Objective Urban agglomerations, as advanced spatial organizational forms resulting from urbanization reaching a certain level, serve as the primary centers of human economic activities and, simultaneously, sensitive areas vulnerable to ecological disturbances. With escalating conflicts between human activities and ecological constraints, urban agglomerations face challenges of ecological space fragmentation, posing intricate issues in ecological risk management. As a typical coastal urban agglomeration with developed economy, the Fujian Delta Urban Agglomeration is dominated by low hills with diverse yet fragile ecological elements. Its ecological services have been compromised, exacerbating conflicts between land resource supply and demand, leading to risks of ecological function degradation and spatial fragmentation during land use evolution. Predicting and mitigating landscape ecological risks in this region are fundamental prerequisites for optimizing land resource allocation and maintaining ecological security. This research aims to construct a landscape ecological risk assessment model using landscape pattern indices to unveil the patterns of land use and landscape pattern evolution in the Fujian Delta Urban Agglomeration, thus providing scientific references for optimizing ecological spatial control and rational land resource allocation.

Methods Taking the Fujian Delta Urban Agglomeration as the research area, this research adopts the data on land use change during the period from 2000 to 2020 as the basis for assessing landscape ecological risks by a grid-based method. To determine the optimal evaluation unit scale, emphasis is placed on precise grid division and rapid calculation. Considering the area of the research area, a 500 m × 500 m fishnet grid is chosen as the basic evaluation unit, increasing by 500 m for each subsequent test. Results show that a 3 km × 3 km basic unit achieves a balance between computational accuracy and speed, thus confirmed as the foundational evaluation unit. Integrated software including Archaist, Frag stats and Geode are employed comprehensively to analyze land use dynamicity, land use type transition matrices, and landscape pattern changes. Constructed from disturbance index, vulnerability index, and loss index, the ecological risk index (ERI) can effectively analyze landscape heterogeneity and ecosystem dynamicity. Additionally, the hotspot analysis method is employed to distinguish the degree of spatial distribution aggregation and reflect high-value clusters and low-value clusters in local spatial regions, namely hot spots and cold spots, thus reviewing the spatial clustering distribution characteristics of the Fujian Delta Urban Agglomeration. Ultimately, the spatiotemporal distribution characteristics of landscape ecological risks and the aggregation of cold and hot spots are summarized.

Results 1) From 2000 to 2020, the primary land use transition in the Fujian Delta Urban Agglomeration was the conversion from arable land to forest land and construction land, with the overall trend of land use evolution shifting towards institutionalization. The evolution rate of land use dynamicity notably accelerated after 2010, mainly attributed to the promulgation of the Overall Plan for Urban Integration Development in the Xiamen-Zhangzhou-Quanzhou Metropolitan Area in 2015, which aims to achieve basic urban integration featuring the high integration of industry, space and society by 2020, thus accelerating the urbanization process in the Fujian Delta Urban Agglomeration region. 2) In terms of the evolution of landscape pattern evolution, arable land faced the most severe fragmentation risk, while forests underwent a trend towards large-scale conversion. The fragmentation degree of grasslands and water bodies initially increased and then decreased, with a decrease in the complexity of spatial form changes. The patchiness of construction land shifted from simple to complex after 2015. 3) In terms of the evolution of landscape ecological risk, influenced by intense human development activities, the ecological risks in coastal and southeastern regions were significantly higher than in other inland areas. Xiamen, Zhangzhou, and Quanzhou exhibited ecological risks “stable and controllable”, “slightly out of control”, and “basically controllable”, respectively. 4) In terms of the analysis of hot and cold spots with respect to the spatial aggregation of landscape ecological risk, the overall distribution of landscape ecological risks in the Fujian Delta Urban Agglomeration exhibited significant spatial heterogeneity, with areas with relatively high or relatively low risk indices more likely to aggregate. “Low-low” and “high-high” aggregation types were distributed in the northwestern inland and southeastern coastal areas, respectively.

Conclusion This research confirms the significant spatial heterogeneity of landscape ecological risks in the Fujian Delta Urban Agglomeration, achieving a quantitative expression of spatial information on land use in the region. Through the analysis of the spatiotemporal distribution characteristics of landscape ecological risks and the spatial aggregation of cold and hot spots, a refined visualization analysis of multidimensional risk prediction effectively reveals the associative patterns and differentiation rules of landscape ecological risks in the research area. The research proposes a method for applying the landscape ecological risk assessment model to analyze the overall distribution characteristics of landscape ecological risks in the region, which can facilitate the integration of scale effects and spatiotemporal effects to rapidly identify areas of risk mismanagement. Leveraging the data on land use change, this research effectively screens and preliminarily assesses regional landscape ecological risks, overcoming the inherent problems of traditional indicator systems based on the relationship between risk sources and exports such as subjectivity, complexity, and reliance on large amounts of natural, social, and economic data. The research simplifies data requirements, focusing on “dynamicity changes in land use” as a key representation directly reflecting the root conditions of landscape ecological risks. The proposed method only requires adjustments to the granularity of land use data to analyze the spatial differentiation characteristics of landscape ecological risks from urban to national scales.