A Grain Carried by the Flood: methods and data for global change ecology amidst a data deluge

Abstract

Forecasting the responses of ecological systems to changing environment is a critical area of modern ecology research. An overwhelming amount of openly-available ecological and environmental data is emerging in service of this goal, but often the methodology for producing ecological insight from these heterogeneous data sources is out of reach of standard ecological practice. In this dissertation, I investigate opportunities to use open, heterogeneous ecological data to produce new insight via contributions in modeling methodology, emerging data sources, and global-scale mechanistic analysis. In the first of three chapters, I find that modern nonlinear modeling methods are able to improve range shift predictions made via species traits. Second, I develop a snow cover data product for montane ecological research from an emerging satellite observation platform with unprecedented spatial and temporal resolution. Finally, I contribute testable predictions of phytoplankton physiological responses to marine heatwave events by pairing a globally-distributed observational dataset with empirically-derived thermal reaction norms of fitness. Taken together, these contributions represent both independent discoveries toward more accurate ecological forecasting and the extraordinary potential of an approach to ecological research driven by open ecological and environmental data sources and modern methods.