Spatial Distribution Characteristics of the Black Soil Layer and Regional Ecological Sensitivity Analysis in the Eastern Songnen High Plain
Abstract
The Northeast Black Soil Region is a vital commercial grain production base in China. However, ecological problems such as black soil degradation and soil erosion directly threaten food supply security. To clarify the distribution characteristics of the black soil layer thickness and ecological sensitivity, this study developed an ecological sensitivity evaluation index system for Bayan County in the eastern Songnen High Plain. Based on a review of relevant domestic and international literature, the system incorporates four dimensions: topography, climate, natural resources, and human activities. A combined Analytic Hierarchy Process (AHP)–Entropy Weight Method (EWM) model was used to calculate comprehensive weights for indicators at different levels. The results show that: (1) The black soil layer thickness in Bayan County ranges from 0 to 199 cm, with medium, thin, and thick layers accounting for 48.6%, 30.77%, and 20.63% of the area, respectively. The total black soil reserve is estimated at approximately 1.369 billion m3. (2) Among the primary indicators, natural resources carried the highest weight (0.56). The top five second-level indicators were soil type (0.17), river buffer zone (0.13), vegetation coverage (0.12), land use type (0.11), and black soil layer thickness (0.10). (3) The overall ecological sensitivity of the county was moderate, with a comprehensive index ranging from 1.60 to 4.47. The proportions of extremely, highly, moderately, mildly, and insensitive areas were 14%, 24.49%, 28.14%, 23.05%, and 10.32%, respectively. These findings provide a scientific basis for ecological and black soil conservation and support the development of targeted, zone-specific protection measures in Bayan County.
Fields of Study & Subjects
Soil and Land Suitability Analysis
Land Use and Ecosystem Services
Soil erosion and sediment transport
Publication details
- Journal / source
- SSRN Electronic Journal
- Publisher
- Elsevier BV
- Publication date
- 1 January 2026
- Document type
- Preprint