the polytypic structure of semi-disordered lizardite and amesite. Because the electron dose was as low as ~6000 e–/Å2, it was possible to directly resolve oxygen atomic columns and all the cations with a resolution of ~1 Å and reveal the short-range order. For lizardite, we identified long-period non-standard polytypes, including examples with 3, 4, 8, and 9 layers stemming from the ordering of the octahedral tilt along the a-axis. For amesite, we found short-range ordered polytypes with periodicities of up to 42 Å stemming from the ordering of interlayer shifts along the b-axis. The resolution was sufficient to determine the relative abundance of 6R2, 6R1, 2H1, and 2H2 polytypes in amesite to be 46.1, 29.6, 7.7, and 1.9%, respectively. This is contrary to the expectation that the most common form of amesite is the 2H2 polytype, which may be more likely to form macroscopic crystals suitable for conventional X-ray diffraction-based studies. We conclude that HAADF-STEM methods open the way for the characterization of beam-sensitive minerals and to resolve the structural details of less well-ordered (but possibly more abundant) minerals at a unit-cell scale.

Natural sulfidation of silver nanomaterials can passivate the surface, while preserving desirable optical and electrical properties, which is beneficial for limiting Ag+ release and cytotoxicity.

O sistema imune inato reconhece estruturas químicas dos vírus, ativando células capazes de bloquear a infecção viral, e ativa, também, o sistema imune adaptativo a desenvolver anticorpos que destroem ou imobilizam os vírus. De forma análoga, os componentes químicos de produtos naturais derivados de plantas e de leveduras podem agir como ativadores do sistema imune, ativando a defesa contra infecção viral. Neste trabalho, examinou-se diversos produtos naturais de alimentos e plantas medicinais, cujos componentes químicos, possivelmente, poderiam contribuir para a defesa contra SARS-CoV-2, o vírus que causa a COVID-19.

O presente volume contém monografias completas de 11 plantas medicinais amplamente empregadas no país, sendo apenas duas exóticas. Nenhuma dessas espécies possui monografia farmacopeica nas seis edições já publicadas da Farmacopeia Brasileira; portanto, é significativa a contribuição desta obra para o desenvolvimento de fitoterápicos, importantes para a Atenção Primária à Saúde, principalmente quando se considera que 82% da população brasileira utiliza produtos à base de plantas medicinais.

Pressure solution, a mechanism that involves tight coupling between the geometry and thermal-hydro-mechanical-chemical (THMC) processes, plays an important role in diagenesis. In this study, we make the first attempt to conduct microscale THMC modeling to understand and quantify the impacts of geometry and temperature on pressure solution, taking natural salt rock as an example. This modeling capability is achieved by expanding a novel MC code that we developed previously (Hu et al. J Geophys Res: Solid Earth 126:e2021JB023112, 2021) to include temperature effects. We first conduct a simulation of an example that involves a single brine inclusion within a single halite grain and find that the temperature impact is limited for that case. We then extract geometry from an image of a natural salt rock and conduct simulations with different cases: (A) only temperature and no stress, (B) only stress and no temperature, and (C) with both stress and temperature. These different cases result in quite different phenomena. In case A, dissolution and precipitation occur across the entire system due to isolated pore space reaching a localized mass balance between dissolution, precipitation, and diffusion. In case B, intense geometric features (e.g., major asperities, inclusions) in one area undergo stress concentration, thus dominating pressure solution in that area. In case C, pressure solution is spread out at contacting highly stressed geometric features close to the hotter side. We conclude that geometric features dominate stress distribution, thus dominating pressure solution in a natural salt rock that may be affected by the temperature if a sufficient temperature gradient is applied.

Beta diversity—the variation among community compositions in a region—is a fundamental indicator of biodiversity. Despite a diverse set of measures to quantify beta diversity, most measures have posited that beta diversity is maximized when each community has one distinct species. However, this postulate has ignored the importance of non-additivity of ecological systems (i.e., a community with two species is ecologically different from two communities with one species). Here, to account for this, we provide a geometric approach to measure beta diversity as the hypervolume of the geometric embedding of a metacommunity. We show that the hypervolume measure is closely linked to and naturally extends previous information- and variation-based measures. In addition, our hypervolume approach provides a unified geometric framework for widely adopted extensions on the basic measure of beta diversity: the contribution of duplications in presence/absence data, temporal changes, turnover-nestedness decomposition, species similarity and functional complementarity, and community/species-specific contributions. We apply our new geometric measures to empirical data and address two long-standing questions on beta diversity (latitudinal pattern and sampling efforts) and present novel ecological insights. In sum, our geometric approach reconceptualizes beta diversity, synthesizes previous measures and is immediately applicable to existing data.

