Philosophy of using RAMP to measure vitality, survival, and mortality of animals

Blue sharks and food, WASC

Mortality can occur over varying time frames after an animal is exposed to potentially lethal stressors. The problem of mortality prediction is made more difficult by animal mobility, as animals can become hidden from observation, especially over longer time frames. Then indicator measures must be used to predict cryptic delayed mortality. What is an effective indicator for predicting mortality? Do we observe the animal immediately after stress induction and before leaving our presence, or do we observe the conditions in which the animal was stressed? 

A common approach to predicting delayed animal mortality is to observe the conditions in which stress is induced and use this information as an indicator for mortality.  Animals are experimentally exposed to important stressors and their combinations in a matrix of interactions. Then animals are sampled for mortality after holding them captive for short periods or tagging, releasing, and recapturing or using biotelemetry over longer time frames. Mortality, and its inverse, survival are then modeled from sampled combinations of risk factors. Since there are relatively unlimited sets of risk factors and their interactions, indicator models for mortality based on stressors often will not give realistic estimates or not include important conditions for stress induction.

Alternatively, animal impairment can be observed as an indicator for delayed mortality after exposure to risk factors. Reflex impairment occurs immediately in an animal when it’s neural, muscular, or organ systems are stressed. Summing presence or absence of several reflex actions calculates an index called RAMP (reflex action mortality predictor) which is a direct measure of reflex impairment and vitality. Correlation of RAMP with immediate and delayed mortality make it an indicator for mortality and survival. With RAMP, the approach of predicting mortality is based on direct observations of animal vitality. The animal continually integrates all the effects of experienced risk factors as reflex impairment and communicates it’s health state, vitality, and fitness through the language of RAMP. Other types of animal impairment that have been tested as potential indicators for mortality include physiological variables (cortisol, glucose, lactate, and electrolytes) and injury.  However these measures are not consistently correlated with delayed mortality.

In an effort to ameliorate mortality risk factors, a hybrid approach can be used for predicting cryptic delayed mortality that conserves and integrates information. Instead of asking the question “Does the animal die?” we can ask “When, where, and under what conditions does the animal die?” Animals are observed in experimentally controlled conditions of mortality risk (Davis 2002, Suuronen 2005). Then initial stressor conditions are sampled, as well as time courses for animal impairment and delayed mortality. Relationships between stressor factors, animal impairment, and delayed mortality can be identified and modeled. The resulting knowledge base can be used to test hypotheses about importance of mortality risk factors and efficacy of predicting cryptic delayed mortality using animal impairment as an indicator. Previous research has shown that reflex impairment measured as RAMP is a powerful predictor for cryptic delayed mortality (Davis 2010). After validation, RAMP can be used to test the effects of experimental or natural changes in mortality risk factors such as design of fishing gears, aquaculture rearing conditions, aquarium trade, pollution exposure, climate change, and other potentially risky situations.

Trawl bycatch reduction device, FRDC

The problem of using indicators to predict cryptic delayed mortality is simplified by shifting from modeling mortality in potentially unlimited sets of risk factors to direct, real time measurement of animal impairment and prediction of delayed mortality. This shift in focus to reflex impairment allows for real time testing of animal fitness in systems of interest and is a cheaper, more efficient use of limited research resources than using risk factor indicators for mortality prediction.