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This study analyzed bird diversity across Sri Lanka by integrating spatial and temporal observation data with environmental variables including vegetation indices, land cover, urbanization metrics, and pollution levels. The research found that land cover type is a stronger predictor of bird diversity than individual environmental variables, while urbanization shows scale-dependent effects that favor generalist species but reduce overall species richness. The analysis employed multiple spatial scales and statistical models to account for sampling bias and observation effort variations.
Why it matters
The findings provide a reproducible framework for biodiversity monitoring and conservation planning in tropical regions. Understanding how urbanization and land use affect bird communities can inform urban planning policies and habitat conservation strategies to maintain avian diversity in rapidly developing areas.
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arXiv:2607.00582v2 Announce Type: replace
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.
Source: How Environment and Urbanization Shape Bird Diversity in Sri Lanka