A mimicked bacterial infection prolongs stopover duration in songbirds—but more pronounced in short- than long-distance migrants

Abstract

Migration usually consists of intermittent travel and stopovers, the latter being crucially important for individuals to recover and refuel to successfully complete migration. Quantifying how sickness behaviours influence stopovers is crucial for our understanding of migration ecology and how diseases spread. However, little is known about infections in songbirds, which constitute the majority of avian migrants. We experimentally immune-challenged autumn migrating passerines (both short- and long-distance migrating species) with a simulated bacterial infection. Using an automated radiotelemetry system in the stopover area, we subsequently quantified stopover duration, “bush-level” activity patterns (0.1–30 m) and landscape movements (30–6,000 m). We show that compared to controls, immune-challenged birds prolonged their stopover duration by on average 1.2 days in long-distance and 2.9 days in short-distance migrants, respectively (100%–126% longer than controls, respectively). During the prolonged stopover, the immune-challenged birds kept a high “bush-level” activity (which was unexpected) but reduced their local movements, independent of migration strategy. Baseline immune function, but not blood parasite infections prior to the immune challenge, had a prolonging effect on stopover duration, particularly in long-distance migrants. We conclude that a mimicked bacterial infection does not cause lethargy, per se, but restricts landscape movements and prolongs stopover duration, and that this behavioural response also depends on the status of baseline immune function and migration strategy. This adds a new level to the understanding of how acute inflammation affect migration behaviour and hence the ecology and evolution of migration. Accounting for these effects of bacterial infections will also enable us to fine-tune and apply optimal migration theory. Finally, it will help us predicting how migrating animals may respond to increased pathogen pressure caused by global change.