Contrasting Seasonal Survivorship of Two Migratory Songbirds Wintering in Threatened Mangrove Forests

Long-distance migrants wintering in tropical regions face a number of critical conservation threats throughout their lives, but seasonal estimates of key demographic parameters such as winter survival are rare. Using mist-netting-based mark-recapture data collected in coastal Costa Rica over a six-year period, we examined variation in within- and between-winter survivorship of the Prothonotary Warbler (Protonotaria citrea; 753 young and 376 adults banded), a declining neotropical habitat specialist that depends on threatened mangrove forests during the nonbreeding season. We derived parallel seasonal survivorship estimates for the Northern Waterthrush (Seiurus noveboracensis; 564 young and 93 adults banded), a cohabitant mangrove specialist that has not shown the same population decline in North America, to assess whether contrasting survivorship might contribute to the observed differences in the species’ population trajectories. Although average annual survival probability was relatively similar between the two species for both young and adult birds, monthly estimates indicated that relative to Northern Waterthrush, Prothonotary Warblers exhibited: greater interannual variation in survivorship, especially within winters; greater variation in survivorship among the three study sites; lower average between-winter survivorship, particularly among females, and; a sharp decline in between-winter survivorship from 2003 to 2009 for both age groups and both sexes. Rather than identifying one seasonal vital rate as a causal factor of Prothonotary Warbler population declines, our species comparison suggests that the combination of variable within-winter survival with decreasing between-winter survival demands a multi-seasonal approach to the conservation of this and other tropical-wintering migrants.

Detectability of migrating raptors and its effect on bias and precision of trend estimates

Annual counts of migrating raptors at fixed observation points are a widespread practice, and changes in numbers counted over time, adjusted for survey effort, are commonly used as indices of trends in population size. Unmodeled year-to-year variation in detectability may introduce bias, reduce precision of trend estimates, and reduce power to detect trends. We conducted dependent double-observer surveys at the annual fall raptor migration count at Lucky Peak, Idaho, in 2009 and 2010 and applied Huggins closed-capture removal models and information-theoretic model selection to determine the relative importance of factors affecting detectability. The most parsimonious model included effects of observer team identity, distance, species, and day of the season. We then simulated 30 years of counts with heterogeneous individual detectability, a population decline (λ = 0.964), and unexplained random variation in the number of available birds. Imperfect detectability did not bias trend estimation, and increased the time required to achieve 80% power by less than 11%. Results suggested that availability is a greater source of variance in annual counts than detectability; thus, efforts to account for availability would improve the monitoring value of migration counts. According to our models, long-term trends in observer efficiency or migratory flight distance may introduce substantial bias to trend estimates. Estimating detectability with a novel count protocol like our double-observer method is just one potential means of controlling such effects. The traditional approach of modeling the effects of covariates and adjusting the index may also be effective if ancillary data is collected consistently.