Migrant birds track seasonally available resources on a continental scale across the annual cycle.

The small size of the billions of migrating songbirds commuting between temperate breeding sites and the tropics has long prevented the study of the largest part of their annual cycle outside the breeding grounds. Using light-level loggers (geolocators), we recorded the entire annual migratory cycle of the red-backed shrike Lanius collurio, a trans-equatorial Eurasian-African passerine migrant. We tested differences between autumn and spring migration for nine individuals. Duration of migration between breeding and winter sites was significantly longer in autumn (average 96 days) when compared with spring (63 days). This difference was explained by much longer staging periods during autumn (71 days) than spring (9 days). Between staging periods, the birds travelled faster during autumn (356 km d ). All birds made a protracted stop (53 days) in Sahelian sub-Sahara on southbound migration. The birds performed a distinct loop migration (22 000 km) where spring distance, including a detour across the Arabian Peninsula, exceeded the autumn distance by 22 per cent. Geographical scatter between routes was particularly narrow in spring, with navigational convergence towards the crossing point from Africa to the Arabian Peninsula. Temporal variation between individuals was relatively constant, while different individuals tended to be consistently early or late at different departure/arrival occasions during the annual cycle. These results demonstrate the existence of fundamentally different spatio-temporal migration strategies used by the birds during autumn and spring migration, and that songbirds may rely on distinct staging areas for completion of their annual cycle, suggesting more sophisticated endogenous control mechanisms than merely clockand-compass guidance among terrestrial solitary migrants. After a century with metal-ringing, year-round tracking of long-distance migratory songbirds promises further insights into bird migration.

Despite an overall advancement in breeding area arrival, one of the latest spring arrivals in northwest Europe since 1950 of several trans-Saharan songbird species occurred in 2011. Year-round tracking of red-backed shrikes and thrush nightingales revealed that the cause of the delay was a prolongation of stopover time during spring migration at the Horn of Africa, which was affected by extreme drought. Our results help to establish a direct link at the individual level between changes in local climate during migration and arrival and breeding condition in Europe thousands of kilometers further north.

Aim To understand how the integration of contextual spatial data on land cover and human infrastructure can help reduce spatial bias in sampling effort, and improve the utilization of citizen science‐based species recording schemes. By comparing four different citizen science projects, we explore how the sampling design's complexity affects the role of these spatial biases. Location Denmark, Europe. Methods We used a point process model to estimate the effect of land cover and human infrastructure on the intensity of observations from four different citizen science species recording schemes. We then use these results to predict areas of under‐ and oversampling as well as relative biodiversity ‘hotspots’ and ‘deserts’, accounting for common spatial biases introduced in unstructured sampling designs. Results We demonstrate that the explanatory power of spatial biases such as infrastructure and human population density increased as the complexity of the sampling schemes decreased. Despite a low absolute sampling effort in agricultural landscapes, these areas still appeared oversampled compared to the observed species richness. Conversely, forests and grassland appeared undersampled despite higher absolute sampling efforts. We also present a novel and effective analytical approach to address spatial biases in unstructured sampling schemes and a new way to address such biases, when more structured sampling is not an option. Main conclusions We show that citizen science datasets, which rely on untrained amateurs, are more heavily prone to spatial biases from infrastructure and human population density. Objectives and protocols of mass‐participating projects should thus be designed with this in mind. Our results suggest that, where contextual data is available, modelling the intensity of individual observation can help understand and quantify how spatial biases affect the observed biological patterns.