Abstract

Energy storage is a common adaptation of fish living in seasonal environments. For some species, the energy accumulated during the growing season, and stored primarily as lipids, is crucial to preventing starvation mortality over winter. Thus, in order to understand the adaptive responses of fish life history to climate, it is important to determine how energy should be allocated to storage and how it trades off with the other body components that contribute to fitness. In this paper, we extend previous life history theory to include an explicit representation of how the seasonal allocation of energy to storage acts as a constraint on fish growth. We show that a strategy that privileges allocation to structural mass in the first part of the growing season and switches to storage allocation later on, as observed empirically in several fish species, is the strategy that maximizes growth efficiency and hence is expected to be favored by natural selection. Stochastic simulations within this theoretical framework demonstrate that the relative performance of this switching strategy is robust to a wide range of fluctuations in growing season length, and to moderate short-term (i.e., daily) fluctuations in energy intake and/or expenditure within the growing season. We then integrate this switching strategy with a biphasic growth modeling framework to predict typical growth rates of walleye Sander vitreus, a cool water species, and lake trout Salvelinus namaycush, a cold water specialist, across a climatic gradient in North America. As predicted, growth rates increased linearly with the duration of the growing season. Regression line intercepts were negative, indicating that growth can only occur when growing season length exceeds a threshold necessary to produce storage for winter survival. The model also reveals important differences between species, showing that observed growth rates of lake trout are systematically higher than those of walleye in relatively colder lakes. This systematic difference is consistent with both (i) the expected superior capacity of lake trout to withstand harsh winter conditions, and (ii) some degree of counter gradient adaptation of lake trout growth capacity to the climatic gradient covered by our data.

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