Apparent breeding success drives long-term population dynamics of a migratory swan

Abstract

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 NW 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 c. 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.

Methods

Encounter history -- data was collected over 47 years of mark-resighting research with both legrings and neckbands. In the csv, the years of the study (1969 - 2015) are indicated with they year index as the column header (1-47) and the individual ID as the rows. When an individual was resighted that year, a '1' is present in the matrix 'encounter-history.csv', otherwise a '0'.

Counts -- internationally coordinated counts of Bewick's swans take place every 5 years in January. The results of these counts are imputed to fill missing years based on a lineary imputation (see Methods section in Manuscript). Census years are indicated with 'TRUE' in the CensusYear column in the csv 'counts-jp.csv'.

Juvenile percentage (jp) -- every year, the proportion of juveniles on the total population are done in the Netherlands and the UK in December/January as a proxy for breeding success. The average of the estimates for both countries are presented in the csv 'counts-jp.csv' in the column 'JuvenilePercentage'.

Output IPM -- in the csv 'ipm-output.csv' the estimates and their sd for adult survival (phi.a), yearling survival (phi.s), juvenile survival (phi.j), apparent breeding succes (kappa) and the population growth rate (lambdaW) are given. The Brooks-Rubin-Gelman diagnostic is given to check convergence of the MCMC chains (should be below 1.1; Brooks & Gelman 1998).

Brooks, S. P. and Gelman, A. 1998. General methods for monitoring convergence of iterative simulations? J. Comput. Graph. Stat. 7: 434–455.

Funding

Nederlandse Organisatie voor Wetenschappelijk Onderzoek, Award: 866.15.206