92 research outputs found

    Principal component analysis and singular spectrum analysis of ULF geomagnetic data associated with earthquakes

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    International audienceIn order to extract any ULF signature associated with earthquakes, the principal component analysis (PCA) and singular spectral analysis (SSA) have been performed to investigate the possibility of discrimination of signals from different sources (geomagnetic variation, artificial noise, and the other sources (earthquake-related ULF emissions)). We adopt PCA to the time series data observed at closely separated stations, Seikoshi (SKS), Mochikoshi (MCK), and Kamo (KAM). In order to remove the most intense signal like the first principal component, we make the differential data sets of filtered 0.01Hz SKS-KAM and MCK-KAM in NS component and 0.01 Hz band. The major findings are as follows. (1) It is important to apply principal component analysis and singular spectral analysis simultaneously. SSA gives the structure of signals and the number of sensors for PCA is estimated. This makes the results convincing. (2) There is a significant advantage using PCA with differential data sets of filtered (0.01 Hz band) SKS-KAM and MCK-KAM in NS component for removing the most intense signal like global variation (solar-terrestrial interaction). This provides that the anomalous changes in the second principal component appeared more sharply. And the contribution of the second principal component is 20?40%. It is large enough to prove mathematical accuracy of the signal. Further application is required to accumulate events. These facts demonstrate the possibility of monitoring the crustal activity by using the PCA and SSA

    Microbial diversity drives carbon use efficiency in a model soil

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    © The Author(s), 2020. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Domeignoz-Horta, L. A., Pold, G., Liu, X. A., Frey, S. D., Melillo, J. M., & DeAngelis, K. M. Microbial diversity drives carbon use efficiency in a model soil. Nature Communications, 11(1), (2020): 3684, doi:10.1038/s41467-020-17502-z.Empirical evidence for the response of soil carbon cycling to the combined effects of warming, drought and diversity loss is scarce. Microbial carbon use efficiency (CUE) plays a central role in regulating the flow of carbon through soil, yet how biotic and abiotic factors interact to drive it remains unclear. Here, we combine distinct community inocula (a biotic factor) with different temperature and moisture conditions (abiotic factors) to manipulate microbial diversity and community structure within a model soil. While community composition and diversity are the strongest predictors of CUE, abiotic factors modulated the relationship between diversity and CUE, with CUE being positively correlated with bacterial diversity only under high moisture. Altogether these results indicate that the diversity × ecosystem-function relationship can be impaired under non-favorable conditions in soils, and that to understand changes in soil C cycling we need to account for the multiple facets of global changes.Funding for this project was provided by the Department of Energy grant DE-SC0016590 to K.M.D. and S.D.F., and an American Association of University Women Dissertation fellowship to G.P. We would also like to thank Stuart Grandy and Kevin Geyer for the fruitful discussions and Mary Waters, Courtney Bly and Ana Horta for their help with samples processing

    Soil respiration in a northeastern US temperate forest: a 22‐year synthesis

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    To better understand how forest management, phenology, vegetation type, and actual and simulated climatic change affect seasonal and inter‐annual variations in soil respiration (Rs), we analyzed more than 100,000 individual measurements of soil respiration from 23 studies conducted over 22 years at the Harvard Forest in Petersham, Massachusetts, USA. We also used 24 site‐years of eddy‐covariance measurements from two Harvard Forest sites to examine the relationship between soil and ecosystem respiration (Re). Rs was highly variable at all spatial (respiration collar to forest stand) and temporal (minutes to years) scales of measurement. The response of Rs to experimental manipulations mimicking aspects of global change or aimed at partitioning Rs into component fluxes ranged from −70% to +52%. The response appears to arise from variations in substrate availability induced by changes in the size of soil C pools and of belowground C fluxes or in environmental conditions. In some cases (e.g., logging, warming), the effect of experimental manipulations on Rs was transient, but in other cases the time series were not long enough to rule out long‐term changes in respiration rates. Inter‐annual variations in weather and phenology induced variation among annual Rs estimates of a magnitude similar to that of other drivers of global change (i.e., invasive insects, forest management practices, N deposition). At both eddy‐covariance sites, aboveground respiration dominated Re early in the growing season, whereas belowground respiration dominated later. Unusual aboveground respiration patterns—high apparent rates of respiration during winter and very low rates in mid‐to‐late summer—at the Environmental Measurement Site suggest either bias in Rs and Re estimates caused by differences in the spatial scale of processes influencing fluxes, or that additional research on the hard‐to‐measure fluxes (e.g., wintertime Rs, unaccounted losses of CO2 from eddy covariance sites), daytime and nighttime canopy respiration and its impacts on estimates of Re, and independent measurements of flux partitioning (e.g., aboveground plant respiration, isotopic partitioning) may yield insight into the unusually high and low fluxes. Overall, however, this data‐rich analysis identifies important seasonal and experimental variations in Rs and Re and in the partitioning of Re above‐ vs. belowground

    Long-term pattern and magnitude of soil carbon feedback to the climate system in a warming world

