Assessment of Urban Ecosystem Services Provided by Animal Communities in Metropolitan Regions
Keywords:
Urban ecosystem services, Urban animal communities, Biodiversity conservation, Artificial intelligence, Geographic Information Systems (GIS), Remote sensing, Ecosystem service assessment, Sustainable urban planning, Smart cities, Climate resilience.Abstract
Metropolitan ecosystems have been seriously impacted by fast urbanization, resulting in loss of ecosystem service delivery, biodiversity loss and fragmentation of habitat. Urban animal communities have an important role to play in maintaining ecological balance through pollination, biological pest control, nutrient cycling, maintenance of habitats and cultural ecosystem services, but they are not sufficiently quantified in conventional urban ecosystem assessments. This study suggests a framework integrating AI to evaluate ecosystem services of urban animal communities that will be applicable to metropolitan areas. It integrates ecological and biodiversity indicators with Geographic Information Systems (GIS), remote sensing, Internet of Things (IoT) sensors, environmental quality indicators, artificial intelligence and Multi-Criteria Decision Analysis (MCDA) into a holistic platform for the evaluation of ecosystem services. Biodiversity index, pollination efficiency, environmental quality, climate resilience and sustainability performance indicators were used to compare the biodiversity of representative metropolitan regions. The results show that well connected green infrastructure in metros achieved better scores in biodiversity indices (91), pollination efficiency (89%), environmental quality (90), climate resilience (88%) and overall sustainability score (90) than the highly urbanized metros (60 – 67). In addition, the best results were obtained for the regulation of ecosystem services (93%), followed by supporting (90%), cultural (87%) and provisioning services (81%). The framework is designed for ongoing monitoring of biodiversity, spatial analysis, and decision making based on evidence and intelligence for urban planners and decision makers. The study shows how the integration of biodiversity conservation and AI-based environmental assessment can significantly improve the resilience, adaptation to climate change and sustainable development of metropolitan regions.