High-temporal resolution in situ imaging and machine learning to observe copepod-parasite interactions

Zooplankton play a critical role in virtually all aquatic ecosystems, forming the link between photosynthetic microorganisms and higher trophic levels. Biotic controls on zooplankton populations are often modeled as top-down, via predation, or bottom-up, via preferred prey availability. There is, however, a growing body of evidence suggesting that parasitism exerts an influence on zooplankton condition (e.g., growth, reproduction, nutritional content). Observing and quantifying these interactions remains difficult due to limited spatial-temporal resolution of traditional sampling techniques and challenges associated with creating realistic environments in the laboratory. In situ microscopy systems alleviate some of these issues and provide a window into these cryptic relationships. Here, we outline the use of the Scripps Plankton Camera to monitor covariations in the relative abundance of the copepod Oithona sp. and Paradinium sp., a parasitic Rhizarian. With human annotators working in concert with a machine classifier, we constructed a two-year long record at hourly resolution from images captured at the Scripps Pier in La Jolla, California. Preliminary time series analysis suggests a coupling between the presence of the parasite and female egg bearing Oithona.