Exploring the Role of Subsurface Traits on Subalpine Ecosystem Response from Seasonal to Decadal Time Scales
Authors
Matthias Sprenger1* (msprenger@lbl.gov), Nicola Falco1, Curtis Beutler1,2, Markus Bill1, Nicholas Bouskill1, Eoin Brodie1 (elbrodie@lbl.gov), Baptiste Dafflon1, Zhao Hao1, Amanda Henderson2, Zelalem Mekonnen1, Pat Sorensen1, Robin Thibaut1, Sebastian Uhlemann1, Lijing Wang1, Kenneth Williams1
Institutions
1Lawrence Berkeley National Laboratory, Berkeley, CA; 2Rocky Mountain Biological Laboratory, Gothic, CO
URLs
Abstract
The response of subalpine ecosystems to varying water availability has important implications for the retention and export of carbon (C), nitrogen (N), and water. Researchers investigate how the dominant subsurface characteristics (traits) play a critical role in forest’s drought response. This research question is addressed by using an iterative model-experiment (ModEx) approach based on observations of ecosystem response dynamics from seasonal to decadal time scales to benchmark simulations of the C, N, and water stores and fluxes along a 2D transect with the mechanistic ecosystem model ecosys. The study site is an intensely instrumented hillslope on Snodgrass mountain in the East River Watershed. The ecosys simulations provide insights into site characteristics (“functional traits”) that determine the ecosystem fluxes (“function”). Based on the modeling results researchers further identify necessary observations to improve model fidelity. The model benchmarking data include decadal observations that show how climatic drivers impact differently on granodiorite and shale bedrock, tree ring growth, and element concentrations (e.g., Ca, P, Sr via XRF imaging) in Lodgepole pine and Engelmann spruce tree cores. Remotely sensed variations of the Normalized Difference Vegetation Index based on Landsat images, allows relating the tree ring data to forest health dynamics along Snodgrass mountain. Researchers further use time-lapse electrical resistivity tomography (ERT) measurements along the modeling transect to understand the contrasting water storage and flux dynamics in shallow soils beneath the conifer forest canopy upslope and deep colluvium soils beneath meadow vegetation downslope. Nine ERT transects in combination with terrestrial Light Detection and Ranging (LiDAR) scans of the forest stand structure further highlight the relation between soil and bedrock traits and ecosystem function (i.e., biomass) that informs the ecosys model structure and parameterization. Regular sampling of suction lysimeters and resin samplers provide dissolved element concentrations (e.g., nitrate) and snapshot sampling campaigns showed the C and N stocks across soil profiles and in the conifer leaves. Stable isotopes of water in soils and tree xylem identify the tree’s dominant water source on Snodgrass mountain. Based on the outlined combination of aboveground and belowground observations providing information of ecosystem response from inter-annual to decadal time scales, researchers improve the mechanistic representation of the climate driven interactions between vegetation and subsurface traits in the ecosys model. Researchers highlight how feedbacks due to these interactions play out during exceptionally wet periods (e.g., 1995) and extremely dry years (e.g., 2010), which prepares researchers to assess ecosystem response to future climate scenarios.