Evidence map›Paper›PMID 38926452›Full record

ArticleScientific data2024

A morphological traits dataset of Heteroptera sampled in biodiversity priority areas of Southwest China.

Shutong Gao, Wenbo Yu, Ting Tian, Zhixing Lu, Xiang Zhang, Qiao Li, Youqing Chen

Abstract readDataset
In one paragraph

Article in Scientific data, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

7 authors.

Shutong GaoInstitute of Highland Forest Science, Chinese Academy of Forestry, Yunan Kunming, 650224, China.ORCID 0000-0002-6572-4697
Wenbo YuNanjing Forestry University, Jiangsu Nanjing, 210037, China.
Ting TianSouthwest Forestry University, Yunan Kunming, 650224, China.
Zhixing LuInstitute of Highland Forest Science, Chinese Academy of Forestry, Yunan Kunming, 650224, China.
Xiang ZhangInstitute of Highland Forest Science, Chinese Academy of Forestry, Yunan Kunming, 650224, China.
Qiao LiSouthwest Forestry University, Yunan Kunming, 650224, China.
Youqing ChenInstitute of Highland Forest Science, Chinese Academy of Forestry, Yunan Kunming, 650224, China. cyqcaf@126.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Functional traits reveal the adaptive strategies of species to their environment, and are relevant to the formation of communities, the function of ecosystems, and the mechanisms underlying biodiversity. However, trait databases have not been established for most biological taxa, especially for insects, which encompass a vast number of species. This study measured the morphological traits of 307 species of Heteroptera insects collected in 2019 from the "Xishuangbanna Priority Conservation Area" in Southwest China using sweep netting and light trapping methods. This study provides a dataset for 307 Heteroptera species, comprising 34 morphometric measurements and 17 morphological traits. The dataset contains information on species sex, abundance, and the average, maximum, and minimum values of traits. This dataset facilitates an enhanced understanding of the functional traits and ecological associations of Heteroptera insects and offers opportunities for exploring a more diverse range of research topics.

Indexed as

BiodiversityHeteropteraAnimalsChinaEcosystemFemaleMale

Identifiers

PMID38926452
PMCPMC11208582

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Registered trials

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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.