Evidence map›Paper›PMID 35991414›Full record

ArticleFrontiers in plant science2022

Canopy nitrogen addition enhance the photosynthetic rate of canopy species by improving leaf hydraulic conductivity in a subtropical forest.

Guilin Wu, Dexiang Chen, Zhang Zhou, Qing Ye, Jianhui Wu

Open access · goldAbstract read
In one paragraph

Article in Frontiers in plant science, 2022. 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
0.8field-weighted citation impact, top 30% of its field
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, 7 citations in OpenAlex.

  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

5 authors at 3 institutions in 1 country.

Guilin WuHainan Jianfengling Forest Ecosystem National Field Science Observation and Research Station, Research Institute of Tropical Forestry, Chinese Academy of Forestry, Guangzhou, China.
Dexiang ChenHainan Jianfengling Forest Ecosystem National Field Science Observation and Research Station, Research Institute of Tropical Forestry, Chinese Academy of Forestry, Guangzhou, China.
Zhang ZhouHainan Jianfengling Forest Ecosystem National Field Science Observation and Research Station, Research Institute of Tropical Forestry, Chinese Academy of Forestry, Guangzhou, China.
Qing YeKey Laboratory of Vegetation Restoration and Management of Degraded Ecosystems, South China Botanical Garden, Chinese Academy of Sciences, Guangzhou, China.
Jianhui WuHainan Jianfengling Forest Ecosystem National Field Science Observation and Research Station, Research Institute of Tropical Forestry, Chinese Academy of Forestry, Guangzhou, China.
Chinese Academy of Forestry · CNResearch Institute of Tropical Forestry · CNSouth China Botanical Garden · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Elucidating the effects of atmospheric nitrogen (N) deposition on the photosynthetic capacity of plants is critical to understand forest growth and conservation under global change. However, studies on this topic generally consider only understory N addition, which ignores the effect of canopy interception. In this study, we conducted a field experiment in a subtropical forest to compare the effects of canopy vs. understory N addition on the photosynthetic rate of canopy and understory species. We found that canopy N addition enhanced the photosynthetic rate of canopy species by increasing leaf hydraulic conductivity and shortening the distance of CO

Indexed as

canopy N additionCO2 transportation distanceleaf hydraulic conductivityphotosynthetic rateunderstory N addition

Identifiers

PMID35991414
PMCPMC9389171
OpenAlexW4289874622

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.