Improving Disturbance and Plant Functional Type Representation in ELM-FATES for Arctic Science Questions
Authors
Jennifer A. Holm1* (jaholm@lbl.gov), Charles Koven1, Yanlan Liu2, William Riley1, Jing Tao1, Margaret S. Torn1, Alistair Rogers1, Verity G. Salmon3, Gregory Lemieux1, Baptiste Bafflon1, Colleen Iversen3
Institutions
1Lawrence Berkeley National Laboratory, Berkeley, CA; 2The Ohio State University–Columbus, OH; 3Oak Ridge National Laboratory, Oak Ridge, TN
URLs
Abstract
Shifts in Arctic vegetation are expected to continue under rapid warming, directly control ecosystem function and climate feedbacks and remain challenging to predict in ecosystem models. Therefore, the team has evaluated the role and sensitivity of the parameterization of plant functional types in model simulations at the Kougarok Hillslope site in Alaska under historical and future climates using the E3SM Land Model–Functionally Assembled Terrestrial Ecosystem Simulator (ELM-FATES). Results show that present-day modeled biomass, composition, and productivity are the most sensitive to traits controlling photosynthetic capacity, carbon allocation, allometry, and phenology. Notably, these same sets of trait configurations produce diverging biomass, composition, and productivity under future climate, where the uncertainty attributable to plant traits is twice the change attributable to climate. This larger divergence due to functional trait uncertainty motivates further work to better constrain model parameters and re-evaluate model predictions under changing climate. In addition to long-term warming, shifts in Arctic disturbance regimes will alter demographic processes of recruitment, growth, and mortality. Dynamic ecosystem modeling that includes successional demographic processes and trait-driven competitive responses to disturbance is a powerful tool to investigate these Arctic dynamics. To better understand Arctic processes under a warming climate, researchers will improve ELM-FATES to simulate the effects of wildfire disturbance on plant distribution and function and evaluate the importance of vegetation-mediated ecosystem responses in driving overall patterns of carbon cycling and greenhouse gas balance. The team presents the framework for updating ELM-FATES, including (1) an improved subgrid hierarchical framework to have modeling “columns” that reflect wildfire disturbance history, (2) differences between “evenly distributed” and “resolved” vegetation distributions in the model grid cell, (3) cross-grid seed dispersal, and (4) initial results of coupled nutrient interactions. The goal of these model developments is to link different types of rapid and heterogeneous change to explore interactions and feedbacks among them using an improved ELM-FATES.