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Articles

Nestedness and modularity in fragmented Shasha Forest Reserve, southwestern Nigeria

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Pages 292-304 | Published online: 19 Nov 2018
 

ABSTRACT

Species co-occurrence and nestedness pattern in Shasha forest reserve were investigated with a view to determining the effect of interactions to species contribution. Three distinct sites (Gmelina arborea plantation, undisturbed forest, and Pinus carribaea (plantation) were selected in the forest reserve. Four 25 m × 25 m plots were established in each of the site within the forest reserve. Species enumeration, identification,, and distribution into families of the standing vegetation were carried out. Woody species represented the most diverse life form. Plant species diversity was highest in UF and lowest in Gmelina plantation. Differences in woody species composition among the three forest types were determined by non-metric multidimensional scaling (NMDS) analysis, analysis of similarity (ANOSIM), and similarity of percentages. Using z-score and NODF (a nestedness metric based on overlap and decreasing fill). Three modules were detected and modularity score Q = 0.2. The composition analyses (NMDS and ANOSIM) revealed a significant difference in the woody species composition among the forest types. Our research may contribute to understand species assemblage in one of the diverse forests of Africa. Current work highlighted species occurrence in Shasha forest and highlighted the importance of non-random pattern which could serve as framework for conservation perspective.

Acknowledgments

The authors thank Gabriel Ibhanessebor former curator at IFE Herbarium for assisting in enumeration of the standing vegetation. We also appreciate anonymous reviewers to make the article better.

Conflicts of Interest

The authors declare no conflict of interest.

Supplementary material

Supplemental data for this article can be accessed here.

Additional information

Funding

The study did not receive any grant from funding agencies in the public, commercial, or not- for profit sectors.

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