The practice of identifying pollen has a large number of scientific applications and is used in fields as diverse as archaeology, biostratigraphy (the dating of rocks), and forensic science. Pollen and spores play a particularly important role in paleontology, because they form the most abundant and extensive record of plant diversity, dating back hundreds of millions of years. However, the most critical hypotheses in plant ecology and evolution (e.g. the assembly of plant communities, speciation and extinction) cannot be fully tested with pollen data due to the extreme difficulty of recognizing species from pollen and spore material. This project develops new methods to probe the shape and fine structural and textural properties of the grains using high-throughput, super-resolution structured illumination microscopy and automated image analysis in order to transform species identification from a subjective, by-eye procedure to a quantitative, computational practice. Since it is not known a priori which morphological features are phylogenetically meaningful, new machine learning techniques are being developed to model pollen images at multiple scales, identify aspects of shape and texture that are statistically informative, and infer their relation to the underlying phylogenetic structure.
The project has the ambitious long-term goal of creating a high-throughput system for analyzing pollen data that incorporates meaningful characterizations of pollen and spore morphology, provides testable hypotheses of biological affinity, and is open and available to the entire scientific community. This will allow researchers to break through the current taxonomic limitations of pollen identification and fundamentally change current practices in the discipline on many levels, from the basic task of identification and counting to the interpretation and use of these data in global climate-vegetation models. The project brings together a diverse, interdisciplinary team including international collaborators at the Smithsonian Tropical Research Institute in Panama and will train graduate and undergraduate students from multiple scientific disciplines and backgrounds in an emerging area of interdisciplinary research. A public outreach component is in development that will include a virtual microscopy web site using images generated by this research to introduce non-experts to the beauty, complexity, and relevance of pollen morphology. Additional information about this project can be found at: www.life.illinois.edu/punyasena
