DOI: 10.5061/dryad.6djh9w18z
title: Trees have similar growth responses to first-entry fires and reburns following long-term fire exclusion

description: Managing fire ignitions for resource benefit decreases fuel loads and
 reduces the risk of high-severity fires in fire-suppressed dry conifer
 forests. However, the reintroduction of low-severity wildfires can injure
 trees, which may decrease their growth after a fire. Post-fire growth
 responses could change from first-entry fires to reburns, as first-entry
 fires reduce fuel loads and the vulnerability among trees to fire effects,
 which may result in trees sustaining less damage during reburns. To
 determine whether trees had growth responses that varied from first-entry
 fires to reburns, we cored 87 ponderosa pine trees in the Gila Wilderness,
 New Mexico, USA that experienced 3-5 fires between 1950 and 2012 following
 long-term fire-exclusion and 67 unburned control trees from the Gila and
 Apache-Sitgreaves National Forests. We assessed tree growth response to
 fire by comparing tree-ring growth among burned and unburned trees during
 the growing season and the two growing seasons before and after the fire.
 We compared growth between burned and unburned trees using a bootstrapping
 procedure to calculate annual median tree-ring width index values with 95%
 confidence intervals. We compared post-fire growth after first-entry fires
 and reburns following long-term fire exclusion. Burned trees had similar
 growth responses following first-entry fires and reburns, with lower
 growth rates during the growing season and the two growing seasons after
 fires compared to unburned controls. Burned tree growth returned to
 expected rates following these immediate post-fire growth reductions.
 Interestingly, trees had lower growth during the year before and the year
 of reburns compared to the first-entry fire, reflecting greater aridity
 before reburns. Greater aridity may have contributed to
 larger-than-expected growth reductions following reburns that could
 explain similar growth responses to first-entry fires and reburns. Our
 results indicate that trees had consistent short-term growth responses to
 low-severity fires following long-term fire exclusion. As trees retained
 vigor after multiple fires, managing fires for resource benefit is an
 effective approach to reduce the likelihood of high-severity fires without
 long-term negative effects on tree growth.
description: # Trees have similar growth responses to first-entry fires and reburns
 following long-term fire exclusion
 [https://doi.org/10.5061/dryad.6djh9w18z](https://doi.org/10.5061/dryad.6djh9w18z) The data and code included in this Dryad submission were used to analyze and compare the effect of first-entry fires and reburns on ponderosa pine growth. Datasets include 1) growth data from 87 burned trees that experienced 3-5 fires from 1950-2018 and 86 unburned trees from fire-excluded forests in the Gila National Forest, NM, USA; 2) the years burned trees experienced fires; 3) climate data for each plot downloaded from PRISM Explorer; and 4) spatial data related to Figure 1. ## Description of the data and file structure data frames: Annual_tree_size.xlsx - This data frame contains estimated annual tree sizes for all trees in the analysis. Estimates were calculated using measured tree DBH and annual growth increments from tree core data. Columns are as follows: "Fire", "Patch", "Transect", "Tree" = identification for each tree, "Year" = the year of the estimated size of the tree, "annual_diameter" = estimated dbh of the tree for that year in cm. All_2022_Cores_Q2_Tucson.txt - This text file contains growth data for all tree cores collected for analysis. Columns are as follows: First column = tree core series identification, Second column = decade affiliated with growth measurements, Third-Twelth columns = tree-ring width measurements (in thousands of mm). Fire_Occurences.xlsx - This data frame contains the number of fires and years of fires that burned through each plot, which was aggregated from monitoring trends in fire severity data, corrected fire boundaries by Parks et al. 2015, and historical fire boundaries from Rollins et al. 2002. Columns are as follows: "Fire", "Patch", and "Transect" = identification for each plot, "Num_fires" = the number of fires each plot experienced, "Fire_year_1" = the year a plot experienced its first fire, "Fire_year_2" = the year a plot experienced its second fire, "Fire_year_3" = the year a plot experienced its third fire, "Fire_year_4" = the year a plot experienced its fourth fire, "Fire_year_5" = the year a plot experienced its fifth fire. Fire_Severity_7-4-24.xlsx - This data frame contains the fire severity values (in relativized burn ratio values, RBR) for every fire that burned plots from 1950-2012. Data was gathered