Identifying determinants of global infectious disease burden is a central goal of disease ecology. While it is widely accepted that host diversity structures parasite diversity and prevalence across large spatial scales, the influence of vector diversity on disease risk has rarely been examined despite the role of vectors as obligatory intermediate hosts for many parasites. Malaria, for instance, can be transmitted by over 70 species of mosquitoes, but the impact of this diversity on malaria risk remains unclear. Further, such relationships are likely dependent on the context in which disease transmission occurs, as arthropod life history and behavior are highly sensitive to environmental factors such as temperature. We studied the relationship between vector diversity, malaria prevalence, and environmental attributes using a unique dataset we curated by integrating several open-access sources. Globally, the association between vector species richness and malaria prevalence differed by latitude, indicating that this relationship is strongly dependent on underlying environmental conditions. Structural equation models further revealed different processes by which the environment impacts vector community assemblage and function, and subsequently disease prevalence, in different regions. In Africa, the environment exerted a top-down influence on disease through its role in shaping vector communities, whereas in Southeast Asia, disease prevalence is influenced by more complex interactions between the physical and socioeconomic environment (i.e., rainfall and GDP) and vector diversity across sites. This work highlights the key role of vector diversity in structuring disease distribution at large spatial scales and offers crucial insights to vector management and disease control.Significance statementThe global health threat from persistent and emerging vector-borne diseases continues to increase and is exacerbated by rapid environmental and societal change. Predicting how disease burden will shift in response to these changes necessitates a clear understanding of existing determinants of disease risk. We focused on an underappreciated potential source of variation in disease burden – vector diversity – and its role in structuring global malaria distribution. Our work revealed that vector diversity influences malaria prevalence and that the strength and nature of this association strongly depend on local environmental context. Extending disease transmission theory, surveillance, and control to embrace heterogeneity in vector community structure and function across space and time is an asset in the fight against vector-borne diseases.

Global changes can lead to species declines and extinctions through their impacts on species habitats at two distinct spatial scales: habitat destruction, in which individual habitat patches are destroyed by land-use change or natural disasters, and habitat degradation, in which larger scale changes, such as nitrogen deposition or climate change, lower mean population abundances across landscapes. We developed a theory showing that, even when these two forms of global change have an identical impact on a species' total amount of habitat, they have qualitatively different consequences for species dynamics and extinction. Using metapopulation theory and simulations, we found distinct impacts of these global changes characterized through several responses: the rate at which populations are lost from the remaining patches, extinction thresholds, and the duration of extinction debts. Habitat degradation causes a faster decline in species populations when habitat reduction is low, making it particularly detrimental for rare species. Habitat destruction has smaller impacts for low habitat reduction, but shows clear thresholds beyond which it surpasses degradation's negative impact; the location and steepness of the threshold depends on species dispersal, with poor dispersers having steeper thresholds. These results highlight the challenge of using population monitoring to assess the consequences of global changes and predict consequences of further change: extinction trajectories cannot be predicted due to thresholds (habitat destruction) and lagged dynamics that lead to extinction debts (habitat degradation). Our research clarifies why the impacts of one type of global change may poorly predict the impacts of the other and suggests general rules for predicting the long-term impacts of global changes based on species traits.

Sulfur (S) is an essential macronutrient and important component of the earth’s crust, and its cycling has critical impacts on trace metal mobility, water quality, and human health. Pyrite weathering is the primary pathway by which sulfur enters surface waters. However, biogeochemical cycling of sulfur in soils and the river corridor mediates sulfate exports. In this study, we identified the major forms of sulfur across multiple compartments and scales in a pristine mountainous watershed, including shale bedrock weathering profiles, hillslope soils, and alluvial floodplain sediments, in order to provide insight into biogeochemical sulfur cycling in a hydrologically variable alpine system. X-ray absorption near-edge spectroscopy (XANES) analysis of shale weathering profiles showed clear evidence of pyrite oxidation to sulfate, with large accumulations of intermediate S(0) (20%–53%). Micro-scale XANES showed evidence of reprecipitation of pyrite at fracture surfaces within the permanently saturated zone. Organic sulfur dominated S speciation in shallow hillslope soil and floodplain sediment, with little evidence of reduced inorganic S. However, mackinawite formation, representing active sulfate reduction, was observed in saturated oxbow sediments and saturated weathered shale underlying floodplain sediments. Further evidence of sulfate reduction from aqueous sulfur isotopic analysis was observed in shallow groundwater transects across an Fe-reducing meander, whereas increases in pore water sulfate concentrations implied sulfur oxidation at other locations. The data present an integrated picture of sulfur cycling in a shale-dominated watershed, where riverine sulfate exports are mediated by biological cycling, particularly in redox-stratified and temporally dynamic hyporheic zone sediments.

