DOI: 10.25338/b8d07v
title: Data from: Canopy seed survival through extreme fire in non-serotinous conifers: An unexpected source of forest resilience

description: Across much of the semiarid conifer forests of western North America (“dry
 conifer forests”), the dominant tree species are non-serotinous, lack soil
 seedbanks, and rarely disperse seeds much farther than 100 m, so tree
 regeneration in large, high-severity burned patches is expected to be
 highly seed-limited. Conifer seedlings do, however, sometimes establish at
 high densities deep within high-severity patches in these forests,
 implying that seeds can sometimes survive intense wildfire even when all
 overstory trees die. Does seed survival in the canopies of non-serotinous
 trees provide an unexpected source of forest resilience? To answer this
 question, we surveyed tree survival, fire severity, and seedling abundance
 across two very large wildfires in the first year after fire. Several of
 the study species had a good seed cone production year at the time of the
 fires. We stratified many of our plots deep within high-severity patches
 far from surviving trees, where existing models predict regeneration
 failure due to a lack of viable seeds. Contrary to such expectations, we
 found that conifer seedling densities in these areas were generally far
 greater than needed to replace fire-killed trees and sometimes approached
 seedling densities observed near surviving trees. Seedling densities in
 high-severity areas far from surviving trees correlated negatively with
 local burn intensity (canopy foliage consumption), supporting the local
 origin of the seeds and highlighting a critical driver of post-fire
 recovery that is easily missed by traditional surveys conducted &gt; 2
 years following fire. Seedling density was also strongly associated with
 burn date, suggesting that persistence of viable canopy seeds depends on
 synchrony between wildfire and cone ripening dates. Together, our results
 demonstrate that under the right conditions, canopy seed survival can lead
 to dense seedling establishment across large, severely burned areas and
 may substantially support the resilience of dry conifer forests to the
 uncharacteristically severe fires that are becoming increasingly prevalent
 in this system.
description: # Data from: Canopy seed survival through extreme fire in non-serotinous
 conifers: An unexpected source of forest resilience ##
 `fire_daily_area_2002_2021.csv` Total area burned by year and day of year
 for California fires burning between 2002 and 2021. Tabular data were
 derived by summarizing fire progression maps for the California fires
 burning between 2002 and 2020 as published by Coop et al. (2022), produced
 using the methods described above, and provided by S. Parks. We combined
 these 2002-2020 data with day of burning maps that we calculated, using
 the same methods, for California fires &gt; 404 ha burning in 2021 based
 on perimeters from the Monitoring Trends in Burn Severity (MTBS) database
 (Eidenshink et al. 2007). ## `plot-data-prepped.csv` Field data from
 high-severity burned areas of the 2021 Caldor and Dixie fires were
 collected for the paper. Each row represents a field plot. The dataset
 includes all field plots sampled by the project, including those excluded
 from the analyses supporting the paper, based on the plot selection
 criteria described in the paper. The dataset also includes field plot
 attributes beyond those analyzed in the paper, to enable future extensions
 of the analysis. Data were collected by a researcher who visited each plot
 and recorded their observations. Percent covers and cone densities are
 recorded for the circle with an 8 m radius surrounding the plot center.
 Seedling densities are estimated by counting seedlings within a radius of
 the plot center determined by the seedling abundance. Note that this
 dataset includes the full set of surveyed plots, from which a subset was
 selected for the analyses supporting the accompanying paper (following the
 plot inclusion criteria described in the published paper). For full plot
 selection, subsetting, and mensuration methodology, please see the methods
 section of the accompanying paper. All missing data represented as NA.
 Fields (columns) include taxon abbreviations as follows: * YLWPINES:
 yellow pines, i.e., *Pinus ponderosa* and *Pinus jeffreyi* * PILA: *Pinus
 lambertiana* * ABCO: *Abies concolor* * PSME: *Pseudotsuga menziesii* *
 CADE: *Calocedrus decurrens* * PINES: *Pinus* spp. * ABIES: *Abies* spp. *
 ALL: all species * FIRS: *Abies* spp. and *Pseudotsuga menziesii* The
 fields (columns) are as follows: * fire: The name of the fire where the
 plot was sampled * plot_id: A unique plot ID * plot_type: `seedwall` for
 edge plots, `core` For interior plots, and for additional interior plots.
