Predicting the impact of climate change on ecosystems presents a major challenge due to Earth’s complexity and adaptive dynamics. Increasing evidence suggests that ecological “memory”—how an ecological system’s past shapes its behavior—are pervasive across the globe. To detect, quantify, and understand these memory effects, new concepts and quantitative tools are needed. In particular, computational mechanics’ view of intrinsic computation—how complex systems store and process information—is ideally suited to represent how plants, communities, and ecosystems display ecological memory.
This novel project will apply computational mechanics to quantify ecological memory in terrestrial ecosystems. By examining how and why ecological memory varies across time, space, and biological levels of organization (leaf to ecosystem), the factors and consequences of ecological resilience, or the loss of resilience, will be evaluated. The candidate will work with leave, canopy, and ecosystem scale carbon-flux data from manipulative experiments, observation networks, and terrestrial biosphere models and form collaborations with experts in those fields. Training in informatics (computing, statistical analysis, and modelling) will be provided through the hosting institutions and collaborating groups. Depending on the candidate’s expertise and interest, other Earth-surface biogeochemical processes may also be considered in the study.
Ultimately, the successful candidate will play a leading role and “blaze new trails” in ecological memory research, and more broadly, in the research on intrinsic computing of plants, to inform prediction and management of ecological responses in changing climate.