DOI: 10.5061/dryad.r7sqv9sks
title: Suppression of reed canarygrass by assisted succession: A sixteen-year restoration experiment

description: Assisted succession could enable long-term restoration of invaded areas
 where successional trajectories have stalled due to competition from
 invasive species. Many invasives are shade-intolerant, therefore
 interventions that reduce light availability should suppress invasion and
 simultaneously re-establish successional processes. However, restoration
 success also depends on identifying critical system thresholds, e.g.,
 invader abundances below which regeneration of desired species is
 possible. We report the successful use of assisted succession to restore a
 swamp forest invaded by Phalaris arundinacea (reed canarygrass; hereafter
 Phalaris), initiated by a high-density planting of woody species to
 outcompete the invader by reducing light availability. We established five
 pre-planting treatments in a Phalaris near-monoculture in Wisconsin, USA:
 herbicide-only, herbicide+plow, herbicide+burn, herbicide+mow, and
 control. In 2003 we planted 23 tree and shrub species at high densities,
 then in 2019 we censused the site to: (1) evaluate the effect of our
 interventions on community composition, (2) document trends in community
 change over time, and (3) determine light availability thresholds that
 influence community composition. We found no differences among
 pre-planting invader removal treatments. Late fall glyphosate application
 suppressed Phalaris long enough that a dense canopy of native woody
 species could establish and eventually out-shade it. Overstory densities
 of 0.071/m2 suppressed Phalaris to 50% cover, but, due to nonlinearities,
 much higher densities were needed to reduce light availability and thus
 Phalaris cover enough to shift the system from being invader-dominated.
 Regeneration of the woody species we had initially planted suggests
 long-term restoration success. Synthesis and applications. An empirical
 understanding of long-term community dynamics can help manage invasive
 species and restore target plant communities. We show a cost-effective
 restoration strategy for forests invaded by shade-intolerant invaders that
 arrest succession. Our data indicate that establishing a dense canopy of
 woody species through assisted succession can re-introduce feedbacks
 enabling long-term ecosystem recovery. We also illustrate the value of
 identifying critical thresholds influencing the abundance and impact of
 key invasive species.
description: <strong>Study area and</strong>
 <strong>treatments</strong>: This study was conducted in
 southeastern Wisconsin, USA at the Huiras Lake State Natural Area (Lat:
 43.5136095, Lon: -87.9828698). In 2002, 0.50 ha of a near-monoculture
 field of <em>Phalaris </em>was divided into 50 plots ranging
 from 30.3 to 154 m2. Except for two large blocks left as eight untreated
 control plots, the entire site was sprayed with 0.7% active ingredient
 glyphosate solution in early November 2002; such late-season herbicide
 application is recommended for <em>Phalaris </em>(Adams
 & Galatowitsch, 2006). Four pre-planting invader removal
 treatments were established in sprayed plots between fall 2002 and spring
 2003 (Hovick & Reinartz, 2007): 1) herbicide-only (H) – no
 additional pre-planting treatment; 2) mow+herbicide (MH) –
 <em>Phalaris</em> biomass mowed in early fall 2002, before
 herbicide application; 3) herbicide+burn (HB) – herbicide application
 followed by burning <em>Phalaris</em> litter in spring 2003;
 and 4) herbicide+plow (HP) – herbicide application followed by plowing in
 spring 2003 (Figure S1).   In
 spring 2003, 22 tree and shrub species were planted by hand at a density
 of 9,500/ha (0.95/m2) across all plots (4668 individual plants; 29 to 146
 per plot, depending on plot size). Most species were bareroot stock,
 although American elm, yellow birch, and basswood were small, rooted plugs
 and willows were live stakes. Initial planting numbers varied widely among
 species, due to availability (Table 1). No additional
 <em>Phalaris</em> management occurred
 post-planting.  
