Faster turnover of new soil carbon inputs under increased atmospheric CO2

This is the author accepted manuscript. The final version is available from Wiley via the DOI in this record.Rising levels of atmospheric CO2 frequently stimulate plant inputs to soil, but the consequences of these changes for soil carbon (C) dynamics are poorly understood. Plant-derived inputs can accumulate in the soil and become part of the soil C pool ("new soil C"), or accelerate losses of pre-existing ("old") soil C. The dynamics of the new and old pools will likely differ and alter the long-term fate of soil C, but these separate pools, which can be distinguished through isotopic labeling, have not been considered in past syntheses. Using meta-analysis, we found that while elevated CO2 (ranging from 550 to 800 parts per million by volume) stimulates the accumulation of new soil C in the short term (<1 year), these effects do not persist in the longer term (1-4 years). Elevated CO2 does not affect the decomposition or the size of the old soil C pool over either temporal scale. Our results are inconsistent with predictions of conventional soil C models and suggest that elevated CO2 might increase turnover rates of new soil C. Because increased turnover rates of new soil C limit the potential for additional soil C sequestration, the capacity of land ecosystems to slow the rise in atmospheric CO2 concentrations may be smaller than previously assumed.This work was supported by the U.S. Department of Energy (DOE), Office of Science, Biological and Environmental Research Program, under Award Number DE-SC-0010632. R.P.P. was supported by the U.S. Department of Agriculture NRI CSREES Program and by DOEs Terrestrial Ecosystem Science Program in the Climate and Environmental Sciences Division

New soil carbon sequestration with nitrogen enrichment: a meta-analysis

This is the author accepted manuscript. The final version is available from Springer via the DOI in this recordBackground and aims: Through agriculture and industry, humans are increasing the deposition and availability of nitrogen (N) in ecosystems worldwide. Carbon (C) isotope tracers provide useful insights into soil C dynamics, as they allow to study soil C pools of different ages. We evaluated to what extent N enrichment affects soil C dynamics in experiments that applied C isotope tracers. Methods: Using meta-analysis, we synthesized data from 35 published papers. We made a distinction between “new C” and “old C” stocks, i.e., soil C derived from plant C input since the start of the isotopic enrichment, or unlabeled, pre-existing soil C. Results: Averaged across studies, N addition increased new soil C stocks (+30.3%), total soil C stocks (+6.1%) and soil C input proxies (+30.7%). Although N addition had no overall, average, effect on old soil C stocks and old soil C respiration, old soil C stocks increased with the amount of N added and respiration of old soil C declined. Nitrogen-induced effects on new soil C and soil C input both decreased with the amount of extraneous N added in control treatments. Conclusion: Although our findings require additional confirmation from long-term field experiments, our analysis provides isotopic evidence that N addition stimulates soil C storage both by increasing soil C input and (at high N rates) by decreasing decomposition of old soil C. Furthermore, we demonstrate that the widely reported saturating response of plant growth to N enrichment also applies to new soil C storage.National Key Research and Development Program of ChinaChina Scholarship Council (CSC)US Department of Energy, Terrestrial Ecosystem SciencesLawrence Livermore National Laboratory (LLNL

Three Dimensional Electrical Impedance Tomography

The electrical resistivity of mammalian tissues varies widely and is correlated with physiological function. Electrical impedance tomography (EIT) can be used to probe such variations in vivo, and offers a non-invasive means of imaging the internal conductivity distribution of the human body. But the computational complexity of EIT has severe practical limitations, and previous work has been restricted to considering image reconstruction as an essentially two-dimensional problem. This simplification can limit significantly the imaging capabilities of EIT, as the electric currents used to determine the conductivity variations will not in general be confined to a two-dimensional plane. A few studies have attempted three-dimensional EIT image reconstruction, but have not yet succeeded in generating images of a quality suitable for clinical applications. Here we report the development of a three-dimensional EIT system with greatly improved imaging capabilities, which combines our 64-electrode data-collection apparatus with customized matrix inversion techniques. Our results demonstrate the practical potential of EIT for clinical applications, such as lung or brain imaging and diagnostic screening

Comparison of normalisation methods for surface-enhanced laser desorption and ionisation (SELDI) time-of-flight (TOF) mass spectrometry data

