An Ecometric Study of Recent Microfossils using High-throughput Imaging

The era of Big Data has ushered in the potential to collect population level information in a manageable time frame. Taxon-free morphological trait analysis, referred to as ecometrics, can be used to examine and compare ecological dynamics between communities with entirely different species compositions. Until recently population level studies of morphology were difficult because of the time intensive task of collecting measurements. To overcome this, we implemented advances in imaging technology and created software to automate measurements. This high-throughput set of methods collects assemblage-scale data, with methods tuned to foraminiferal samples (e.g., light objects on a dark background). Methods include serial focused dark-field microscopy, custom software (Automorph) to batch process images, extract 2D and 3D shape parameters and frames, and implement landmark-free geometric morphometric analyses. Informatics pipelines were created to store, catalog and share images through the Yale Peabody Museum(YPM; peabody.yale.edu). We openly share software and images to enhance future data discovery. In less than a year we have generated over 25TB of high resolution semi 3D images for this initial study.

Here, we take the first step towards developing ecometric approaches for open ocean microfossil communities with a calibration study of community shape in recent sediments. We will present an overview of the ‘shape’ of modern planktonic foraminiferal communities from 25 Atlantic core top samples (23 sites in the North and Equatorial Atlantic; 2 sites in the South Atlantic). In total, more than 100,000 microfossils and fragments were imaged from these sites’ sediment cores, an unprecedented morphometric sample set. Correlates of community shape, including diversity, temperature, and latitude, will be discussed. These methods have also been applied to images of limpets and fish teeth to date, and have the potential to be used on modern taxa to extract meaningful information on community responses to changing climate.