Seasonal Monitoring and Predictive Analysis of Zooplankton Dynamics Using Data-Driven Ecological Modeling

Freshwater systems actually need regular checking to definitely keep nature balanced and healthy. Moreover, zooplankton are important indicators of water quality as they are sensitive to environmental changes. Further, their presence itself shows the health of water bodies. Basically, this paper shows how we built a model using data that looks at seasonal changes and water chemistry parameters to study zooplankton behavior in the same ecosystem. As per the field data collection, the system uses predictive analysis regarding zooplankton populations to find patterns and trends. We are seeing that by checking things like temperature, pH, oxygen in water, and food levels together, this new model only makes ecological monitoring more accurate. The results show that the system itself can predict seasonal changes and further help in managing freshwater resources properly.