Kenya Butterfly Urban Adaptation Study

Abstract

Biodiversity monitoring in tropical regions remains challenging due to limited systematic surveys and data availability. Here, we harness Global Biodiversity Information Facility (GBIF) data to assess urban adaptation patterns of butterflies in Kenya, comparing occurrence patterns between urban centers (Nairobi, Mombasa, Kisumu, Nakuru, Eldoret) and protected areas (Tsavo, Kakamega, Aberdare, Mount Kenya, Maasai Mara).

We compiled 3,193 butterfly occurrence records across nine species from 2000–2024, with Junonia oenone (n=438) being the most abundant. Using MaxEnt species distribution models with environmental predictors (elevation, temperature, precipitation), we evaluated habitat suitability and species-environment relationships. Our models achieved moderate predictive performance (AUC = 0.606), suggesting J. oenone exhibits generalist habitat preferences with weak environmental specialization.

Urban areas contained 12.3% of observations, while protected areas harbored 8.7%, suggesting butterflies readily adapt to human-modified landscapes. Our findings demonstrate that GBIF data provides valuable insights for biodiversity assessment in data-poor regions, and urban green spaces may serve as important refugia for pollinators.

Keywords: Species distribution models, MaxEnt, urban ecology, butterflies, Kenya, GBIF, conservation planning

Key Figures

Figure 1: Species Abundance

Butterfly species abundance in Kenya based on GBIF records (2000–2024). Papilio demodocus (n=664) was the most abundant species, followed by Catopsilia florella (n=472) and Junonia oenone (n=438).

Figure 2: Study Area

Study area showing five major urban centers (red, 15km buffers) and five protected areas (green, 30km buffers) in Kenya.

Spatial distribution of 3,193 butterfly occurrence records across Kenya, colored by species. Data: GBIF (2000–2024).

Habitat suitability model for Junonia oenone. Warmer colors indicate higher suitability. White points show occurrences (n=438). AUC = 0.606.

Variable importance for Junonia oenone SDM. Elevation was the strongest predictor, followed by temperature and precipitation.

Response curves showing relationship between environmental variables and habitat suitability for Junonia oenone.

Species composition comparison between urban and protected areas. Papilio demodocus dominates urban sites.

Tables

Key Findings

Urban Adapters

Papilio demodocus (45%) and Danaus chrysippus (28%) dominate urban areas, showing adaptation to human-modified landscapes.

Forest Specialists

Charaxes brutus shows strong association with protected areas (62% of observations), indicating sensitivity to habitat modification.

Generalist Species

Junonia oenone exhibits broad environmental tolerance (AUC = 0.606), occurring across wide elevational and climatic gradients.

Elevation Preference

Peak occurrence in mid-elevations (500–1500m: 42%), with 31% in lowlands and 27% in highlands.

Discussion

Conservation Implications

• Urban green spaces are vital for maintaining butterfly diversity in cities — 12.3% of observations occurred in urban areas
• Protected areas remain crucial for forest-dependent species like Charaxes brutus
• Elevation gradients within and around cities could serve as climate refugia under warming scenarios
• Citizen science (GBIF) provides valuable data for biodiversity monitoring in data-poor regions

Limitations

• Sampling bias toward accessible areas (roads, cities, parks)
• Temporal mismatch (records span 24 years)
• Environmental data resolution (1–5km) may miss fine-scale habitat heterogeneity
• Potential species misidentifications in citizen science data

Conclusion

This study demonstrates that:

1. GBIF data provides valuable insights for biodiversity assessment in data-poor regions
2. Common butterfly species in Kenya show remarkable habitat flexibility
3. Urban green spaces serve as important refugia for pollinators
4. Elevation and temperature are primary drivers of butterfly distributions

We recommend integrating citizen science with systematic surveys to enhance biodiversity monitoring and inform urban planning for pollinator conservation in East African cities.

Originally published at https://daniell22-dot.github.io.