Assessing the performance of restored landscapes using tree species diversity and carbon stocks in selected forest types of Kenya
Abstract
This study investigated the performance of three recently restored forests of Kakamega (tropical rainforest), Kaberua (moist-montane), and Kabaru-Naromoru (dry-montane) to inform restoration strategies that balance ecological and climate change mitigation goals. Using data from 43 plots with 7-year-old native trees, biodiversity was assessed using Shannon–Wiener (H') and Simpson's (D) indices. Forest sustainability was evaluated using reverse J-curves and carbon sequestration was estimated using IPCC guidelines and an allometric equation by Chave et al. 2014. Results revealed low sequestration rates in the early growth phase of native trees with 1.70, 1.36 and 0.63 tCO 2 e/ha/yr for Kabaru-Naromoru, Kakamega and Kaberua, respectively. Low survival was identified in all forests. The relationship between tree numbers in increasing diameter sizes was sustainable, with R 2 values above 0.92. Kakamega had the highest diversity (H’ = 1.50, D = 0.77), Kaberua (H’ = 1.13, D = 0.68) and Kabaru-Naromoru the lowest diversity (H’ = 0.68, D = 0.44). Spearman's rank correlation analysis showed no significant correlation between Shannon Wiener biodiversity index and carbon accumulation across the three sites: Kakamega (rho = −0.34, p = 0.22), Kaberua (rho = 0.30, p = 0.30) and Kabaru-Naromoru (rho = 0.25, p = 0.39). The association between forests' stock accumulation and Simpson's Diversity Index varied across forests, with Kakamega showing a significant moderate negative correlation (rho =−0.56, p = 0.031). These findings suggest that tree diversity-carbon relationships are context-dependent, with areas of high carbon build-up using fewer but fast-growing species instead of restoration that uses a wider scope of species. This highlights the need for tailored restoration strategies to optimise ecological and climate outcomes.
Fields of Study & Subjects
Forest ecology and management
Conservation
Biodiversity
and Resource Management
African Botany and Ecology Studies
Publication details
- Journal / source
- Discover Forests
- Volume
- 2
- Issue
- 1
- Publication date
- 7 January 2026
- Language
- EN