Topographic Heterogeneity and Aspect Moderate Exposure to Climate Change Across an Alpine Tundra Hillslope

Academic Article

Abstract

  • AbstractAlpine tundra ecosystems are highly vulnerable to climate warming but are governed by local‐scale abiotic heterogeneity, which makes it difficult to predict tundra responses to environmental change. Although land models are typically implemented at global scales, they can be applied at local scales to address process‐based ecological questions. In this study, we ran ecosystem‐scale Community Land Model (CLM) simulations with a novel hillslope hydrology configuration to represent topographically heterogeneous alpine tundra vegetation across a moisture gradient at Niwot Ridge, Colorado, USA. We used local observations to evaluate our simulations and investigated the role of topography and aspect in mediating patterns of snow, productivity, soil moisture, and soil temperature, as well as the potential exposure to climate change across an alpine tundra hillslope. Overall, our simulations captured observed gradients in abiotic conditions and productivity among heterogeneous, hydrologically connected vegetation communities (moist, wet, and dry). We found that south facing aspects were characterized by reduced snowpack and drier and warmer soils in all communities. When we extended our simulations to the year 2100, we found that earlier snowmelt altered the timing of runoff, with cascading effects on soil moisture, productivity, and growing season length. However, these effects were not distributed equally across the tundra, highlighting potential vulnerabilities of alpine vegetation in dry, wind‐scoured, and south facing areas. Overall, our results demonstrate how land model outputs can be applied to advance process‐based understanding of climate change impacts on ecosystem function.
  • Authors

  • Holland-Moritz, Hannah
  • Jay, KR
  • Wieder, WR
  • Swenson, SC
  • Knowles, JF
  • Elmendorf, SC
  • Holland‐Moritz, H
  • Suding, KN
  • Status

    Publication Date

  • November 2023
  • Digital Object Identifier (doi)

    Volume

  • 128
  • Issue

  • 11