DOI: 10.5061/dryad.tmpg4f4x1
title: Data from: Warmer and drier fire seasons contribute to increases in area burned at high severity in western US forests from 1985-2017

description: Increases in burned area across the western US since the mid-1980’s have
 been widely documented and linked partially to climate factors, yet
 evaluations of trends in fire severity are lacking. Here, we evaluate fire
 severity trends and their interannual relationships to climate for western
 US forests from 1985-2017. Significant increases in annual area burned at
 high severity (AABhs) were observed across most ecoregions, with an
 overall eight-fold increase in AABhs across all western US forests. The
 relationships we identified between the annual fire severity metrics and
 climate, as well as the observed and projected trend toward warmer and
 drier fire seasons, suggest that climate change will contribute to
 increased fire severity in future decades where fuels remain abundant. The
 growing prevalence of high-severity fire in western US forests has
 important implications to forest ecosystems, including an increased
 probability of fire-catalyzed conversions from forest to alternative
 vegetation types.
description: Fire severity: We produced raster datasets (resolution = 30m)
 representing the <i>predicted</i> composite burn index (CBI)
 using Google Earth Engine and the model developed by Parks et al. (2019).
 The CBI is a composite field measure of fire severity that rates
 &gt;20 individual factors such as duff consumption, char height, and
 canopy mortality; as such, modeled CBI allows for improved ecological
 interpretations of fire effects compared to non-standardized indices such
 as the delta normalized burn ratio (dNBR). This procedure maps the
 predicted CBI using a Random Forest model developed using field data from
 &gt;250 fires across North America; explanatory variables in this
 model include Landsat spectral indices, latitude, and 1981-2010 annual
 average climatic water deficit. We provide the bias-corrected CBI
 described in detail by Parks et al. (2019). Also included here are
 pre-fire NDVI rasters for each fire. Pre-fire NDVI represents the mean
 NDVI from one-year before the fire using the same composite imagery used
 to produce the CBI predictions. CWD: Gridded monthly
 CWD at 1/120<sup>th</sup> degree resolution was calculated
 following Dobrowski et al. (2013) using PRISM inputs for temperature,
 precipitation, and humidity (version LT81m), 10-m wind and downward
 shortwave radiation from NLDAS2 (Mitchell et al., 2004), and soil water
 holding capacity from POLARIS (Chaney et al., 2016).
 Forest mask: We identified forest, woodland, and savanna
 (hereafter forest) from a combination of landscape level vegetation
 products that include Landfire’s (Rollins, 2009) Existing Vegetation Cover
 (EVC), Environmental Site Potential (ESP) and the Landsat Time Series
 Stacks – Vegetation Change Tracker (LTSS-VCT) (Huang et al., 2010). If you
 use this dataset, please cite Dillon et al. (2020).
   References: Chaney, N. W., Wood, E. F., McBratney, A. B., Hempel, J. W., Nauman, T. W., Brungard, C. W., & Odgers, N. P. (2016). POLARIS: A 30-meter probabilistic soil series map of the contiguous United States. <i>Geoderma</i>, <i>274</i>, 54–67. Dillon, G. K., Panunto, M. H., Davis, B., Morgan, P., Birch, D. S., & Jolly, W. M. (2020). Development of a severe fire potential map for the contiguous United States. Gen. Tech. Rep. RMRS-GTR-415. Fort Collins, CO: US Department of Agriculture, Forest Service, Rocky Mountain Research Station. Dobrowski, S. Z., J. Abatzoglou, A. K. Swanson, J. A. Greenberg, A. R. Mynsberge, Z. A. Holden, and M. K. Schwartz. 2013. The climate velocity of the contiguous United States during the 20th century. <i>Global Change Biology</i> 19(1), 241–251. Huang, C., Goward, S. N., Masek, J. G., Thomas, N., Zhu, Z., & Vogelmann, J. E. (2010). An automated approach for reconstructing recent forest disturbance history using dense Landsat time series stacks. <i>Remote Sensing of Environment</i>, <i>114</i>(1), 183–198. Mitchell, K. E., Lohmann, D., Houser, P. R., Wood, E. F., Schaake, J. C., Robock, A., et al. (2004). The multi-institution North American Land Data Assimilation System (NLDAS): Utilizing multiple GCIP products and partners in a continental distributed hydrological modeling system. <i>Journal of Geophysical Research: Atmospheres</i>, <i>109</i>(D7). Parks, Holsinger, Koontz, Collins, Whitman, Parisien, et al. (2019). Giving Ecological Meaning to Satellite-Derived Fire Severity Metrics across North American Forests. <i>Remote Sensing</i>, <i>11</i>(14), 1735. Rollins, M. G. (2009). LANDFIRE: a nationally consistent vegetation, wildland fire, and fuel assessment. <i>International Journal of Wildland Fire</i>, <i>18</i>(3), 235–249.    
description: fire.severity.zip: This file contains all of the
 satellite-inferred fire severity and pre-fire NDVI raster datasets used in
 this study.  CWD.zip: This file contains gridded
 monthly climatic water deficit from 1979-2017 for the conterminuous United
 States. forest.mask.zip: This file contains a gridded
 representation (30m resolution) of forest and non-forest for the western
 conterminuous United States.