Sea otters (Enhydra lutris kenyoni) are an apex consumer in the North Pacific Ocean and are known to influence and structure nearshore marine communities. Sea otters were extirpated from southeastern Alaska prior to 1911 due to the commercial fur trade; however, 413 sea otters were reintroduced to southeastern Alaska from 1965 to 1969. By 1988, sea otters had expanded into lower Glacier Bay and the U.S. Geological Survey (USGS) began aerial survey monitoring efforts to monitor the colonization, distribution, and abundance of sea otters; these efforts continued through 2012. Currently, sea otters are one of the most abundant marine mammals in the park. In 2015, sea otters were identified as a vital sign by the National Park Service’s Southeast Alaska Network (SEAN) Monitoring Program due to their role as a keystone species in the nearshore marine ecosystem. The primary objectives of the monitoring program are to use contemporary field and analytical methods to monitor the abundance and spatial distribution of sea otters in Glacier Bay. A spatio-temporal statistical model representing current knowledge of sea otter abundance and distribution, including underlying ecological processes governing colonization dynamics in Glacier Bay, was constructed using multiple sources of data collected on sea otters between 1993 and 2012 by USGS and will accommodate future data to be collected via aerial photographic surveys (Williams et al. 2017, Ecology). Contemporary methods for obtaining digital imagery and counting sea otters from the imagery were developed to replace prior observer-based methods. Aerial photographic surveys will be conducted and digital imagery will be archived as a permanent record enabling independent verification of counts of sea otters and quantification of habitat covariates. The new monitoring design implements an iterative optimal dynamic sampling scheme to increase sampling efficiency, providing the most information from the data that can be collected affordably. The spatio-temporal model will be used to generate forecasts of sea otter abundance and associated uncertainty for subsequent monitoring periods. Forecasts then will be used as a template to select a set of survey transects that minimize the uncertainty in model-based forecasts of predicted abundance of sea otters. Optimal survey designs will be updated following each year data are collected and, therefore, are dynamic through time. A set of random transects also will be selected to supplement, validate, and compare abundance estimates of sea otters among sampling approaches. Real location of effort among survey types will be considered in the future as another means to optimize program performance and efficiency. The combination of using (1) aerial photographs for collecting data, (2) advanced and flexible statistical models that incorporate our understanding of the ecological system, permitting rigorous estimates of occupancy, abundance, and colonization dynamics, and (3) a sampling framework that explicitly links our statistical model and future data to be collected will improve monitoring efficiency and our ecological understanding of sea otters in Glacier Bay.