The management of North American waterfowl is predicated on long‐term, continental‐scale banding implemented prior to the hunting season (i.e., July–September) and subsequent reporting of bands recovered by hunters. However, single‐season banding and encounter operations have a number of characteristics that limit their application to estimating demographic rates and evaluating hypothesized limiting factors throughout the annual cycle. We designed and implemented a two‐season banding program for American Black Ducks (Anas rubripes), Mallards (A. platyrhynchos), and hybrids in eastern North America to evaluate potential application to annual life cycle conservation and sport harvest management. We assessed model fit and compared estimates of annual survival among data types (i.e., pre‐hunting season only [July–September], post‐hunting season only [January–March], and two‐season [pre‐ and post‐hunting season]) to evaluate model assumptions and potential application to population modeling and management. There was generally high agreement between estimates of annual survival derived using two‐season and pre‐season only data for all age and sex cohorts. Estimates of annual survival derived from post‐season banding data only were consistently higher for adult females and juveniles of both sexes. We found patterns of seasonal survival varied by species, age, and to a lesser extent, sex. Hunter recovered birds exhibited similar spatial distributions regardless of banding season suggesting banded samples were from the same population. In contrast, goodness‐of‐fit tests suggest this assumption was statistically violated in some regions and years. We conclude that estimates of seasonal and annual survival for Black Ducks and Mallards based on the two‐season banding program are valid and accurate based on model fit statistics, similarity in survival estimates across data and models, and similarities in the distribution of recoveries. The two‐season program provides greater precision and insight into the survival process and will improve the ability of researchers and managers to test competing hypotheses regarding population regulation resulting in more effective management. [ABSTRACT FROM AUTHOR]
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