Study on the Distribution Patterns and Driving Mechanisms of Urban Plant Diversity in Green Building Demonstration and Non-Demonstration Areas of Jinan, China

Urban street greenery plays a crucial role in enhancing biodiversity, environmental quality, and human well-being. However, how different street greening strategies shape urban plant diversity across functional urban contexts remains insufficiently understood. Taking Jinan, a rapidly urbanizing city in China, as a case study, this research investigates the spatial patterns, compositional differences, and driving mechanisms of plant diversity between Green Streets (GS) and Non-Green Streets (NGS) across various Urban Functional Units (UFUs). A 1 km × 1 km grid was used to delineate UFUs, combined with field-based plant surveys, linear regression analyses, and the public space assessment framework of Sustainable Development Goal (SDG) 11.7.1. Results indicate that plant diversity is strongly dependent on urban functional types, with higher species richness observed in residential and recreation/leisure districts, and lower levels in industrial, commercial, and transportation districts. The ecological effects of GS exhibit clear context dependence, being more pronounced in residential, educational, and public service areas, but limited in commercial and industrial zones. NGS recorded a significantly higher total number of plant species (346) than GS (116), with NGS dominated by native spontaneous species and GS characterized by introduced cultivated plants, reflecting the filtering effects of different management intensities. Management variables, particularly watering (positive) and fertilization frequency (negative), is primarily positively associated with plant diversity in GS, whereas diversity in NGS is more closely associated with socio-economic and spatial factors such as UFU area and housing prices. Furthermore, the current SDG 11.7.1 indicator emphasizes the quantity and accessibility of public spaces but insufficiently captures their ecological quality. This study highlights the need to integrate biodiversity and vegetation structural complexity into public space assessments, providing scientific support for quality-oriented urban green infrastructure planning and sustainable urban development.