Evidence map›Paper›PMID 35851664›Full record

ArticleBotanical studies2022

Plant diversity and community analysis of Sele-Nono forest, Southwest Ethiopia: implication for conservation planning.

Alemayehu Kefalew, Teshome Soromessa, Sebsebe Demissew

Open access · goldAbstract read
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Article in Botanical studies, 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
7.0field-weighted citation impact, top 3% of its field
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What it found

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3 · Its place in the literature

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2 citing papers in PubMed, 12 citations in OpenAlex.

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4 · The record

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5 · Who and what money

Authors and funding

3 authors at 2 institutions in 1 country.

Alemayehu KefalewDepartment of Plant Biology and Biodiversity Management, the National Herbarium, Addis Ababa University, P. O. Box 3434, Addis Ababa, Ethiopia. alemayehukefalew2011@gmail.com.ORCID http://orcid.org/0000-0001-8259-9309
Teshome SoromessaCenter for Environmental Science, Addis Ababa University, P. O. Box 1176, Addis Ababa, Ethiopia.
Sebsebe DemissewDepartment of Plant Biology and Biodiversity Management, the National Herbarium, Addis Ababa University, P. O. Box 3434, Addis Ababa, Ethiopia.
Addis Ababa University · ETEthiopian Biodiversity Institute · ET

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundStudying the floristic diversity of a certain forest is a basic aspect of the design and management of forest vegetation; and consequently this study focused on the plant diversity and community analysis of the Sele-Nono forest. For the current study, plants were sampled from 90 plots using a stratified random sampling technique along the established strata of the study forest. In all the plots, both floristic and environmental data that were relevant to the study were collected following the state of the art. Based on the collected data, the community types, ordination, floristic diversity, and threats to the forest were analyzed using R-package and SPSS software.

resultsCluster analysis produced seven distinct community types which significantly differed among themselves (Cophentic correlation coefficient = 0.785, P < 0.001) of which community types 2 and 6 were relatively poor; whereas communities 1 and 4 were rich in terms of their species richness and diversity. In addition, Canonical Correspondence Analysis (CCA) suggests that a number of environmental factors such as altitude and slope (topographic factor), OM and N (edaphic factors) and disturbance were the main drivers for the current distribution of plant species and disparity in plant community composition in Sele-Nono forest. Moreover, the study revealed high beta diversity ([Formula: see text] >12) of plant species at the landscape level (i.e., throughout the study forest). Deforestation for agricultural land expansion and degradation through selective logging are the main threats to the Sele-Nono forest.

conclusionsThe present study revealed that the Sele-Nono forest is a large and heterogenous forest at the landscape level (150, 325.27 ha; [Formula: see text] >12). Moreover, it is one of the richest and diverse forest ecosystems in terms of plant biodiversity, and it could qualify to be labeled as a keystone ecosystem. However, currently it is exposed to a variety of threats. We recommend the forest to be developed into a biosphere reserve. We also recommend the prioritization of areas belonging to community types 2 and 6 of the forest for any possible conservation actions so as to maximize species richness and diversity of the native plants of the area.

Indexed as

Canonical correspondence analysisCluster analysisCommunity typesMultivariate techniqueOrdinationSele-Nono Forest

Identifiers

PMID35851664
PMCPMC9294133
OpenAlexW4285793488

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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.