How Environment and Urbanization Shape Bird Diversity in Sri Lanka

2026-07-01

AI Summary

This study investigates the influence of environmental factors and urbanization on avian diversity patterns across Sri Lanka. Integrating multisource remote sensing and bird observation data, the research employs spatial rarefaction, Poisson generalized linear models, and β-diversity analyses to develop multiscale spatiotemporal models. Findings indicate that land use categories outperform single continuous variables in predicting bird species richness, and that artificial light at night (ALAN) exerts scale-dependent effects on diversity. The study elucidates the critical roles of land cover and urbanization in shaping avian community structure and establishes a transferable framework for biodiversity assessment and conservation planning.

Abstract

This study presents a comprehensive analysis of bird diversity across Sri Lanka by integrating spatial, temporal, and environmental data. Bird observation records were combined with environmental variables, including weather conditions, air pollution, the Normalized Difference Vegetation Index (NDVI), land cover, elevation, and Artificial Light At Night (ALAN), and rigorously preprocessed to ensure data quality. Spatial analyses were conducted on multiple grid scales (2 km, 5 km, 10 km) to evaluate patterns in species richness while minimizing sampling bias through spatial thinning. Temporal trends were assessed using effort-corrected metrics including rarefied richness and occupancy rates to account for variations in observation effort over time. Environmental drivers of bird diversity were examined using multivariate statistical models, including Poisson Generalized Linear Models (GLMs) and correlation analyses, to identify key associations between ecological factors and species richness. Additionally, community structure, dominance patterns, and beta diversity were analyzed to understand variations in species composition across regions and time. The study found that land-cover type is a stronger predictor of bird diversity than individual continuous variables such as NDVI or temperature alone. Urbanization, measured by ALAN, exhibits nuanced scale-dependent effects, supporting high abundances of a few generalist species while reducing overall richness. The findings provide actionable insights into the patterns and drivers of avian diversity in Sri Lanka, offering a scalable and reproducible framework for biodiversity research and conservation planning.

Problem

• bird diversity
• urbanization
• environmental drivers
• land cover
• Artificial Light At Night

Innovation

• multiscale spatial analysis
• effort-corrected diversity metrics
• Poisson GLM
• Artificial Light At Night (ALAN)
• land-cover heterogeneity