Project description

The Arctic is warming at twice the global average, a dynamic amplified by rapid declines in regional sea ice cover.  Despite compelling signals of biome-scale terrestrial responses, fundamental knowledge gaps about the rate, magnitude, and drivers of these dynamics in the tundra remain widespread.  

At AIAS, I will explore how scale, and its pervasive influence on pattern, influences regional and local measures of plant and animal response to climatic and/or biotic disturbances.

With emerging satellite datasets and AI approaches, one aspect of my project will examine weather-mediated and time-delayed linkages between marine cryosphere and terrestrial ecological dynamics across candidate regions of tundra. 

At the landscape level, variability in the life history progression of individual plants ultimately drives broader-scale dynamics.  I will investigate the structure of and landscape controls on this variability using collaborative datasets derived from drones and time-lapse cameras.  Using computer vision approaches, these image sets will be mined for data comprising tens-of-thousands of individual-level plant life cycles. These in turn will allow for investigation into new, yet fundamental, questions about plant life-history variation through space.