Reduction of bycatch through spatial management is one possible approach in fisheries management. One requirement is description of the habitat of the species in question, and this is now possible for a range of species using data collected from electronic tags. Here we report on a spatial management approach used to limit unwanted capture of southern bluefin tuna (SBT, Thunnus maccoyii) in the eastern Australia longline fishery. The approach combines a habitat model conditioned with temperature preference data from 56 pop-up satellite archival tags deployed on SBT, and an ocean model to produce near real-time habitat predictions utilized by fishery managers during the fishing season. Three habitat types based on probability of SBT occurrence are identified in the fishing region, and spatial zoning by managers is used to regulate fisher access to these zones. This management approach has been used since 2003, and despite dynamic spatial management often being resisted by fishers or managers because of perceived implementation complexity, there has been an increase in complexity of the management actions over the 6-yr period. Managers now request more habitat predictions each season, update the spatial zoning more frequently, and apply more complicated management lines dividing the habitat types. This has resulted in an improved fit to the modeled habitat predictions, and as catch per unit effort (CPUE) of SBT is related to the habitat type, has contributed to the overall success of the management approach. This implemented management approach illustrates that managers and fishers can successfully implement complex dynamic spatial zoning.