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- Title
Near‐Surface Hydrology and Soil Properties Drive Heterogeneity in Permafrost Distribution, Vegetation Dynamics, and Carbon Cycling in a Sub‐Arctic Watershed.
- Authors
Shirley, Ian A.; Mekonnen, Zelalem A.; Wainwright, Haruko; Romanovsky, Vladimir E.; Grant, Robert F.; Hubbard, Susan S.; Riley, William J.; Dafflon, Baptiste
- Abstract
Discontinuous permafrost environments exhibit strong spatial heterogeneity at scales too small to be driven by weather forcing or captured by Earth System Models. Here we analyze effects of observed spatial heterogeneity in soil and vegetation properties, hydrology, and thermal dynamics on ecosystem carbon dynamics in a watershed on the Seward Peninsula in Alaska. We apply a Morris global sensitivity analysis to a process‐rich, successfully tested terrestrial ecosystem model (TEM), ecosys, varying soil properties, boundary conditions, and weather forcing. We show that landscape heterogeneity strongly impacts soil temperatures and vegetation composition. Snow depth, O‐horizon thickness, and near‐surface water content, which vary at scales of O(m), control the soil thermal regime more than an air temperature gradient corresponding to a 140 km north–south distance. High shrub productivity is simulated only in talik (perennially unfrozen) soils with high nitrogen availability. Through these effects on plant and permafrost dynamics, landscape heterogeneity impacts ecosystem productivity. Simulations with near‐surface taliks have higher microbial respiration (by 78.0 gC m−2 yr−1) and higher net primary productivity (by 104.9 gC m−2 yr−1) compared to runs with near‐surface permafrost, and simulations with high shrub productivity have outlying values of net carbon uptake. We explored the prediction uncertainty associated with ignoring observed landscape heterogeneity, and found that watershed net carbon uptake is 60% larger when heterogeneity is accounted for. Our results highlight the complexity inherent in discontinuous permafrost environments and demonstrate that missing representation of subgrid heterogeneity in TEMs could bias predictions of high‐latitude carbon budget. Plain Language Summary: At high‐latitudes, properties such as soil temperatures, soil wetness, snowpack, and vegetation cover vary considerably across a landscape. The scale of this variation can be as small as 1–10 m (e.g., a patch of tall shrubs with a deep snowpack and warm soil temperatures is surrounded by low‐lying tundra vegetation with shallow snowpack and cold soil temperatures). The resolution of terrestrial ecosystem models that are used to predict global responses to climate change, however, is much coarser (∼100–300 km). The mismatch between the scales of landscape variation and the scales of models may introduce bias into predictions of ecosystem processes. In order to better understand the causes and implications of landscape variability, we explore the response of an ecosystem model to variation in soil properties, boundary conditions, and weather forcing. We find that landscape variability in snowpack and soil properties strongly influences soil temperatures, vegetation cover, and ecosystem carbon cycling. In particular, we show that net carbon uptake of the studied area is 60% higher when we account for the observed variability in shrub distribution. These results demonstrate the need for higher resolution measurements and improved model representation of landscape variability. Key Points: Discontinuous permafrost environments are characterized by strong spatial heterogeneity and complex feedback loopsNear‐surface hydrology and soil properties are strong drivers of spatial heterogeneity in these systemsMissing representation of subgrid heterogeneity in Terrestrial Ecosystem Models could bias predictions of high‐latitude carbon budget
- Publication
Journal of Geophysical Research. Biogeosciences, 2022, Vol 127, Issue 9, p1
- ISSN
2169-8953
- Publication type
Article
- DOI
10.1029/2022JG006864