As urbanization accelerates worldwide, understanding the impact of urban expansion on habitat quality has become increasingly critical in environmental science research. This study examines the impact of urban expansion on habitat quality in Beijing, forecasting land cover changes and ecological effects by 2030. Using CA–Markov and FLUS models, the research analyzes habitat quality from 2000 to 2030 through the InVEST model, revealing a significant urban land increase of 1316.47 km² and a consequent habitat quality decline. Predictions for 2030 indicate varying habitat quality outcomes across three scenarios: ecological priority (0.375), natural growth (0.373), and urban development (0.359). We observed that the natural growth scenario forecasts a further decline in habitat quality, primarily due to increased low–value habitat regions. Conversely, the ecological priority scenario projects a notable improvement in habitat quality. To mitigate habitat degradation in Beijing and enhance regional habitat quality and ecological conditions, it is recommended to control urban land cover expansion, adopt effective ecological conservation policies, and systematically carry out national spatial restructuring and ecological restoration. This research provides vital decision–making support for urban planning and ecological conservation, emphasizing the need for comprehensive land cover and ecological strategies in urban development. Additionally, our findings and methodologies are applicable to other rapidly urbanizing cities worldwide. This demonstrates the broader applicability and relevance of our research, providing a framework for sustainable urban planning in diverse global contexts.

The decline in biodiversity poses a serious threat to natural ecosystems and has become one of the most pressing global environmental issues. Establishing conservation priorities for protected areas (PAs) is one of the most direct and effective biodiversity conservation measures. However, conservation gaps arise as a result of existing problems in spatial layout of PAs, including overlapping protection scopes, artificial fragmentation of natural ecological regions, as well as “over‐protection” and “over‐exploitation.” To optimize the spatial layout of PAs and improve the efficiency of biodiversity conservation, we employed the Habitat Quality module of the Integrated Assessment of Ecosystem Services and Tradeoffs (InVEST) model and the Maximum Entropy (MaxEnt) model to assess the PAs in the Songnen Plain, China. The combined model (MaxEnt‐InVEST) revealed that the conservation priorities for PAs in the Songnen Plain occupied a total area of 14,764.14 km ² (10.24% of the total area of the Songnen Plain). The conservation priorities outside PAs occupied a total area of 7858.45 km ² (5.45% of the total area of the Songnen Plain) and were primarily distributed in the northeastern, central, and southwestern regions of the Songnen Plain. This indicated that existing PAs did not offer adequate protection for local biodiversity. The consistency of our combined modeling framework was 72.11%, which enabled a more accurate assessment of biodiversity hotspots and respects the land uses of the Songnen Plain. In addition, the modeling framework successfully created maps of conservation gaps of biodiversity hotspots based on actual species distribution data and considers current land uses. Our study was aimed at optimizing the spatial conservation efficiency of the Songnen Plain by assessing the conservation gaps in the Songnen Plain. It could provide a reference for the future development of a PA system centering on national parks.

Understanding cultural keystone species (CKS) is fundamental to preserving biocultural diversity, yet prior studies often focus on single species, qualitative data, and minority regions. This study examines CKS in a non‑indigenous rural area through three complementary analyses. A participatory survey (274 respondents) recorded 91 plant species, of which 42 were classified as CKS using quantitative criteria. Species with more uses had higher cultural importance. Social perception analysis identified income as a predictor of individual CKS valuation, while community‑level recognition showed no socio‑demographic association. Ecological analyses suggested that patch area was associated with shrub diversity in Lindera glauca communities, while associations in Quercus forests were not significant; in pond habitats, road proximity and pond area were related to herbaceous evenness. Together, these three analyses link plant‑use records, social perceptions, and habitat ecology through a common survey base and species list, providing a framework for integrating local knowledge with ecological assessment.