By Maria Fungomeli, Anthony Githitho, Fabrizio Frascaroli, Saidi Chidzinga, Marcus Cianciaruso & Alessandro Chiarucci
After two years of intense research work as a collaboration between the University of Bologna and the National Museums of Kenya, we produced the first standardised data set of the coastal forests of Kenya. This data set is the first to develop a systematic collection of plant community data, that can be used for monitoring and conservation of this biodiversity hotspot. It contains rich data that has been surveyed across a large proportion of the present existing forest remnants, ranging in size from 10 to 42,000 ha. The data set consists of plant community data recorded in 158 plots subdivided into 3160 subplots, within 25 forest fragments. All plots include data on tree identity, diameter at breast height and height. The abundance of shrubs is presented for 316 subplots. We recorded 600 taxa belonging to 80 families, 549 of which were identified to species and 51 to genus level.
The coastal forests of Kenya are an intriguing biodiversity hotspot in the tropical African forest fragments, presenting rich biodiversity and high endemism. They are known to support local livelihoods while playing a major role as high conservation value ecosystems. However, they face threats from increasing anthropogenic activities coupled with climate change effects. These threats have led to their degradation and deforestation, which has reduced the ecosystem services and livelihoods-support they can provide. It is in this context that we call for their quantitative biodiversity ecological survey that can be a foundation to guide conservation measures.
We found high values of plant species diversity across the 25 surveyed forest remnants, with results displaying differences in species composition and forest structure for each forest. We look forward to providing detailed information on the current biodiversity status of these ecosystems and develop a conservation plan model for future monitoring. We are currently preparing papers on the plant diversity patterns across these forests, and the data set will be soon integrated into global infrastructures such as sPLot.
This is a plain language summary for the paper of Maria Fungomeli et al. published in the Vegetation Classification and Survey (https://doi.org/10.3897/VCS/2020/47180).