Evidence map›Paper›PMID 37091562›Full record

ArticleEcology and evolution2023

Monitoring insect biodiversity and comparison of sampling strategies using metabarcoding: A case study in the Yanshan Mountains, China.

Min Li, Ting Lei, Guobin Wang, Danli Zhang, Huaxi Liu, Zhiwei Zhang

Abstract read
In one paragraph

Article in Ecology and evolution, 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

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3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Constructing a lower-bound estimate of the global number of insect species on a hyperdiverse empirical foundation.Proceedings of the National Academy of Sciences of the United States of America · 2026
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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

6 authors.

Min LiCollege of Biological Science and Technology Taiyuan Normal University Jinzhong China.ORCID https://orcid.org/0000-0002-5471-1575
Ting LeiCollege of Biological Science and Technology Taiyuan Normal University Jinzhong China.
Guobin WangCollege of Biological Science and Technology Taiyuan Normal University Jinzhong China.
Danli ZhangCollege of Biological Science and Technology Taiyuan Normal University Jinzhong China.
Huaxi LiuDepartment of Life Sciences Natural History Museum London UK.
Zhiwei ZhangCollege of Forestry, Shanxi Agricultural University Jinzhong China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Insects are the richest and most diverse group of animals and yet there remains a lack, not only of systematic research into their distribution across some key regions of the planet, but of standardized sampling strategies for their study. The Yanshan Mountains, being the boundary range between the Inner Mongolian Plateau and the North China Plain, present an indispensable piece of the insect biodiversity puzzle: both requiring systematic study and offering opportunities for the development of standardized methodologies. This is the first use of DNA metabarcoding to survey the insect biodiversity of the Yanshan Mountains. The study focuses on differences of community composition among samples collected via different methods and from different habitat types. In total, 74 bulk samples were collected from five habitat types (scrubland, woodland, wetland, farmland and grassland) using three collection methods (sweep netting, Malaise traps and light traps). After DNA extraction, PCR amplification, sequencing and diversity analysis were performed, a total of 7427 Operational Taxonomic Units (OTUs) at ≥97% sequence similarity level were delimited, of which 7083 OTUs were identified as belonging to Insecta. Orthoptera, Diptera, Coleoptera and Hemiptera were found to be the dominant orders according to community composition analysis. Nonmetric multidimensional scaling (NMDS) analysis based on Bray-Curtis distances revealed highly divergent estimates of insect community composition among samples differentiated by the collection method (

Indexed as

habitatinsect biodiversitylight trapsmalaise trapsmetabarcodingsweep netting

Identifiers

PMID37091562
PMCPMC10121320

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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.