Urban ecosystems (UE) are among the most prominent examples of socio-ecological systems. These highly anthropogenic environments are widespread across the globe and currently host more than 50% of the world's human population—rising to 80% in highly developed nations. Despite their artificial nature, urban ecosystems have the potential to support rich biodiversity and even contribute to its conservation. In some cases, they serve as refuges for endangered species.
Beyond conservation, urban biodiversity provides numerous benefits to human societies, including carbon sequestration, air and water purification, and protection against extreme weather events such as heatwaves. However, biodiversity-rich urban areas also present certain challenges. First, cities often act as entry points and suitable habitats for invasive alien species, potentially disrupting local ecosystems. Second, the close and frequent interactions between humans and urban wildlife increase the risk of zoonotic disease transmission, raising concerns about infectious disease outbreaks.
As urban development accelerates and the demand for sustainable, eco-friendly cities grows, understanding human-wildlife interactions in urban environments is more critical than ever. Addressing these complexities is essential for designing cities that balance biodiversity conservation, public health, and human well-being.
To explore how urbanization shapes species distribution at the landscape scale, I applied multivariate and machine-learning-based niche modeling techniques. My findings revealed that ant species respond differently to urban environmental factors such as the urban heat island effect and habitat fragmentation. In some species, these responses were also climate-dependent. This study underscored the importance of viewing urbanization as a multifactorial environmental change with complex, context-dependent effects on ecological communities.
Using the invasive ant Lasius neglectus as a model system, I investigated how different types of ecological data (presence-only, presence/absence, and population size) influence our understanding of the link between urbanization and biological invasions. The results demonstrated that the observed relationship varied depending on the dataset used, providing empirical evidence of how sampling bias shapes our perception of ecological processes. This study also suggested that invasive species may be more abundant in remote, biodiversity-rich habitats than previously assumed, highlighting the need for more comprehensive and unbiased data collection methods.