Severe fire weather and intensive forest management increase fire severity in a multi‐ownership landscape

Abstract

Many studies have examined how fuels, topography, climate, and fire weather influence fire severity. Less is known about how different forest management practices influence fire severity in multi-owner landscapes, despite costly and controversial suppression of wildfires that do not acknowledge ownership boundaries. In 2013, the Douglas Complex burned over 19,000 ha of Oregon & California Railroad (O&C) lands in Southwestern Oregon, USA. O&C lands are composed of a checkerboard of private industrial and federal forestland (Bureau of Land Management, BLM) with contrasting management objectives, providing a unique experimental landscape to understand how different management practices influence wildfire severity. Leveraging Landsat based estimates of fire severity (Relative differenced Normalized Burn Ratio, RdNBR) and geospatial data on fire progression, weather, topography, pre-fire forest conditions, and land ownership, we asked (1) what is the relative importance of different variables driving fire severity, and (2) is intensive plantation forestry associated with higher fire severity? Using Random Forest ensemble machine learning, we found daily fire weather was the most important predictor of fire severity, followed by stand age and ownership, followed by topographic features. Estimates of pre-fire forest biomass were not an important predictor of fire severity. Adjusting for all other predictor variables in a general least squares model incorporating spatial autocorrelation, mean predicted RdNBR was higher on private industrial forests (RdNBR 521.85 ± 18.67 [mean ± SE]) vs. BLM forests (398.87 ± 18.23) with a much greater proportion of older forests. Our findings suggest intensive plantation forestry characterized by young forests and spatially homogenized fuels, rather than pre-fire biomass, were significant drivers of wildfire severity. This has implications for perceptions of wildfire risk, shared fire management responsibilities, and developing fire resilience for multiple objectives in multi-owner landscapes.

Mixed‐severity wildfire and habitat of an old‐forest obligate

“…)—which dramatically changed fire behavior and greatly improved the effectiveness of suppression efforts. Mean daily burning index (BI) for the first 4 d of the fire was 52–76, which was above the historic (1991–2017 1 June–30 September) 90th percentile for this period (Zald and Dunn ). Mean daily energy release component (ERC) values ranged from 49 to 67, also above the 90th percentile for this area (Dalton et al.…”

“…, Donato et al. , Thompson and Spies , Zald and Dunn ). High‐severity wildfire can alter soil and successional pathways and potentially shift the system into an alternative stable state (Peterson ).…”

“…). Furthermore, Zald and Dunn () found that ownership patterns were the best predictor for high‐severity fire in the Douglas Complex Fires, where federal lands, with primarily older forests in late‐successional reserves, burned at lower severity than non‐federal forests that were primarily private timber industry lands.…”

“…). In and near the study area, lightning from a thunderstorm on 26 July 2013 started 54 fires that burned under very high fire weather conditions and were managed as the Douglas Complex and Big Windy Fires (Zald and Dunn ). Most of the fires joined into several large fires that burned with mixed severity over an area of about 38,000 ha.…”

Seasonal variability of forest sensitivity to heat and drought stresses: A synthesis based on carbon fluxes from North American forest ecosystems

“…Many studies had reported the significant negative impact of heat and drought events in planted forests (Goldstein et al, ; Migliavacca et al, ; Sun, Wen, Yu, Liu, & Liu, ). Comparisons between managed forests and their counterpart natural forests also revealed that their response to the same extreme event could be opposite (van Gorsel et al, ; Zald & Dunn, ). Other studies have indicated that resistance of forests to climate extremes is determined by the species composition and stand density (Arthur & Dech, ; Giuggiola, Bugmann, Zingg, Dobbertin, & Rigling, ).…”