Wildfire Incidence Data from Juaso Forest District, Ghana (2014–2024)

This dataset provides a structured compilation of wildfire incidence records integrating both global contextual information and detailed regional data from the Juaso Forest District in the Ashanti Region of Ghana. The dataset was developed to support research on wildfire dynamics, drivers, and management strategies within complex socio-ecological systems. The Juaso Forest District dataset spans a ten-year period (2014–2024) and includes wildfire occurrence records across multiple forest reserves, including Bandai Hills, Bandai North, Dome River, North Formangso, Onyimso, and South Formangso. Variables captured include year of occurrence, location (forest reserve and compartment level where available), area burned (hectares), forest type, and identified causes of wildfire (e.g., farming, hunting, arson, and unknown sources). The dataset also incorporates qualitative classifications derived from field-based assessments and stakeholder interviews, providing insights into anthropogenic drivers, socio-economic influences, and management interventions such as firebreaks, green firebreaks, and awareness campaigns. Globally, wildfire occurrence is influenced by interactions between climatic conditions, vegetation characteristics, and human activities. This dataset contributes to understanding these dynamics by linking empirical wildfire records with socio-ecological drivers in a tropical forest context. It is particularly relevant for examining non-linear wildfire trends, spatial heterogeneity in fire incidence, and the effectiveness of management strategies in reducing fire risk. The dataset is suitable for: Time-series analysis of wildfire incidence and trends Spatial analysis of fire distribution across forest reserves Investigation of human–environment interactions driving wildfire occurrence Evaluation of wildfire management and prevention strategies All data were obtained from the Forest Service Division (FSD) and Resource Management Support Centre (RMSC) in Ghana, complemented by field interviews and observational assessments. Ethical considerations were followed, and all qualitative data have been anonymised. Keywords: Wildfire, Forest fire, Ghana, Juaso Forest District, Fire incidence, Socio-ecological systems, Fire management, Tropical forests, Anthropogenic drivers, Ecological complexity Data Collection Period: 2014–2024 Geographic Coverage: Juaso Forest District, Ashanti Region, Ghana (West Africa) Methodology Summary: A mixed-methods approach was used, combining quantitative wildfire records with qualitative interview data from forest managers, local communities, and stakeholders. Secondary data were analysed using descriptive statistics, while qualitative data were used to contextualise wildfire drivers and management effectiveness.t