Evidence map›Paper›PMID 35140268›Full record

ArticleScientific reports2022

Investigating physical and mechanical properties of nest soils used by mud dauber wasps from a geotechnical engineering perspective.

Joon S Park, Noura S Saleh, Hai Lin, Hussein Alqrinawi, Nathan P Lord

Abstract read
In one paragraph

Article in Scientific reports, 2022. 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

5 authors.

Joon S ParkDepartment of Civil and Environmental Engineering, Louisiana State University, Baton Rouge, LA, 70803, USA.
Noura S SalehDepartment of Civil and Environmental Engineering, Louisiana State University, Baton Rouge, LA, 70803, USA.
Hai LinDepartment of Civil and Environmental Engineering, Louisiana State University, Baton Rouge, LA, 70803, USA. hailin1@lsu.edu.
Hussein AlqrinawiDepartment of Civil and Environmental Engineering, Louisiana State University, Baton Rouge, LA, 70803, USA.
Nathan P LordDepartment of Entomology, Louisiana State University, Baton Rouge, LA, 70803, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The quality of nest soils has significant effects on reproductive success in mud dauber species. This study investigated the physical and mechanical properties of the nest soils used by mud daubers from a geotechnical engineering perspective. One hundred thirty-one nests of black and yellow mud daubers were collected from five locations in the south of Louisiana. Moisture and organic contents, densities, void ratios, plasticity, grain size distributions, soil classifications, and penetration resistances of the nest soils were measured. Also, the performance of mud daubers' nest-compaction method (i.e., repetitive tapping produced by the front legs and mandibles) was evaluated by comparing the densities and penetration resistances between mud dauber nests and Proctor compacted nest soil samples. Scanning electron microscopy, energy-dispersive X-ray spectroscopy, and X-ray diffraction were used to measure the morphology, elemental composition, and mineralogy of the nest soils. Mud dauber nests were made of hard and very stiff well-graded silty soils. The high strengths and high densities of mud dauber nests were attributed to repetitive tapping (similar to vibratory compaction in geotechnical engineering) used by mud daubers for nest construction, high capillary cohesion in the nest soils, well-graded soil grain size distribution, and clay minerals serving as cementing agents in the nest soils.

Identifiers

PMID35140268
PMCPMC8828900

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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.