Evidence map›Paper›PMID 33997415›Full record

ArticleHeliyon2021

Impact of exclosures on woody species diversity in degraded lands: the case of Lemo in Southwestern Ethiopia.

Abebe Fikadu, Mekuria Argaw

Abstract read
In one paragraph

Article in Heliyon, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. 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

2 authors.

Abebe FikaduDepartment of Natural Resources Management, Arba Minch University, Ethiopia.
Mekuria ArgawCenter for Environmental Science, Addis Ababa University, Ethiopia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Exclosures are popularly applied to rehabilitate degraded lands and to gradually restore the productive potential of the land in the long term. This study was conducted to examine the impact of removing human and livestock interference from a degraded land to allow natural recuperation for extended period of years. The aim was to assess the trend of changes in the composition, diversity and structure of the woody component of the vegetation within the exclosures. Degraded lands with different years of exclosure were compared with adjacent open grazing lands under similar environmental conditions. A Systematic transect sampling method was employed to collect vegetation data in sampling quadrat plots, each with a size of 20 m × 20 m, evenly distributed along parallel transect lines. All the woody plant species in each plot were identified and measured for DBH and height. The species diversity and density were analyzed using standard indices. The structural pattern and regeneration status of the woody vegetation was described using size class distribution plots. The findings showed that the woody vegetation composition significantly varied between exclosures and open grazing land. There was significantly (P < 0.05) higher diversity, richness and stand density of the woody species in the exclosures than in the open grazing lands. The size class distribution of the DBH and height of the recorded species exhibited an inverted "J" shape pattern suggesting a healthy regeneration status of the important species, while the distribution pattern in the open grazing lands revealed irregular and less interpretable pattern. This study evidently showed exclosures can successfully contribute to biodiversity restoration in highly degraded lands, perhaps due to improvements in the important micro-climate conditions such as moisture and organic matter.

Indexed as

DensityExclosureOpen grazing landRestorationStructure

Identifiers

PMID33997415
PMCPMC8100080

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.