Structural Variability Of Mangrove Forests along the Coast of Kenya

Abstract

Mangrove forests occur across a diversity of coastal landforms with different geomorphological, climatic and oceanographic influences. These factors influence mangrove structural development and productivity and as a result, the structural development of mangroves varies with the coastal geomorphology. Earlier inventory studies in Kenya suggest that mangroves growing in north of the Tana River have different structural attributes from those growing south of the river. The current study characterised the structure and floristic composition of mangroves in Kenya by describing species composition, basal area (m2 ha-1), stem density (trees ha-1), importance value index complexity index and above ground biomass (Mg ha-1) across 14 sites spread across the coastline of Kenya. Variability in mangrove floristic composition was tested using analysis of similarities (ANOSIM) and the differences illustrated using non-metric multidimensional scaling (nMDS). Mangrove structural variability was tested using analysis of variance (ANOVA) and comparisons made by performing a post-hoc Tukey pairwise test. A hierarchical cluster analysis was then performed to determine the degree of similarity in mangrove species across the sites based on complexity index, biomass, tree diameter and tree height. To investigate the relationship between mangrove structure and possible drivers of variability, a regression fit model was used. The model described associations between mangrove standing biomass, environmental settings, precipitation, population density, and riverine influence across the sampled sites. Rhizophora mucronata was the most important species in most of the sites while Avicennia marina was the most important species in the estuarine area of Ungwana Bay. High values of structural complexity were observed in the estuarine and deltaic settings of Ngomeni and Kipini while relatively low levels of structural complexity were observed for the periurban mangroves of Mombasa and Mtwapa. Mangrove forest species composition differed significantly across the sampled sites (ANOSIM R: 0.24, p = 0.001). The mangroves of Kipini were significantly different from the rest of the sites. The study revealed significant differences in structural attributes of mangroves growing along the coast of Kenya, specifically, tree diameter [F (13, 34050) =163.01, p=0.000], tree height [F (13, 34050) =1827.28, p=0.000], basal area [F (13, 358) =5.45, p=0.000)], stand density [F (13, 358) =8.68, p=0.000], and standing biomass [F (13, 358) =15.36, p=0.000] across the sampled sites. Environmental settings and population density best explained the variability in mangrove standing biomass. The study suggests that the patterns of mangrove structural variability in Kenya closely follows the patterns of geomorphic variability along the coast. The study concluded that mangroves in Kenya are highly influenced by geomorphological and climatic variability along the coast as well as human influences. These findings are useful for mangrove managers and policy makers and have the potential to guide strategies and actions aimed towards sustainable management of mangrove forests in Kenya.