Multiscale patterns and future dynamics of cultivated land fragmentation in Northeast China

The three northeastern provinces of China are key national grain production bases. However, accelerating cultivated land fragmentation(CLF) has reduced agricultural productivity and poses a threat to food security. This study develops an integrated assessment framework combining a multidimensional indicator system, multiscale effects, future scenario simulations, and spatially driven attribution analysis to characterize CLF from 1993 to 2023. A combined "area loss-aemivariogram function" approach identified the optimal analysis scale (120 m resolution, 16 × 16 km grid), effectively addressing scale dependency. Using the AHP-Entropy Weight TOPSIS method, Theil index, Scale Variance, Theil-Sen Median, and Mann-Kendall tests, reveals pronounced multi-level spatial differentiation and dynamic evolution. By integrating the G-MOP-PLUS model, optimal parameter geodetector (OPGD), and multiscale geographically weighted regression (MGWR), it further quantifies future evolution pathways and driving mechanisms under alternative policy scenarios. Results show that the fragmentation index increased from 0.349 to 0.360, with high-value clusters concentrated in central Heilongjiang, central-eastern Jilin, and northern and southeastern Liaoning. Fragmentation exhibits a hierarchical pattern of "top-level stability and bottom-level variation," with grid-scale variance contributing over 91 % to spatial heterogeneity. Population density, DEM, and GDP are the dominant drivers, with strong urban-rural interaction effects. A three-tier coordinated governance framework is proposed to support precision land management and the sustainable utilization of cultivated land in China's major grain-producing regions.