Wet–dry seasonal transitions drive butterfly community dynamics more than habitat type in a tropical rainforest fragment
Abstract
Abstract Seasonal climatic variability is a fundamental driver of ecological processes in tropical forests, yet its influence relative to habitat heterogeneity remains insufficiently understood for many insect groups. Butterflies are particularly responsive to environmental change and are widely recognised as sensitive indicators of ecosystem condition. This study evaluated the relative effects of seasonal transitions and habitat type on butterfly community dynamics in the Kakamega Forest ecosystem, the easternmost remnant of the Guineo–Congolian rainforest in Africa. Butterflies were surveyed weekly from January to June 2024 across six forest cover types representing a gradient of disturbance and land-use intensity, while precipitation, temperature, relative humidity and wind speed were monitored concurrently. A total of 10,334 individuals representing 146 species, 64 genera and five families were recorded. Butterfly abundance, species richness and Shannon diversity increased significantly during the wet season across habitat types. Although natural and secondary forests supported the highest abundance and diversity, seasonal variation explained a greater proportion of community variation than habitat type. Community composition differed significantly between seasons, with non-metric multidimensional scaling showing distinct seasonal clustering. Behavioural activity also varied seasonally, with feeding and mating increasing during the wet season, while resting and basking predominated during the dry season. Environmental modelling identified precipitation, particularly one-month-lagged rainfall, as the strongest predictor of butterfly abundance, highlighting the importance of moisture-mediated ecological processes. These findings demonstrate that temporal climatic variability can outweigh habitat heterogeneity in structuring tropical butterfly communities and emphasize the need to incorporate seasonal dynamics into biodiversity monitoring and conservation under changing rainfall regimes.