Dear MARMAM colleagues, We are pleased to announce that the following paper is now available online: Enrico Pirotta, Cormac G. Booth, David E. Cade, John Calambokidis, Daniel P. Costa, James A. Fahlbusch, Ari S. Friedlaender, Jeremy A. Goldbogen, John Harwood, Elliott L. Hazen, Leslie New and Brandon L. Southall. 2021. Context-dependent variability in the predicted daily energetic costs of disturbance for blue whales. Conservation Physiology 9(1): coaa137. Abstract: Assessing the long-term consequences of sub-lethal anthropogenic disturbance on wildlife populations requires integrating data on fine-scale individual behavior and physiology into spatially and temporally broader, population-level inference. A typical behavioral response to disturbance is the cessation of foraging, which can be translated into a common metric of energetic cost. However, this necessitates detailed empirical information on baseline movements, activity budgets, feeding rates, and energy intake, as well as the probability of an individual responding to the disturbance-inducing stressor within different exposure contexts. Here, we integrated data from blue whales (Balaenoptera musculus) experimentally exposed to military active sonar signals with fine-scale measurements of baseline behavior over multiple days or weeks obtained from accelerometry loggers, telemetry tracking and prey sampling. Specifically, we developed daily simulations of movement, feeding behavior and exposure to localized sonar events of increasing duration and intensity, and predicted the effects of this disturbance source on the daily energy intake of an individual. Activity budgets and movements were highly variable in space and time and among individuals, resulting in large variability in predicted energetic intake and costs. In half of our simulations, an individual’s energy intake was unaffected by the simulated source. However, some individuals lost their entire daily energy intake under brief or weak exposure scenarios. Given this large variation, population-level models will have to assess the consequences of the entire distribution of energetic costs, rather than only consider single summary statistics. The shape of the exposure-response functions also strongly influenced predictions, reinforcing the need for contextually explicit experiments and improved mechanistic understanding of the processes driving behavioral and physiological responses to disturbance. This study presents a robust approach for integrating different types of empirical information to assess the effects of disturbance at spatio-temporal and ecological scales that are relevant to management and conservation. Keywords: data integration, behavioral response studies, energy budget, population consequences of disturbance, navy sonar, marine mammals. A PDF copy of the paper can be downloaded for free from: https://academic.oup.com/conphys/article/9/1/coaa137/6102278 Please do not hesitate to contact me for any question regarding our work. Best Regards, Enrico Pirotta