 <strong>Sampling design</strong>: We surveyed
 vegetation in July 2019, complementing this data set with survival data
 from summer 2003 and 2004 (Hovick & Reinartz, 2007). The 2019
 survey had three main components:  
 1. Groundcover - We quantified <em>Phalaris</em>
 cover and that of any non-<em>Phalaris</em> herbaceous
 species, recording visual estimates of each group in two 1m2 quadrats per
 plot. We used modified Daubenmire cover classes: &lt;5%, 5-24%,
 25-49%, 50-74%, and 75-100% (Daubenmire, 1959), allowing the sum of
 <em>Phalaris</em> and non-<em>Phalaris</em> cover
 to exceed 100%. For each quadrat, we also estimated cover of litter,
 vegetation, or bare soil, constraining the summed estimates of these
 components to equal 100%. Prior to analysis, cover estimates were
 transformed to the midpoint of each cover class (restricting midpoints to
 minimum 2.5%, maximum 87.5%) and averaged to yield a single estimate per
 plot.   2. Tree and shrub
 abundance – To characterize the woody plant community, we separately
 quantified species-specific abundances in the overstory, sapling layer,
 and seedling layer. In the overstory, we recorded all woody species in the
 plot ≥2.5 cm diameter at breast height (DBH). Due to widespread mortality
 in some species (most notably green and black ash [Fraxinus americana and
 F. nigra]), we noted whether overstory individuals were alive (foliage
 green), dead (no green foliage), or resprouting (most foliage dead, but
 some recent growth with green leaves). We sampled saplings within two 2×2
 m sampling quadrats per plot (each of which contained a groundcover
 sampling plot at one corner), counting as saplings all woody species
 &gt;1 m tall and &lt;2.5 cm DBH. We sampled seedlings using four 1
 m2 quadrats per plot, positioning two quadrats at opposite corners within
 each sapling quadrat. We counted as seedlings all woody species &lt;1
 m but &gt;30 cm in height. Individuals in each stratum were identified
 to species whenever possible, except for lumping together ashes (as
 Fraxinus spp.) and dogwoods (<em>Cornus sericea </em>and
 <em>C. stolonifera </em>as <em>Cornus
 spp</em>.).   3. Light
 availability - Total light availability above the herbaceous level was
 estimated as percent canopy openness using hemispherical photos. We took
 two pictures per plot, centered in each sapling quadrant, and analyzed
 with Gap Light Analyzer, Version 2.0 (Frazer et al., 1999). Data were
 averaged to yield a single estimate per plot.   
 <strong>Statistical analysis</strong>:
 Using census data from three years (2003, 2004, 2019), we quantified
 density and survival trajectory. Density is per-plot abundance of a given
 species divided by plot area (overstory) or sampling area (saplings,
 seedlings). Survival trajectory is per-species density, relative to the
 number of planted individuals (2003) or relative to density in the
 preceding survey (2004, 2019). Survival trajectory in 2019 was divided by
 fifteen to compare all density changes on a per-year basis.  
 As preliminary tests of differences
 among removal treatment types, we compared light availability,
 <em>Phalaris</em> cover, and overstory density across
 treatments using linear mixed models (R Core Team, 2021) lme4::lmer,
 (Bates et al., 2015); car::Anova, (Fox & Weisberg, 2019) with
 random effects, included to account for spatial nonindependence among
 plots within blocks and among blocks themselves (Figure S1). All pairwise
 comparisons among removal treatments and controls were then contrasted
 with Tukey’s post-hoc tests. Seeing negligible differences among removal
 treatments themselves, as expected, we shifted our focus to be on
 <em>Phalaris</em> removal vs. control differences in density,
 survival trajectory and groundcover percentages. We present linear mixed
 models followed by Dunnett’s post-hoc tests comparing each treatment to
 the control (emmeans, (Lenth et al., 2020)). Most response variables were
 nonnormal, but model residuals were largely normally distributed,
 supporting model fits.  We
 estimated nonlinear relationships at the plot scale (n=50), combining data
 from all pre-planting treatments to describe 1) the ability of increased
 overstory densities to decrease light availability and (by extension)
 <em>Phalaris</em> cover, 2) the ability of decreased light to
 suppress <em>Phalaris</em>, and 3) the impact of
 <em>Phalaris </em>cover in suppressing sapling density. These
 models allowed us to estimate, for example, the overstory density or
 reduction in light availability required to suppress <em>Phalaris
 </em>to a target percent cover. Preliminary analyses indicated no
 support for treatment-specific models and that these relationships were
 best characterized using log-logistic curves (drc::drm (Ritz et al.,
 2015)), with slope and inflection point the estimated parameters. We fixed
 lower and upper limits to realistic ranges of y: 0 to 100 for
 <em>Phalaris</em> percent cover or light availability, and 0
 to 3.125 saplings/m2 (the maximum observed value) for sapling density. We
 used these curves to estimate predictor values required to suppress
 <em>Phalaris</em> to 50%, 25%, and 10% cover. For the three
 models with <em>Phalaris</em> cover as a variable, we achieved
 estimates directly by substituting the target percentage and solving for
 the corresponding value. We used model-estimated light availability
 corresponding to 50%, 25%, and 10% <em>Phalaris</em> cover to
 predict overstory densities required to achieve those light levels. These
 estimated nonlinear relationships imply causal direction, but to examine
 other relationships lacking clear causality we calculated Pearson
 correlations (stats::cor, stats::cor.test, (R Core Team, 2021). 
