The effect of weather on the decision to migrate from stopover sites by autumn-migrating ducks

• Main Authors: Benjamin J. O’Neal, Joshua D. Stafford, Ronald P. Larkin, Eric S. Michel
• Format: Article
• Language: English
• Published: BMC 2018-11-01
• Series: Movement Ecology
• Subjects: Anatidae; Migration; Radar; Remote sensing
• Online Access: http://link.springer.com/article/10.1186/s40462-018-0141-5

Abstract Background Previous investigations of autumn-migrating ducks have reported weak connections between weather conditions and the decision to migrate from stopover sites. We leveraged relatively new weather surveillance radar technology to remotely detect departures of discrete groups of various species of migratory dabbling ducks (Anatidae) in autumn to more directly assess the effect of specific weather conditions on departure from discrete stopover sites. Methods Using radar data collected over fifteen years (1995–2009), we documented a consistent phenomenon where a single, identifiable group departed from our study area on 30% of days during the autumn study period, and no ducks departed on the other days. We gathered weather variables from nearby stations and used them to develop competing models to explain temporal patterns of departure versus non-departure to better understand the potential mechanisms associated with binomial patterns of departures. Results The best approximating model of departure probability was our integrated model, which included variables accounting for wind aloft direction favorable for departure (i.e., tailwind), absence of precipitation, and a partially or completely clear sky. The integrated model accounted for all model weight in the candidate set and explained 55% of the variation in departure probability. Estimated probability of departure was 0.76 after parameterizing the best model with favorable conditions for all covariates. Conclusions Our results contrasted those of previous studies of autumn duck migration as a small set of simplistic, extrinsic conditions substantially influenced departure decision.