Evidence map›Paper›PMID 39695748›Full record

ArticleParasites & vectors2024

Reliability of wing morphometrics for species identification of human-biting black flies (Diptera: Simuliidae) in Thailand.

Kittipat Aupalee, Wichai Srisuka, Kwankamol Limsopatham, Sangob Sanit, Hiroyuki Takaoka, Atiporn Saeung

Abstract read
In one paragraph

Article in Parasites & vectors, 2024. 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

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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. Multiplex PCR for the differentiation ofCurrent research in parasitology & vector-borne diseases · 2026
    Article
  3. Geometric morphometric analysis of wing size and shape variation inJournal of advanced veterinary and animal research · 2026
    Article
  4. Taxonomic signal in the wing cells ofJournal of advanced veterinary and animal research · 2025
    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.

Kittipat AupaleeParasitology and Entomology Research Cluster (PERC), Department of Parasitology, Faculty of Medicine, Chiang Mai University, Chiang Mai, 50200, Thailand.
Wichai SrisukaEntomology Section, Queen Sirikit Botanic Garden, Mae Rim, Chiang Mai, 50180, Thailand.
Kwankamol LimsopathamParasitology and Entomology Research Cluster (PERC), Department of Parasitology, Faculty of Medicine, Chiang Mai University, Chiang Mai, 50200, Thailand.
Sangob SanitParasitology and Entomology Research Cluster (PERC), Department of Parasitology, Faculty of Medicine, Chiang Mai University, Chiang Mai, 50200, Thailand.
Hiroyuki TakaokaTropical Infectious Diseases Research and Education Centre (TIDREC), Higher Institution Centre of Excellence (HICoE), Universiti Malaya, 50603, Kuala Lumpur, Malaysia.
Atiporn SaeungParasitology and Entomology Research Cluster (PERC), Department of Parasitology, Faculty of Medicine, Chiang Mai University, Chiang Mai, 50200, Thailand. atisaeung.noi@gmail.com.

Funding

Faculty of Medicine, Chiang Mai University 106-2565
6 · The paper itself

Abstract

backgroundFast and reliable species identification of black flies is essential for research proposes and effective vector control. Besides traditional identification based on morphology, which is usually supplemented with molecular methods, geometric morphometrics (GM) has emerged as a promising tool for identification. Despite its potential, no specific GM techniques have been established for the identification of black fly species.

methodsAdult female black flies collected using human bait, as well as those reared from pupae, were used in this study. Here, landmark-based GM analysis of wings was assessed for the first time to identify human-biting black fly species in Thailand, comparing this approach with the standard morphological identification method and DNA barcoding based on the mitochondrial cytochrome c oxidase subunit I (COI) gene. To explore genetic relationships between species, maximum likelihood (ML) and neighbor-joining (NJ) phylogenetic trees were built. Additionally, three different methods of species delimitation, i.e., assemble species by automatic partitioning (ASAP), generalized mixed yule coalescent (GMYC), and single Poisson tree processes (PTP), were utilized to identify the morphologically defined species. The effectiveness of a COI barcode in identifying black fly species was further examined through the best match (BM) and best close match (BCM) methods.

resultsSeven black fly species, namely Simulium tenebrosum Takaoka, Srisuka & Saeung, 2018 (complex), S. doipuiense Takaoka & Choochote, 2005 (complex), S. nigrogilvum Summers, 1911, S. nodosum Puri, 1933, S. asakoae Takaoka & Davies, 1995, S. chamlongi Takaoka & Suzuki, 1984, and S. umphangense Takaoka, Srisuka & Saeung, 2017 were morphologically identified. Compared with the standard method, the GM analysis based on wing shape showed high success in separating species, achieving an overall accuracy rate of 88.54%. On the other hand, DNA barcoding surpassed wing GM for species identification with a correct identification rate of 98.57%. Species delimitation analyses confirmed the validity of most nominal species, with an exception for S. tenebrosum complex and S. doipuiense complex, being delimited as a single species. Moreover, the analyses unveiled hidden diversity within S. asakoae, indicating the possible existence of up to four putative species.

conclusionsThis study highlights the potential of wing GM as a promising and reliable complementary tool for species identification of human-biting black flies in Thailand.

Indexed as

DNA Barcoding, TaxonomicElectron Transport Complex IVPhylogenySimuliidaeWings, AnimalAnimalsFemaleHumansReproducibility of ResultsThailandElectron Transport Complex IVDNA barcodesHematophagous insectMedical entomologyMorphometric analysisSimuliumSpecies delimitation

Identifiers

PMID39695748
PMCPMC11658325

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LicenceCC BY
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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.