Predicting Changes in Arctic Tundra Vegetation: Towards an Understanding of Plant Trait Uncertainty

Arctic tundra plant communities are currently undergoing unprecedented changes in both composition and distribution under a warming climate. Predicting how these dynamics may play out in the future is important since these vegetation shifts impact both biogeochemical and biogeophysical processes. More precise estimates of these future vegetation shifts is a key challenge due to both a scarcity of data with which to parameterize vegetation models, particularly in the Arctic, as well as a limited understanding of the importance of each of the model parameters and how they may vary over space and time. Here, we incorporate newly available field data from arctic Alaska into a dynamic vegetation model specifically developed to take into account a particularly wide array of plant species as well as the permafrost soils of the arctic tundra (the Terrestrial Ecosystem Model with Dynamic Vegetation and Dynamic Organic Soil, Terrestrial Ecosystem Model; DVM-DOS-TEM). We integrate the model within the Predicative Ecosystem Analyzer (PEcAn), an open-source integrated ecological bioinformatics toolbox that facilitates the flows of information into and out of process models and model-data integration. We use PEcAn to evaluate the plant functional traits that contribute most to model variability based on a sensitivity analysis. We perform this analysis for the dominant types of tundra in arctic Alaska, including heath, shrub, tussock and wet sedge tundra. The results from this analysis will help inform future data collection in arctic tundra and reduce model uncertainty, thereby improving our ability to simulate Arctic vegetation structure and function in response to global change.