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burnr_revision-2018-02-15.pdf
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Final Accepted Manuscript
Affiliation
Univ Arizona, Dept GeosciUniv Arizona, Lab Tree Ring Res
Issue Date
2018-06
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ELSEVIER GMBH, URBAN & FISCHER VERLAGCitation
Malevich, S. B., Guiterman, C. H., & Margolis, E. Q. (2018). burnr: Fire history analysis and graphics in R. Dendrochronologia, 49, 9–15. https://doi.org/10.1016/j.dendro.2018.02.005Journal
DENDROCHRONOLOGIARights
© 2018 Elsevier GmbH. All rights reserved.Collection Information
This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.Abstract
We developed a new software package, burnr, for fire history analysis and plotting in the R statistical programming environment. It was developed for tree-ring fire-scar analysis, but is broadly applicable to other event analyses (e.g., avalanches, frost rings, or culturally modified trees). Our new package can read, write, and manipulate standard tree-ring fire history FHX files, produce fire-demography charts, calculate fire frequency and seasonality statistics, and run superposed epoch analysis (SEA). A key benefit of burnr is that it enables automation of analyses and plotting, especially for large data sets. The package also facilitates creative plotting, mapping, and analyses when combined with the thousands of packages available in R. In this paper, we describe the basic functionality of burnr and introduce users to fire history analyses in R.Note
24 month embargo; published online: 2 March 2018ISSN
11257865Version
Final accepted manuscriptSponsors
Central Oregon Fire Management Service (Deschutes and Ochoco National Forests); Central Oregon Fire Management Service (Crooked River National Grassland); Central Oregon Fire Management Service (Prineville District Bureau of Land Management); EPA STAR Fellowship; U.S. Geological Survey Western Mountains InitiativeAdditional Links
https://linkinghub.elsevier.com/retrieve/pii/S1125786517301418ae974a485f413a2113503eed53cd6c53
10.1016/j.dendro.2018.02.005