Cryoturbation and Carbon Stocks in Gelisols under Late‐Successional Black Spruce Forests of the Copper River Basin, Alaska

Abstract

In the Alaskan discontinuous permafrost zone, soils developed under black spruce [Picea mariana (Mill.) Britton, Sterns & Poggenb.] forests are affected by fire over return intervals ranging from decades to centuries and cycle between recently burned and late‐successional stages. Soils under late‐successional forests therefore provide foundational information regarding the potential recovery of soil and permafrost characteristics following disturbance by fire. Twenty‐two permafrost‐affected soils (predominantly Histoturbels with minor components of Sapristels and Aquiturbels) were investigated under late‐successional black spruce in the Copper River Basin, which contains the largest expanse of glaciolacustrine sediments in Alaska. Although these soils are well insulated (organic layer thicknesses of 31 ± 10 cm) and fine‐textured with a relatively shallow permafrost table (69 ± 19 cm), 87% of the 129 described mineral soil horizons across these sites showed morphological evidence of cryoturbation. Depth trends in water content and bulk density were consistent with an ice‐rich upper permafrost, with suspended cryostructures most common in the upper permafrost. Soil organic carbon (SOC) stocks to 1 m averaged 46 ± 12 kg m−2, with 44% of the SOC stocks contained in cryoturbated mineral horizons, many of which were identified well below the current permafrost table. The most likely mechanism of cryoturbation in these soils is post‐fire active layer deepening followed by solutioning and diapirism, generating SOC stocks in cryoturbated mineral materials of the upper permafrost. Future changes in climate or fire frequency that affect active layer depth may therefore have the potential to affect cryoturbation processes and carbon stocks in these soils.

High-resolution predictions of ground ice content for the Northern Hemisphere permafrost region

“…The transformation was done for the GIC values associated with individual samples before computing the core average. The following equation was utilized (adapted from Bilskie, 2001;Jelinski et al, 2019) to estimate VIC based on GIC and dry bulk density Eq. ( 1):…”