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Data and code for: Rocky Mountain subalpine forests now burning more than any time in recent millennia

Citation

Higuera, Philip; Shuman, Bryan; Wolf, Kyra (2021), Data and code for: Rocky Mountain subalpine forests now burning more than any time in recent millennia, Dryad, Dataset, https://doi.org/10.5061/dryad.rfj6q579n

Abstract

The 2020 fire season punctuated a decades-long trend of increased fire activity across the western United States, nearly doubling the total area burned in the central Rocky Mountains since 1984. Understanding the causes and implications of such extreme fire seasons, particularly in subalpine forests that have historically burned infrequently, requires a long-term perspective not afforded by observational records. We place 21st century fire activity in subalpine forests in the context of climate and fire history spanning the past 2,000 y using a unique network of 20 paleofire records. Largely because of extensive burning in 2020, the 21st century fire rotation period is now 117 y, reflecting nearly double the average rate of burning over the past 2,000 y. More strikingly, contemporary rates of burning are now 22% higher than the maximum rate reconstructed over the past two millennia, during the early Medieval Climate Anomaly (MCA) (770 to 870 Common Era), when Northern Hemisphere temperatures were ∼0.3 °C above the 20th century average. The 2020 fire season thus exemplifies how extreme events are demarcating newly emerging fire regimes as climate warms. With 21st century temperatures now surpassing those during the MCA, fire activity in Rocky Mountain subalpine forests is exceeding the range of variability that shaped these ecosystems for millennia.

Methods

Datasets used in this study are all publicly available through the links described in the manuscript (i.e., MTBS, NIFC, GridMET, LANDFIRE) or data repositories associated with the original publications (i.e., http://www.ncdc.noaa.gov/data-access/paleoclimatology-data/datasets/fire-history for Calder et al. (2015), https://doi.org/10.5061/dryad.q2b8t for Higuera et al. (2014), https://doi.org/10.6084/m9.figshare.988687.v19 for Dunnette et al. (2014)). This Dryad repository includes all data used here, as well as all code use for analysis and to generate figures.  

Usage Notes

README TEXT FROM GITHUB REPOSITORY: https://github.com/HigueraLab/BreakingPaleoRecords

Data and code for "Rocky Mountain subalpine forests now burning more than any time in recent millennia"

Overview

This archive includes data and scripts needed to reproduce the analyses in Higuera, Shuman, and Wolf (2021). After extracting the .zip archive, there are three directories: code, data, and figures. Contents in each directory are describe in detail below.

Contact: Philip Higuera, University of Montana PaleoEcology and Fire Ecology Lab, https://www.cfc.umt.edu/research/paleoecologylab/philip.higuera@umontana.edu

Citation Information

Data and code - please cite if you use data, code, or figures in your own work

Higuera, Philip; Shuman, Bryan; Wolf, Kyra (2021), Data and Code for "Rocky Mountain subalpine forests now burning more than any time in recent millennia," PNAS, Dryad, Dataset, https://doi.org/10.5061/dryad.rfj6q579n

Reference to paper

Higuera, P.E., B.N. Shuman, and K.D. Wolf. 2021. Rocky Mountain subalpine forests now burning more than any time in recent millennia. Proceedings of the National Academy of Sciences. https://doi.org/10.1073/pnas.2103135118

Contents

1. CODE

File: Figures_all_script.m

Written for MATLAB software (*.m file type; www.mathworks.com), and fully commented, including dependencies.

File: RCode_ContemporaryFRPCalc.R

Written for R software (*.R file type), and fully commented, including dependencies.

Subdirectory: "html"

Matlab "markdown" html page that can be used to walk through the script "Figures_all_script.m", which includes the figures embedded in the html page.

2. DATA

Paleo-fire datasets:

1. SouthernRockies_site_metadata.csv -- metadata for all paleofire sites used

2. Calder_et_al_CharResults.csv -- charcoal-inferred fire history for sites from Calder et al. (2015, PNAS)

3. ROMO_CharResults.csv -- charcoal-inferred fire history for sites from Higuera et al. (2014, J of Ecology), Dunnette et al. (2014, New Phytologist), and Caffrey and Doerner (2012, Physical Geography), in Rocky Mnt. Nat. Park

4. Minckley_et_al_LWH_CharResults.csv -- charcoal-inferred fire history for sites from Minckley et al. (2012, Ecological Monographs)

Spatial datasets: study area, focal study area, fire perimeters

5. ecoregp075_M331H_M331I.shp -- Shape file for M331H and M331I ecoregions, defining "central Rockies"

6. FocalStudyArea_SubalpineConiferForestESPP_WGS84.tif -- Subalpine forest vegetation in the focal study area (unprojected)

7. FocalStudyArea_SubalpineConiferForestESP_Albers.tif -- Subalpine forest vegetation raster in the focal study area (projected)

8. SRockies_Fires_1984_2020_WGS84.shp -- Fire perimeters (unprojected)

9. SRockies_Fires_1984_2020_Albers.shp -- Fire perimeters (projected)

Summary statistics: contemporary annual area burned, fire rotation periods from tree-ring reconstructions

10. AreaBurned_Ecoregion_FocalStudy_1984_2020.csv -- Area burned statistics

11. Dendro_FRP_Calculations.xlsx -- Spreadsheet with calculations of fire rotation periods from four published tree-ring fire-history reconstructions

Climate datasets: contemporary VPD, paleo-temperature records

12. EcoSec_M331H_M331I_Mean_VPD_MaySep_1979_2020.csv -- VPD data for Southern Rockies study area, averaged across space.

13. GrandLake_Mean_VPD_MaySep_1980_2020.csv -- VPD data for Grand Lake, CO, as point representation for focal study area.

14. trouet2013nam480pollen.csv -- Paleoclimate (temperature) reconstruction by Trouet et al. (2013).

15. Mann08_nhcru_eiv_composite_updatedCRU_v102520.csv -- Paleoclimate (temperature) reconstruction by Mann et al. (2008), update with CRU data from 2009-2020.

3. FIGURES

Figures in .tiff format, at 600 dpi.

Files:

  • Fig_1.tiff
  • Fig_2.tiff
  • Fig_S1.tiff
  • Fig_S2.tiff
  • Fig_S3.tiff

Funding

National Science Foundation, Award: DEB-1655121