Data from: Variations in age- and sex-specific survival rates help explain population trend in a discrete marine mammal population

1. Understanding the drivers underlying fluctuations in the size of animal
populations is central to ecology, conservation biology and wildlife
management. Reliable estimates of survival probabilities are key to
population viability assessments, and patterns of variation in survival
can help inferring the causal factors behind detected changes in
population size. 2. We investigated whether variation in age and
sex-specific survival probabilities could help explain the increasing
trend in population size detected in a small, discrete population of
bottlenose dolphins Tursiops truncatus off the east coast of Scotland. 3.
To estimate annual survival probabilities we applied capture-recapture
models to photo-identification data collected from 1989 to 2015. We used
robust design models accounting for temporary emigration to estimate
juvenile and adult survival, multi-state models to estimate sex-specific
survival, and age-models to estimate calf survival. 4. We found strong
support for an increase in juvenile/adult annual survival from 93.1% to
96.0% over the study period, most likely caused by a change in juvenile
survival. Examination of sex-specific variation showed weaker support for
this trend being a result of increasing female survival, which was overall
higher than for males and animals of unknown sex. Calf survival was lower
in the first than second year; a bias in estimating third-year survival
will likely exist in similar studies. There was some support first-born
calf survival being lower than for calves born subsequently. 5. Coastal
marine mammal populations are subject to the impacts of environmental
change, increasing anthropogenic disturbance and the effects of management
measures. Survival estimates are essential to improve our understanding of
population dynamics and help predict how future pressures may impact
populations, but obtaining robust information on the life history of
long-lived species is challenging. Our study illustrates how knowledge of
survival can be increased by applying a robust analytical framework to
photo-identification data.