Evidence map›Paper›PMID 31988738›Full record

ArticleEcology and evolution2020

Biomass allocation and productivity-richness relationship across four grassland types at the Qinghai Plateau.

Licong Dai, Xiaowei Guo, Xun Ke, Yuting Lan, Fawei Zhang, Yikang Li, Li Lin, Qian Li, Guangmin Cao, Bo Fan and 3 more

Abstract read
In one paragraph

Article in Ecology and evolution, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. Article
  2. Biomass Allocation inPlants (Basel, Switzerland) · 2024
    Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
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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

13 authors.

Licong DaiQinghai Provincial Key Laboratory of Restoration Ecology for Cold Region Northwest Institute of Plateau Biology Chinese Academy of Sciences Xining China.ORCID https://orcid.org/0000-0002-9686-4262
Xiaowei GuoQinghai Provincial Key Laboratory of Restoration Ecology for Cold Region Northwest Institute of Plateau Biology Chinese Academy of Sciences Xining China.
Xun KeQinghai Provincial Key Laboratory of Restoration Ecology for Cold Region Northwest Institute of Plateau Biology Chinese Academy of Sciences Xining China.
Yuting LanQinghai Provincial Key Laboratory of Restoration Ecology for Cold Region Northwest Institute of Plateau Biology Chinese Academy of Sciences Xining China.
Fawei ZhangQinghai Provincial Key Laboratory of Restoration Ecology for Cold Region Northwest Institute of Plateau Biology Chinese Academy of Sciences Xining China.
Yikang LiQinghai Provincial Key Laboratory of Restoration Ecology for Cold Region Northwest Institute of Plateau Biology Chinese Academy of Sciences Xining China.
Li LinQinghai Provincial Key Laboratory of Restoration Ecology for Cold Region Northwest Institute of Plateau Biology Chinese Academy of Sciences Xining China.
Qian LiQinghai Provincial Key Laboratory of Restoration Ecology for Cold Region Northwest Institute of Plateau Biology Chinese Academy of Sciences Xining China.
Guangmin CaoQinghai Provincial Key Laboratory of Restoration Ecology for Cold Region Northwest Institute of Plateau Biology Chinese Academy of Sciences Xining China.
Bo FanQinghai Provincial Key Laboratory of Restoration Ecology for Cold Region Northwest Institute of Plateau Biology Chinese Academy of Sciences Xining China.
Dawen QianQinghai Provincial Key Laboratory of Restoration Ecology for Cold Region Northwest Institute of Plateau Biology Chinese Academy of Sciences Xining China.
Huakun ZhouQinghai Provincial Key Laboratory of Restoration Ecology for Cold Region Northwest Institute of Plateau Biology Chinese Academy of Sciences Xining China.
Yangong DuQinghai Provincial Key Laboratory of Restoration Ecology for Cold Region Northwest Institute of Plateau Biology Chinese Academy of Sciences Xining China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Aboveground biomass (AGB) and belowground biomass (BGB) allocation and productivity-richness relationship are controversial. Here, we assessed AGB and BGB allocation and the productivity-richness relationship at community level across four grassland types based on the biomass data collected from 80 sites across the Qinghai Plateau during 2011-2012. The reduced major axis regression and general linear models were used and showed that (a) the median values of AGB were significantly higher in alpine meadow than in other three grassland types; the ratio of root to shoot (R/S) was significantly higher in desert grassland (36.06) than intemperate grassland (16.60), alpine meadow (13.35), and meadow steppe (19.46). The temperate grassland had deeper root distribution than the other three grasslands, with about 91.45% roots distributed in the top 30 cm soil layer. (b) The slopes between log AGB and log BGB in the temperate grassland and meadow steppe were 1.09 and 1, respectively, whereas that in the desert grassland was 1.12, which was significantly different from the isometric allocation relationship. A competitive relationship between AGB and BGB was observed in the alpine meadow with a slope of -1.83, indicating a trade-off between AGB and BGB in the alpine meadow. (c) A positive productivity-richness relationship existed across the four grassland types, suggesting that the positive productivity-richness relationship might not be affected by the environmental factors at the plant location. Our results provide a new insight for biomass allocation and biodiversity-ecosystem functioning research.

Indexed as

above‐ and belowground biomass allocationgrassland typesproductivity–richness relationshipQinghai Plateaureduced major axis

Identifiers

PMID31988738
PMCPMC6972799

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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.