Enhancing ecological resilience is essential for safeguarding ecological security in high-latitude cold regions under the combined pressures of climate change and intensive human disturbance. Focusing on Heilongjiang Province, China, this study develops a multi-scale analytical framework based on the resistance-adaptability-recovery (RAR) perspective and covering 11 indicators to reveal the spatial differentiation, internal coordination, and dominant constraints of ecological resilience (ER). Quantifications were conducted using 2024 multi-source spatial data at a 1 km × 1 km grid scale, with results aggregated to 120 counties at the county scale and further identified by applying Global Moran’s I, hot spot analysis, the coupling coordination degree model, and the obstacle degree model. The results reveal spatial heterogeneity in ER and its components. Resistance is generally weak, adaptability is strong, and recovery is polarized. ER components exhibit positive spatial autocorrelation. Medium coordination predominates (47.5% of counties), followed by low coordination (33.33%) and high coordination (19.17%). Low-coordination is constrained by weak resistance and recovery. Identifying soil conservation and habitat quality as primary constraints, which jointly constrain 88.4% of counties. These findings provide a mechanism-oriented basis for differentiated ecological governance in cold-region ecological security barriers.

The Sanjiang Plain supports globally important freshwater marsh ecosystems, yet intensive agricultural reclamation has caused extensive wetland loss and fragmentation. The role of substrate heterogeneity in wetland-type differentiation remains poorly understood. This study investigated the Eighty-Five-Two Farm in the Sanjiang Plain, Northeast China, using portable drilling and profile surveys to characterize substrate properties to a depth of 5 m. A four-category indicator framework covering physical–hydrological, nutrient–biogenic, mineral–geochemical, and chemical–redox properties was established. GIS-based spatial analysis and the GeoDetector model were used to identify substrate factors associated with wetland-type differentiation and quantify their depth-dependent explanatory power and interactions. Substrate configuration exhibited relatively strong explanatory power (q = 0.485). Factor importance varied with depth: grain-size variables were strongest in the upper layers; pH, TiO₂, and MnO were strongest at 1 m; and organic matter, Na₂O, and SiO₂ remained influential at 5 m. Upper-layer grain-size patterns are consistent with texture-related infiltration and drainage, while broad 1-m and heterogeneous 5-m interactions indicate depth-specific coupling among substrate properties. Interaction analysis showed that many factor pairs had greater explanatory power than individual factors, with nonlinear enhancement in some pairs. Interactions were broadest at 1 m and strong but heterogeneous at 5 m. These results indicate that wetland-type differentiation was associated with depth-dependent coupling among substrate structure, hydrological conditions, nutrient retention, and mineral–geochemical processes. These findings support incorporating substrate conditions into wetland restoration planning and may inform the identification of suitable restoration areas and target wetland types for degraded wetlands in the Sanjiang Plain.