Methods for surveying and estimating breeding waterfowl populations in the Prairie Pothole Region of Iowa

The southern portion of the Prairie Pothole Region (PPR), including the Des Moines Lobe of northwest and north-central Iowa, is predicted to become increasingly important to breeding waterfowl as climatic changes drive a southeastward shift in wetland distribution. The history of intense agriculture in this region has created a low-density network of wetlands that complicates the use of traditional survey techniques to gather much needed information on breeding waterfowl distribution used to guide strategic habitat conservation for this high-value wildlife resource. My research was aimed at identifying an optimal survey design that produced robust breeding waterfowl population estimates for the southern PPR of Iowa. Using breeding waterfowl pair counts collected during both aerial and ground-based surveys in 2016-2018, I estimated and compared detection probabilities of indicated pairs for both aerial and ground-based surveys to identify the survey approach that maximized detection of four breeding waterfowl species: Canada Goose (Branta canadensis), Wood Duck (Aix sponsa), Blue-winged Teal (Spatula discors), and Mallard (Anas platyrhynchos). I also developed a Bayesian, hierarchical state-space model to estimate breeding waterfowl abundance that is robust to different survey designs (e.g., single versus multiple surveys within a season), incorporates annual spatial variation in breeding waterfowl pair densities inherent in the highly-modified landscape of the southern PPR, and includes factors from the original model used to estimate breeding waterfowl abundance in this region, and compared predictions from this model to existing breeding abundance estimates from the annual Four-Square-Mile Survey. Lastly, I assessed the precision and bias of breeding waterfowl pair estimates as a function of survey replication and the use of three different wetland sampling strategies: equal, proportional, and Neyman allocation. Detection probabilities of breeding waterfowl indicated pairs were relatively low overall (<0.40) for both aerial and ground-based surveys across all species. Aerial surveys produced higher detection probabilities for all Canada Goose indicated pair criteria as well as for Blue-winged Teal pairs and both Blue-winged Teal and Mallard grouped males. Detection probabilities for all species during aerial surveys generally decreased throughout the season and were significantly influenced by wind speed during ground-based surveys. My Bayesian, hierarchical state-space model demonstrated that breeding waterfowl pair densities are significantly different among wetlands of different water regimes (e.g., temporary, semi-permanent) and produced breeding waterfowl abundance estimates for the Four-Square-Mile-Survey area that were higher than existing estimates for two of three survey years, a result potentially influenced by wetland sampling strategies. Lastly, I found that the Neyman sampling strategy consistently produced breeding abundance estimates that were similar to predicted abundances, but that both the equal and proportional sampling strategies produced estimates that were more precise but only slightly lower than predicted abundances. These combined results suggest that additional investigation is needed to identify the sampling strategy that both minimizes bias and maximizes precision of breeding waterfowl abundance estimates across a gradient of wetland conditions. Furthermore, my results indicate that an aerial survey with at least two survey visits within a season combined with a Neyman sampling approach will produce robust breeding waterfowl abundance estimates in the Iowa portion of the PPR, information critical to strategic allocation of conservation resources for waterfowl in this region.

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