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The paleoclimate during the Early Eocene in Maritime Antarctica is characterized by cool conditions without a pronounced dry season. Soils formed on volcanic material under such climate conditions in modern analogue environments are usually Andosols rich in nanocrystalline minerals without pedogenic smectite. The paleosols formed on volcanic material on King Georges Island are covered by basalts, dated by 6 new 40Ar/39Ar datings to 51-48 Ma, and are rich in smectite. A pedogenic origin of the smectites would suggest a semi-arid rather than a wet non-seasonal humid paleoclimate. To investigate the origin of the smectites in these paleosols we used X-ray diffraction and microscopic techniques. Minor mineralogical changes between the volcanic parent material and the paleosols and a homogenous distribution of smectites throughout the paleosol horizons indicate that these smectites were mainly inherited from the pyroclastic parent material, which was altered prior to surficial weathering. Nevertheless, the mineralogical properties, such as degree of crystallinity and octahedral site occupancy, of these smectites were modified during the ancient soil formation. Our findings highlight that trioctahedral smectites were a product of deuteric alteration of pyroclastic rocks and were progressively transformed to dioctahedral smectites during weathering in a soil environment on King George Island.
James Ross Island (JRI) offers the exceptional opportunity to study microbial-driven pedogenesis without the influence of vascular plants or faunal activities (e.g., penguin rookeries). In this study, two soil profiles from JRI (one at Santa Martha Cove - SMC, and another at Brandy Bay BB) were investigated, in order to gain information about the initial state of soil formation and its interplay with prokaryotic activity, by combining pedological, geochemical and microbiological methods. The soil profiles are similar with respect to topographic position and parent material but are spatially separated by an orographic barrier and therefore represent windward and leeward locations towards the mainly southwesterly winds. These different positions result in differences in electric conductivity of the soils caused by additional input of bases by sea spray at the windward site and opposing trends in the depth functions of soil pH and electric conductivity. Both soils are classified as Cryosols, dominated by bacterial taxa such as Actinobacteria, Proteobacteria, Acidobacteria, Gemmatimonadetes and Chloroflexi. A shift in the dominant taxa was observed below 20 cm in both soils as well as an increased abundance of multiple operational taxonomic units (OTUs) related to potential chemolithoautotrophic Acidiferrobacteraceae. This shift is coupled by a change in microstructure. While single/pellicular grain microstructure (SMC) and platy microstructure (BB) are dominant above 20 cm, lenticular microstructure is dominant below 20 cm in both soils. The change in microstructure is caused by frequent freeze-thaw cycles and a relative high water content, and it goes along with a development of the pore spacing and is accompanied by a change in nutrient content. Multivariate statistics revealed the influence of soil parameters such as chloride, sulfate, calcium and organic carbon contents, grain size distribution and pedogenic oxide ratios on the overall microbial community structure and explained 49.9% of its variation. The correlation of the pedogenic oxide ratios with the compositional distribution of microorganisms as well as the relative abundance certain microorganisms such as potentially chemolithotrophic Acidiferrobacteraceae-related OTUs could hint at an interplay between soil-forming processes and microorganisms.
Background: Population-specificity of exploratory dietary patterns limits their generalizability in investigations with type 2 diabetes incidence.
Objective: The aim of this study was to derive country-specific exploratory dietary patterns, investigate their association with type 2 diabetes incidence, and replicate diabetes-associated dietary patterns in other countries.
Methods: Dietary intake data were used, assessed by country-specific questionnaires at baseline of 11,183 incident diabetes cases and 14,694 subcohort members (mean age 52.9 y) from 8 countries, nested within the European Prospective Investigation into Cancer and Nutrition study (mean follow-up time 6.9 y). Exploratory dietary patterns were derived by principal component analysis. HRs for incident type 2 diabetes were calculated by Prentice-weighted Cox proportional hazard regression models. Diabetes-associated dietary patterns were simplified or replicated to be applicable in other countries. A meta-analysis across all countries evaluated the generalizability of the diabetes-association.
Results: Two dietary patterns per country/UK-center, of which overall 3 dietary patterns were diabetes-associated, were identified. A risk-lowering French dietary pattern was not confirmed across other countries: pooled HRFrance per 1 SD: 1.00; 95% CI: 0.90, 1.10. Risk-increasing dietary patterns, derived in Spain and UK-Norfolk, were confirmed, but only the latter statistically significantly: HRSpain: 1.09; 95% CI: 0.97, 1.22 and HRUK-Norfolk: 1.12; 95% CI: 1.04, 1.20. Respectively, this dietary pattern was characterized by relatively high intakes of potatoes, processed meat, vegetable oils, sugar, cake and cookies, and tea. Conclusions: Only few country/center-specific dietary patterns (3 of 18) were statistically significantly associated with diabetes incidence in this multicountry European study population. One pattern, whose association with diabetes was confirmed across other countries, showed overlaps in the food groups potatoes and processed meat with identified diabetes-associated dietary patterns from other studies. The study demonstrates that replication of associations of exploratory patterns with health outcomes is feasible and a necessary step to overcome population-specificity in associations from such analyses.
Soil bacteria play a fundamental role in pedogenesis. However, knowledge about both the impact of climate and slope aspects on microbial communities and the consequences of these items in pedogenesis is lacking. Therefore, soil-bacterial communities from four sites and two different aspects along the climate gradient of the Chilean Coastal Cordillera were investigated. Using a combination of microbiological and physicochemical methods, soils that developed in arid, semi-arid, mediterranean, and humid climates were analyzed. Proteobacteria, Acidobacteria, Chloroflexi, Verrucomicrobia, and Planctomycetes were found to increase in abundance from arid to humid climates, while Actinobacteria and Gemmatimonadetes decreased along the transect. Bacterial-community structure varied with climate and aspect and was influenced by pH, bulk density, plant-available phosphorus, clay, and total organic-matter content. Higher bacterial specialization was found in arid and humid climates and on the south-facing slope and was likely promoted by stable microclimatic conditions. The presence of specialists was associated with ecosystem-functional traits, which shifted from pioneers that accumulated organic matter in arid climates to organic decomposers in humid climates. These findings provide new perspectives on how climate and slope aspects influence the composition and functional capabilities of bacteria, with most of these capabilities being involved in pedogenetic processes.
Probabilistic seismic-hazard analysis (PSHA) is the current tool of the trade used to estimate the future seismic demands at a site of interest. A modern PSHA represents a complex framework that combines different models with numerous inputs. It is important to understand and assess the impact of these inputs on the model output in a quantitative way. Sensitivity analysis is a valuable tool for quantifying changes of a model output as inputs are perturbed, identifying critical input parameters, and obtaining insight about the model behavior. Differential sensitivity analysis relies on calculating first-order partial derivatives of the model output with respect to its inputs; however, obtaining the derivatives of complex models can be challenging.
In this study, we show how differential sensitivity analysis of a complex framework such as PSHA can be carried out using algorithmic/automatic differentiation (AD). AD has already been successfully applied for sensitivity analyses in various domains such as oceanography and aerodynamics. First, we demonstrate the feasibility of the AD methodology by comparing AD-derived sensitivities with analytically derived sensitivities for a basic case of PSHA using a simple ground-motion prediction equation. Second, we derive sensitivities via AD for a more complex PSHA study using a stochastic simulation approach for the prediction of ground motions. The presented approach is general enough to accommodate more advanced PSHA studies of greater complexity.