Evidence map›Paper›PMID 39271672›Full record

ReviewNature communications2024

Emerging multiscale insights on microbial carbon use efficiency in the land carbon cycle.

Xianjin He, Elsa Abs, Steven D Allison, Feng Tao, Yuanyuan Huang, Stefano Manzoni, Rose Abramoff, Elisa Bruni, Simon P K Bowring, Arjun Chakrawal and 14 more

Abstract readReview
In one paragraph

Review in Nature communications, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

21 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

24 authors.

Xianjin HeLaboratoire des Sciences du Climat et de l'Environnement, IPSL-LSCE, CEA/CNRS/UVSQ, Orme des Merisiers, Gif sur Yvette, France.ORCID 0000-0002-5573-607X
Elsa AbsLaboratoire des Sciences du Climat et de l'Environnement, IPSL-LSCE, CEA/CNRS/UVSQ, Orme des Merisiers, Gif sur Yvette, France.
Steven D AllisonDepartment of Ecology and Evolutionary Biology, University of California Irvine, Irvine, CA, USA.ORCID 0000-0003-4629-7842
Feng TaoDepartment of Ecology and Evolutionary Biology, Cornell University, Ithaca, NY, USA.
Yuanyuan HuangKey Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China.ORCID 0000-0003-4202-8071
Stefano ManzoniDepartment of Physical Geography and Bolin Centre for Climate Research, Stockholm University, Stockholm, Sweden.ORCID 0000-0002-5960-5712
Rose AbramoffWintergreen Earth Science, Kennebunk, ME, USA.ORCID 0000-0002-3393-3064
Elisa BruniLG-ENS (Laboratoire de géologie) CNRS UMR 8538-Ecole normale supérieure, PSL University -IPSL, Paris, France.ORCID 0000-0001-8074-0516
Simon P K BowringLaboratoire des Sciences du Climat et de l'Environnement, IPSL-LSCE, CEA/CNRS/UVSQ, Orme des Merisiers, Gif sur Yvette, France.
Arjun ChakrawalEnvironmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, WA, USA.ORCID 0000-0003-4572-4347
Philippe CiaisLaboratoire des Sciences du Climat et de l'Environnement, IPSL-LSCE, CEA/CNRS/UVSQ, Orme des Merisiers, Gif sur Yvette, France.ORCID 0000-0001-8560-4943
Lars ElsgaardDepartment of Agroecology, Aarhus University, AU Viborg, Tjele, Denmark.ORCID 0000-0003-0058-7609
Pierre FriedlingsteinFaculty of Environment, Science and Economy, University of Exeter, Exeter, UK.
Katerina GeorgiouPhysical and Life Sciences Directorate, Lawrence Livermore National Laboratory, Livermore, CA, USA.ORCID 0000-0002-2819-3292
Gustaf HugeliusDepartment of Physical Geography and Bolin Centre for Climate Research, Stockholm University, Stockholm, Sweden.ORCID 0000-0002-8096-1594
Lasse Busk HolmDepartment of Agroecology, Aarhus University, AU Viborg, Tjele, Denmark.
Wei LiDepartment of Earth System Science, Ministry of Education Key Laboratory for Earth System Modeling, Institute for Global Change Studies, Tsinghua University, Beijing, China.ORCID 0000-0003-2543-2558
Yiqi LuoSoil and Crop Sciences Section, School of Integrative Plant Science, Cornell University, Ithaca, NY, USA.ORCID 0000-0002-4556-0218
Gaëlle MarmasseLaboratoire des Sciences du Climat et de l'Environnement, IPSL-LSCE, CEA/CNRS/UVSQ, Orme des Merisiers, Gif sur Yvette, France.
Naoise NunanInstitute of Ecology and Environmental Sciences-Paris, Sorbonne Université, CNRS, IRD, INRA, P7, UPEC, Paris, France.ORCID 0000-0003-3448-7171
Chunjing QiuResearch Center for Global Change and Complex Ecosystems, East China Normal University, Shanghai, China.ORCID 0000-0002-9951-3951
Stephen SitchFaculty of Environment, Science and Economy, University of Exeter, Exeter, UK.ORCID 0000-0003-1821-8561
Ying-Ping WangCSIRO Environment, Private Bag 10, Commonwealth Scientific and Industrial Research Organization, Clayton South, VIC 3169, Australia.ORCID 0000-0002-4614-6203
Daniel S GollLaboratoire des Sciences du Climat et de l'Environnement, IPSL-LSCE, CEA/CNRS/UVSQ, Orme des Merisiers, Gif sur Yvette, France. dsgoll123@gmail.com.ORCID 0000-0001-9246-9671

Funding

EC | Horizon 2020 Framework Programme (EU Framework Programme for Research and Innovation H2020) 101001608EC | Horizon 2020 Framework Programme (EU Framework Programme for Research and Innovation H2020) 101003890EC | Horizon 2020 Framework Programme (EU Framework Programme for Research and Innovation H2020) 862695
6 · The paper itself

Abstract

Microbial carbon use efficiency (CUE) affects the fate and storage of carbon in terrestrial ecosystems, but its global importance remains uncertain. Accurately modeling and predicting CUE on a global scale is challenging due to inconsistencies in measurement techniques and the complex interactions of climatic, edaphic, and biological factors across scales. The link between microbial CUE and soil organic carbon relies on the stabilization of microbial necromass within soil aggregates or its association with minerals, necessitating an integration of microbial and stabilization processes in modeling approaches. In this perspective, we propose a comprehensive framework that integrates diverse data sources, ranging from genomic information to traditional soil carbon assessments, to refine carbon cycle models by incorporating variations in CUE, thereby enhancing our understanding of the microbial contribution to carbon cycling.

Indexed as

CarbonCarbon CycleEcosystemSoilSoil MicrobiologyBacteriaCarbonSoil

Identifiers

PMID39271672
PMCPMC11399347

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.