Importance of context for RAMP curves used to predict mortality and survival of stressed animals

Relationships between reflex/buoyancy impairment and post-capture mortality for Atlantic cod (Humborstad et al. 2016).

Humborstad et al. (2016) looked at the relationship between reflex/buoyancy impairment and post-capture mortality for Atlantic cod exposed to fishing stressors. RAMP curves were generated for (a) fish exposed to laboratory simulated forced swimming, air exposure, and net abrasion, (b) field longline capture, and (c) field pot capture. The authors concluded that:

“It appears that specific RAMP curves may be needed for gears that involve different stressors, including consideration of any additional stress associated with captive observation of delayed mortality. Differences in stressors and holding conditions certainly reduce the general applicability of RAMP across different stressors and fisheries. However, once a RAMP curve has been established for a specific set of stressors or gears, the strong relationship between reflex impairment and mortality shows the potential for predicting mortality outcomes, especially at high and low levels of impairment.”

“Reflex impairment could predict mortality among fish caught by pot and longline. However, different RAMP curves were observed between laboratory and field conditions, indicating that careful consideration must be given to the types of stressors present and captive-observation conditions for delayed mortality when comparing RAMP curves for different fisheries. The inclusion of buoyancy status in modelling greatly improved mortality predictability.”

Science and medicine generally do not know proximate and ultimate causes for why fish and other animals die. This lack of mechanistic knowledge precludes us from direct understanding and prediction of death. However, we can observe correlates with death; animal size, stressors, vitality impairment, and physiological impairment. These correlates can be used to identify risk factors and predict immediate and delayed mortality. 

Successful mortality and survival prediction requires that the context of animal exposure to stressor risk and recovery be included in any experimental analysis of this problem.  We cannot simply identify stressors, impairment, or physiological numbers and say that they will result in a particular mortality (Davis 2002). RAMP curves clearly show the importance of context for exposure to stressors and potential mortality or survival (Davis 2010). The question of interactions among stressors and their context has recently been elaborated for freshwater and marine systems (Jackson et al. in press).