Removing dead trees after mass drought mortality enhances fire-adapted tree recruitment, reduces future fire severity, and has mixed effects on carbon stocks

Despite the vast area and large numbers of trees affected by drought- and bark beetle-induced tree mortality worldwide, relatively little is known about how post-mortality management practices affect forest recovery, particularly in forests historically adapted to frequent fire. Cutting and removing dead trees after a mass-mortality event provides an opportunity to salvage timber and lessen wildfire risk by reducing fuel loads, but the ecological impacts of this strategy extend beyond fuel reduction. A severe drought in California, USA (2012–2016) precipitated a mass die-off of conifers in the Sierra Nevada range. We examined how the management treatment of removing dead trees affected mixed-conifer forests in four key areas: fuels, tree regeneration, carbon stocks, and future fire behavior and severity. We collected data in 122 paired plots (22 m diameter) in treated and adjacent untreated areas spanning 300 km of the Sierra Nevada, one to 5 years after the removal of recently dead trees. We found that sound coarse woody debris mass was 51% higher with removal, but rotten coarse woody debris was not different. Litter depth and 1-h and 10-h fuel mass decreased with removal. Combined Pinus ponderosa and P. jeffreyi (shade-intolerant) seedling densities were 349% higher with removal, while P. lambertiana (moderately shade-tolerant) and Abies concolor (shade-tolerant) seedling densities were 64 and 55% lower with removal. Sapling density was 56% lower in treated plots but did not differ by species. Total forest carbon was 32% lower in treated sites, predominantly driven by dead-tree removal. Using the Forest Vegetation Simulator, we simulated future fire severity (% basal area mortality) and behavior (torch potential) over 100 years at 10-year intervals and predicted that after a 20-year lag, treatment persistently reduced simulated fire severity and behavior. Removal of dead trees initially enhanced regeneration of fire-adapted yellow pine species but negatively affected sugar pine regeneration, had varying effects on different fuel types, had predictable effects on on-site carbon stores, and lowered modeled future wildfire severity.

Authors

Institutions

Publication Details

Journal
Frontiers in Forests and Global Change
Published
2025-11-10
DOI
https://doi.org/10.3389/ffgc.2025.1691015
Primary Topic
Fire effects on ecosystems
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Removing dead trees after mass drought mortality enhances fire-adapted tree recruitment, reduces future fire severity, and has mixed effects on carbon stocks

Rebecca Bewley Wayman, Hugh D. Safford, Quinn M. Sorenson, Tara L. Ursell
Frontiers in Forests and Global Change
Fire effects on ecosystems
article

Removing dead trees after mass drought mortality enhances fire-adapted tree recruitment, reduces future fire severity, and has mixed effects on carbon stocks

Rebecca Bewley Wayman, Hugh D. Safford, Quinn M. Sorenson, Tara L. Ursell
article en

Abstract

Despite the vast area and large numbers of trees affected by drought- and bark beetle-induced tree mortality worldwide, relatively little is known about how post-mortality management practices affect forest recovery, particularly in forests historically adapted to frequent fire. Cutting and removing dead trees after a mass-mortality event provides an opportunity to salvage timber and lessen wildfire risk by reducing fuel loads, but the ecological impacts of this strategy extend beyond fuel reduction. A severe drought in California, USA (2012–2016) precipitated a mass die-off of conifers in the Sierra Nevada range. We examined how the management treatment of removing dead trees affected mixed-conifer forests in four key areas: fuels, tree regeneration, carbon stocks, and future fire behavior and severity. We collected data in 122 paired plots (22 m diameter) in treated and adjacent untreated areas spanning 300 km of the Sierra Nevada, one to 5 years after the removal of recently dead trees. We found that sound coarse woody debris mass was 51% higher with removal, but rotten coarse woody debris was not different. Litter depth and 1-h and 10-h fuel mass decreased with removal. Combined Pinus ponderosa and P. jeffreyi (shade-intolerant) seedling densities were 349% higher with removal, while P. lambertiana (moderately shade-tolerant) and Abies concolor (shade-tolerant) seedling densities were 64 and 55% lower with removal. Sapling density was 56% lower in treated plots but did not differ by species. Total forest carbon was 32% lower in treated sites, predominantly driven by dead-tree removal. Using the Forest Vegetation Simulator, we simulated future fire severity (% basal area mortality) and behavior (torch potential) over 100 years at 10-year intervals and predicted that after a 20-year lag, treatment persistently reduced simulated fire severity and behavior. Removal of dead trees initially enhanced regeneration of fire-adapted yellow pine species but negatively affected sugar pine regeneration, had varying effects on different fuel types, had predictable effects on on-site carbon stores, and lowered modeled future wildfire severity.

Frontiers in Forests and Global ChangeVol. 8
University of Nevada, Reno (US), Louisiana Department of Natural Resources (US), University of California, Davis (US)
U.S. Forest Service, California Department of Forestry and Fire Protection
Openalex Percentile: Top 69%
Fire effects on ecosystems
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.