FR-Mamba is a novel spatiotemporal flow field reconstruction framework based on state space modeling.It combines Fourier Neural Operator (FNO) and State Space Model (SSM) to capture global spatial features and long-range temporal dependencies.The proposed approach outperforms existing methods in flow field reconstruction tasks, achieving high-accuracy performance on long sequences.The use of Mamba and FNO enables efficient modeling of long-range temporal dependencies and non-local spatial features, respectively.