Implications of resource driven size-structure for population stability and sustainable harvest

Background/Question/Methods

While in marine systems fish often need to reach a minimum size to mature; that is typically not the case in freshwater systems. This can allow for a wide range of sizes within the adult portion of the population without implications for population growth. In fact, variable growth trajectories from fast growing larger fish to slow growing smaller fish are often seen within a lake, resulting in “wide” growth curves. However this variance in growth trajectories isn’t consistent between all lakes, some populations have thin growth curves, and some even have large gaps in their growth curves. For energetic and gape limitation purposes, it is often the case that fish predators change resource types throughout their growth and ontogeny. In order to reach a particular size, a succession of larger and larger prey types are required.  This implies that the number of growth trajectories, or width of the growth curve, is directly related to the availability of resources. As a reflection of food-web interactions, the growth curve, a commonly measured metric in fisheries management, has the potential to provide insight on population stability.

Results/Conclusions

By creating a simple discrete size-structured population model, we were able to replicate the different growth curves found in natural populations by altering growth rates and size specific resource availability.  Based on the principles of energy flow and stability, we hypothesised that when energy flows quickly through a population, the population is more excitable than when there is structure within the population to slow down the flow of energy. This implies that if you were to perturb the population, the width of the growth curve would determine how quickly the population will return to the equilibrium.  This type of stability was chosen to represent the implications of a fishing event.  The model supported this hypothesis; faster growth rates were less stable.  Because energy was able to move quickly through the population, thicker growth curves were the result of faster growth rates and the thicker the growth curve, the more likely the model was to be unstable.  Length-at-age and time-series data from several lakes in Ontario supported this result. These results are encouraging in terms of using commonly collected data to provide managers with information about population stability.