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 Hirundo rustica 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

Ambrosini, R., Borgoni, R., Rubolini, D., Sicurella, B., Fiedler, W., Bairlein, F., et al. (2014). Modelling the Progression of Bird Migration with Conditional Autoregressive Models Applied to Ringing Data. PLOS ONE, 9(7) [10.1371/journal.pone.0102440].

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

AMBROSINI, ROBERTO;BORGONI, RICCARDO;SICURELLA, BEATRICE CARLOTTA;
2014

Abstract

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 Hirundo rustica 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
Articolo in rivista - Articolo scientifico
ringing data, Conditional Autoregressive Models
English
2014
9
7
e102440
none
Ambrosini, R., Borgoni, R., Rubolini, D., Sicurella, B., Fiedler, W., Bairlein, F., et al. (2014). Modelling the Progression of Bird Migration with Conditional Autoregressive Models Applied to Ringing Data. PLOS ONE, 9(7) [10.1371/journal.pone.0102440].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/53524
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