Knowledge of the exchange of carbon isotopes between dissolved inorganic carbon and calcite minerals is of long-standing importance for the interpretation of sedimentary paleoclimate records and 14...

The efficient computation of dynamic (time-dependent) molecular properties is a broad field with numerous applications in aiding molecular synthesis and design, with a particular preva- lence in spectroscopic predictions. Typical methods for computing the response of a molecu- lar system to an electromagnetic field (EMF) considers a quantum mechanical description of the molecule and a classical approximation for the EMF. Methods for describing light-matter interactions with high-accuracy electronic structure methods, such as coupled cluster (CC), are discussed, with a focus on improving the efficiency of such methods. The CC method suffers from high-degree polynomial scaling. In addition to the ground-state calculation, computing dynamic properties requires the description of sensitive excited-state effects. The cost of such methods often prohibits the accurate calculation of response prop- erties for systems of significant importance, such as large-molecule drug candidates or chiral species present in biological systems. While the literature is ripe with reduced-scaling meth- ods for CC ground-state calculations, considerably fewer approaches have been applied to excited-state properties, with even fewer still providing adequate results for realistic systems. This work presents three studies on the reduction of the cost of molecular property evalu- ations, in the hopes of closing this gap in the literature and widening the scope of current theoretical methods. There are two main ways of simulating time-dependent light-matter interactions: one may consider these effects in the frequency domain, where the response of the system to an EMF is computed directly; or, the response may be considered explicitly in the time domain, where wave function (or density) parameters can be propagated in time and examined in detail. Each methodology has unique advantages and computational bottlenecks. The first two studies focus on frequency-domain calculations, and employ fragmentation and machine- learning techniques to reduce the cost of single-molecule calculations or sets of calculations across a series of geometric conformations. The third study presents a novel application of the local correlation technique to real-time CC calculations, and highlights deficiencies and possible solutions to the approach. Doctor of Philosophy Theoretical chemistry plays a key role in connecting experimental results with physical inter- pretation. Paramount to the success of theoretical methods is the ability to predict molecular properties without the need for costly high-throughput synthesis, aiding in the determina- tion of molecular structure and the design of new materials. Light-matter interactions, which govern spectroscopic techniques, are particularly complicated, and sensitive to the theoreti- cal tools employed in their prediction. Compounding the issue of accuracy is one of efficiency — accurate theoretical methods typically incur steep scaling of computational cost (memory and processor time) with respect to the size of the system. An important aspect in improving the efficiency of these methods is understanding the nature of light-matter interactions at a quantum level. Many unanswered questions still remain, such as, "Can light-matter interactions be thought of as a sum of interactions be- tween smaller fragments of the system?" and "Can conventional methods of accelerating ground-state calculations be expected to perform well for spectroscopic properties?" The present work seeks to answer these questions through three studies, focusing on improving the efficiency of these techniques, while simultaneously addressing their fundamental flaws and providing reasonable alternatives.

Allee effects are common to diverse taxa but their consequences for coexistence are poorly understood. Recent studies suggest they cause priority effects through ‘inverse’, or positive, density dependence when a population is at low density, but mathematical theory suggests more outcomes are possible. We develop a simple and generalizable competition model that incorporates an Allee effect, with the Allee effect characterized by its low-density strength and dissipation rate. By incorporating Allee effects into modern coexistence theory, we show how Allee effects alter both fitness differences and stabilizing differences. We then determine when Allee effects promote or limit diversity, and when modern coexistence theory fails to predict coexistence outcomes. Our model offers an intuitive extension of modern coexistence theory while identifying one of its limits for predicting diversity, and promises to guide empirical research on how Allee effects structure ecological diversity.

Calcium carbonate (CaCO 3 ) biomineralizing organisms have played major roles in the history of life and the global carbon cycle during the past 541 Ma. Both marine diversification and mass extinctions reflect physiological responses to environmental changes through time. An integrated understanding of carbonate biomineralization is necessary to illuminate this evolutionary record and to understand how modern organisms will respond to 21st century global change. Biomineralization evolved independently but convergently across phyla, suggesting a unity of mechanism that transcends biological differences. In this review, we combine CaCO 3 skeleton formation mechanisms with constraints from evolutionary history, omics, and a meta-analysis of isotopic data to develop a plausible model for CaCO 3 biomineralization applicable to all phyla. The model provides a framework for understanding the environmental sensitivity of marine calcifiers, past mass extinctions, and resilience in 21st century acidifying oceans. Thus, it frames questions about the past, present, and future of CaCO 3 biomineralizing organisms.

Using atomic-resolution electron microscopy to observe ion-exchange processes in atomically thin layered and restacked clays, substantially larger ion diffusion constants and moire effects on ion dynamics are seen.