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      Microbial carbon use efficiency promotes global soil carbon storage

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      1 , 2 , 3 , 4 , 5 , 6 , 7 , 8 , 9 , 2 , 2 , 10 , 11 , 12 , 13 , 14 , 15 , 2 , 16 , 17 , 7 , 6 , 18 , 19 , 3 , 13 , 3 , 3 , 3 , 20 , 3 , 3 , 3 , 3 , 1 , 1 , 3 , 1 , , 12 ,
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      Nature Publishing Group UK
      Carbon cycle, Carbon cycle

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          Abstract

          Soils store more carbon than other terrestrial ecosystems 1, 2 . How soil organic carbon (SOC) forms and persists remains uncertain 1, 3 , which makes it challenging to understand how it will respond to climatic change 3, 4 . It has been suggested that soil microorganisms play an important role in SOC formation, preservation and loss 57 . Although microorganisms affect the accumulation and loss of soil organic matter through many pathways 4, 6, 811 , microbial carbon use efficiency (CUE) is an integrative metric that can capture the balance of these processes 12, 13 . Although CUE has the potential to act as a predictor of variation in SOC storage, the role of CUE in SOC persistence remains unresolved 7, 14, 15 . Here we examine the relationship between CUE and the preservation of SOC, and interactions with climate, vegetation and edaphic properties, using a combination of global-scale datasets, a microbial-process explicit model, data assimilation, deep learning and meta-analysis. We find that CUE is at least four times as important as other evaluated factors, such as carbon input, decomposition or vertical transport, in determining SOC storage and its spatial variation across the globe. In addition, CUE shows a positive correlation with SOC content. Our findings point to microbial CUE as a major determinant of global SOC storage. Understanding the microbial processes underlying CUE and their environmental dependence may help the prediction of SOC feedback to a changing climate.

          Abstract

          A deep learning and data-driven modelling study finds that microbial carbon use efficiency is a major determinant of soil organic carbon storage and its spatial variation across the globe.

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              A global analysis of root distributions for terrestrial biomes

              Understanding and predicting ecosystem functioning (e.g., carbon and water fluxes) and the role of soils in carbon storage requires an accurate assessment of plant rooting distributions. Here, in a comprehensive literature synthesis, we analyze rooting patterns for terrestrial biomes and compare distributions for various plant functional groups. We compiled a database of 250 root studies, subdividing suitable results into 11 biomes, and fitted the depth coefficient β to the data for each biome (Gale and Grigal 1987). β is a simple numerical index of rooting distribution based on the asymptotic equation Y=1-βd, where d = depth and Y = the proportion of roots from the surface to depth d. High values of β correspond to a greater proportion of roots with depth. Tundra, boreal forest, and temperate grasslands showed the shallowest rooting profiles (β=0.913, 0.943, and 0.943, respectively), with 80-90% of roots in the top 30 cm of soil; deserts and temperate coniferous forests showed the deepest profiles (β=0.975 and 0.976, respectively) and had only 50% of their roots in the upper 30 cm. Standing root biomass varied by over an order of magnitude across biomes, from approximately 0.2 to 5 kg m-2. Tropical evergreen forests had the highest root biomass (5 kg m-2), but other forest biomes and sclerophyllous shrublands were of similar magnitude. Root biomass for croplands, deserts, tundra and grasslands was below 1.5 kg m-2. Root/shoot (R/S) ratios were highest for tundra, grasslands, and cold deserts (ranging from 4 to 7); forest ecosystems and croplands had the lowest R/S ratios (approximately 0.1 to 0.5). Comparing data across biomes for plant functional groups, grasses had 44% of their roots in the top 10 cm of soil. (β=0.952), while shrubs had only 21% in the same depth increment (β=0.978). The rooting distribution of all temperate and tropical trees was β=0.970 with 26% of roots in the top 10 cm and 60% in the top 30 cm. Overall, the globally averaged root distribution for all ecosystems was β=0.966 (r 2=0.89) with approximately 30%, 50%, and 75% of roots in the top 10 cm, 20 cm, and 40 cm, respectively. We discuss the merits and possible shortcomings of our analysis in the context of root biomass and root functioning.
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                Author and article information

