Toward a physiological explanation of juvenile growth curves

Juvenile growth curves are generally sigmoid in shape: Growth is initially nearly exponential, but it slows to near zero as the animal approaches maturity. The drop‐off in growth rate is puzzling because, everything else being equal, selection favors growing as fast as possible. Existing theory posits sublinear scaling of resource acquisition with juvenile body mass and linear scaling of the requirement for maintenance, so the difference, fuel for growth, decreases as the juvenile increases in size. Experimental evidence, however, suggests that maintenance metabolism increases sublinearly not linearly with size. Here, we develop a new theory consistent with the experimental evidence. Our theory is based on the plausible assumption that there is a trade‐off in the capacity of capillaries to supply growing and developed cells. As the proportion of non‐growing cells increases, they take up more macromolecules from the capillaries, leaving fewer to support growing cells. The predicted growth curves are realistic and similar to those of previous models (Bertalanffy, Gompertz, and Logistic) but have the advantage of being derived from a plausible physiological model. We hope that our focus on resource delivery in capillaries will encourage new experimental work to identify the detailed physiological basis of the trade‐off underlying juvenile growth curves

Prediction of daphnid survival after in situ exposure to complex mixtures

We applied a mechanistically based model to predict the effects of complex mixtures as occurring in the field on the survival of Daphnia magna. We validated the model by comparing predicted survival with observed survival of in situ exposed laboratory cultured daphnids to polluted surface waters, in which over 90 chemical contaminants were measured. Using the chemical composition of the surface water at each sampling site, we calculated whether or not any of the individual or shared no effect concentrations were exceeded. If they were, we calculated the effect on survival. In 34 out of 37 cases (92%) we correctly predicted daphnid survival in surface waters. In the case of mortality we could also appoint the compound or group of compounds causing the effect. It is concluded that the proposed mechanistically based model accurately predicts effects on daphnids in the field, given the chemical composition of the water. Hence it is a powerful tool to link the chemical and ecological status of surface waters