Assessing the role of climate and lithology in vegetation distribution

The proposed project will use machine learning to predict vegetation biomass across the state of California using climate variables (precipitation, temperature). This will create a map of what vegetation is expected to be in a given climate regime. This modeled vegetation distribution will be compared to a map of observed vegetation to identify regions where climate cannot explain the observed patterns. In these regions, we hypothesize the subsurface bedrock exerts a control on plant productivity. We will compare with geologic maps to examine how rock type may correspond to areas of limited vegetation. The expected outcome of the project is a map of where climate data can and cannot predict plant biomass, as well as statistical relationships between each of the input variables and plant biomass. These results will inform future studies on how the subsurface controls water availability to plants.

Faculty Supervisor:

William Jesse Hahm

Student:

Partner:

The University of Texas at Austin

Discipline:

Earth science

Sector:

Education

University:

Simon Fraser University

Program: