Background and aims – Deforestation and forest degradation have hugely affected the Southern Ethiopian Rift Valley, jeopardizing biodiversity conservation and ecosystem service provisioning. Quantifying the impacts of human activities on the remaining woody plant communities and recognizing vegetation–environment relationships provide the basis for targeted conservation and rehabilitation.Material and methods – The study was performed in the Nech Sar National Park (NSNP). Based on a large systematic vegetation survey of 104 plots, we quantified the woody vegetation composition, and we provided a vegetation classification based on Non Metric Multidimensional Scaling, cluster analysis and indicator species analysis. Furthermore, we evaluated vegetation – environment relationships and the effects of human disturbance on community composition and woody plant species richness and diversity.Key results – Our analyses revealed three very distinct woody vegetation types (Acacia mellifera-Combretum aculeatum; Lecaniodiscus fraxinifolius-Deinbollia kilimandscharica and Acacia polyacantha-Ficus sycomorus) which were significantly differentiated by soil pH, electrical conductivity, available soil phosphorus and organic matter, and by elevation. Human disturbance, as quantified by a compound Human Disturbance Index (HDI) significantly affected community composition, species richness and diversity, and was significantly positively correlated with species richness and diversity. The latter is likely due to intermediate levels of disturbance and encroachment of disturbance affiliated shrubs such as Dichrostachys cinerea, Lantana camara, and Acalypha fruticosa. Furthermore, the demographic structure of key woody species such as Acacia polyacantha, Acacia tortilis, Balanites aegyptiaca, Diospyros abyssinica, Lecaniodiscus fraxinifolius and Terminalia brownii, showed impacts of human disturbance.Conclusion – Our results provide a baseline for further conservation actions in the NSNP which should be differentially targeted on the different plant community types. Overall, human disturbance seems not to have resulted yet in species richness declines, although it has started to affect the integrity of the delineated vegetation types and resulted in small scale succession.
Tropical moist evergreen forests provide key ecosystem services for human wellbeing. However, due to human pressure, Afromontane forests have lost much of their natural species composition and structure. In this study, vegetation surveys were carried out with the aim of investigating woody species composition and structure and their drivers of degradation in SW Ethiopia. Woody plant species were identified, forest structure measured and environmental variables determined in 75 plots across four forest patches along an altitudinal gradient. The result shows that the remaining patches still have 63 woody species from 36 families. Our results showed the presence of three plant communities: a first mid-elevation degraded mountain forest community, a second mid-elevation more intact community and a third higher elevation degraded cloud forest community. The Shannon diversity index of the second community was significantly higher than the first and the third community. Exotic tree planting and charcoal production were important determinants of the first community composition. Despite their socioecological importance, the expansion of exotic tree planting showed to be a major threat for natural forest ecosystem. In the study area, intervention is needed to maintain the ecological balance between plantation and natural forest.
Background: Attempts to restore degraded highlands by tree planting are common in East Africa. However, up till now, little attention has been given to effects of tree species choice on litter decomposition and nutrient recycling. Method: In this study, three indigenous and two exotic tree species were selected for a litter decomposition study. The objective was to identify optimal tree species combinations and tree diversity levels for the restoration of degraded land via enhanced litter turnover. Litterbags were installed in June 2019 into potential restoration sites (disturbed natural forest and forest plantation) and compared to intact natural forest. The tested tree leaf litters included five monospecific litters, ten mixtures of three species and one mixture of five species. Standard green and rooibos tea were used for comparison. A total of 1033 litters were retrieved for weight loss analysis after one, three, six, and twelve months of incubation. Results: The finding indicates a significant effect of both litter quality and litter diversity on litter decomposition. The nitrogen-fixing native tree Millettia ferruginea showed a comparable decomposition rate as the fast decomposing green tea. The exotic conifer Cupressus lusitanica and the native recalcitrant Syzygium guineense have even a lower decomposition rate than the slowly decomposing rooibos tea. A significant correlation was observed between litter mass loss and initial leaf litter chemical composition. Moreover, we found positive non-additive effects for litter mixtures including nutrient-rich and negative non-additive effects for litter mixtures including poor leaf litters respectively. Conclusion: These findings suggest that both litter quality and litter diversity play an important role in decomposition processes and therefore in the restoration of degraded tropical moist evergreen forest.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.