from RBR raster data calculated by Parks et al. 2015. Columns are as follows: "Fire", "Patch", and "Transect" = identification for each plot, "Year" = the year of a fire, "Severity" = RBR value for that plot of that fire, "First_Sub" = delineation for whether the first was the first-entry fire ("First") that burned the plot after fire-exclusion or a reburn ("Subsequent"). PRISM_Monthly_Climate_1900-1915_SPEI.csv - This data frame contains monthly climate data for all plots in the study from 1900-1915, which was used to quantify annual VPD values for that period and to assess seasonal climate-growth correlation patterns with temperature and precipitation. Columns are as follows: "Name" = identification for each plot, "Longitude" = longitude for each plot location, "Latitude" = latitude for each plot location, "Elevation" = elevation (in meters) of the centroid for the 4-km grid cell the plot occurred in, "Date" = Year and month of the climate data point, "ppt (mm)" = total precipitation for that year/month in millimeters, "tmin (degrees C)" = minimum temperature recorded during that year/month in degrees Celsius, "tmax (degree C)" = maximum temperature recorded during that year/month in degrees Celsius, "vpdmax (hPa)" = maximum vapor pressure deficit recorded during that year/month in Hectopascals. PRISM_Monthly_Climate_1915-1930_SPEI.csv - This data frame contains monthly climate data for all plots in the study from 1915-1930, which was used to quantify annual VPD values for that period and to assess seasonal climate-growth correlation patterns with temperature and precipitation. Columns are as follows: "Name" = identification for each plot, "Longitude" = longitude for each plot location, "Latitude" = latitude for each plot location, "Elevation" = elevation (in meters) of the centroid for the 4-km grid cell the plot occurred in, "Date" = Year and month of the climate data point, "ppt (mm)" = total precipitation for that year/month in millimeters, "tmin (degrees C)" = minimum temperature recorded during that year/month in degrees Celsius, "tmax (degree C)" = maximum temperature recorded during that year/month in degrees Celsius, "vpdmax (hPa)" = maximum vapor pressure deficit recorded during that year/month in Hectopascals. PRISM_Monthly_Climate_1930-1945_SPEI.csv - This data frame contains monthly climate data for all plots in the study from 1930-1945, which was used to quantify annual VPD values for that period and to assess seasonal climate-growth correlation patterns with temperature and precipitation. Columns are as follows: "Name" = identification for each plot, "Longitude" = longitude for each plot location, "Latitude" = latitude for each plot location, "Elevation" = elevation (in meters) of the centroid for the 4-km grid cell the plot occurred in, "Date" = Year and month of the climate data point, "ppt (mm)" = total precipitation for that year/month in millimeters, "tmin (degrees C)" = minimum temperature recorded during that year/month in degrees Celsius, "tmax (degree C)" = maximum temperature recorded during that year/month in degrees Celsius, "vpdmax (hPa)" = maximum vapor pressure deficit recorded during that year/month in Hectopascals. PRISM_Monthly_Climate_1945-1960_SPEI.csv - This data frame contains monthly climate data for all plots in the study from 1945-1960, which was used to quantify annual VPD values for that period and to assess seasonal climate-growth correlation patterns with temperature and precipitation. Columns are as follows: "Name" = identification for each plot, "Longitude" = longitude for each plot location, "Latitude" = latitude for each plot location, "Elevation" = elevation (in meters) of the centroid for the 4-km grid cell the plot occurred in, "Date" = Year and month of the climate data point, "ppt (mm)" = total precipitation for that year/month in millimeters, "tmin (degrees C)" = minimum temperature recorded during that year/month in degrees Celsius, "tmax (degree C)" = maximum temperature recorded during that year/month in degrees Celsius, "vpdmax (hPa)" = maximum vapor pressure deficit recorded during that year/month in Hectopascals. PRISM_Monthly_Climate_1960-1975_SPEI.csv - This data frame contains monthly climate data for all plots in the study from 1960-1975, which was used to quantify annual VPD values for that period and to assess seasonal climate-growth correlation patterns with temperature and precipitation. Columns are as follows: "Name" = identification for each plot, "Longitude" = longitude for each plot location, "Latitude" = latitude for each plot location, "Elevation" = elevation (in meters) of the centroid for the 4-km grid cell the plot occurred in, "Date" = Year and month of the climate data point, "ppt (mm)" = total precipitation for that year/month in millimeters, "tmin (degrees C)" = minimum temperature recorded