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Understanding how ecological processes combine to shape population dynamics is crucial in a rapidly changing world. Evidence has been emerging for how fundamental drivers of density dependence in mobile species are related to two differing types of environmental variation—temporal variation in climate, and spatiotemporal variation in food resources. However, to date, tests of these hypotheses have been largely restricted to mid‐trophic species in terrestrial environments and thus their general applicability remains unknown.We tested if these same processes can be identified in marine upper trophic level species. We assembled a multi‐decadal data set on population abundance of 10 species of colonial seabirds comprising a large component of the UK breeding seabird biomass, and covering diverse phylogenies, life histories and foraging behaviours.We tested for evidence of density dependence in population growth rates using discrete time state‐space population models fit to long time‐series of observations of abundance at seabird breeding colonies. We then assessed if the strength of density dependence in population growth rates was exacerbated by temporal variation in climate (sea temperature and swell height), and attenuated by spatiotemporal variation in prey resources (productivity and tidal fronts).The majority of species showed patterns consistent with temporal variation in climate acting to strengthen density dependent feedbacks to population growth. However, fewer species showed evidence for a weakening of density dependence with increasing spatiotemporal variation in prey resources.Our findings extend this emerging theory for how different sources of environmental variation may shape the dynamics and regulation of animal populations, demonstrating its role in upper trophic marine species. We show that environmental variation leaves a signal in long‐term population dynamics of seabirds with potentially important consequences for their demography and trophic interactions. [ABSTRACT FROM AUTHOR]

The ability of individual animals to balance their energy budgets throughout the annual cycle is important for their survival, reproduction and population dynamics. However, the annual cycles of many wild, mobile animals are difficult to observe and our understanding of how individuals balance their energy budgets throughout the year therefore remains poor.We developed a hierarchical Bayesian state‐space model to investigate how key components of animal energy budgets (namely individual energy gain and storage) varied in space and time. Our model used biologger‐derived estimates of time‐activity budgets, locations and energy expenditure to infer year‐round time series of energy income and reserves. The model accounted for seasonality in environmental drivers such as sea surface temperature and daylength, allowing us to identify times and locations of high energy gain.Our study system was a population of common guillemots Uria aalge breeding at a western North Sea colony. These seabirds manage their energy budgets by adjusting their behaviour and accumulating fat reserves. However, typically during severe weather conditions, birds can experience an energy deficit over a sustained period, leading to starvation and large‐scale mortality events.We show that guillemot energy gain varied in both time and space. Estimates of guillemot body mass varied throughout the annual cycle and birds periodically experienced losses in mass. Mass losses were likely to have either been adaptive, or due to energetic bottlenecks, the latter leading to increased susceptibility to mortality. Guillemots tended to be lighter towards the edge of their spatial distribution.We describe a framework that combines biologging data, time‐activity budget analysis and Bayesian state‐space modelling to identify times and locations of high energetic reward or potential energetic bottlenecks in a wild animal population. Our approach can be extended to address ecological and conservation‐driven questions that were previously unanswerable due to logistical complexities in collecting data on wild, mobile animals across full annual cycles. Read the free Plain Language Summary for this article on the Journal blog. [ABSTRACT FROM AUTHOR]

1. Understanding the degree to which reproductive success varies with an individual’s age and lifespan, and the degree to which population-level variation mirrors individual-level variation, is central to understanding life-history evolution and the dynamics of age-structured populations. We quantified variation in the survival probability of offspring, one key component of reproductive success and fitness, in relation to parent age and lifespan in a wild population of red-billed choughs ( Pyrrhocorax pyrrhocorax). 2. On average across the study population, the first-year survival probability of offspring decreased with increasing parent age and lifespan; offspring of old parents were less likely to survive than offspring of young parents, and offspring of long-lived parents were less likely to survive than offspring of short-lived parents. 3. However, survival did not vary with parent age across offspring produced by groups of parents that ultimately had similar lifespans. 4. Rather, across offspring produced by young parents, offspring survival decreased with increasing parent lifespan; parents that ultimately had long lifespans produced offspring that survived poorly, even when these parents were breeding at young ages. 5. The average decrease in offspring survival with increasing parent age observed across the population therefore reflected the gradual disappearance of short-lived parents that produced offspring that survived well, not age-specific variation in offspring survival within individual parents. 6. The negative correlation between offspring survival and maternal lifespan was strongest when environmental conditions meant that offspring survival was low across the population. 7. These data suggest an environment-dependent trade-off between parent and offspring survival, show consistent individual variation in the resolution of this trade-off that is set early in a parent’s life, and demonstrate that such structured life-history variation can generate spurious evidence of senescence in key fitness components when measured across a population. [ABSTRACT FROM AUTHOR]