Key fishing stressor factors, Davis, 2002
Knowledge of key factors controlling fisheries is necessary for sustainable management of fishery stocks. Scientific hypothesis testing in the form of fishing experiments is a necessary component of fisheries knowledge development and validation. Fishing experiments are performed in the field by simulating actual fishing conditions, by actual fishing, and during survey cruises. Fishing experiments can be used to identify key stressor factors that control and contribute to the survival and mortality of captured, discarded, or escaped animals as well as identifying the key factors controlling fishing gear capture efficiency and selectivity.
Trawl captured animals, Robert A. Pawlowski, NOAA Corps
While field fishing experiments represent realistic conditions, they are a matrix of confounded factors which cannot be easily separated into mechanistic hypothesis tests and explanations of factor importance. Effects of factors are often synergistic and prior animal stressor history can alter relative effects of subsequent exposure to factors, e.g., depth changes, injury, elevated temperature, air exposure, and size and species differences.
Flow chart of experimental fishing stressor factors, Davis and Olla 2001
Simulated fishing experiments with factors in controlled laboratory conditions is one way to test hypotheses about mechanistic effects of individual factors and their interactions. However these laboratory experiments are generally viewed as not realistic to field conditions and they are used to identify factors that may be important in the field. Furthermore, modern requirements of animal care laws and committees restrict the use of laboratory fishing experiments by not allowing human application of experimental stressor factors on animals and the use of mortality outcomes. These same laws and committees do not have jurisdiction over field fishing experiments.
Given that factors are confounded in field fishing experiments, how can we test for effects of factors in the traditional mechanistic hypothesis test? We can test for changes in animal vitality. Since vitality has been shown to be correlated with survival and mortality, it is a useful indicator of animal outcomes before and after exposure to experimental stressor factors. For example, we generally do not know the exposure of animals to stressors prior to experimental manipulation of factors. Not knowing the complete stressor profile is not an obstacle since the animal knows the complete stressor profile and presents vitality levels that have integrated the effects of that profile. Then we can expose animals to additional stressor factors and measure further changes in vitality from their initial levels.
Important to shift mechanistic thinking from needing to know the effects of individual factors to knowing the effects of fishing variability. Manipulations of time in air and elevated temperature represent differences in fisher sorting and handling behavior on deck and are appropriate for defining the effects of fishing variability. Effects of variation in tow time and catch quantity can be manipulated and are included in the mix of animals landed. The questions of associations among individual fishing stressor factors is left for another day and are more of interest to mechanistic scientists than to managers and fishers. Fishing variability will give a picture of the fishery and its potential effects on animal vitality. By measuring animal vitality, which integrates the effects of stressor factors, you have measured a key master variable that indicates the important effects of fishing.
Vitality is the key variable that can be used to indicate and predict delayed survival and mortality outcomes for discards and escapees from fishing. The relationships between vitality and survival and mortality are defined by captive observation or tagging and biotelemetry experiments. During exposure of animals it is important to insure that all stressor types normally in the fishery in question are present for the population of tested animals (e.g., temperature, air exposure, fatigue, injury) and that a full range (0-100%) of vitality impairment and mortality are observed. Then relationships can be calculated for each species of interest that do not extrapolate beyond available data ranges and that apply to the fishery of interest. These relationships can then be used to predict survival and mortality for animals under any condition of interest in the fishery without the need for further captive observations or tagging.
Consider how scientific peer-reviewers may see this shift from mechanistic thinking and develop thoughts that elaborate the importance of vitality from the animal’s point of view. Some resistance is expected from mechanists who believe that they can attribute cause and effect to individual factors. There is always a matrix of interactions, even under the most restrictive and controlled experimental conditions. There are always interactions and synergisms to account for. As a result, there are associations among factors, rather than cause and effect. In other words, there are causes and conditions associated with effects.
From the fishing experiment perspective, we set up fishing conditions that are real or that simulate fishing and then measure animal vitality, which is an integrated measure of the effects of interacting factors. It is useful to identify the important stressors by experimentally changing them in fishing experiments; changes in time in air, trawl time, trap retrieval time, depth, season, temperature, catch amount, and injuries. Always remember that there is a hidden context of conditions, i.e., the animals are prestressed by other factors not being controlled. But this hidden context can be accounted for by observing and comparing vitality impairment among animals observed in all treatments, including simply captured animals without additional stressor exposures (using positive controls). This experimental approach is useful both for fishers who wish to modify fishing gear and practices, as well as managers who wish to observe animal vitality and correlate that with mortality and survival.
