Effects of immune status on stopover departure decisions are subordinate to those of condition, cloud cover and tailwind in autumn-migrating common blackbirds (Turdus merula)

Migratory birds encounter a large variety of parasites and pathogens en route and invest in immune defences to limit the risk and fitness costs of infection. Since both migration and immune defences carry costs, individuals on tight budgets may face trade-offs between migratory progress and immune status. Many species alternate legs of strenuous migratory flight with stopovers during which birds refuel, rest, and recover physiologically. Despite this, most time and energy consumed during migration are actually spent on stopovers. As a result, identifying what determines stopover duration is key in understanding how migratory birds balance investments in immune defences and migration. Yet, it is unknown under what conditions an individual’s immune status may affect migratory progress through the duration of stopovers. We explored whether immune status at arrival affects stopover duration by radio-tagging and blood-sampling common blackbirds (Turdus merula) during autumn stopovers on the ..., By deploying radio transmitters on common blackbirds during stopover on the Dutch Island of Vlieland, we tested the relationships between body condition (scaled mass index) and several indices of immune status/function and stopover departures. We include temporal covariates for cloud cover and tailwind components in the model, which are included for each potential night of departure., , # Effects of immune status on stopover departure decisions are subordinate to those of condition, cloud cover and tailwind in autumn-migrating Common blackbirds (*Turdus merula*)

[https://doi.org/10.5061/dryad.ffbg79d3q](https://doi.org/10.5061/dryad.ffbg79d3q)

The data file (\"data_v2\"): Minimum stopover durations of Common blackbirds are based on tag detections by the Motus receiver system. These form the basis of this dataset. Included covariates include several indices of immune status/function (haptoglobin, lysis and agglutionation scores, bacterial killing ability and heterophil-lymphocyte ratio's), scaled mass index (based on tarsus and body weight), weather conditions (cloud cover, from the local KNMI weather station, and interpolated tailwind components derived from the u and v wind components in the NCEP dataset).The R script (\"Analysis\"): includes the time-dependent Cox proportional hazard models we used to analyse these data. 

## Description of the data and file structure
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