OLAGOKE Adewole Olasiyan (Basic Profile)
Other Names Adewole Olasiyan
Post Assistant Lecturer
Email Address aoolagoke[at]futa.edu.ng; adewoleolagoke[at]gmail.com
Telephone +234-810-291-9537
Nationality NIGERIA
Affiliations Member, Commonwealth Forestry Association; Member, Society for Wetland Scientists; Member, Forests and Forest Products Society
Education MSc Tropical Forestry and Management, Dresden University of Technology, Germany (2012); MSc Environmental Forestry, Bangor University, United Kingdom (2011); B. Agric. Tech. Forestry and Wood Technology, Federal University of Technology Akure, Nigeria (2007)
Background My research focuses on functional ecology and systematics of tropical forests. I am interested in applying quantitative techniques to explore the ecological processes that structure and maintain plant population distribution and diversity in space and time, from the nature of the complex local neighbourhood interactions, plant-to-plant and plant-to-environment interactions, morphological adaptations and regeneration patterns, to resilience and functional stability for continuous supply of ecosystem services in dynamic environment. Specific field experiences traverse tropical humid forests in Nigeria, dry forests in Costa Rica and mangrove forest ecosystems in the coasts of Kenya and Brazil. My doctoral research seeks to provide insights into plant trait plasticity – environmental stress correlations and the associated consequences for ecosystem structure and functioning of mangrove forests, with field sites located in the Amazon-Influenced Coasts in Bragança (Brazil) and French Guyana. I am combining field-based data of tree architecture from contrasting coastal conditions, to be rendered in a Tree Architecture Model (AmapStudio XPLO) with Individual Based Simulation Modelling approach (MesoFON model) to answer a key question: how do mangrove species adapt tree morphology in changing coastal situations? My research also relies on multivariate statistics, including spatial point pattern statistics and Hierarchical Bayesian inference. The overall goal of my research is to improve the understanding of how such knowledge can be applied in predicting and managing the ecological consequences of rapidly changing climate, as well as to aid decision-making processes in ecosystem restoration and conservation.