Migratory connectivity and effects of winter temperatures on migratory behaviour of the European robin Erithacus rubecula: A continent-wide analysis

Many partially migratory species show phenotypically divergent populations in terms of migratory behaviour, with climate hypothesized to be a major driver of such variability through its differential effects on sedentary and migratory individuals. Based on long-term (1947-2011) bird ringing data, we analysed phenotypic differentiation of migratory behaviour among populations of the European robin Erithacus rubecula across Europe. We showed that clusters of populations sharing breeding and wintering ranges varied from partial (British Isles and Western Europe, NW cluster) to completely migratory (Scandinavia and north-eastern Europe, NE cluster). Distance migrated by birds of the NE (but not of the NW) cluster decreased through time because of a north-eastwards shift in the wintering grounds. Moreover, when winter temperatures in the breeding areas were cold, individuals from the NE cluster also migrated longer distances, while those of the NW cluster moved over shorter distances. Climatic conditions may therefore affect migratory behaviour of robins, although large geographical variation in response to climate seems to exist.We thank Dr. Dario Massimino (BTO) for providing population indices for UK. JJC was supported by the Spanish National Research Council (grant EST001196)

Data from: Migratory connectivity and effects of winter temperatures on migratory behaviour of the European robin Erithacus rubecula: a continent-wide analysis

1. Many partially migratory species show phenotypically divergent populations in terms of migratory behaviour, with climate hypothesized to be a major driver of such variability through its differential effects on sedentary and migratory individuals. 2. Based on long-term (1947–2011) bird ringing data, we analysed phenotypic differentiation of migratory behaviour among populations of the European robin Erithacus rubecula across Europe. 3. We showed that clusters of populations sharing breeding and wintering ranges varied from partial (British Isles and Western Europe, NW cluster) to completely migratory (Scandinavia and north-eastern Europe, NE cluster). 4. Distance migrated by birds of the NE (but not of the NW) cluster decreased through time because of a north-eastwards shift in the wintering grounds. Moreover, when winter temperatures in the breeding areas were cold, individuals from the NE cluster also migrated longer distances, while those of the NW cluster moved over shorter distances. 5. Climatic conditions may therefore affect migratory behaviour of robins, although large geographical variation in response to climate seems to exist

Data from Robin migration and climate change

Variable name description: ID = ID for individual robins (progressive numbers); Lat2 = Latitude of the site where Robin was recovered during wintering; Lon2 = Longitude of the site where Robin was recovered during wintering; Lat1 = Latitude of the site where Robin was recovered during breeding; Lon1 = Longitude of the site where Robin was recovered during breeding; Year = Year when a robin was recovered in winter (from November of year i to February of year i + 1); Country = Country where a robin was observed during the breeding period; gridID = ID of the 2.5 ° lat x 2.5° lon cell where the robin was observed during the breeding period; Cluster = Cluster to which the robin belong, as assessed by migratory connectivity analysis; DistMig = migration distance calculated as the great-circle (orthodromic) distance between breeding and wintering position (km); CminT = temperature anomaly for the cell where the robin was observed breeding during the winter when it was recovered in winter (°C); CmaxTS = temperature anomaly for the cell where the robin was observed breeding during the summer when it was recovered in winter (°C); CminAT = temperature anomaly for the cell where the robin was observed breeding during the autumn when it was recovered in winter (°C); CminT1 = temperature anomaly for the cell where the robin was observed breeding during the winter preceding the one when it was recovered in winter; pop.index = population index in the country where a robin was observed breeding in the year when it was recovered in winter (index in the reference year = 0); Adult = whether a robin was adult or young when recovered in winter

Modelling the Progression of Bird Migration with Conditional Autoregressive Models Applied to Ringing Data

<div><p>Migration is a fundamental stage in the life history of several taxa, including birds, and is under strong selective pressure. At present, the only data that may allow for both an assessment of patterns of bird migration and for retrospective analyses of changes in migration timing are the databases of ring recoveries. We used ring recoveries of the Barn Swallow <i>Hirundo rustica</i> collected from 1908–2008 in Europe to model the calendar date at which a given proportion of birds is expected to have reached a given geographical area (‘progression of migration’) and to investigate the change in timing of migration over the same areas between three time periods (1908–1969, 1970–1990, 1991–2008). The analyses were conducted using binomial conditional autoregressive (CAR) mixed models. We first concentrated on data from the British Isles and then expanded the models to western Europe and north Africa. We produced maps of the progression of migration that disclosed local patterns of migration consistent with those obtained from the analyses of the movements of ringed individuals. Timing of migration estimated from our model is consistent with data on migration phenology of the Barn Swallow available in the literature, but in some cases it is later than that estimated by data collected at ringing stations, which, however, may not be representative of migration phenology over large geographical areas. The comparison of median migration date estimated over the same geographical area among time periods showed no significant advancement of spring migration over the whole of Europe, but a significant advancement of autumn migration in southern Europe. Our modelling approach can be generalized to any records of ringing date and locality of individuals including those which have not been recovered subsequently, as well as to geo-referenced databases of sightings of migratory individuals.</p></div

Progression of Barn Swallow migration in the British Isles.

<p>Contour plots of the calendar date in which the CAR model predicts that a given percentage of Barn Swallows have been recorded during (A) spring and (B) autumn migration. Contours were generated by linear kriging interpolation. Numbers in the colour scale represent the mean date for each 4-days (spring) or 2-days (autumn) colour belt (1 January  = 1). For ease of interpretation we here report some reference dates: 100 = 31 March, 120 = 30 April; 150 = 30 May, 180 = 29 June, 200 = 19 July, 230 = 18 August, 260 = 17 September.</p

Maps of Barn Swallow movements.

<p>Each line connects the ring and recovery position of individual Barn Swallows in (A) March-June and (B) August-October in the British Isles or in (C) February-June and (D) August-November in western Europe and north Africa. To facilitate the interpretation of the figure only Barn Swallows that moved more than 1 and less than 8 degrees latitude or longitude are shown.</p

Progression of Barn Swallow migration in western Europe and north Africa.

<p>Contour plots of the date in which the CAR model predicts that a given percentage of Barn Swallows have been recorded during (A) spring and (B) autumn migration. Contours were generated by linear kriging interpolation. Numbers in the colour scale represent the mean date for each 10-days colour belt (1 January  =  1). For ease of interpretation we here report some reference dates: 100 = 31 March, 120 = 30 April; 150 = 30 May, 180 = 29 June, 200 = 19 July, 230 = 18 August, 260 = 17 September, 300 = 27 October.</p

Boxplot of median A) spring and B) autumn migration dates in western Europe and north Africa.

<p>Dates were estimated at each cell (t₀ parameter of cloglog curves interpolated at each cell) in all belt-by-period combinations. The solid line represent the median value, the top and the bottom of the boxes represent the first and the third quartile while whiskers approximately include 95% of data. Circles represent outliers. Numbers represent sample size (i.e. number of cells per period and belt). Asterisk denotes the belt that differs significantly from the others at Tukey post-hoc tests (z≤-3.212, P≤0.004 in all cases). Different letters denote periods that differ significantly to each other within each latitudinal belt at Tuckey post-hoc tests (z = 3.612, P = 0.001).</p