Evidence map›Paper›PMID 30640931›Full record

ArticlePloS one2019

Plant biomass and soil organic carbon are main factors influencing dry-season ecosystem carbon rates in the coastal zone of the Yellow River Delta.

Yong Li, Haidong Wu, Jinzhi Wang, Lijuan Cui, Dashuan Tian, Jinsong Wang, Xiaodong Zhang, Liang Yan, Zhongqing Yan, Kerou Zhang and 2 more

Abstract read
In one paragraph

Article in PloS one, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Soil carbon in the world's tidal marshes.Nature communications · 2024
    Article
  5. Article
  6. Article
  7. Factors controlling organic carbon distributions in a riverine wetland.Environmental science and pollution research international · 2020
    Article
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

12 authors.

Yong LiBeijing Key Laboratory of Wetland Services and Restoration, Institute of Wetland Research, Chinese Academy of Forestry, Beijing, China.ORCID 0000-0001-9146-8044
Haidong WuBeijing Key Laboratory of Wetland Services and Restoration, Institute of Wetland Research, Chinese Academy of Forestry, Beijing, China.
Jinzhi WangBeijing Key Laboratory of Wetland Services and Restoration, Institute of Wetland Research, Chinese Academy of Forestry, Beijing, China.
Lijuan CuiBeijing Key Laboratory of Wetland Services and Restoration, Institute of Wetland Research, Chinese Academy of Forestry, Beijing, China.
Dashuan TianKey Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China.
Jinsong WangKey Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China.
Xiaodong ZhangBeijing Key Laboratory of Wetland Services and Restoration, Institute of Wetland Research, Chinese Academy of Forestry, Beijing, China.
Liang YanBeijing Key Laboratory of Wetland Services and Restoration, Institute of Wetland Research, Chinese Academy of Forestry, Beijing, China.
Zhongqing YanBeijing Key Laboratory of Wetland Services and Restoration, Institute of Wetland Research, Chinese Academy of Forestry, Beijing, China.
Kerou ZhangBeijing Key Laboratory of Wetland Services and Restoration, Institute of Wetland Research, Chinese Academy of Forestry, Beijing, China.
Xiaoming KangBeijing Key Laboratory of Wetland Services and Restoration, Institute of Wetland Research, Chinese Academy of Forestry, Beijing, China.
Bing SongSchool of Resources and Environmental Engineering, Ludong University, Yantai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Coastal wetlands are considered as a significant sink of global carbon due to their tremendous organic carbon storage. Coastal CO2 and CH4 flux rates play an important role in regulating atmospheric CO2 and CH4 concentrations. However, the relative contributions of vegetation, soil properties, and spatial structure on dry-season ecosystem carbon (C) rates (net ecosystem CO2 exchange, NEE; ecosystem respiration, ER; gross ecosystem productivity, GEP; and CH4) remain unclear at a regional scale. Here, we compared dry-season ecosystem C rates, plant, and soil properties across three vegetation types from 13 locations at a regional scale in the Yellow River Delta (YRD). The results showed that the Phragmites australis stand had the greatest NEE (-1365.4 μmol m-2 s-1), ER (660.2 μmol m-2 s-1), GEP (-2025.5 μmol m-2 s-1) and acted as a CH4 source (0.27 μmol m-2 s-1), whereas the Suaeda heteroptera and Tamarix chinensis stands uptook CH4 (-0.02 to -0.12 μmol m-2 s-1). Stepwise multiple regression analysis demonstrated that plant biomass was the main factor explaining all of the investigated carbon rates (GEP, ER, NEE, and CH4); while soil organic carbon was shown to be the most important for explaining the variability in the processes of carbon release to the atmosphere, i.e., ER and CH4. Variation partitioning results showed that vegetation and soil properties played equally important roles in shaping the pattern of C rates in the YRD. These results provide a better understanding of the link between ecosystem C rates and environmental drivers, and provide a framework to predict regional-scale ecosystem C fluxes under future climate change.

Indexed as

Carbon CycleWetlandsBiomassCarbon DioxideChenopodiaceaeChinaClimate ChangeEcosystemMethanePlantsPoaceaeRiversSoilTamaricaceaeCarbon DioxideMethaneSoil

Identifiers

PMID30640931
PMCPMC6331112

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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.