Estimating transient populations of unmarked individuals at a migratory stopover site using generalized N‐mixture models

Abstract

Abstract Migration counts are popular indices used to monitor population trends over time. Advanced analytical methods for estimating abundance of unmarked, open populations now incorporate population growth models and simultaneously test for covariate effects on abundance and detection probability. However, estimating population abundance at a staging site is complicated by daily immigration and emigration of unmarked individuals. We applied a set of generalized N‐mixture models to simulated count data to test their applicability for transient populations. Using simulated datasets, parameters were unbiased when the apparent survival rate varied within a season or was mis‐specified in a model, but not when the immigration or detection probability was mis‐specified. With knowledge from the simulated data, we applied these models to daily counts of staging migratory shorebirds and estimated daily abundances accounting for variation in the detection and immigration rates. Daily counts of ruddy turnstones (Arenaria interpres) staging at Westhampton Island, New York, were collected during northward migration (1997–1999). We tested the effects of weather and tides on detection probability, and we modelled within‐season variation in immigration rates as a function of time. Covariates affecting the detection probability differed among years, but tide height consistently was correlated with detection probability. Accounting for detection and immigration rates, the predicted maximum single‐day populations of ruddy turnstones were 172%, 165% and 129% of the observed counts for each year. Synthesis and applications. Management and conservation plans for migratory species require abundance estimates that are near the true population size though they are difficult to obtain. Our study is the first empirical application of the generalized N‐mixture model that incorporates temporal trends in immigration and estimates daily abundance of a staging unmarked migratory population. Despite its inherent limitation, we suggest that the generalized N‐mixture model can estimate the abundance of transient populations with low individual heterogeneity when counts are intensively surveyed. Correct estimation of population sizes and the environmental factors affecting them can aid the conservation prioritization of species and staging sites. Moreover, the use of generalized N‐mixture models can improve our understanding of the environmental factors that shape migratory movements.