Estimating body condition in right whales and elephant seals as a key link between disturbance and population level consequences

Speaker: Robert S. Schick (Duke University)

Abstract

Natural and anthropogenic environmental changes affect the behavior and physiology of individual organisms, but their ecological significance depends on their consequences at the population level. Understanding how individual condition can be affected by behavior-altering disturbance, and how in turn changes at the individual level can cascade through to population level effects in vital rates is a key goal of marine ecology. Despite the advances in biotelemetry, we still lack the ability to monitor changes in body condition at fine temporal scales while marine predators are at sea. To address this discrepancy, we examine changes in body condition in three different species of marine predator: northern and southern elephant seals, and north atlantic right whales. To estimate condition in these species we used two different modeling approaches. The first case study, elephant seals, relied on inferring daily changes in lipid content in pregnant adult females using observations on drift rates through the water column. The second case study, right whales, relied on estimating daily changes in health as a function of sporadic observations of body condition using photo mark-recapture. For elephant seals we have successfully fit a hierarchical Bayesian state-space model to 29 northern elephant seals, and 30 southern elephant seals, providing daily estimates of lipid status with uncertainty. For right whales, though we are in the early stages of modeling, we have been able to assimilate many types of data from a wide range of sources, and provide initial estimates of underlying health at a monthly time-step for each individual in the population. The modeling approach can also be used to infer condition in a variety of species – both marine and terrestrial. Results from this effort can be used to link disturbance to individual and population health, and inform both where and when management efforts will be most effective.