Qibin Zhang

The current research indicates that the Ecological Spatial Network (ESN) supports critical regulating services, yet the quantitative coupling between its topological structure and the sand fixation function has received limited attention. This study investigates this relationship in the Zhangbei region, China, from 2002 to 2022. By integrating the Minimum Cumulative Resistance (MCR) model, complex network theory, and the Revised Wind Erosion Equation (RWEQ), we systematically evaluated the network’s structural evolution and its correlation with the sand fixation capacity. The results reveal a significant enhancement in ecosystem service: the actual wind erosion amount decreased from 20.18 t/ha in 2002 to 2.83 t/ha in 2022, while the network structure matured, characterized by stable high modularity (Q ≈ 0.67) and a marked “core densification” trend. Correlation and regression analyses confirm that topological metrics—specifically PageRank, Betweenness Centrality, and Degree—are effective indicators, jointly explaining 48–65% of the spatial variation in the sand fixation capacity. Notably, PageRank emerged as the most robust predictor, highlighting the functional importance of high-quality patch clusters. Furthermore, optimization simulations suggest that a low-eigenvector centrality edge-adding strategy is most effective for enhancing network connectivity. These findings provide a theoretical basis and spatial guidance for ecological restoration in arid and semi-arid regions.

The destruction of vegetation structure and quantity leads to the weakening of the carbon sequestration capacity of the ecosystem. Building an ecological spatial network is a potent method for studying vegetation spatial distribution structures. The relationship between the spatial distribution structure of vegetation networks and carbon sequestration, as approached from the perspective of complex network theory, is understudied. This study uses the minimum resistance model (MCR) and morphological spatial pattern analysis (MSPA) to study the eco-space network and ecological node spatial structure and topological characteristics of vegetation in the ecologically sensitive area of the middle reaches of the Yellow River (ESAMRYR). Based on the Carnegie-Ames-Stanford approach (CASA) model, the vegetation Net Primary Productivity (NPP) of the study area is calculated, and the ecological carbon sequestration function of the ecological node is estimated, and the relationship between the ecological node and the topological indicators is analyzed. The study shows that the forest land carbon storage in the regions situated toward the south and east of the Yellow River ecologically sensitive area is the highest, accounting for twice the proportion of the area, and is very important in terms of increasing carbon storage. Most of the ecological sources in the study area have a higher topological importance than functional importance, and the sources with low coordination are mainly distributed in the southwest and northeast. We construct a topology and function coupling optimization model (TFCO) to explore the coordination between vegetation structure and carbon sequestration function, to determine the network optimization direction, and to propose optimization solutions. Analysis of network robustness and carbon sequestration capacity shows that the sturdiness and carbon sequestration of the enhanced network are significantly improved. This study provides strategies and methods for protecting ecological sensitive areas, optimizing vegetation spatial distribution, and enhancing carbon sequestration capacity.