Evidence map›Paper›PMID 36680674›Full record

SynthesisScience China. Life sciences2023

Dynamic carbon-nitrogen coupling under global change.

Shuli Niu, Lei Song, Jinsong Wang, Yiqi Luo, Guirui Yu

Abstract readSystematic Review
PubMed Publisher
In one paragraph

Synthesis in Science China. Life sciences, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed, 3 pooled it
–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

17 citing papers in PubMed, 3 syntheses or guidelines pooled it.

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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

5 authors.

Shuli NiuKey Laboratory of Ecosystem Network Observation and Modelling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China. sniu@igsnrr.ac.cn.
Lei SongKey Laboratory of Ecosystem Network Observation and Modelling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China.
Jinsong WangKey Laboratory of Ecosystem Network Observation and Modelling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China.
Yiqi LuoCenter for Ecosystem Science and Society, Department of Biological Sciences, Northern Arizona University, Flagstaff, AZ, 86011, USA.
Guirui YuKey Laboratory of Ecosystem Network Observation and Modelling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Carbon-nitrogen coupling is a fundamental principle in ecosystem ecology. However, how the coupling responds to global change has not yet been examined. Through a comprehensive and systematic literature review, we assessed how the dynamics of carbon processes change with increasing nitrogen input and how nitrogen processes change with increasing carbon input under global change. Our review shows that nitrogen input to the ecosystem mostly stimulates plant primary productivity but inconsistently decreases microbial activities or increases soil carbon sequestration, with nitrogen leaching and nitrogenous gas emission rapidly increasing. Nitrogen fixation increases and nitrogen leaching decreases to improve soil nitrogen availability and support plant growth and ecosystem carbon sequestration under elevated CO

Indexed as

EcosystemNitrogenCarbonCarbon DioxideSoilSoil MicrobiologyCarbonCarbon DioxideNitrogenSoilcarbon-nitrogen interactioncarbon sequestrationglobal changenitrogen limitationsoil nitrogen cycle

Identifiers

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.