Costs of migratory decisions: A comparison across eight white stork populations

Abstract

Annual migratory movements can range from a few tens to thousands of kilometers, creating unique energetic requirements for each specific species and journey. Even within the same species, migration costs can vary largely because of flexible, opportunistic life history strategies. We uncover the large extent of variation in the lifetime migratory decisions of young white storks originating from eight populations. Not only did juvenile storks differ in their geographically distinct wintering locations, their diverse migration patterns also affected the amount of energy individuals invested for locomotion during the first months of their life. Overwintering in areas with higher human population reduced the stork's overall energy expenditure because of shorter daily foraging trips, closer wintering grounds, or a complete suppression of migration. Because migrants can change ecological processes in several distinct communities simultaneously, understanding their life history decisions helps not only to protect migratory species but also to conserve stable ecosystems.

Keywords: Animal movement; White storks; acceleration; energy expenditure; high-resolution GPS; lifetime tracking; migration costs; population comparison.

Fig. 1. Migratory behavior of juveniles from eight different populations.

(A) Migration paths of 62 individuals tracked with GPS/GSM (Global System for Mobile Communications) (eight individuals died before migrating). Maps depicted are OpenStreetMap images (www.openstreetmap.org/copyright; https://creativecommons.org/licenses/by-sa/2.0/) accessed through the R package OpenStreetMap. (B) Departure date of the studied populations. Color scale indicates departure dates (white indicating no departure). (C) Departure date as a function of maximum distance reached (each color represents one population). Dots in the light gray–shaded area represent individuals that left their natal grounds but survived for less than 150 days. SW, southwest.

Fig. 2. Activity measures of juvenile white storks.

(A) Summed activity (ODBA) of the first 5 months of a juvenile’s life as a function of total distance flown during the same time. The solid gray line represents the third-order polynomial regression. The best-fitting regression is provided by the equation Y = 387.2 + 1.344 × 10⁻¹¹ X³. (B) Average activity (ODBA) of a migration day in relation to average activity of a stopover day. Color represents the different populations. Gray dashed line is a reference line.

Fig. 3. Activity and thermal uplift.

Activity (sum of daily ODBA values) as a function of thermal uplift (mean of daily thermal uplift), during flight days, depending on the location of the bird (B). Blue and light brown correspond to Europe/Middle East (north of 33°N) and Africa (south of 33°N), respectively. Plots on the top (A) and the side (C) are the density histograms of thermal uplift (top) and ODBA (right).

Fig. 4. Activity in relation to human population density and vegetation cover.

Daily activity (sum of hourly ODBA averages) as a function of human population density (mean of the day) (B) and vegetation cover of shrubs and low-lying bushes [“low vegetation cover,” European Centre for Medium-Range Weather Forecasts (ECMWF), mean of the day] (D). Blue and light brown correspond to birds that overwintered north and south of 33°N, respectively. Plots on the top and the side are the density histograms of population density (A), vegetation cover (C), and ODBA (E).