Evidence map›Paper›PMID 36655042›Full record

ArticlePeerJ2023

Research on the application of a cement and soil aggregate for the ecological restoration of vegetation in artificial soil.

Zhuxin Mao, Qian Li, Yuchao Wang

Abstract read
In one paragraph

Article in PeerJ, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

3 authors.

Zhuxin MaoXi'an Botanical Garden of Shaanxi Province, Institute of Botany of Shaanxi Province, Xi'an, PR China.
Qian LiXi'an Botanical Garden of Shaanxi Province, Institute of Botany of Shaanxi Province, Xi'an, PR China.
Yuchao WangXi'an Botanical Garden of Shaanxi Province, Institute of Botany of Shaanxi Province, Xi'an, PR China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The construction of high-speed roads has resulted in large amounts of steep and exposed cut slopes, posing more potential hazards in areas with mountains and hills. Vegetation restoration is an effective and environmentally-friendly way to restore exposed slopes using outside soil spray seeding, though it is difficult to establish a vegetation cover. Spraying artificial soil on high and steep slopes is a challenging task as it is difficult to keep the fluid mixture on sloped surfaces. Because of these challenges, this study applied different combinations of cement and soil aggregates in artificial soil, measuring final soil properties after one growing season. Experimental results showed that there were substantial differences in all basic soil parameters and in the soil quality index after different treatments. In particular, adding 5-10% cement content could improve the adhesion of artificial soil without remarkably reducing soil quality; adding 0.09% of soil aggregate was also beneficial to soil nutrient availability. These findings indicate that the combination of cement and soil aggregates could be applied in artificial soils for the ecological restoration of steep slope vegetation. Adding cement to the soil increased the alkaline levels of the soil, so it is important to reduce artificial soil pH in the future. The application of a cement and soil aggregate should be considered in the field for the ecological restoration of slope vegetation, and the impact of this addition on slope stability and vegetation growth should be explored with further research.

Indexed as

NutrientsSoilSeasonsNutrientsSoilArtificial soilCementCutting slopsSoil aggregateSoil quality indexVegetation restoration

Identifiers

PMID36655042
PMCPMC9841899

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.