OPTIMAL DIGESTIVE INVESTMENT - A MODEL FOR FILTER FEEDERS EXPERIENCING VARIABLE DIETS

A functional model of feeding behavior and physiology of suspension-feeding bivalves assumes that the net rate of energy gain from the available diet is maximized. Unlike previous models, a term is included for the rate of energy investment in digestive processes, such as the production of digestive enzymes and intracellular digestive products. In the model the digestive investment is applied within an absorption efficiency-gut residence time relationship. The choice of this relationship is based partly on two important assumptions. They are that the rate of digestion and absorption of the food should increase with the amount of digestive investment and that resorption of the digestive investment should depend on gut residence time. The choice of relationship has also been based on extensive empirical evidence of net enrichment of feces with endogenous metabolic products when gut residence times are short. The model suggests that the net rate of energy gain can be maximized through an optimal combination of gut residence time, digestive investment, and dietary selection coefficients. Analysis of the model with respect to variation in dietary quality and quantity suggests that feeding rate is constrained by the energetic costs of processing the food when food availability is low. When food is abundant, the rate of feeding is limited by constraints imposed by digestibility of the food and limitations on the rate of absorption of energy within the gut. The effect of a variable rate of digestive investment is to provide greater flexibility within the feeding system, particularly at the upper and lower extremes of food abundance. When particle concentrations and qualitities are such that behavioral dietary selection, coupled with increased rates of filtration, can be utilized to improve net energy gain, metabolic digestive investment is predicted to remain relatively constant. Relationships predicted by the model are in good agreement with empirical data.