Abstract: Leveraging flexibility for on-demand deployment and unique aerial sensing perspectives， low-altitude uncrewed aerial vehicle （UAV） networks serve as a key platform for transitioning future sixth-generation mobile communications from terrestrial two-dimensional to air-ground three-dimensional integrated sensing and communication （ISAC）. However， their efficient deployment and performance enhancement face some formidable challenges. These challenges primarily stem from the high mobility of UAV platforms， complex and dynamic wireless propagation environments， and the inherent performance trade-offs between sensing and communication functions. To address these challenges， we propose an innovative network framework that synergistically leverages two cutting-edge technologies， including movable antennas （MAs） and intelligent reflecting surface （IRS， also known as reconfigurable intelligent surface， RIS）， and position them as dual enablers to reconfigure the wireless environment. Within this framework， MA performs active transceiver reconfiguration through flexible adjustments of antenna position and orientation， while IRS conducts passive channel reconstruction via intelligent control over the amplitude and phase of electromagnetic waves. Working in synergy， these two technologies can significantly enhance the performance of the entire ISAC system. We begin by holistically elaborating on the fundamental gains that MA and IRS bring to ISAC networks， and subsequently present two simplified system models and optimization problems regarding the synergy of antenna position and orientation with IRS. We also describe how we validated the immense potential of the synergistic “MA-IRS” architecture through preliminary simulations. The simulation results indicate that this architecture can effectively improve signal coverage quality and system sum-rate while ensuring sensing performance. Subsequently， we focus on two core deployment scenarios for UAVs in low-altitude ISAC networks， including （1） UAVs as ISAC users and （2） as aerial network nodes. In the former scenario， the network’s primary objectives are to achieve high-precision tracking of UAVs and to ensure low-altitude safety. We explore the evolutionary path from non-cooperative to cooperative targets and analyze how MA and IRS can synergistically enhance tracking accuracy and counter potential security threats. In the latter scenario， we focus on the multiple roles played by UAVs in low-altitude networks and discuss how to match the diverse configuration modes of MA and IRS with the functions of these roles. Thus， we propose new application paradigms or improvements to existing applications based on the MA-IRS synergistic schemes. Finally， for each of these two core scenarios， we systematically identify and analyzes key technical challenges and avenues for future research. Overall， we aimed to provide a clear， forward-looking roadmap and describe emerging research directions for the design and implementation of advanced next-generation low-altitude ISAC networks.