A causal hypothesis explaining predator-prey dynamics in Great Salt Lake, Utah

Abstract

A hypothesis explaining the recurring annual plankton dynamics found in a natural two-species system in Great Salt Lake, Utah is developed, and tested via computer simulation. A springtime peak of the phytoplankter Dunaliella viridis is followed by a peak of the sole grazing zooplankter Artemia salina. The annual time patterns of these two species are analyzed using Forrester's feedback dynamics methodology. The goal is to obtain a model with coupled feedback loops sufficient to reproduce the major features shown in three years of field data (e.g., spring phytoplankton blooms and crashes followed by zooplankton). Some details are ignored until a sensitivity analysis has revealed important needed information. For example, we consider an average liter of water, at an average depth, in a homogeneous lake; and we include only eggs, nauplii and adults in the brine shrimp life cycle. Emphasis is given to overall pattern reproduction and model stability. The system is driven by solar energy, but the dynamics arise primarily from the feedback loop structure. Feedback loops included are the life cycles of algae and brine shrimp; algal self-shading; algal grazing by brine shrimp; and brine shrimp starvation. The algae are hypothesized to be limited in spring by self-shading, and then by grazing until the fall disappearance of brine shrimp, when the algae become temperature- and light-limited. Brine shrimp are limited only by food.