Andrew Irwin, Ph.D.

CBIOMES Project: Predicting plankton biogeography and stoichiometry

Our long-term objective is to develop skills at predicting phytoplankton biogeography from both statistical and simple differential equation models. A synthesis of biogeographic information and complex ecosystem models will enable testing of modeling approaches and the development of improved biogeographies to fill in the under sampled regions of the ocean. We seek to advance three new research efforts: an expanded effort to document plankton biogeography, improved species distribution and co-occurrence models, and macromolecular models of phytoplankton growth focused on stoichiometry and variability linked to acclimation strategies.

SCOPE-Gradients Project: Macromolecular Bases of Carbon-Nitrogen-Phosphorus (CNP) Variation: Modeling and Statistical Analyses

Our central hypothesis is that changes in environmental conditions and microbial taxonomic composition determine variability in microbial macromolecular and storage allocation strategies, influencing growth rate and particulate C:N:P. The quantitative importance of different environmental conditions and variation in taxonomic composition to the variability in particulate C:N:P is not known. Limited laboratory work indicates that mineral nutrient limitation/supply/ratios (nitrate, phosphate, iron) is likely the dominant factor. We propose a series of field observations and complementary laboratory experiments to quantify how phytoplankton alter their growth rate, macromolecular content and elemental composition in response to key environmental variables. The laboratory work will focus on poorly studied pico- and nano-phytoplankton groups found along the Gradients cruises’ transects. This data will be used in the development and testing of new macromolecule-based models of phytoplankton growth that will be used to better understand how environmental conditions drive changes in phytoplankton taxonomic structure and C:N:P.

Bio:
Andrew Irwin is a professor in the Department of Mathematics and Statistics at Dalhousie University. His training is in applied mathematics with a focus on evolutionary theory and phytoplankton ecology. In recent years Irwin has been working on phytoplankton physiological modeling, plankton niche modeling and Bayesian time-series analysis. Irwin is an expert in numerical modeling and advanced computational methods for handling large datasets.