A new Vegetation-Plot Database for the Coastal Forests of Kenya

Biodiversity data based on standardised sampling designs are key to ecosystem conservation. Data of this sort have been lacking for the Kenyan coastal forests despite being biodiversity hotspots. Here, we introduce the Kenyan Coastal Forests Vegetation-Plot Database (GIVD ID: AF-KE-001), consisting of data from 158 plots, subdivided into 3,160 subplots, across 25 forests. All plots include data on tree identity, diameter and height. Abundance of shrubs is presented for 316 subplots. We recorded 600 taxa belonging to 80 families, 549 of which identified to species and 51 to genus level. Species richness per forest site varied between 43 and 195 species; mean diameter between 13.0 ± 9.8 and 30.7 ± 20.7 cm; and mean tree height between 5.49 ± 3.99 and 12.29 ± 10.61 m. This is the first plot-level database of plant communities across Kenyan coastal forests. It will be highly valuable for analysing biodiversity patterns and assessing future changes in this ecosystem. Taxonomic reference: African Plant Database (African Plant Database version 3.4.0). Abbreviations: DBH = diameter at breast height; GIVD = Global Index of Vegetation-Plot Databases; KECF-VPD = Kenyan Coastal Forests Vegetation Plot Database

Coastal Forests of Kenya-Ecology, Biodiversity & Conservation

Aims: the broad objective of this study is to investigate the ecological, biodiversity and conservation status of the coastal forests of Kenya fragments. The specific aims of the study are: (1) to investigate current quantitative trends in plant diversity; (2) develop a spatial and standardised vegetation database for the coastal forests Kenya; (3) investigate forest structure, species diversity and composition across the forests; (4) investigate the effect of forest fragment area on plant species diversity; (5) investigate phylogenetic diversity across these coastal remnants (6) assess vulnerability and provide conservation perspectives to concrete policy issues; (7) investigate plant and butterfly diversity correlation. Methods: I performed various analytical methods including species diversity metrics; multiple regression models for species-area relationship and small island effect; non-metric multidimensional scaling; ANOSIM; PERMANOVA; multiplicative beta diversity partitioning; species accumulation curve and species indicator analysis; statistical tests, rarefaction of species richness; phylogenetic diversity metrics of Phylogenetic diversity index, mean pairwise distance, mean nearest taxon distance, and their null-models: and Co-correspondence analysis. Results: developed the first large standardised, spatial and geo-referenced vegetation database for coastal forests of Kenya consisting of 600 plant species, across 25 forest fragments using 158 plots subdivided into 3160 subplots, 18 sacred forests and seven forest reserves; species diversity, composition and forest structure was significantly different across forest sites and between forest reserves and sacred forests, higher beta diversity, species-area relationship explained significant variability of plant diversity, small Island effect was not evident; sacred forests exhibited higher phylogenetic diversity compared to forest reserves; the threatened Red List species contributed higher evolutionary history; a strong correlation between plants and butterfly diversity. Conclusions: This study provides for the first time a standardized and large vegetation data. Results emphasizes need to improve sacred forests protection status and enhance forest connectivity across forest reserves and sacred forests

Plant Species Diversity of Kenyan Coastal forests: Gaps of knowledge

The coastal eco-region of Kenya, Africa, is known for high levels of endemism on the African continent for plant and other taxa like birds, butterflies, and amphibians. The continued management and survival of these forests has been through different means such as government protection, traditional management of sacred forests, and local community engagement. Forest-adjacent communities have always relied heavily on forest resources for their livelihood. Currently, these forests are facing an increasing pressure from local economic development and surrounding urban expansion. Therefore a pressing challenge is to conciliate sustainable forest management with community needs. In some forests, butterfly farming was introduced as a management strategy to address this challenge. Experience so far shows that butterfly farming has been a viable approach for reshaping the community’s relation to the forest, supporting conservation, improving livelihoods , and creating social enterprises. Overall, knowledge about status and trends of biodiversity is the baseline for enhancing conservation strategies. Plant diversity is the crucial factor for the ecosystem productivity and services of the coastal forests. This affects the ecological processes and ecosystem services they provide. There is therefore need for an update on the plant species checklists, their values on the forest and uses by forest reliant communities. Here we investigated the knowledge status on plant species diversity, distribution, and plant conservation status across coastal forests in Kenya. The occurrences of more than 3,000 species were recorded in 16 patches of coastal forests. Due to lack of data and variation in sampling methods, data of species richness are affected by major biases across the national forest parks of Arabuko Sokoke Forest, Shimba Hills and sacred sites. Thus, there is an urgent need to assess and improve the knowledge base of Kenyan coastal forests biodiversity through standardized field sampling. Such information is needed to better guide forest management, conservation policy and human interventions at both local and regional scales. Key words: Plant species diversity, coastal forests, forest management, local community engagement, KenyapeerReviewe