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ZENODO
Dataset . 2023
License: CC BY
Data sources: Datacite
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Dataset . 2023
License: CC BY
Data sources: Datacite
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Dataset . 2023
License: CC BY
Data sources: ZENODO
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Characterizing ground and surface fuels across Sierra Nevada forests shortly after the 2012–2016 drought

Authors: Emilio Vilanova; Leif A. Mortenson; Lauren E. Cox; Beverly M. Bulaon; Jamie M. Lydersen; Christopher J. Fettig; John J. Battles; +1 Authors

Characterizing ground and surface fuels across Sierra Nevada forests shortly after the 2012–2016 drought

Abstract

These files include the main processed data and R script used in the analysis for the publication Characterizing ground and surface fuels across Sierra Nevada forests shortly after the 2012–2016 drought accepted in the journal Forest Ecology and Management. Abtract The 2012–2016 hotter drought in the Sierra Nevada, California, USA led to the mortality of millions of trees. This disruption to the disturbance regime is an example of how climate extremes can exacerbate current and future wildfire risks. In this study, we used data from an extensive network of forest plots across 13 different sites in the Sierra Nevada to characterize ground (i.e., duff) and surface fuels and their potential drivers shortly after the drought (2016–2018), but before snag (standing dead tree) fall associated with this massive tree mortality event occurred. Overall, we found high biomass of fuels for most sites (138.2 ± 21.7 Mg ha-1, Mean ± 95% CI), especially in areas lacking recent fire or active management, with values up to five times higher than estimates for pre-settlement conditions for mixed-conifer forests in the region. Four major groups of forest overstory structure were identified with some distinct fuel characteristics. These ranged from a cluster of ponderosa pine (Pinus ponderosa Douglas ex Lawson)-dominated plots with the highest density of snags, lowest live tree basal area, and lowest total ground and surface fuel biomass (mean = 90.1 Mg ha-1) to a group of giant sequoia (Sequoiadendron giganteum (Lindl.) J. Buchholz)-dominated plots with the highest live tree basal area and highest total fuel biomass (mean = 547.6 Mg ha-1). Although we found relatively weak relationships between forest characteristics and fuel loads, their inclusion in a model selection framework that also considered biophysical variables and disturbance history explained more than 80% of the observed variation in litter + fine woody debris loads. The baseline fuel conditions described here will not only inform the management of drought-impacted forests in the Sierra Nevada, but also help identify key drivers of fuel succession in a changing environment.

Keywords

bark beetle; California; ground fuels; forest management; tree mortality; wildfires.

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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