Land-use change contributes significantly to climate change mitigation through biophysical changes (albedo, α) and biogeochemical (greenhouse gases, GHG) emissions (here refers to methane, CH₄, and nitrous oxide, N₂O). While the impact of grassland–cropland conversion on global warming potential (GWP) is well-documented globally, research remains scarce in the saline-alkaline agropastoral transition zone (APTZ) of the western Songnen Plain, Northeast China, an ecotone uniquely characterized by soil-crusting and seasonal inundation. We conducted in situ bi-weekly measurements of N₂O and CH₄ fluxes (June–September) to acquire growing season ${\mathrm{GWP}}_{{\mathrm{N}}_2\mathrm{O}}$ and ${\mathrm{GWP}}_{{\mathrm{C}\mathrm{H}}_4}$, alongside α. The study compared an undisturbed fenced meadow (FMD) with three adjacent land-use types, clipped meadow (CMD), saline-alkaline meadow (SAL), and paddy rice field (PDY), converted from FMD from 2018 to 2022. Annual α-induced GWP (GWPΔα) was positive across all converted sites (CMD, SAL, and PDY), indicating a warming effect due to lower α compared to FMD. The PDY exhibited the highest CH₄ emission (5.04 kg CO₂ m⁻² yr⁻¹), exceeding other land uses by three orders of magnitude (p < 0.05). Conversely, N₂O emissions remained consistently minimal and stable across all sites. When integrating the net ecosystem exchange of CO₂ (NEE), the PDY functioned as a net warming source. In contrast, the warming effects of α and non-CO₂ GHGs were effectively offset by the NEE in other land uses. Machine learning identified soil water content (SWC) as the dominant predictor of α across all land uses in growing season. However, a mechanistic divergence was observed, i.e., α in low saline-alkali ecosystems (FMD, CMD and PDY) was shaped by coupled biotic and soil moisture controls, whereas in the degraded SAL ecosystem, α is almost exclusively abiotic-driven. These findings demonstrate that land-use conversion in the Songnen Plain governs complex land-surface feedbacks through distinct pathways. This study provides a quantitative framework for integrating biophysical and biogeochemical impacts to optimize land management for climate resilience in saline-alkaline agropastoral ecotones.