The Northeast Black Soil Region is an important commercial grain production base in China. However, ecological issues such as black soil degradation and soil erosion pose direct threats to food security. Previous studies have mainly examined individual factors of black soil degradation. Few have integrated spatial thickness distribution with multi-dimensional ecological sensitivity. To address this gap, this study establishes an ecological sensitivity evaluation index system for Bayan County, located in the eastern Songnen High Plain. Based on a review of relevant literature, the system includes four dimensions: topography, climate, natural resources, and human activities. A combined Analytic Hierarchy Process (AHP) and Entropy Weight Method (EWM) was used to determine indicator weights. Compared with single-weighting methods, this approach balances expert judgment with data-driven variation. The results are as follows. (1) The thickness of the black soil layer in Bayan County ranges from 18 to 77 cm. Medium, thin, and thick layers account for 78.81%, 16.32%, and 4.87% of the area, respectively. The total black soil reserve is estimated at about 1.267 billion m³. (2) Among the primary indicators, natural resources have the highest weight (0.53). The five most important secondary indicators are the river buffer zone (0.14), NDVI (0.13), soil type (0.12), land use type (0.12), and road buffer zone (0.09). (3) The overall ecological sensitivity of the county is moderate, with a composite index ranging from 1.45 to 4.45. The proportions of extremely sensitive, highly sensitive, moderately sensitive, mildly sensitive, and insensitive areas are 10.79%, 25.51%, 28.95%, 24.23%, and 10.52%, respectively. These findings provide a scientific basis for ecological protection and black soil conservation. They also support the development of targeted, zone-specific management strategies in Bayan County.

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.

Rapid urbanization and mega-events have reshaped land use in Beijing’s Yanqing District, making post-event balance between ecological protection and urban development a critical challenge for territorial spatial planning. This study analyzes land use evolution from 2015 to 2025, simulates 2035 patterns under natural development (ND), ecological protection (EP), and urban development (UD) using the PLUS model (Kappa = 0.91, OA = 0.95), and constructs an Ecological Conversion Direction Index (ECDI) to characterize the net direction of ecological quality change. Results show forest and construction land increased (+40.17 km²; +14.83 km²), grassland declined sharply (−38.23 km², −36.47%), cropland decreased (−25.36 km², −5.17%), and water expanded (+8.59 km², +62.38%). The ECDI remained positive (0.313 to 0.178) but weakened post-event. The driving mechanism showed a trend of transition from “event-response” toward “ecological constraint”—the contribution of distance to landmarks/venues declined substantially for most land types, while NDVI emerged as a prominent predictor negatively associated with construction land (18.24%) and positively associated with forest quality improvement (17.55%). The EP scenario was identified as optimal, reducing construction land by 8.05 km² to 98.67 km² while increasing forest to 1388.57 km², effectively safeguarding both the ecological baseline and cropland redline. We recommend adopting EP, strengthening the construction land reclamation rate, and coordinating the three control lines. These findings provide evidence-based policy support for reconciling urban development with ecological conservation in rapidly urbanizing ecological protection areas.

Rapid urbanization has significantly altered land use patterns in Deqing County, placing increasing pressure on its ecosystem. This study establishes a Driving Force–Pressure–State–Impact (DPSI) framework and selects ten indicators to evaluate ecological sensitivity for 2014, 2019, and 2024. It then couples this framework with the PLUS model to simulate land use and ecological sensitivity changes under the following three 2034 scenarios: natural development (ND), ecological protection (EP), and urban development (UD). Results show that ecological sensitivity exhibits a “high west, low east” spatial pattern and it fluctuated with an initial decline followed by a rise from 2014 to 2024, though the overall trend was a slow decrease. Land use type (weight 0.342), distance to rivers (weight 0.191), and distance to roads (weight 0.146) were the dominant influencing factors, together depicting Deqing’s ecological landscape of “western forests, eastern farmlands, and dense water networks”. The PLUS model demonstrated good validation accuracy (Kappa = 0.81), and the contributions of driving factors shifted over time. Multi-scenario simulation indicates that the ecological protection (EP) scenario is more suitable for sustainable urban development. We recommend implementing differentiated ecological control zones, integrating sensitivity evaluation into planning decisions, and improving the differentiated ecological compensation mechanism.