Evidence map›Paper›PMID 37773228›Full record

ArticleNature communications2023

Reducing risks of antibiotics to crop production requires land system intensification within thresholds.

Fangkai Zhao, Lei Yang, Haw Yen, Qingyu Feng, Min Li, Liding Chen

Abstract read
In one paragraph

Article in Nature communications, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. 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.

Fangkai ZhaoSchool of Ecology and Environmental Sciences, Yunnan University, Kunming, 650500, China.ORCID http://orcid.org/0000-0002-5683-7868
Lei YangState Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing, 100085, China.
Haw YenSchool of Forestry and Wildlife Sciences, Auburn University, Auburn, AL, 36849, USA.
Qingyu FengState Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing, 100085, China.
Min LiState Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing, 100085, China.
Liding ChenSchool of Ecology and Environmental Sciences, Yunnan University, Kunming, 650500, China. liding@ynu.edu.cn.ORCID http://orcid.org/0000-0001-8713-8552

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Land system intensification has substantially enhanced crop production; however, it has also created soil antibiotic pollution, undermining crop production. Here, we projected soil antibiotic pollution risks to crop production at multiple geographical scales in China and linked them to land system intensification (including arable land expansion and input increase). Our projections suggest that crop production will substantially decrease when the soil antibiotic pollution risk quotient exceeds 8.30-9.98. Land systems explain most of the variability in antibiotic pollution risks (21-66%) across spatial scales. The convex nonlinearities in tradeoffs between antibiotic pollution risk and crop production indicate that vegetable and wheat production have higher thresholds of land system intensification at which the risk-yield tradeoffs will peak than do maize and rice production. Our study suggests that land system intensification below the minimum thresholds at multiple scales is required for acceptable antibiotic pollution risks related to crop yield reduction.

Indexed as

AgricultureCrop ProductionChinaSoilVegetablesSoil

Identifiers

PMID37773228
PMCPMC10541423

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.