Evidence map›Paper›PMID 28176873›Full record

ArticleScientific reports2017

Long-term growth of temperate broadleaved forests no longer benefits soil C accumulation.

Yu-He Ji, Ke Guo, Shi-Bo Fang, Xiao-Niu Xu, Zhi-Gao Wang, Shu-Dong Wang

Abstract read
In one paragraph

Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

6 authors.

Yu-He JiState Key Laboratory of Severe Weather (LASW), Chinese Academy of Meteorological Science, Beijing 100081, China.
Ke GuoState Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences, Beijing 100093, China.
Shi-Bo FangState Key Laboratory of Severe Weather (LASW), Chinese Academy of Meteorological Science, Beijing 100081, China.
Xiao-Niu XuSchool of Forestry &Landscape Architecture, Anhui Agricultural University, Hefei 230036, China.
Zhi-Gao WangDepartment of Life Science, Anqing Normal University, Anqing 246133, China.
Shu-Dong WangState Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Science, Beijing 100101, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

It is widely recognized that the long-term growth of forests benefits biomass carbon (C) sequestration, but it is not known whether the long-term growth of forests would also benefit soil C sequestration. We selected 79 representative soil profiles and investigated the influence of the forest stand age on the soil C dynamics of three soil layers (0-10, 10-20 and 20-30 cm) in temperate broadleaved forests in East China. The results suggest that the soil C density in temperature broadleaved forests significantly changes with the stand age, following a convex parabolic curve. At an early stand age, the soil C density usually increases, reaching its peak value at a pre-mature stand age (approximately 50 years old). At later stand ages, the soil C density usually decreases. Therefore, our results reveal a turning point in the soil C density at a pre-mature stand age. The long-term growth of temperate broadleaved forests after pre-mature stand age no longer benefits soil C accumulation, probably promotes topsoil C loss. In addition, we found that the soil C density in the upper soil layer usually changes with the forest stand development more significantly than that in deeper soil layers.

Indexed as

RainforestCarbonChinaGeographySoilTime FactorsCarbonSoil

Identifiers

PMID28176873
PMCPMC5296757

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.