during that year/month in degrees Celsius, "tmax (degree C)" = maximum temperature recorded during that year/month in degrees Celsius, "vpdmax (hPa)" = maximum vapor pressure deficit recorded during that year/month in Hectopascals. PRISM_Monthly_Climate_1975-1990_SPEI.csv - This data frame contains monthly climate data for all plots in the study from 1975-1990, which was used to quantify annual VPD values for that period and to assess seasonal climate-growth correlation patterns with temperature and precipitation. Columns are as follows: "Name" = identification for each plot, "Longitude" = longitude for each plot location, "Latitude" = latitude for each plot location, "Elevation" = elevation (in meters) of the centroid for the 4-km grid cell the plot occurred in, "Date" = Year and month of the climate data point, "ppt (mm)" = total precipitation for that year/month in millimeters, "tmin (degrees C)" = minimum temperature recorded during that year/month in degrees Celsius, "tmax (degree C)" = maximum temperature recorded during that year/month in degrees Celsius, "vpdmax (hPa)" = maximum vapor pressure deficit recorded during that year/month in Hectopascals. PRISM_Monthly_Climate_1990-2005_SPEI.csv - This data frame contains monthly climate data for all plots in the study from 1990-2005, which was used to quantify annual VPD values for that period and to assess seasonal climate-growth correlation patterns with temperature and precipitation. Columns are as follows: "Name" = identification for each plot, "Longitude" = longitude for each plot location, "Latitude" = latitude for each plot location, "Elevation" = elevation (in meters) of the centroid for the 4-km grid cell the plot occurred in, "Date" = Year and month of the climate data point, "ppt (mm)" = total precipitation for that year/month in millimeters, "tmin (degrees C)" = minimum temperature recorded during that year/month in degrees Celsius, "tmax (degree C)" = maximum temperature recorded during that year/month in degrees Celsius, "vpdmax (hPa)" = maximum vapor pressure deficit recorded during that year/month in Hectopascals. PRISM_Monthly_Climate_2005-2020_SPEI.csv - This data frame contains monthly climate data for all plots in the study from 2005-2020, which was used to quantify annual VPD values for that period and to assess seasonal climate-growth correlation patterns with temperature and precipitation. Columns are as follows: "Name" = identification for each plot, "Longitude" = longitude for each plot location, "Latitude" = latitude for each plot location, "Elevation" = elevation (in meters) of the centroid for the 4-km grid cell the plot occurred in, "Date" = Year and month of the climate data point, "ppt (mm)" = total precipitation for that year/month in millimeters, "tmin (degrees C)" = minimum temperature recorded during that year/month in degrees Celsius, "tmax (degree C)" = maximum temperature recorded during that year/month in degrees Celsius, "vpdmax (hPa)" = maximum vapor pressure deficit recorded during that year/month in Hectopascals. Spatial Data: Fire_recurrence_shapefile.shp - Shapefile of fire history in the Gila from 1909-2018 used to make Figure 1. Locations did not experience any fire until 1950 at the earliest. Gila_DEM.tif - 10-meter elevation raster across the Gila national forest used to calculate hillshade in the Gila wilderness. Gila_hillshade.tif - 10-meter hillshade of the Gila wilderness used to make Figure 1. ## Code/Software 1 - Question2-3 averaging cores.R = Code to remove undateable cores and average growth between series for each tree 2 - Question 2 analysis prep std-growth.R = Code to detrend growth data among trees from fire-maintained forests and create a long data frame to use in future analyses 3 - Control tree selection.R = Code for selecting trees from fire-excluded forests to use as controls for analyses 4 - Control detrend prep.R = Code to detrend growth data among the 67 control trees from fire-excluded forests and create a long data frame to use in future analyses 5 - Seascorr control check.R = Code to assess climate-growth correlation patterns among burned and control trees 6 - Five-ish year window comparisons burned and control.R = Code to assess pre-fire growth rates among burned and control trees 7 - Control vs fire cluster bootstrap comparison.R = Code to make Figure 4, which assesses growth patterns before and after first entry fires and reburns among burned and control trees 8 - VPD figure and stats.R = Code to make Figure 2, which compares a growth chronology against annual VPD and plots the number of trees burned by year against 20-year normals for VPD. This script also includes some stats used in the results section. 9 - Fire severity and RWI~VPD regression code.R = Code to quantify the relationship between tree growth (RWI), aridity (VPD), and fire severity.