High-resolution time series of plankton to understand trait-based community and food-web dynamics

Ewa Merz1, Jules S Jaffe2, Paul L Roberts3, Peter D Isles1, Marta Reyes1, Thomas Lormier1, Thea Kozakiewicz1, Nelson Stevens1, Stuart Dennis1 and Francesco Pomati1, (1)EAWAG Swiss Federal Institute of Aquatic Science and Technology, Duebendorf, Switzerland, (2)Scripps Institution of Oceanography, La Jolla, CA, United States, (3)Monterey Bay Aquarium Research Institute, Moss Landing, CA, United States
Plankton community dynamics and trait distributions emerge from a complex interplay between a highly variable environment and biotic interactions within and between trophic levels. Community shifts and turnovers can occur in natural ecosystems at a scale of minutes to hours and milli- to micrometers. Traditional plankton measurements, taken at a weekly or monthly basis, are not sufficient to characterize plankton community dynamics thoroughly. Here we used underwater imaging, as provided by a dual-magnification plankton camera, as a new tool to phenotype and study species dynamics and size distributions in lakes across three levels of the food web in situ, with high frequency and high spatial resolution. We benchmarked plankton imaging by comparing abundance, richness and size data with traditional microscopy. Our results promote underwater imaging as an auspicious approach to generate empirical high-resolution time series of changes in plankton co-occurrence across trophic levels and size distributions. Such complex datasets increase prediction accuracy of community changes in planktonic networks — and therefore ecosystem processes and services — across environmental gradients in space and time.