LB 41-347 - Scale Dependency of Canopy Structure on Bird Diversity in Urban Areas

Effective urban greenspace planning and management requires a robust understanding of the relationship between urban green spaces and biodiversity. Complex vegetation structure has been strongly linked to bird species diversity. LiDAR data can characterize three-dimensional (3D) canopy structures across large areas but there is currently no consensus on the appropriate spatial scales for calculating LiDAR-derived canopy metrics to assess bird species diversity in urban areas. This study aims to assess the capacity of urban greenspace to provide suitable habitat to support diverse bird communities by 1) examining the relationship between vegetation 3D structures (configuration and distribution) and urban biodiversity, and 2) identify the scale dependency of LiDAR-derived canopy metrics by analyzing data across different buffer sizes.The study was conducted in Cook, DuPage, and Lake counties, part of the greater Chicago region, in Illinois, USA. These counties encompass a range of urbanized areas, from dense urban cores to suburban residential neighborhoods. We used eBird to gather information on bird species observations across the study area site. To analyze the scale dependency of LiDAR-derived canopy metrics, we created buffer areas ranging from 25 m to 1,000 m around the filtered eBird observation points. We then calculated LiDAR-derived canopy structural metrics (e.g., height, canopy density, complexity and openness) inside each buffer area. Finally, we used negative binomial models to examine the relationship between bird species richness and the LiDAR-derived canopy metrics at different spatial scales. The results show that exterior canopy complexity (top rugosity, roughness) had a positive correlation with bird species richness, while interior canopy complexity (Gini index, evenness of vertical canopy distribution) had a negative correlation with bird species richness, indicating that a more complex canopy structure can be beneficial for bird species in urban areas. Furthermore, canopy structures had variable relationships with bird species diversity observations, which depended substantially on the scale at which these relationships were examined. For example, top rugosity and Gini index were strongly correlated with bird diversity as neighborhood scale increased, while canopy density was insensitive to scale. This highlights the importance of considering scale dependence when using LiDAR data to assess urban biodiversity. Our study can contribute to more effective urban greenspace planning and management, which can help to support biodiversity conservation efforts in urban areas.