Estimating the spatial distribution of soil organic matter density and geochemical properties in a polygonal shaped Arctic Tundra using core sample analysis and X-ray computed tomography
Abstract
The Arctic tundra with its permafrost dominated soils is one of the regions most affected by global climate change, and in turn, can also influence the changing climate through biogeochemical processes, including greenhouse gas release or storage. Characterization of shallow permafrost distribution and characteristics are required for predicting ecosystem feedbacks to a changing climate over decadal to century timescales, because they can drive active layer deepening and land surface deformation, which in turn can significantly affect hydrological and biogeochemical responses, including greenhouse gas dynamics. In this study, part of the Next-Generation Ecosystem Experiment (NGEE-Arctic), we use X-ray computed tomography (CT) to estimate wet bulk density of cores extracted from a field site near Barrow AK, which extend 2-3m through the active layer into the permafrost. We use multi-dimensional relationships inferred from destructive core sample analysis to infer organic matter density, dry bulk density and ice content, along with some geochemical properties from nondestructive CT-scans along the entire length of the cores, which was not obtained by the spatially limited destructive laboratory analysis. Multi-parameter cross-correlations showed good agreement between soil properties estimated from CT scans versus properties obtained through destructive sampling. Soil properties estimated from cores located in different types of polygons provide valuable information about the vertical distribution of soil and permafrost properties as a function of geomorphology.
- Publication:
-
AGU Fall Meeting Abstracts
- Pub Date:
- December 2016
- Bibcode:
- 2016AGUFM.B43C0627S
- Keywords:
-
- 0428 Carbon cycling;
- BIOGEOSCIENCESDE: 0486 Soils/pedology;
- BIOGEOSCIENCESDE: 0702 Permafrost;
- CRYOSPHEREDE: 1615 Biogeochemical cycles;
- processes;
- and modeling;
- GLOBAL CHANGE