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Keywords:

  • Bayesian methods;
  • climate change;
  • Cygnus buccinator;
  • missing data;
  • population trend;
  • survey data

ABSTRACT  Alaska (USA) contains a large proportion of the breeding population of trumpeter swans (Cygnus buccinator) in the United States. However, tracking population trends in Alaska trumpeter swans is complicated by variables such as an increase in survey effort over time, periodic surveys (1968 and every 5 yr after 1975), and missing data. We therefore constructed Bayesian hierarchical negative binomial models to account for nuisance variables and to estimate population size of trumpeter swans using aerial survey data from all known breeding habitats in Alaska, 1968–2005. We also performed an augmented analysis, where we entered zeroes for missing data. This approach differed from the standard (nonaugmented) analysis where we generated estimates for missing data through simulation. We estimated that adult swan populations in Alaska increased at an average rate of 5.9% annually (95% credibility interval = 5.2–6.6%) and cygnet production increased at 5.3% annually (95% credibility interval = 2.2–8.0%). We also found evidence that cygnet production exhibited higher rates of increase at higher latitudes in later years, which may be a response to warmer spring temperatures. Augmented analyses always produced higher swan population estimates than the nonaugmented estimates and likely overestimate true population abundance. Our results provide evidence that trumpeter swan populations are increasing in Alaska, especially at northern latitudes. Changes in population size and distribution could negatively affect tundra swans (Cygnus columbianus) breeding in Alaska, and biologists should monitor these interactions. We recommend using nonaugmented Bayesian hierarchical analyses to estimate wildlife populations when missing survey data occur.