                Contributors
                hxm@tsinghua.edu.cn
                yiqi.luo@cornell.edu
                Journal
                Nature
                Nature
                Nature
                Nature Publishing Group UK (London )
                0028-0836
                1476-4687
                24 May 2023
                24 May 2023
                2023
                : 618
                : 7967
                : 981-985
                Affiliations
                [1 ]GRID grid.12527.33, ISNI 0000 0001 0662 3178, Department of Earth System Science, Ministry of Education Key Laboratory for Earth System Modelling, , Institute for Global Change Studies, Tsinghua University, ; Beijing, China
                [2 ]GRID grid.419500.9, ISNI 0000 0004 0491 7318, Max Planck Institute for Biogeochemistry, ; Jena, Germany
                [3 ]GRID grid.420153.1, ISNI 0000 0004 1937 0300, Food and Agricultural Organization of the United Nations, ; Rome, Italy
                [4 ]GRID grid.424975.9, ISNI 0000 0000 8615 8685, Key Laboratory of Ecosystem Network Observation and Modeling, , Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, ; Beijing, China
                [5 ]GRID grid.261120.6, ISNI 0000 0004 1936 8040, Center for Ecosystem Science and Society, Department of Biological Sciences, , Northern Arizona University, ; Flagstaff, AZ USA
                [6 ]GRID grid.261120.6, ISNI 0000 0004 1936 8040, School of Informatics, Computing and Cyber Systems, , Northern Arizona University, ; Flagstaff, AZ USA
                [7 ]GRID grid.10548.38, ISNI 0000 0004 1936 9377, Department of Physical Geography and Bolin Centre for Climate Research, , Stockholm University, ; Stockholm, Sweden
                [8 ]GRID grid.167436.1, ISNI 0000 0001 2192 7145, Center for Soil Biogeochemistry and Microbial Ecology, Department of Natural Resources and the Environment, , University of New Hampshire, ; Durham, NH USA
                [9 ]GRID grid.7400.3, ISNI 0000 0004 1937 0650, Department of Geography, , University of Zurich, ; Zurich, Switzerland
                [10 ]GRID grid.10772.33, ISNI 0000000121511713, Departamento de Ciências e Engenharia do Ambiente, , DCEA, Faculdade de Ciências e Tecnologia, FCT, Universidade Nova de Lisboa, ; Caparica, Portugal
                [11 ]GRID grid.460789.4, ISNI 0000 0004 4910 6535, Laboratoire des Sciences du Climat et de l’Environnement, LSCE/IPSL, CEA-CNRS-UVSQ, , Université Paris-Saclay, ; Gif-sur-Yvette, France
                [12 ]GRID grid.5386.8, ISNI 000000041936877X, School of Integrative Plant Science, , Cornell University, ; Ithaca, NY USA
                [13 ]GRID grid.5386.8, ISNI 000000041936877X, Soil and Crop Sciences Section, School of Integrative Plant Science, , Cornell University, ; Ithaca, NY USA
                [14 ]CSIRO Environment, Aspendale, Victoria Australia
                [15 ]GRID grid.5386.8, ISNI 000000041936877X, Department of Ecology and Evolutionary Biology and Department of Global Development, , Cornell University, ; Ithaca, NY USA
                [16 ]GRID grid.474523.3, ISNI 0000000403888279, Computational Biology and Biophysics, , Sandia National Laboratories, ; Livermore, CA USA
                [17 ]GRID grid.184769.5, ISNI 0000 0001 2231 4551, Joint BioEnergy Institute, , Lawrence Berkeley National Laboratory, ; Emeryville, CA USA
                [18 ]GRID grid.12981.33, ISNI 0000 0001 2360 039X, School of Atmospheric Sciences, , Sun Yat-sen University, ; Guangzhou, China
                [19 ]GRID grid.266900.b, ISNI 0000 0004 0447 0018, Institute for Environmental Genomics and Department of Microbiology and Plant Biology, , University of Oklahoma, ; Norman, OK USA
                [20 ]GRID grid.7107.1, ISNI 0000 0004 1936 7291, School of Biological Sciences, , University of Aberdeen, ; Aberdeen, UK
                Author information
                http://orcid.org/0000-0001-6105-860X
                http://orcid.org/0000-0003-4202-8071
                http://orcid.org/0000-0002-7337-1887
                http://orcid.org/0000-0002-5960-5712
                http://orcid.org/0000-0002-9221-5919
                http://orcid.org/0000-0002-7227-0646
                http://orcid.org/0000-0001-5736-1112
                http://orcid.org/0000-0003-0465-1436
                http://orcid.org/0000-0001-8560-4943
                http://orcid.org/0000-0002-4701-2936
                http://orcid.org/0000-0002-4614-6203
                http://orcid.org/0000-0001-7226-6682
                http://orcid.org/0000-0002-8096-1594
                http://orcid.org/0000-0002-3783-3212
                http://orcid.org/0000-0003-4866-9072
                http://orcid.org/0000-0002-4158-1089
                http://orcid.org/0000-0002-4556-0218
                Article
                6042
                10.1038/s41586-023-06042-3
                10307633
                37225998
                20071a6e-b4c6-4e9a-b396-5ccef3885fe4
                © The Author(s) 2023

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 16 August 2021
                : 3 April 2023
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