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      Modeling Global Soil Carbon and Soil Microbial Carbon by Integrating Microbial Processes into the Ecosystem Process Model TRIPLEX-GHG : GLOBAL SOIL CARBON AND MICROBIAL CARBON

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          An Overview of CMIP5 and the Experiment Design

          The fifth phase of the Coupled Model Intercomparison Project (CMIP5) will produce a state-of-the- art multimodel dataset designed to advance our knowledge of climate variability and climate change. Researchers worldwide are analyzing the model output and will produce results likely to underlie the forthcoming Fifth Assessment Report by the Intergovernmental Panel on Climate Change. Unprecedented in scale and attracting interest from all major climate modeling groups, CMIP5 includes “long term” simulations of twentieth-century climate and projections for the twenty-first century and beyond. Conventional atmosphere–ocean global climate models and Earth system models of intermediate complexity are for the first time being joined by more recently developed Earth system models under an experiment design that allows both types of models to be compared to observations on an equal footing. Besides the longterm experiments, CMIP5 calls for an entirely new suite of “near term” simulations focusing on recent decades and the future to year 2035. These “decadal predictions” are initialized based on observations and will be used to explore the predictability of climate and to assess the forecast system's predictive skill. The CMIP5 experiment design also allows for participation of stand-alone atmospheric models and includes a variety of idealized experiments that will improve understanding of the range of model responses found in the more complex and realistic simulations. An exceptionally comprehensive set of model output is being collected and made freely available to researchers through an integrated but distributed data archive. For researchers unfamiliar with climate models, the limitations of the models and experiment design are described.
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            Summarizing multiple aspects of model performance in a single diagram

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              The Microbial Efficiency-Matrix Stabilization (MEMS) framework integrates plant litter decomposition with soil organic matter stabilization: do labile plant inputs form stable soil organic matter?

              The decomposition and transformation of above- and below-ground plant detritus (litter) is the main process by which soil organic matter (SOM) is formed. Yet, research on litter decay and SOM formation has been largely uncoupled, failing to provide an effective nexus between these two fundamental processes for carbon (C) and nitrogen (N) cycling and storage. We present the current understanding of the importance of microbial substrate use efficiency and C and N allocation in controlling the proportion of plant-derived C and N that is incorporated into SOM, and of soil matrix interactions in controlling SOM stabilization. We synthesize this understanding into the Microbial Efficiency-Matrix Stabilization (MEMS) framework. This framework leads to the hypothesis that labile plant constituents are the dominant source of microbial products, relative to input rates, because they are utilized more efficiently by microbes. These microbial products of decomposition would thus become the main precursors of stable SOM by promoting aggregation and through strong chemical bonding to the mineral soil matrix. © 2012 Blackwell Publishing Ltd.
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                Author and article information

                Journal
                Journal of Advances in Modeling Earth Systems
                J. Adv. Model. Earth Syst.
                Wiley
                19422466
                October 2017
                October 2017
                October 27 2017
                : 9
                : 6
                : 2368-2384
                Affiliations
                [1 ]Center for Ecological Forecasting and Global Change, College of Forestry; Northwest A&F University; Yangling Shaanxi China
                [2 ]Department of Biology Sciences, Institute of Environment Sciences; University of Quebec at Montreal; Centre-Ville, Montreal QC Canada
                [3 ]Oak Ridge National Laboratory; Environmental Sciences Division & Climate Change Science Institute; Oak Ridge TN USA
                Article
                10.1002/2017MS000920
                31f1f592-e493-431f-af22-61f220ae7cd2
                © 2017

                http://doi.wiley.com/10.1002/tdm_license_1.1

                http://creativecommons.org/licenses/by-nc-nd/4.0/

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