Evaluating the demographic buffering hypothesis with vital rates estimated for Weddell seals from 30 years of mark–recapture data

Abstract

Summary1. Life-history theory predicts that those vital rates that make larger contributions to population growth rate ought to be more strongly buffered against environmental variability than are those that are less important. Despite the importance of the theory for predicting demographic responses to changes in the environment, it is not yet known how pervasive demographic buffering is in animal populations because the validity of most existing studies has been called into question because of methodological deficiencies. 2. We tested for demographic buffering in the southern-most breeding mammal population in the world using data collected from 5558 known-age female Weddell seals over 30 years. We first estimated all vital rates simultaneously with mark-recapture analysis and then estimated process variance and covariance in those rates using a hierarchical Bayesian approach. We next calculated the population growth rate's sensitivity to changes in each of the vital rates and tested for evidence of demographic buffering by comparing properly scaled values of sensitivity and process variance in vital rates. 3. We found evidence of positive process covariance between vital rates, which indicates that all vital rates are affected in the same direction by changes in annual environment. Despite the positive correlations, we found strong evidence that demographic buffering occurred through reductions in variation in the vital rates to which population growth rate was most sensitive. Process variation in vital rates was inversely related to sensitivity measures such that variation was greatest in breeding probabilities, intermediate for survival rates of young animals and lowest for survival rates of older animals. 4. Our work contributes to a small but growing set of studies that have used rigorous methods on long-term, detailed data to investigate demographic responses to environmental variation. The information from these studies improves our understanding of life-history evolution in stochastic environments and provides useful information for predicting population responses to future environmental change. Our results for an Antarctic apex predator also provide useful baselines from a marine ecosystem when its top-and middle-trophic levels were not substantially impacted by human activity.

Environmental extremes versus ecological extremes: impact of a massive iceberg on the population dynamics of a high-level Antarctic marine predator

“…The apparent behavioural response of seals was in keeping with a strategy of saving and allocating a larger proportion of energy to survival, as would be expected in a long-lived organism [9,33]. The ability to buffer adult survival against environmental variability by adjusting reproductive effort has already been shown in this population [44], but previous work did not investigate the particulars of the iceberg event. Here, by explicitly assessing how demography during the iceberg period contrasted with that recorded in years with typical conditions, we demonstrated that the iceberg event had a substantial impact on reproduction, but that survival was well buffered from environmental variation.…”

“…Because vital rates are probabilities, their maximum possible variance is a function of the mean [10]. Therefore, following previous authors [9,10,15,44], we scaled the process variance by the maximum possible variance for the corresponding mean before making comparisons among different periods. For local abundance estimates, which were obtained independently for each year, the method of moments was performed in program R (v. 2.12.0, [46]), using the generalized weighted procedure [41].…”

“…We then compared the distributions of l between the two periods. The values of survival used in these simulations were adjusted for tag loss [37,44]. Because all vital rates are probabilities and thus belong to the interval [0;1], random values were generated at the scale of log odds using random normal deviates based on the estimated mean and variance of the log odds of each vital rate.…”

“…Recruitment was defined as the transition from state P to F (c PF ) and reproduction as transition from state F, E or S to state E (c FE , c EE , c SE ). Several combinations of age and year effects were considered for each reproductive status [36,37,44] and evaluated with the Akaike information criterion (AIC) corrected for sample size (AICc) and overdispersion (QAICc). The estimates that were subsequently used in the analysis come from the most supported of these models.…”

Agent-based modeling of the dynamics of mammal-eating killer whales and their prey

“…If we assume that most density-dependent changes in vital rates are driven by consumption, then what are often thought of as density-dependent responses in vital rates are more usefully analyzed as consumptiondependent responses in vital rates that control the abundance of predators. We expected these responses to adhere to density-dependent patterns in that juvenile survival and reproductive rates should be the most responsive to changes in the per capita prey consumption rates of killer whales, as in other large mammals (Eberhardt & Siniff 1977, Gaillard et al 1998, Eberhardt 2002, Rotella et al 2012). This expectation was confirmed by a high degree of consumption-dependence (p << 0.05; Fig.…”