TY - JOUR
T1 - Fire severity and carbon combustion from tussock tundra fires in Southwest Alaska
AU - Diaz, Lucas R
AU - Saperstein, Lisa B
AU - van Gerrevink, Max J
AU - Wangchuk, Sonam
AU - Hessilt, Thomas D
AU - Janssen, Thomas A J
AU - Scholten, Rebecca C
AU - Delcourt, Clement J F
AU - Veraverbeke, Sander
PY - 2026/6
Y1 - 2026/6
N2 - Major advances have been made in understanding carbon emissions from boreal forest fires, yet substantial knowledge gaps remain for tundra fires. Tundra ecosystems are increasingly susceptible to fire activity due to climate change, posing a threat to their large organic soil carbon stocks and the permafrost they insulate. Additionally, studies assessing remote sensing fire severity metrics in tundra landscapes are limited. Here, we report carbon (C) combustion estimates from two large tussock tundra fires (1048 km2) that occurred in Southwest Alaska, USA, in 2022. We quantified above- and belowground carbon stocks and combustion (in kg C m−2) at 45 field plots (36 burned, 9 unburned) 1 year post-fire. Soil burn depth was determined using paired moss patches, and aboveground carbon stocks were calculated using allometric equations for shrubs and tussocks. Fire severity was estimated using the field-based geometrically structured composite burn index (GeoCBI) at these 45 plots and at 41 additional plots where only GeoCBI was measured. We upscaled our field-based findings using the differenced normalized burn ratio (dNBR) derived from Sentinel-2 imagery. Tussock tundra landscapes emitted an average of (±standard deviation) 1.59 ± 0.55 kg C m−2, consuming 11% of the total pre-fire carbon stock. The majority of the loss (75%) came from belowground stocks, with an average burn depth of 6.9 ± 2.1 cm. By scaling carbon combustion with the dNBR (R2 = 0.42, p < 0.001), we estimated total carbon emissions from tussock tundra across both fires at 0.81 ± 0.22 Tg. GeoCBI estimates were moderately correlated with the dNBR (R2 = 0.63, p < 0.001) across vegetation types. This work provides important information on the impacts of fires on the carbon balance of tundra ecosystems and demonstrates that dNBR, a well-established remote sensing proxy for forest fires, is also effective for mapping fire severity in tundra landscapes.
AB - Major advances have been made in understanding carbon emissions from boreal forest fires, yet substantial knowledge gaps remain for tundra fires. Tundra ecosystems are increasingly susceptible to fire activity due to climate change, posing a threat to their large organic soil carbon stocks and the permafrost they insulate. Additionally, studies assessing remote sensing fire severity metrics in tundra landscapes are limited. Here, we report carbon (C) combustion estimates from two large tussock tundra fires (1048 km2) that occurred in Southwest Alaska, USA, in 2022. We quantified above- and belowground carbon stocks and combustion (in kg C m−2) at 45 field plots (36 burned, 9 unburned) 1 year post-fire. Soil burn depth was determined using paired moss patches, and aboveground carbon stocks were calculated using allometric equations for shrubs and tussocks. Fire severity was estimated using the field-based geometrically structured composite burn index (GeoCBI) at these 45 plots and at 41 additional plots where only GeoCBI was measured. We upscaled our field-based findings using the differenced normalized burn ratio (dNBR) derived from Sentinel-2 imagery. Tussock tundra landscapes emitted an average of (±standard deviation) 1.59 ± 0.55 kg C m−2, consuming 11% of the total pre-fire carbon stock. The majority of the loss (75%) came from belowground stocks, with an average burn depth of 6.9 ± 2.1 cm. By scaling carbon combustion with the dNBR (R2 = 0.42, p < 0.001), we estimated total carbon emissions from tussock tundra across both fires at 0.81 ± 0.22 Tg. GeoCBI estimates were moderately correlated with the dNBR (R2 = 0.63, p < 0.001) across vegetation types. This work provides important information on the impacts of fires on the carbon balance of tundra ecosystems and demonstrates that dNBR, a well-established remote sensing proxy for forest fires, is also effective for mapping fire severity in tundra landscapes.
U2 - 10.1088/2752-5295/ae4cc3
DO - 10.1088/2752-5295/ae4cc3
M3 - Article
SN - 2752-5295
VL - 5
SP - 1
EP - 21
JO - Environmental Research. Climate
JF - Environmental Research. Climate
IS - 2
M1 - 025011
ER -