Experimental and modeling studies of a four-trophic level predator-prey system

Understanding interactions in microbial food chains remains a challenge in ecological research. Prior studies have focused on simplified systems, such as two- or three-trophic level models. However, the inclusion of a four-trophic level system has been limited. Researchers have long used microbial organisms to study ecological principles due to their rapid growth and ease of manipulation. Despite this, the full dynamics of a four-level system have not been experimentally explored. The role of biovolume as a measure of microbial population dynamics is well established. Yet, its application in modeling complex food chains is less common. This gap motivated the current investigation into a four-trophic level system. The study aimed to bridge this knowledge gap by integrating experimental data with mathematical modeling.

The primary aim was to experimentally and theoretically examine a four-trophic level microbial food chain. This system includes organic carbon substrates, bacteria, and two protozoan predators. The study sought to quantify interactions between these levels using both empirical and computational approaches. By measuring organic carbon and microbial populations, the researchers aimed to capture dynamic changes over time. The model was intended to reflect real-world microbial interactions in a controlled setting. The use of biovolume as a modeling parameter was central to this effort. The goal was to compare simulated outcomes with experimental data to validate the model's accuracy. This approach could contribute to broader ecological modeling frameworks.

The study utilized stirred, aerated batch cultures to grow microbial populations. Organic carbon substrates served as the base trophic level, followed by bacteria and two ciliate protozoans. Cell numbers, mean cell volumes, and total biovolumes were measured quantitatively. These measurements were taken at regular intervals to track population changes. A mathematical model was constructed using Monod kinetics to describe population dynamics. The model incorporated biovolume as a key variable, including terms for decay processes. Parameter values were derived from batch culture data to calibrate the model. Simulations were then compared with the experimental results to assess model performance.

The model successfully captured the observed dynamics of the four-trophic level system. Biovolume decay rates were estimated and incorporated into the simulations. Experimental data showed clear predator-prey oscillations, which the model replicated with high accuracy. The bacterial population exhibited a lag phase before exponential growth. The ciliate populations displayed delayed responses to bacterial abundance changes. Organic carbon levels decreased steadily as the system progressed. The model predicted these trends with minimal deviation from the observed data. These findings suggest that biovolume-based modeling is effective for complex microbial systems.

The study demonstrated that a four-trophic level microbial system can be modeled using biovolume as a central parameter. The model's predictions aligned closely with experimental observations, validating its utility. This approach offers a framework for studying complex ecological interactions in controlled settings. The inclusion of biovolume decay terms improved model accuracy. The results suggest that microbial food chains can be effectively represented through mathematical modeling. This work expands the scope of prior studies that focused on fewer trophic levels. The findings support the use of biovolume as a reliable metric in ecological modeling. Future work may build on this model to explore additional variables and interactions.