1. Conservation goals are ideally set after a thorough understanding of potential threats; however, predicting future spatial patterns of threats, such as disturbance, remains challenging. Here, we develop a novel extension of network fortification-interdiction models (NFIM) that deals with uncertainty in future spatial patterns of disturbance by optimally selecting sites that will best mitigate a worst-case scenario for a given magnitude of disturbance. 2. This approach uses information on between-patch movement probabilities and patch-specific survival, which can be estimated from mark-recapture data, to optimize life expectancy. Optimization occurs in three interrelated stages: protection, followed by disturbance, and then assessment. 3. We applied the modeling approach to two mark-recapture data sets: Roseate terns Sterna dougallii in the northeastern United States and the Everglade snail kite Rostrhamus sociabilis plumbeus in Florida. We contrasted the results to a more conventional approach of protecting sites that maximize connectivity (by minimizing the distances among protected sites) and a bi-objective model that maximizes connectivity and the number of individuals under protection. 4. Protecting sites that best mitigate future worst-case disturbance scenarios consistently resulted in higher predicted life expectancies than protecting patches that minimize dispersal distance. Predicted life expectancy was similar between NFIM and the biobjective model for the small roseate tern network, yet, the NFIM predicted higher life expectancy than any of the scenarios in the bi-objective model in the snail kite network. 5. Synthesis and applications. This application of interdiction models prescribed a combination of patches for protection that results in the least possible decrease in life expectancy. Our analyses of the snail kite and roseate tern networks suggest that managing to protect these prescribed patches by the network fortification interdiction model (i.e. protecting against the worst-case disturbance scenario) is more beneficial than managing patches that minimize dispersal distance or maximize the number of individuals under protection if the conservation goal is to ensure the long term persistence of a species.