 The latter plot type refers to "delayed mortality" plots, which
 were designed to capture highly injured trees that were not completely
 killed and were expected to die in future years. Some of these plots were
 far enough from the highly injured green trees that they satisfied the
 criteria for interior plots for the paper. Edge plots are those near an
 unburned forest edge, and interior plots are those far from healthy
 surviving green trees. * survey_date: The date the plot was surveyed * lat
 and lon: The geographic coordinates of the plot, in decimal degrees,
 rounded to the nearest thousandth * shrub_cover: The shrub cover in the
 plot (%) * shrub_height: The mean height of shrubs in the plot (cm). Only
 recorded if shrub cover &gt; 1% * herb_cover: The cover of herbaceous
 vegetation in the plot (%) * herb_height: The mean height of herbaceous
 vegetation in the plot (cm). Only recorded if herb cover &gt; 1% *
 litter_cover: The cover of litter in the plot (%) * litter_depth: The
 depth of litter in the plot, sampled at a representative point where
 litter was present * moss_cover: The cover of moss in the plot (%) *
 branches_cover: The cover of the plot by dropped branches (%) *
 vol_*aaa*_*bbb*: The estimated percentage of the pre-fire foliage volume
 that is now green (*aaa* = grn), brown (*aaa* = brn), or missing (*aaa* =
 blk) within either a 50 m radius (*bbb* = 50m) or 10 m radius (*bbb* =
 10m) surrounding the plot * sight_line: The distance to the nearest
 obstruction (in any direction) that would prevent viewing a surviving or
 scorched tree behind it (m). Measured using a laser rangefinder *
 mean_tree_dbh: The diameter at breast height of the (fire-killed) tree
 that most closely matches the mean tree size (of trees &gt; 20 cm DBH),
 within 50 m of the plot center (cm) * mean_seedwall_height: The mean
 height of trees on the near side of the nearest unburned forest edge
 (recorded for edge plots only) (m). Measured using a laser rangefinder *
 prefire_prop_*aaaa*: The estimated prefire proportion of trees of taxon
 *aaaa* (%) * seedwall_density_cat: The categorical density/abundance of
 trees in the seed wall (surviving forest edge): L for &lt; 25 trees, H for
 an entire continuous intact forest, and M for an intermediate value *
 dom_yellpine_cone_sp: The species of the most abundant yellow pine cone in
 the plot. pije = *Pinus jeffreyi*, pipo = *Pinus ponderosa* *
 seedl_dens_*aaaa*: The density of seedlings of taxon *aaaa* within the
 field plot (seedlings m^-2) * cone_dens_*aaaa*: The density of cones of
 taxon *aaaa* within the field plot (cones m^-2) * under_cones_new_*aaaa*:
 The categorical density of cones of taxon *aaaa* under the nearest
 canopy-dominant tree of the taxon. The value is recorded as
 "low" if there were &lt; 10 conspecific cones (except &lt; 5 for
 *Pinus lambertiana*) underneath the tree, and "high" otherwise *
 dist_grn_*aaaa*: The distance to the nearest visible tree of taxon *aaaa*
 with &gt;= 5% of its prefire green canopy volume remaining (m). For edge
 plots, the distance to the green edge is recorded in the column
 dist_grn_ALL * *aaaa*_green_vol: Of the current green canopy volume, the
 proportion contributed by taxon *aaaa* (%) * *aaaa*_green_vol_abs: Of the
 estimated prefire green canopy volume, the proportion that is currently
 green and is of taxon *aaaa* (%) * ba: Live and dead tree basal area at
 the plot, estimated using a basal area gauge (variable-radius method)
 (ft^2 ac^-1) * cabable_growing_area: The percentage of the plot area that
 is not covered by large woody debris on the ground and rocks &gt; 10 cm in
 the short dimension (%) * fire_intens: Canopy burn fraction, computed by
 subtracting from 100 the average of the percent litter cover and scorched
 canopy foliage percent (%) * day_of_burning: The day of the year (1 to
 365) that the plot was estimated to have burned, following the methods of
 Parks (2014) as described in the paper accompanying this dataset. * ppt:
 Normal annual precipitation (1981-2010 mean) extracted from the 800-m
 resolution PRISM dataset (PRISM Climate Group 2022) using bilinear
 interpolation (mm) * tmean: Normal annual temperature (1981-2010 mean)
 extracted from the 800-m resolution PRISM dataset (PRISM Climate Group
 2022) using bilinear interpolation °C)