Constructing an ecological network integrating avian biodiversity and ecosystem services in highly urbanized areas: A Case Study of Tianjin, China

Abstract

Rapid urbanization has caused significant biodiversity loss and a decline in ecosystem services, directly impacting human well-being. Developing an ecological network that integrates both biodiversity and ecosystem services could enhance the effectiveness of conservation efforts. However, research in this field remains limited, particularly in highly urbanized regions. This study focuses on Tianjin, China, and employs multiple models, including MaxEnt and InVEST, to identify priority conservation areas. A total of 228 protected bird species with diverse ecological niches were selected as biodiversity conservation targets. Water retention, soil retention, carbon sequestration, habitat quality, temperature regulation, and natural recreation were defined as targets for ecosystem service conservation. We analyzed the spatial relationship between avian biodiversity and ecosystem services and evaluated the conservation status of protected areas. The Minimum Cumulative Resistance (MCR) model was used to construct an ecological network that integrates avian biodiversity and ecosystem service hotspots. The results indicate that: (1) there is a synergistic relationship between avian biodiversity and both individual and comprehensive ecosystem services in Tianjin, supporting the feasibility of integrated conservation; (2) the coverage of protected areas over overlapping avian biodiversity and ecosystem service hotspots (core ecological zones) is only 37.7 %, revealing significant conservation gaps; (3) the ecological network identified 20 ecological sources and 31 important corridors, with spatial conservation management recommendations provided. This study incorporates multiple ecological protection indicators, which improve the ecological representativeness of sources within the network and provides valuable insights for constructing ecological networks in highly urbanized regions.