Vegetation dynamics in a changing Arctic: Improved biogeochemistry response to a warming climate through a detailed representation of leaf phenology

Background/Question/Methods

Dynamic modeling of arctic tundra vegetation requires representation of the heterogeneous tundra landscape.  This includes representation of each type of tundra ecosystem, including shrub, heath, wet sedge, and tussock tundra types, as well as unique representations of the grouping of species, or plant functional types, within each of these ecosystems, such as the deciduous shrubs, evergreen shrubs, forbs, grasses, sedges, mosses, and lichens.   One potential sensitive and valuable indicator of the dynamic responses of terrestrial ecosystems to climate change is leaf phenology.  However, while the plant functional types in arctic ecosystems require differing amounts of accumulated heat for leaf-out, dynamic vegetation models simulated over a regional to global scale typically assume some average leaf-out for all of the plant functional types within an ecosystem.  Here, we make use of air temperature records and observations of spring leaf phenology collected across dominant plant functional types in arctic and boreal ecosystems in Alaska.  We then parameterize a dynamic vegetation model based on these data for tundra ecosystems, as well as ecotonal boreal white spruce forest. 

Results/Conclusions

This implementation improves the timing of the onset of carbon uptake in the spring, permitting a more accurate study of the contribution of each plant functional type to ecosystem performance.   Furthermore, this implementation impacts the ecosystem composition, and may favor the plant functional types that leaf-out earlier compared to those that leaf-out later in the growing season.  These findings demonstrate that dynamic vegetation models should consider variation in leaf-out by plant functional types within these ecosystems in order to provide more accurate projections of feedbacks to climate and plant distributions in Arctic regions.