Task scheduling in data relay satellite networks (DRSNs) is subject to dynamic disruptions such as resource failures, sudden surges in task demands, and variations in service duration requirements. These disturbances may degrade the performance of pre-established scheduling plans. To improve adaptability and robustness under such uncertainties, this paper presents a dynamic scheduling model for DRSN that integrates comprehensive task constraints and link connectivity requirements. The model aims to maximize overall task utility while minimizing deviations from the original schedule. To efficiently solve this problem, an ensemble heuristic adaptive contract net protocol (EH-ACNP) is developed, which supports dynamic scheduling strategy adaptation and efficient rescheduling through iterative negotiations. Extensive simulation results show that, in scenarios with sudden task surges, the proposed method achieves a 3.1% improvement in yield compared to the state-of-the-art dynamic scheduling algorithm HMCNP, and it also outperforms HMCNP in scenarios involving resource interruptions. Sensitivity analysis further indicates that the algorithm maintains strong robustness when the disposal rate parameter exceeds 0.2. These results highlight the practical potential of the EH-ACNP for dynamic scheduling in complex and uncertain DRSN environments.