The ability of a species to adapt to environmental change is ultimately reflected in its vital rates – i.e. survival and reproductive success of individuals. Together, vital rates determine trends in numbers, commonly monitored using counts of species abundance. Rapid changes in abundance can give rise to concern, leading to calls for research into the biological mechanisms underlying variations in demography. For the northwest European population of Bewick's swan Cygnus columbianus bewickii, there have been major changes in the population trends recorded during nearly five decades of monitoring (1970–2016). The total number of birds increased to a maximum of ca 30 000 in 1995 and subsequently decreased to about 18 000 individuals in 2010. Such large fluctuation in population numbers is rare in long‐lived species and understanding the drivers of this population change is crucial for species management and conservation. Using the integrated population model (IPM) framework, we analysed three demographic datasets in combination: population counts, capture–mark–resightings (CMR) and the proportion of juveniles in winter over a period of ~50 years. We found higher apparent breeding success in the years when the population had a positive growth rate compared to years with a negative growth rate. Moreover, no consistent trend in adult and yearling survival, and an increasing trend in juvenile survival was found. A transient life‐table response experiment showed that apparent breeding success and adult survival contributed most to the variation in population trend. We explored possible explanatory variables for the different demographic rates and found a significant association between juvenile survival both with the water level in lakes during autumn migration, which affects food accessibility for the swans, and with summer temperatures. Such associations are important for understanding the dynamics of species with fluctuating population sizes, and thus for informing management and conservation decisions.
- Bewick’s swan
- integrated population model
- environmental drivers
- transient life table response experiment