Estimates of animal abundance are widely used to support conservation and resource management. For populations in open systems, abundance estimates from tagging data can be highly uncertain or biased. Here, we develop a novel approach to estimate abundance of an open population by pairing two models, each utilizing distinct tagging data. Using data from telemetry tags, we infer movement rates to and from the study site with a Markovian model allowing for an environmental effect. Then, using data from conventional passive tags, we apply a Lincoln–Petersen abundance estimator modified to account for mortality and movement. After developing the model within a Bayesian framework, we demonstrate its application to data on gray triggerfish (Balistes capriscus) tagged in the Atlantic Ocean off North Carolina, USA. For this open population, we estimate site abundance to be ∼1000 fish (∼2000 fish·km –2 ) and additionally find evidence for an effect of hurricanes on movement. The general approach may be useful for fisheries, wildlife, and other ecological studies utilizing multiple tag types, particularly for estimating abundance of an open population.