2023
DOI: 10.1111/geb.13634
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Spatial interactions among short‐interval fires reshape forest landscapes

Abstract: Aim Ecological disturbances are increasing as climate warms, and how multiple disturbances interact spatially to drive landscape change is poorly understood. We quantified burn severity across fire regimes in reburned forest landscapes to ask how spatial patterns of high‐severity fire differ between sequential overlapping fires and how landscape heterogeneity is shaped by cumulative disturbance patterns. We also characterized the amount and configuration of an emerging phenomenon: areas burned as high‐severity… Show more

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Cited by 11 publications
(8 citation statements)
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“…Our calculation of RdNBR included an offset term to account for phenological differences between pre‐ and postfire imagery and to facilitate comparison of RdNBR between fire events (Parks, Holsinger, Voss, et al, 2018b). Following Harvey et al (2023), we used statistical models calibrated to northwestern United States field plots (Saberi & Harvey, 2023) to identify a threshold of RdNBR (RdNBR ≥ 542) corresponding to ≥75% tree basal area mortality. We then used this threshold to categorize each burn‐severity map into high (RdNBR ≥ 542) and low‐to‐moderate (RdNBR < 542) burn‐severity classes.…”
Section: Methodsmentioning
confidence: 99%
“…Our calculation of RdNBR included an offset term to account for phenological differences between pre‐ and postfire imagery and to facilitate comparison of RdNBR between fire events (Parks, Holsinger, Voss, et al, 2018b). Following Harvey et al (2023), we used statistical models calibrated to northwestern United States field plots (Saberi & Harvey, 2023) to identify a threshold of RdNBR (RdNBR ≥ 542) corresponding to ≥75% tree basal area mortality. We then used this threshold to categorize each burn‐severity map into high (RdNBR ≥ 542) and low‐to‐moderate (RdNBR < 542) burn‐severity classes.…”
Section: Methodsmentioning
confidence: 99%
“…Stand‐level percent serotiny of lodgepole pine is highest at lower elevations (up to ~2300–2400 m) and ranges widely (0 to more than 85% of trees with serotinous cones; Schoennagel et al, 2003; Tinker et al, 1994). Approximately one‐third of 1984–2010 area burned in United States Northern Rocky Mountains subalpine forests was stand‐replacing (Harvey et al, 2016a), and 19%–25% of 1984–2020 short‐interval area burned in Northwest United States forests was stand‐replacing in both the initial and subsequent fire (Harvey et al, 2023). Mean aboveground biomass in lodgepole pine‐dominated forests averages 139 Mg ha −1 (live tree) and 98 Mg ha −1 (dead woody) across a 300‐year chronosequence, and stand density stabilizes to approximately 1200 stems ha −1 after 200 years of stand development (Kashian et al, 2013; Kashian, Turner, & Romme, 2005).…”
Section: Methodsmentioning
confidence: 99%
“…Independent effects of short-interval reburns and long distances to live forest on post-fire conifer densities are well documented (Stevens-Rumann & Morgan, 2019), and here we found amplifying interactions. This is particularly concerning in western United States forests, where current trends in area burned and stand-replacing fire indicate that these two conditions will co-occur with increasing likelihood (Buma et al, 2020;Harvey et al, 2016aHarvey et al, , 2023Westerling, 2016). Climate-driven increases in other agents of tree mortality, such as bark beetles, wind, drought, and pathogens (Anderegg et al, 2020;Seidl et al, 2017), could further reduce seed source availability throughout forest landscapes and exacerbate impacts on post-fire regeneration (Coop et al, 2020).…”
Section: Interacting Drivers Amplify Effects On Forest Regenerationmentioning
confidence: 99%
“…We included an offset term in our calculation of RdNBR to account for phenological differences between pre‐ and postfire imagery (Parks, Holsinger, Voss, et al, 2018). Following Harvey et al (2023), we used statistical models calibrated to Northwest United States field plots (Saberi & Harvey, 2023) to identify a threshold of RdNBR (RdNBR ≥542) corresponding to ≥75% tree basal area mortality. We then used this threshold to categorize each burn severity map into high (RdNBR ≥542) and low‐to‐moderate (RdNBR <542) burn severity classes.…”
Section: Methodsmentioning
confidence: 99%