The Effect of Post-Fire Disturbances on a Seasonally Thawed Layer in the Permafrost Larch Forests of Central Siberia

Abstract

We examined and simulated the consequences of the degradation of the litter and the moss–lichen layer after fire impact, which could affect the seasonal temperature of the soil and the depth of the seasonally thawed layer (STL) in the permafrost zone. According to the analysis of satellite imagery for 2000 to 2019, the fire-disturbed area in the region of interest amounted to 20%. The main aims of the study included quantitative evaluation of the variation range of summer temperature anomalies at fire-damaged plots, summarizing the statistical norm of the STL depending on natural conditions, and numerical simulation of the response of the STL. Using Terra and Aqua/MODIS imagery, we analyzed surface temperature (in bands of λ = 10.780–11.280 and 11.770–12.270 μm) coupled with the normalized difference vegetation index (NDVI) for non-disturbed and fire-damaged sites under the same natural conditions of larch forests in Central Siberia. Heat transfer, freezing and thawing processes were numerically simulated for two extreme cases of soil conditions: dry soil and water-saturated soil. The model was also applied to soil with non-homogeneous water content. As input parameters, we used data on the properties of cryogenic soils collected in larch forests (Larix gmelinii) in the flat-mountainous taiga region of the Evenkia (Central Siberia). For post-fire plots, surface temperature anomalies observed during summer months remained significant for more than 15–20 years after fire impact, while the NDVI values were restored to the statistical norm within 7–10 years of the fire. According to the results of numerical simulation, the thickness of the STL could show a 30–50% increase compared to the statistical norm. In the first approximation, we showed the annual soil temperature dynamics at various depths in disturbed and non-disturbed plots.

Soil Temperature in Disturbed Ecosystems of Central Siberia: Remote Sensing Data and Numerical Simulation

“…Greater heating of soils in disturbed plots causes an increase in the depth of the active layer by ΔZ = 29% according to the results of numerical modeling (Figure 4b) in comparison with the background areas, both due to the absence of an additional thermal insulating horizon and due to lower albedo and emissivity values. The calculated increase in thawing depth for disturbed soil is consistent with observational data, which show the magnitude of the relative increase in thawing depth in the range of 25-40% [34].…”

“…For instance, the effect of post-fire rapid increase in the thawing depth (by 30-100% in the first year after the fire) [34] leads to a unique path of soil evolution, when the underlying gleyed rock layers are included in soil formation for a significant period [55]. This type of evolution is possible only in the permafrost zone.…”

“…The set of input parameters (Tables 1 and 2) for the numerical simulation of the soil temperature regime was summarized from the data of field studies of the morphological and physical properties of soils carried out in the region [49,50,[56][57][58][59]. For instance, the effect of post-fire rapid increase in the thawing depth (by 30-100% in the first year after the fire) [34] leads to a unique path of soil evolution, when the underlying gleyed rock layers are included in soil formation for a significant period [55]. This type of evolution is possible only in the permafrost zone.…”

“…During at least 20 years (the stabilization time lag T stab , Figure 5a), the anomaly amplitudes decrease to the level of background values and the measurement error of 3 ± 1% (Table 4, Figure 5a). Thus, during the period under consideration, stabilization of temperature parameters is observed in PF plot, which is determined by the thermal insulation properties of the surface layer recovering to the pre-fire state under conditions of a successful vegetation regeneration [11,34,56,77]. The considered post-technogenic plots were characterized by a higher level of initial relative surface temperature anomalies (up to 100% of the background).…”

“…In the context of the diversity of soil properties, the issue of mathematical modeling based on ground-based and remote sensing data is urgent [7,27,[31][32][33][34][35]. Available models of heat and moisture transfer in soil under freezing and thawing conditions take into account the moisture conductivity of soil [36][37][38][39].…”