Objective Rapid urbanization has profoundly reshaped land-use patterns and ecological processes in global mega-urban regions, posing major challenges to habitat sustainability and regional ecological security. As one of the most densely populated and intensively developed urban agglomerations in China, the Guangdong−Hong Kong−Macao Greater Bay Area (GBA) accommodates nearly 5% of the national population and generates over 12% of the gross domestic product (GDP) on less than 0.6% of the national land area. This highly compact development model has driven the continuous expansion of construction land at the expense of cropland, forest, grassland, and aquatic ecosystems, resulting in increasing habitat degradation and ecological pressure. Although previous studies have examined habitat quality or ecological patterns in the GBA, most have focused on static assessments or single-period analyses and rarely integrated historical evolution, future land-use simulation, and mechanisms of contribution within a unified analytical framework. Moreover, uncertainties remain regarding how different development pathways may shape future habitat quality trajectories. Against this background, this study aims to systematically investigate the spatiotemporal evolution of habitat quality in the GBA from 2000 to 2020, quantify the contribution of land-use transitions to habitat quality change, and explore the potential responses of habitat quality under multiple land-use scenarios through 2030. By coupling the patch-generating land use simulation (PLUS) model with the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) habitat quality module, this research seeks to provide scientific evidence for regional ecological governance, spatial planning optimization, and sustainable development strategies in high-density urban agglomerations.

Methods This study integrates land-use analysis, habitat quality assessment, and scenario-based simulation within a coupled PLUS−InVEST modeling framework. Multi-period land use/land cover data for 2000, 2010, and 2020 were obtained from the Chinese Land Use/Cover Change (CLUCC) dataset and reclassified into seven major land-use categories. Habitat quality was evaluated using the InVEST habitat quality module by incorporating habitat suitability, anthropogenic threat sources, threat intensity, and land-type sensitivity. Cropland, construction land, and unused land were identified as major threat sources to reflect human disturbance. Spatial patterns, temporal trends, and grade transitions of habitat quality were analyzed using GIS-based spatial analysis methods. Future land-use patterns for 2030 were simulated using the PLUS model, which applies a random forest algorithm to identify land expansion drivers and a multi-type random patch seed mechanism to generate spatially explicit land-use patches. Ten natural, socioeconomic, and accessibility-related driving factors were incorporated. Model performance was validated by simulating land use in 2020 based on 2010 data, achieving a Kappa coefficient of 0.897, indicating high simulation accuracy. Four future scenarios were designed: natural development (ND), agricultural development (AD), economic development (ED), and ecological protection (EP), reflecting different policy orientations. The contribution degree and habitat quality dynamic indices were employed to quantify the positive and negative effects of specific land-use transitions on habitat quality change under each scenario.

Results From 2000 to 2020, the average habitat quality in the Guangdong−Hong Kong−Macao Greater Bay Area declined from 0.431 to 0.395, indicating an overall degradation trend. However, the rate of degradation slowed significantly after 2010, suggesting that ecological conservation measures implemented in recent years have partially mitigated the habitat deterioration. Spatially, habitat quality exhibited significant heterogeneity, showing a distinct “periphery-high, core-low” pattern. High-quality habitats were primarily located in the northern and peripheral mountainous regions dominated by forests and grasslands, whereas low-quality habitats were concentrated in the highly urbanized core areas, including Guangzhou, Shenzhen, Foshan, and Dongguan. Land-use transition analysis revealed that the conversion of cropland and ecological land to construction land was the primary driver of habitat quality degradation. Approximately 75.76% of the study area remained stable in habitat quality grade, while degraded areas were mainly distributed in regions experiencing intense urban expansion. Scenario simulations indicated divergent future trajectories. Under the ND scenario, habitat quality showed slight improvement compared with that in 2020. The AD scenario moderately alleviated habitat degradation by reducing cropland loss and constraining construction land expansion. In contrast, the ED scenario significantly exacerbated habitat degradation, with extensive conversion of cropland and grassland to construction land leading to increased fragmentation. The EP scenario produced the most favorable outcomes, increasing mean habitat quality by approximately 1.8% relative to that under the ND scenario, primarily due to the expansion of forests, grasslands, and water bodies and strict control of construction land growth. Contribution analysis further confirmed that construction land expansion was the dominant negative factor, whereas ecological land restoration played a critical positive role in improving habitat quality.

Conclusion This study demonstrates that land-use change plays a decisive role in shaping habitat quality dynamics in high-density urban agglomerations. By integrating PLUS and InVEST, the research provides a comprehensive framework linking land-use simulation, habitat quality assessment, and contribution-based mechanism analysis. The results indicate that while recent ecological policies have slowed habitat degradation in the GBA, future habitat quality trajectories remain highly sensitive to development pathways. Unregulated economic expansion may lead to persistent habitat deterioration, whereas ecological protection-oriented strategies can effectively enhance habitat quality even under continued urbanization pressure. These findings highlight the necessity of controlling construction land expansion, safeguarding cropland and blue−green spaces, and strengthening ecological restoration in core urban areas. The proposed framework and empirical insights offer transferable methodological references for other mega-urban regions, such as the Yangtze River Delta and the Beijing−Tianjin−Hebei urban agglomeration, and provide robust scientific support for regional ecological governance and spatial planning toward sustainable urban futures.