Woody plant species diversity of the coastal forests of Kenya: filling in knowledge gaps in a biodiversity hotspot

Abstract

The coastal forests of Kenya are global biodiversity hotspots known for rich plant diversity and endemism. They exist as fragmented forest islands, and their current conservation status and quantitative trends in plant diversity are understudied. We investigated these knowledge gaps by providing a comprehensive literature review and comparing to field data collected using standardized sampling protocol. Our goals were to build a robust basis for future analyses, biodiversity monitoring, and to understand the role of fragment area in determining species richness. We recorded a total of 937 woody species belonging to 88 families in 30 forest patches from reviewed and sampled data. Species richness per site from literature review was affected by biases in data scarcity, forest size and variation in sampling methods. In general, large forests reserves of Shimba hills and Arabuko exhibited a high number of cumulative species compared to smaller forest patches. Species-area relationship showed a significant proportion of species richness per forest was determined by forest area, according to Arrhenius model. This study is the first to review forest patch woody plant species diversity knowledge gaps in the coastal forests of Kenya, and the resulting comparison provides the first quantitative overview and foundation of these forests.

Keywords:

• Biodiversity knowledge
• coastal forests
• conservation
• plant species diversity
• sacred forests
• sampling gaps
• species richness
• Kenya

Acknowledgements

Authors are indebted to the data review sources that led to the compilation of the review dataset. These included both published and grey sources. We thank Dr Wayne Edwards who carried out his vegetation research work on coastal forests of Kenya under funding from the Wild Planet Trust, UK. We acknowledge the botanists and guides in Kenya and the UK team for their support to this research: Erustas Kanga (Kenya Wildlife Service), Willy Kombe (Kenya Wildlife Service), Saidi (Diani Beach botanist), Bakari (Kipini Conservancy botanist), Dr Simon Tollington (Durrel University), Dr Amy Plowman (Wild Planet Trust), Dr Andrew Bowkett (Wild Planet Trust), Dr Natasha De Vere (Wild Planet Trust), Dr Stephen Burchett (University of Plymouth), Dr Wayne Edwards (Wild Planet Trust). We also thank James C. Moomaw and Thomas N.R for their work and data on the coastal forest of Kenya. We thank the online data sources for Moomaw JC (1960) and Thomas NR (1984) through https://edepot.wur.nl/493400. We thank Chiara Lelli for contribution to earlier poster presentation work of the review data. We are grateful to the review data sources of Burgess and Clarke (2000), Burgess et al. 1998, Luke (2005), Kenya Forest Research Institute (KEFRI) and Arocha Kenya online technical reports, that formed source to data from Robertson (1987), Robertson and Luke (1993). We thank the team that led to the field sampled dataset. Our special thanks to Saidi Chidzinga for field sampling and plant specimen identification, Geoffrey Mashauri and Abbas Shariff for assistance in plant identification and knowledge of the Coastal forests. We are grateful to the colleagues who helped in setting the field work, sampling and support during the entire field period: Lawrence Chiro and Abdulrahman Matano of Coastal forests conservation unit-NMK; Joseph Muthini of Kenya Forest Research Institute and George Wara and Blessingtone Magangha of Kenya Forest Service.

Disclosure statement

The authors have declared that no competing interest exist.

Data availability

The reviewed dataset and part of the sampled dataset are included in the article as appendix and can be provided as supplementary material. They will also soon be accessed on Zenodo.org data repository.

The sampled dataset can be referred to Fungomeli et al. (2020). It is presently stored at the University of Bologna. Its availability is currently restricted to the PhD project within which it was developed. Possible uses by other interested researchers are presently limited on the bases of specific agreement to be discussed with the database administrators. The data will soon be available on sPlot – the global vegetation plot database (Bruelheide et al. 2019).