Dynamic modeling of female neutering interventions for free-roaming dog population management in an urban setting of southeastern Iran.

Understanding dynamics of free-roaming dog (FRD) population is critical for planning and implementation of dog population management programs. FRD population size estimation as well as dynamic modeling of dog population under different female dog neutering interventions were investigated in order to determine the most appropriate animal birth control approach. We performed population size estimate of dogs using sight-resight surveys by photography in a randomly selected 25 blocks of the city and all the suburbs of greater Kerman area. Main demographic features were characterized and the dog density distribution was mapped. A dynamic model was developed to predict free-roaming dog population variations after 5 and 10 years. Different scenarios based on 10, 30, 50, 60 and 70% female dog sterilization were considered to predict the effects of animal birth control measures. Free roaming dog population was estimated at 6781 dogs (65.3% males) in Kerman and suburbs with several major population hotspots. Analysis of the dog locations within the city showed that the largest proportion of the dogs were observed in the vacant lots (46.2%). Modeling predictions indicated that, in the absence of management, the free-roaming dog population could increase from a baseline of 6781 to 13,665 dogs (2.02 fold increase) in 5 years and to 19,376 dogs in 10 years (2.86 fold increase). Using a population dynamics model, we simulated five neutering coverages to explore the impact of female neutering on free-roaming dog population size. The 5-year projections of the model have shown that 50% annual female dog sterilization significantly reduced free-roaming dog population by 0.44 comparing to the baseline population. Findings of the present study improve our knowledge on the nature and extent of dog population dynamics in Iran. Effective population control and selection of the most appropriate neutering interventions require a comprehensive knowledge of the characteristics and dynamics of FRD population.