A PHYSIOLOGICALLY BASED TRITROPHIC PERSPECTIVE ON BOTTOM-UP-TOP-DOWN REGULATION OF POPULATIONS'

A general tritrophic model of intermediate complexity representing the dy- namics of trophic level biomass and numbers is presented. The rudiments of the behavior and physiology of resource acquisition and conversion are incorporated as functional and numerical response models. The tritrophic model is used to examine the effects of trophic position on bottom-up-top-down regulation of populations in theory and in practice. The zero growth isoclines of the interacting populations are used to examine the dynamics of the tritrophic system. The herbivore (M2) and predator (M3) but not the plant (M1) isoclines can be solved explicitly. The plant and herbivore isoclines have two forms that depend on whether the proportion of the trophic level available to its consumer (i.e., its apparency) is greater than or less than its potential per unit biomass population growth rate. Rough estimates of the parameters of these inequalities may be deduced from our knowledge of the search biology of the species and known size to growth rate relationships. The model shows clearly that bottom-up regulation sets the upper limit for trophic- level growth and top-down regulation determines the level of realized growth. The model explains the paradoxes of enrichment and of biological control that arise from the standard Lotka-Volterra models, and its qualitative predictions compare well to the general con- clusions of intensive studies on biological control of the cassava mealybug on cassava by an exotic parasitoid. However, discrepancies that were found caution against unconsidered extrapolation of theoretical predictions to specific situations. The model qualitatively de- fines the dynamics required of a successful weed biological control agent, of a stable fresh water algal-arthropod herbivore-vertebrate predator system, and of a marine phytoplank- ton-krill-whale system. The utility of the model is its generality and its basis in quantifiable biology.

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