Unmanned aerial vehicles swarm persistent surveillance is an important application in the multiple unmanned aerial vehicles (UAVs). With the increasing complexity of environment and tasks in surveillance mission，the requirement of UAV swarm reconfiguration and flexibility is also rising. To the adaptive and reconfigurable UAVs swarm, the amount of UAV is one of the basic control factors. However, most studies in UAV swarm control focus on control cooperative path planning in given mission, while dynamic deployment of the UAV amount in swarm system is neglected. In the surveillance design of traditional UAVs swarm, the amount of swarm is hard to adaptively adjust to match the different surveillance environments and various situations. To solve this kind of problem, a “digital turf” variation model is proposed on the base of the regional information entropy. Moreover, we imitate a dynamic balancing mechanism in the turf-herbivore ecosystem and design the scale control method in target region-UAV swarm. What’s more, on this basis, we study the biomes matrix and equilibrium point situation when surveillance system reaches stable and discusses adaptive adjusting method of UAV swarm in different mission environments with different efficiency constraints. Finally, the existence of equilibrium point and the convergence of system are demonstrated by simulation.