Using effort, sightings, and body condition data to estimate survival and health of individuals and the entire right whale population.

Mary Woodcock Kroble
Saturday 10 November 2012
Date: 27 March 2013
Time: 4:00 pm - 5:00 pm

Speaker: Rob Schick (CREEM)


Natural and anthropogenic stressors are presumed to impact the health and survival of right whales, yet the effect of these stressors has proven difficult to quantify. To address this issue we built a Hierarchical Bayesian model for survival of individual right whales and fit this model to 30 years worth of sighting data. We assimilate the photographic evidence of visual health parameters for individuals as observations of true, but hidden, health. We use the model to make inference on movement, individual survival, and individual health. In this talk I will present and discuss estimates of health of individuals, population sub-categories, and the entire population.

Estimates of individual health fluctuated across broad ranges, with a mean “healthy” score equaling 84 (on a 0 to 100) scale. We were able to quantitatively link discrete health observations to underlying continuous states, though estimates are less certain for animals with sparse sighting histories. For individuals, discrete observations of poor skin and body condition in particular, appeared to have a strong impact on health. We explored the health trajectories of different population classes, which suggest that females who bring their calves to known habitat regions (i.e. the Bay of Fundy, Canada) fared worse in the 1990’s. Since that time, however, this population class appears in better health than females who do not bring their calves to the Bay of Fundy. At the population level, health was stable throughout much of the 1980’s. Health values in the 1990’s decline from a population average of 85 to a low of 72 in 1999. Population health stabilizes and increases in the 2000’s, though the decade scale average (76) is lower than the 1980’s.

In the future we hope to use these estimates of movement, survival and health to suggest possible management scenarios that increase survival among individuals and the population as a whole.

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