The black soil region of northeastern China, one of the world’s major black soil belts, is China’s main grain-producing area, producing a quarter of China’s commercial grain. However, over-exploitation and unsustainable management practices have led to a steady decline in the quality of arable land. Scientific and reasonable zoning of arable land is the key to ensuring that black soil arable land achieves sustainable development. In this study, the 317 districts and counties under the jurisdiction of Heilongjiang, Jilin, and Liaoning Provinces in the northeast region and the four eastern leagues of the Inner Mongolia Autonomous Region were taken as the study area, and arable land zoning in the northeast black soil region was explored through group analysis. Ten types of indicators were selected according to the four levels of climate, soil, vegetation, and topography of the northeast black soil region, including average precipitation and average temperature for many years at the climate level, organic matter content and soil texture (including clay, silt, and sand) at the soil level, NDVI and EVI indicators at the vegetation level, and DEM and slope indicators at the topographic level. In accordance with the principle of distinguishing differences and summarizing commonalities, nine scenarios of dividing the northeast black soil zones into 2 regions to 10 regions were explored, and these nine zoning scenarios were evaluated in terms of zoning. The results showed that (1) the spatial variability of cropland zoning in the northeast black soil zone based on four indicators, namely climate, soil, vegetation, and topography, was significant; (2) the results of the nine types of zoning based on cropland in the northeast black soil zone showed that intra-zonal zoning was optimal when zoning the northeast black soil zone into six types of zones, which enhanced the variability between the zones and the consistency within the zones; and (3) the assessment of large-scale cropland zoning using the pseudo F-statistic and area-weighted standard deviation methods revealed similarities in their outcomes. The results provide a scientific basis for the subregional protection of arable land in the black soil zone and help to formulate effective policies for different regions.

In recent decades, the integrity and security of the ecosystem in the Sanjiang Plain have faced severe challenges due to land reclamation. Understanding the impact of paddy field expansion on regional ecosystem services (ESs), as well as revealing the trade-offs and synergies (TOS) between these services to achieve optimal resource allocation, has become an urgent issue to address. This study employs the InVEST model to map the spatial and temporal dynamics of five key ESs, while the Optimal Parameter Geodetector (OPGD) identifies primary drivers of these changes. Correlation analysis and Geographically Weighted Regression (GWR) reveal intricate TOS among ESs at multiple scales. Additionally, the Partial Least Squares-Structural Equation Model (PLS-SEM) elucidates the direct impacts of paddy field expansion on ESs. The main findings include the following: (1) The paddy field area in the Sanjiang Plain increased from 5775 km² to 18,773.41 km² from 1990 to 2020, an increase of 12,998.41 km² in 40 years. And the area of other land use types has generally decreased. (2) Overall, ESs showed a recovery trend, with carbon storage (CS) and habitat quality (HQ) initially decreasing but later improving, and consistent increases were observed in soil conservation, water yield (WY), and food production (FP). Paddy fields, drylands, forests, and wetlands were the main ES providers, with soil type, topography, and NDVI emerging as the main influencing factors. (3) Distinct correlations among ESs, where CS shows synergies with HQ and SC, while trade-offs are noted between CS and both WY and FP. These TOS demonstrate significant spatial heterogeneity and scale effects across subregions. (4) Paddy field expansion enhances regional SC, WY, and FP, but negatively affects CS and HQ. These insights offer a scientific basis for harmonizing agricultural development with ecological conservation, enriching our understanding of ES interrelationships, and guiding sustainable ecosystem management and policymaking.

The Naoli River (NLR) Basin is a crucial distribution area for wetlands in China. Investigating the link between land use changes and carbon storage in this basin is of significant importance for protecting regional ecosystems and promoting the sustainable development of the social economy. This paper uses long-term Landsat satellite images provided on the GEE (Google Earth Engine) platform and the random forest classification algorithm to create spatial distribution maps of land use in the NLR Basin from 1993 to 2022. The study analyzes the dynamic changes in wetlands in the basin over the past 30 years and employs the InVEST (Integrated Valuation of Ecosystem Services and Tradeoffs) model to explore the temporal and spatial evolution characteristics of carbon storage. The results reveal that the wetland area of the NLR Basin showed a downward trend from 1993 to 2022, with a total decrease of 1507.18 hm² over 30 years. During this period, the carbon storage in the NLR Basin decreased, with a cumulative loss of 1.98 × 10⁷ t, mainly due to the continuous reductions in wetland and forest land. Additionally, the change in carbon storage in the basin has a strong spatial and temporal relationship with the changes in land use/cover area. The total carbon storage is positively associated with the areas of wetland, forest land, and water bodies. The conversion of wetlands into any other land type results in the reduction in carbon storage. These findings can improve our understanding of the spatial and temporal dynamics of wetlands in the NLR Basin over the past 30 years and enable us to analyze the relationship between land use changes and regional carbon storage. The results of this study have great significance for protecting the wetland ecology and regional carbon balance in the NLR Basin.