Vegetation, floristic composition and structure of a tropical montane forest in Cameroon

Background: The Rumpi Hills Forest Reserve (RHFR) is a montane forest area in south-western Cameroon. Although RHFR is presumed to be rich in biodiversity and vegetation types, little information exists regarding its floristic composition and vegetation patterns. Objectives: Our goal was to characterise vegetation patterns in the reserve and to understand how elevation influences distributions and diversity of species. We aimed to provide a first detailed plant species inventory for this important forest area, as well as basic information on forest structure. Method: We characterised floristic composition and vegetation patterns of the reserve in 25 1-ha plots along an elevational gradient from 50 m to 1778 m. In each plot, trees and lianas of diameter at breast height (dbh) ≥ 10 cm were measured; shrubs 10 cm were measured in nested plots of 0.01 ha. Results: In all, 16 761 trees, shrubs and lianas with dbh ≥ 1 cm were censused, representing 71 families, 279 genera and 617 morphospecies. Floristic composition ranged from 94 to 132 species, with a mean of 117.5 species per hectare in lowland forest (50 m – 200 m) and 36–41 species, with a mean of 38.5 species per hectare in montane cloud forest (1600 m – 1778 m) near the summit of Mount Rata. Two-way indicator species analysis classified the 25 plots into six vegetation types corresponding to lowland evergreen rainforest, lowland evergreen rainforest on basalt rocks, middle-elevation evergreen forest, submontane forest, transitional submontane forest and montane cloud forest. In all, 0.006% of the reserve was included in our sample plots. Detrended correspondence analysis highlighted the importance of elevation in shaping vegetation patterns. Conclusion: The RHFR is composed of different vegetation types, which show impressive variation in terms of structure, species composition and diversity. The detailed, fine-scale inventory data obtained in this study could be useful in planning efficient management of this and other montane tropical forests.

Abstract licence: CC BY

A person counts once a day per paper. We keep no cookie and no address: a reader is a hash that changes every day. Any month under five reads shows no number.