<p>Abstract</p> <p>Background</p> <p>Mass spectrometry for biological data analysis is an active field of research, providing an efficient way of high-throughput proteome screening. A popular variant of mass spectrometry is SELDI, which is often used to measure sample populations with the goal of developing (clinical) classifiers. Unfortunately, not only is the data resulting from such measurements quite noisy, variance between replicate measurements of the same sample can be high as well. Normalisation of spectra can greatly reduce the effect of this technical variance and further improve the quality and interpretability of the data. However, it is unclear which normalisation method yields the most informative result.</p> <p>Results</p> <p>In this paper, we describe the first systematic comparison of a wide range of normalisation methods, using two objectives that should be met by a good method. These objectives are minimisation of inter-spectra variance and maximisation of signal with respect to class separation. The former is assessed using an estimation of the coefficient of variation, the latter using the classification performance of three types of classifiers on real-world datasets representing two-class diagnostic problems. To obtain a maximally robust evaluation of a normalisation method, both objectives are evaluated over multiple datasets and multiple configurations of baseline correction and peak detection methods. Results are assessed for statistical significance and visualised to reveal the performance of each normalisation method, in particular with respect to using no normalisation. The normalisation methods described have been implemented in the freely available MASDA R-package.</p> <p>Conclusion</p> <p>In the general case, normalisation of mass spectra is beneficial to the quality of data. The majority of methods we compared performed significantly better than the case in which no normalisation was used. We have shown that normalisation methods that scale spectra by a factor based on the dispersion (e.g., standard deviation) of the data clearly outperform those where a factor based on the central location (e.g., mean) is used. Additional improvements in performance are obtained when these factors are estimated locally, using a sliding window within spectra, instead of globally, over full spectra. The underperforming category of methods using a globally estimated factor based on the central location of the data includes the method used by the majority of SELDI users.</p

Interactive Effects of Time, CO\u3csub\u3e2\u3c/sub\u3e, N, and Diversity on Total Belowground Carbon Allocation and Ecosystem Carbon Storage in a Grassland Community

Predicting if ecosystems will mitigate or exacerbate rising CO2 requires understanding how elevated CO2 will interact with coincident changes in diversity and nitrogen (N) availability to affect ecosystem carbon (C) storage. Yet achieving such understanding has been hampered by the difficulty of quantifying belowground C pools and fluxes. Thus, we used mass balance calculations to quantify the effects of diversity, CO2, and N on both the total amount of C allocated belowground by plants (total belowground C allocation, TBCA) and ecosystem C storage in a periodically burned, 8-year Minnesota grassland biodiversity, CO2, and N experiment (BioCON). Annual TBCA increased in response to elevated CO2, enriched N, and increasing diversity. TBCA was positively related to standing root biomass. After removing the influence of root biomass, the effect of elevated CO2 remained positive, suggesting additional drivers of TBCA apart from those that maintain high root biomass. Removing root biomass effects resulted in the effects of N and diversity becoming neutral or negative (depending on year), suggesting that the positive effects of diversity and N on TBCA were related to treatmentdriven differences in root biomass. Greater litter production in high diversity, elevated CO2, and enhanced N treatments increased annual ecosystem C loss in fire years and C gain in non-fire years, resulting in overall neutral C storage rates. Our results suggest that frequently burned grasslands are unlikely to exhibit enhanced C sequestration with increasing atmospheric CO2 levels or N deposition

The Formation and Evolution of the First Massive Black Holes

The first massive astrophysical black holes likely formed at high redshifts (z>10) at the centers of low mass (~10^6 Msun) dark matter concentrations. These black holes grow by mergers and gas accretion, evolve into the population of bright quasars observed at lower redshifts, and eventually leave the supermassive black hole remnants that are ubiquitous at the centers of galaxies in the nearby universe. The astrophysical processes responsible for the formation of the earliest seed black holes are poorly understood. The purpose of this review is threefold: (1) to describe theoretical expectations for the formation and growth of the earliest black holes within the general paradigm of hierarchical cold dark matter cosmologies, (2) to summarize several relevant recent observations that have implications for the formation of the earliest black holes, and (3) to look into the future and assess the power of forthcoming observations to probe the physics of the first active galactic nuclei.Comment: 39 pages, review for "Supermassive Black Holes in the Distant Universe", Ed. A. J. Barger, Kluwer Academic Publisher

Three new chondrosarcoma cell lines: one grade III conventional central chondrosarcoma and two dedifferentiated chondrosarcomas of bone

BackgroundChondrosarcoma is the second most common primary sarcoma of bone. High-grade conventional chondrosarcoma and dedifferentiated chondrosarcoma have a poor outcome. In pre-clinical research aiming at the identification of novel treatment targets, the need for representative cell lines and model systems is high, but availability is scarce.MethodsWe developed and characterized three cell lines, derived from conventional grade III chondrosarcoma (L835), and dedifferentiated chondrosarcoma (L2975 and L3252) of bone. Proliferation and migration were studied and we used COBRA-FISH and array-CGH for karyotyping and genotyping. Immunohistochemistry for p16 and p53 was performed as well as TP53 and IDH mutation analysis. Cells were injected into nude mice to establish their tumorigenic potential.ResultsWe show that the three cell lines have distinct migrative properties, L2975 had the highest migration rate and showed tumorigenic potential in mice. All cell lines showed chromosomal rearrangements with complex karyotypes and genotypic aberrations were conserved throughout late passaging of the cell lines. All cell lines showed loss of CDKN2A, while TP53 was wild type for exons 5–8. L835 has an IDH1 R132C mutation, L2975 an IDH2 R172W mutation and L3252 is IDH wild type.ConclusionsBased on the stable culturing properties of these cell lines and their genotypic profile resembling the original tumors, these cell lines should provide useful functional models to further characterize chondrosarcoma and to evaluate new treatment strategies