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    Author Posting. © The Author(s), 2017. This is the author's version of the work. It is posted here for personal use, not for redistribution. The definitive version was published in Science 358 (2017): 101-105, doi:10.1126/science.aan2874.In a 26-year soil warming experiment in a mid-latitude hardwood forest, we documented changes in soil carbon cycling to investigate the potential consequences for the climate system. We found that soil warming results in a four-phase pattern of soil organic matter decay and carbon dioxide fluxes to the atmosphere, with phases of substantial soil carbon loss alternating with phases of no detectable loss. Several factors combine to affect the timing, magnitude, and thermal acclimation of soil carbon loss. These include depletion of microbially accessible carbon pools, reductions in microbial biomass, a shift in microbial carbon use efficiency, and changes in microbial community composition. Our results support projections of a long-term, self-reinforcing carbon feedback from mid-latitude forests to the climate system as the world warms.This research has been supported by grants from the Department of Energy - DE-SC0010740; DOE DE-SC0016590: and the National Science Foundation - DEB 1237491 (LTER) ; DEB 1456528 (LTREB)

    Soil respiration in a northeastern US temperate forest: a 22‐year synthesis

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    To better understand how forest management, phenology, vegetation type, and actual and simulated climatic change affect seasonal and inter‐annual variations in soil respiration (Rs), we analyzed more than 100,000 individual measurements of soil respiration from 23 studies conducted over 22 years at the Harvard Forest in Petersham, Massachusetts, USA. We also used 24 site‐years of eddy‐covariance measurements from two Harvard Forest sites to examine the relationship between soil and ecosystem respiration (Re). Rs was highly variable at all spatial (respiration collar to forest stand) and temporal (minutes to years) scales of measurement. The response of Rs to experimental manipulations mimicking aspects of global change or aimed at partitioning Rs into component fluxes ranged from −70% to +52%. The response appears to arise from variations in substrate availability induced by changes in the size of soil C pools and of belowground C fluxes or in environmental conditions. In some cases (e.g., logging, warming), the effect of experimental manipulations on Rs was transient, but in other cases the time series were not long enough to rule out long‐term changes in respiration rates. Inter‐annual variations in weather and phenology induced variation among annual Rs estimates of a magnitude similar to that of other drivers of global change (i.e., invasive insects, forest management practices, N deposition). At both eddy‐covariance sites, aboveground respiration dominated Re early in the growing season, whereas belowground respiration dominated later. Unusual aboveground respiration patterns—high apparent rates of respiration during winter and very low rates in mid‐to‐late summer—at the Environmental Measurement Site suggest either bias in Rs and Re estimates caused by differences in the spatial scale of processes influencing fluxes, or that additional research on the hard‐to‐measure fluxes (e.g., wintertime Rs, unaccounted losses of CO2 from eddy covariance sites), daytime and nighttime canopy respiration and its impacts on estimates of Re, and independent measurements of flux partitioning (e.g., aboveground plant respiration, isotopic partitioning) may yield insight into the unusually high and low fluxes. Overall, however, this data‐rich analysis identifies important seasonal and experimental variations in Rs and Re and in the partitioning of Re above‐ vs. belowground

    Reduced carbon use efficiency and increased microbial turnover with soil warming

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    Global soil carbon (C) stocks are expected to decline with warming, and changes in microbial processes are key to this projection. However, warming responses of critical microbial parameters such as carbon use efficiency (CUE) and biomass turnover (rB) are not well understood. Here, we determine these parameters using a probabilistic inversion approach that integrates a microbial-enzyme model with 22 years of carbon cycling measurements at Harvard Forest. We find that increasing temperature reduces CUE but increases rB, and that two decades of soil warming increases the temperature sensitivities of CUE and rB. These temperature sensitivities, which are derived from decades-long field observations, contrast with values obtained from short-term laboratory experiments. We also show that long-term soil C flux and pool changes in response to warming are more dependent on the temperature sensitivity of CUE than that of rB. Using the inversion-derived parameters, we project that chronic soil warming at Harvard Forest over six decades will result in soil C gain of \u3c1.0% on average (1st and 3rd quartiles: 3.0% loss and 10.5% gain) in the surface mineral horizon. Our results demonstrate that estimates of temperature sensitivity of microbial CUE and rB can be obtained and evaluated rigorously by integrating multidecadal datasets. This approach can potentially be applied in broader spatiotemporal scales to improve long-term projections of soil C feedbacks to climate warming

    Decreased mass specific respiration under experimental warming is robust to the microbial biomass method employed

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    Author Posting. © The Author(s), 2009. This is the author's version of the work. It is posted here by permission of Blackwell for personal use, not for redistribution. The definitive version was published in Ecology Letters 12 (2009): E15-E18, doi:10.1111/j.1461-0248.2009.01332.x.Hartley et al. question whether reduction in Rmass, under experimental warming, arises because of the biomass method. We show the method they treat as independent yields the same result. We describe why the substrate-depletion hypothesis cannot alone explain observed responses, and urge caution in the interpretation of the seasonal data.This research was supported by the Office of Science (BER), U.S. Department of Energy, the Andrew W. Mellon Foundation and U.S. National Science Foundation grants to the Coweeta LTER program
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