The survival of North Atlantic right whales (Eubalaena glacialis) is seriously threatened by mortality caused by ships and entanglements in fishing gear. Demographic modeling indicates that the population is declining despite efforts to reduce anthropogenic mortalities, and in spite of recent increases in calving. The authors of this Policy Forum recommend immediate emergency management actions to reduce shipping and entanglement mortalities in right whales, so as to avoid a catastrophic population decline and inevitable extinction.

The North Atlantic northern right whale (Eubalaena glacialis) is considered the most endangered large whale species. Its population has recovered only slowly since the cessation of commercial whaling and numbers about 300 individuals. We applied mark-recapture statistics to a catalog of photographically identified individuals to obtain the first statistically rigorous estimates of survival probability for this population. Crude survival decreased from about 0.99 per year in 1980 to about 0.94 in 1994. We combined this survival trend with a reported decrease in reproductive rate into a branching process model to compute population growth rate and extinction probability. Population growth rate declined from about 1.053 in 1980 to about 0.976 in 1994. Under current conditions the population is doomed to extinction; an upper bound on the expected time to extinction is 191 years. The most effective way to improve the prospects of the population is to reduce mortality. The right whale is at risk from entanglement in fishing gear and from collisions with ships. Reducing this human-caused mortality is essential to the viability of this population.

Demographic heterogeneity—variation among individuals in survival and reproduction—is ubiquitous in natural populations. Structured population models address heterogeneity due to age, size, or major developmental stages. However, other important sources of demographic heterogeneity, such as genetic variation, spatial heterogeneity in the environment, maternal effects, and differential exposure to stressors, are often not easily measured and hence are modeled as stochasticity. Recent research has elucidated the role of demographic heterogeneity in changing the magnitude of demographic stochasticity in small populations. Here we demonstrate a previously unrecognized effect: heterogeneous survival in long‐lived species can increase the long‐term growth rate in populations of any size. We illustrate this result using simple models in which each individual's annual survival rate is independent of age but survival may differ among individuals within a cohort. Similar models, but with nonoverlapping generations, have been extensively studied by demographers, who showed that, because the more “frail” individuals are more likely to die at a young age, the average survival rate of the cohort increases with age. Within ecology and evolution, this phenomenon of “cohort selection” is increasingly appreciated as a confounding factor in studies of senescence. We show that, when placed in a population model with overlapping generations, this heterogeneity also causes the asymptotic population growth rate λ to increase, relative to a homogeneous population with the same mean survival rate at birth. The increase occurs because, even integrating over all the cohorts in the population, the population becomes increasingly dominated by the more robust individuals. The growth rate increases monotonically with the variance in survival rates, and the effect can be substantial, easily doubling the growth rate of slow‐growing populations. Correlations between parent and offspring phenotype change the magnitude of the increase in λ, but the increase occurs even for negative parent–offspring correlations. The effect of heterogeneity in reproductive rate on λ is quite different: growth rate increases with reproductive heterogeneity for positive parent–offspring correlation but decreases for negative parent–offspring correlation. These effects of demographic heterogeneity on λ have important implications for population dynamics, population viability analysis, and evolution.

Summary: Winter survival rate in Harbour Seal pups is significantly correlated with the autumn body mass of pups. Multi‐type mark–recapture statistics were applied to individual re‐sighting histories of branded seals, and survival probability was estimated with weight as a covariate. The probability of surviving to an age of 1 year is only 0·63 for the smallest pups at 17 kg, whereas pups at 32 kg have a survival probability of 0·96. An energetic model for juvenile Harbour Seals reveals how metabolic rate is related to body mass, skin surface area, blubber thickness and water temperature. There is an increasing thermal stress with decreasing body size of pups. Low winter water temperatures induce a negative energy balance in small pups, which is a probable cause of the observed mass‐dependent survival. This study explicitly links a physical property of the environment, sea‐water temperature, to energetics and life history. The approach opens possibilities for studying aspects of life‐history evolution, such as optimal weaning weight and pupping time, in marine mammals.