Models for predicting nitrogen tensions and decompression sickness risk in diving beaked whales

Saunders, K.J., White, P.R. and Leighton, T.G. (2008) Models for predicting nitrogen tensions and decompression sickness risk in diving beaked whales. Institute of Acoustics: Underwater Noise Measurement, Impact and Mitigation 2008 Conference, Southampton, UK. 13 - 14 Oct 2008. pp. 82-89 .

Abstract

A model was produced which enables the nitrogen tensions generated in the tissues of diving beaked whales to be predicted for any given dive profile input. The results of a series of parameter sensitivity tests conducted on this model are also presented. These reveal that of the variables yet to be quantified specifically in the beaked whale species of interest – Ziphius cavirostris and Mesoplodon densirostris – the assumed depth of lung collapse is the most important determinant of the model output, followed by the Ostwald solubility constants for nitrogen in different tissue types, and the rate of blood flow to both individual tissues and the tissues of the body as a whole. Research is currently underway to design experiments that will allow these parameters to be quantified in these species, so that once substituted into the model, the resulting model output will be more specific to the beaked whales. This work represents the second and third stages in the development of a future version of the model, which will be designed to predict the risk of decompression sickness (DCS) occurring during any behavioural response exhibited by specific beaked whale species following their exposure to mid-frequency active sonar. The first stage of this work, which is also described here in brief, was to identify static diffusion as the primary mechanism of the bubble growth thought to lead to the DCS-like gas embolic disease observed in specimens of stranded whales exposed to naval sonar. It is intended that the tissue nitrogen tensions predicted by the current model will be combined with the theory of bubble growth via static diffusion to produce the final version of the model described above. This model will then be used to identify the behaviours theoretically conferring the highest risk of DCS, so that they may then be compared with those actually observed during controlled exposure experiments such as those currently underway in the Bahamas.

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Contributors

Author: P.R. White

Author: T.G. Leighton

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