Beyond bulk: Density fractions explain heterogeneity in global soil carbon abundance and persistence.

Understanding the controls on the amount and persistence of soil organic carbon (C) is essential for predicting its sensitivity to global change. The response may depend on whether C is unprotected, isolated within aggregates, or protected from decomposition by mineral associations. Here, we present a global synthesis of the relative influence of environmental factors on soil organic C partitioning among pools, abundance in each pool (mg C g-1  soil), and persistence (as approximated by radiocarbon abundance) in relatively unprotected particulate and protected mineral-bound pools. We show that C within particulate and mineral-associated pools consistently differed from one another in degree of persistence and relationship to environmental factors. Soil depth was the best predictor of C abundance and persistence, though it accounted for more variance in persistence. Persistence of all C pools decreased with increasing mean annual temperature (MAT) throughout the soil profile, whereas persistence increased with increasing wetness index (MAP/PET) in subsurface soils (30-176 cm). The relationship of C abundance (mg C g-1  soil) to climate varied among pools and with depth. Mineral-associated C in surface soils (<30 cm) increased more strongly with increasing wetness index than the free particulate C, but both pools showed attenuated responses to the wetness index at depth. Overall, these relationships suggest a strong influence of climate on soil C properties, and a potential loss of soil C from protected pools in areas with decreasing wetness. Relative persistence and abundance of C pools varied significantly among land cover types and soil parent material lithologies. This variability in each pool's relationship to environmental factors suggests that not all soil organic C is equally vulnerable to global change. Therefore, projections of future soil organic C based on patterns and responses of bulk soil organic C may be misleading.

Model cortical association fields account for the time course and dependence on target complexity of human contour perception.

Can lateral connectivity in the primary visual cortex account for the time dependence and intrinsic task difficulty of human contour detection? To answer this question, we created a synthetic image set that prevents sole reliance on either low-level visual features or high-level context for the detection of target objects. Rendered images consist of smoothly varying, globally aligned contour fragments (amoebas) distributed among groups of randomly rotated fragments (clutter). The time course and accuracy of amoeba detection by humans was measured using a two-alternative forced choice protocol with self-reported confidence and variable image presentation time (20-200 ms), followed by an image mask optimized so as to interrupt visual processing. Measured psychometric functions were well fit by sigmoidal functions with exponential time constants of 30-91 ms, depending on amoeba complexity. Key aspects of the psychophysical experiments were accounted for by a computational network model, in which simulated responses across retinotopic arrays of orientation-selective elements were modulated by cortical association fields, represented as multiplicative kernels computed from the differences in pairwise edge statistics between target and distractor images. Comparing the experimental and the computational results suggests that each iteration of the lateral interactions takes at least [Formula: see text] ms of cortical processing time. Our results provide evidence that cortical association fields between orientation selective elements in early visual areas can account for important temporal and task-dependent aspects of the psychometric curves characterizing human contour perception, with the remaining discrepancies postulated to arise from the influence of higher cortical areas.

Soil minerals affect taxon-specific bacterial growth.

Secondary minerals (clays and metal oxides) are important components of the soil matrix. Clay minerals affect soil carbon persistence and cycling, and they also select for distinct microbial communities. Here we show that soil mineral assemblages-particularly short-range order minerals-affect both bacterial community composition and taxon-specific growth. Three soils with different parent material and presence of short-range order minerals were collected from ecosystems with similar vegetation and climate. These three soils were provided with 18O-labeled water and incubated with or without artificial root exudates or pine needle litter. Quantitative stable isotope probing was used to determine taxon-specific growth. We found that the growth of bacteria varied among soils of different mineral assemblages but found the trend of growth suppression in the presence of short-range order minerals. Relative growth of bacteria declined with increasing concentration of short-range order minerals between 25-36% of taxa present in all soils. Carbon addition in the form of plant litter or root exudates weakly affected relative growth of taxa (p = 0.09) compared to the soil type (p < 0.01). However, both exudate and litter carbon stimulated growth for at least 34% of families in the soils with the most and least short-range order minerals. In the intermediate short-range order soil, fresh carbon reduced growth for more bacterial families than were stimulated. These results highlight how bacterial-mineral-substrate interactions are critical to soil organic carbon processing, and how growth variation in bacterial taxa in these interactions may contribute to soil carbon persistence and loss.

Surface tension of quantum fluids from molecular simulations.

We present the first molecular simulations of the vapor-liquid surface tension of quantum liquids. The path integral formalism of Feynman was used to account for the quantum mechanical behavior of both the liquid and the vapor. A replica-data parallel algorithm was implemented to achieve good parallel performance of the simulation code on at least 32 processors. We have computed the surface tension and the vapor-liquid phase diagram of pure hydrogen over the temperature range 18-30 K and pure deuterium from 19 to 34 K. The simulation results for surface tension and vapor-liquid orthobaric densities are in very good agreement with experimental data. We have computed the interfacial properties of hydrogen-deuterium mixtures over the entire concentration range at 20.4 and 24 K. The calculated equilibrium compositions of the mixtures are in excellent agreement with experimental data. The computed mixture surface tension shows negative deviations from ideal solution behavior, in agreement with experimental data and predictions from Prigogine's theory. The magnitude of the deviations at 20.4 K are substantially larger from simulations and from theory than from experiments. We conclude that the experimentally measured mixture surface tension values are systematically too high. Analysis of the concentration profiles in the interfacial region shows that the nonideal behavior can be described entirely by segregation of H(2) to the interface, indicating that H(2) acts as a surfactant in H(2)-D(2) mixtures.