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Knowing whether, and to what extent, populations are regulated by density‐dependent factors is important both in its own right and when developing management strategies for wildlife species. However, available tests for density dependence are typically sensitive to sampling errors in the data. By using a state‐space modeling approach, incorporating both an ecological process model and an observation model, it is possible to account for both measurement and process error. Here we focus on the detection and estimation of direct density dependence in two species of North American ducks: the Mallard (Anas platyrhynchos) and the Canvasback (Aythya valisineria). Yearly aerial counts on the major breeding grounds of ducks in North America provide estimates of abundances as well as standard errors of these estimates for both species. Including the number of ponds as a covariate, we demonstrate evidence for density dependence in prairie areas for both species. The appropriateness of the applied state‐space method is validated through a simulation study.

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