description: ## Palacio-Lopez K, Hovick SM, Mattingly KZ, Weston LM, Hofford NP, Finley
 L, Tayal A, Reinartz JA. Suppression of reed canarygrass by assisted
 succession: A sixteen-year restoration experiment. Journal of Applied
 Ecology.
 [https://doi.org/10.5061/dryad.r7sqv9sks](https://doi.org/10.5061/dryad.r7sqv9sks) ## Summary 1. Assisted succession could enable long-term restoration where successional trajectories stall due to competition from invasive plants. Many invasives are shade-intolerant, therefore interventions reducing light availability should suppress invasion and re-establish successional processes. However, given how ubiquitous nonlinearities are in ecology, restoration success also depends on identifying critical system thresholds, e.g., invader abundances below which regeneration of desired species is possible. We report the successful use of assisted succession to restore a swamp forest invaded by Phalaris arundinacea (reed canarygrass; hereafter Phalaris), initiated by a high-density planting of woody species to outcompete Phalaris by reducing light availability. 2. We established five pre-planting treatments in a Phalaris near-monoculture in Wisconsin, USA: herbicide-only, herbicide+plow, herbicide+burn, mow+herbicide, and control. In 2003 we planted 22 tree and shrub species at high densities, then in 2019 we censused the site to: (1) screen for long-term differences among treatments, (2) evaluate long-term effects of our interventions on community composition, and (3) characterize the critical thresholds that enable invader suppression and restoration success. 3. Vegetation responses and light availability across our four pre-planting invader removal treatments did not differ. Late fall glyphosate application suppressed Phalaris long enough that a dense canopy of native woody species could establish and eventually out-shade it. Overstory tree and shrub densities of 0.071/m2 suppressed Phalaris to 50% cover, but, due to nonlinearities, much higher densities were needed to reduce light availability and thus Phalaris cover enough to shift the system from being invader-dominated. Compositional similarities between juvenile woody species and the overstory suggest a long-term restoration success. 4. Synthesis and applications. Invasive species management and the restoration of target plant communities can be aided by assisting successional trajectories that have stalled. We document a restoration strategy for forests invaded by shade-intolerant invaders that is both effective and economical, as only a simple site preparation and single planting effort is required. Establishing a dense canopy of woody species in this way can break the feedbacks maintaining invader dominance and re-introduce feedbacks enabling long-term ecosystem recovery. We also illustrate the value of identifying critical thresholds influencing the abundance and impact of key invasive species. ## Description of the data and file structure "_df_diversity_richness_051320.csv" - 2019 richness and diversity of woody species calculated on a per-plot basis. * plot - Experimental plot. See Figure S1 for experimental design layout. * block - Experimental block. See Figure S1 for experimental design layout. * area - Plot area in sq m. * treat - Phalaris removal treatment. (P)–herbicide+plow; (B)–herbicide+burn; (M)–mow+herbicide; (H)–herbicide-only; and (C)–control. * diversity.all - Inverse Simpson's index for all woody species (trees and shrubs). * richness.all - Number of woody species (trees and shrubs). * diversity.trees - Inverse Simpson's index for trees. * richness.trees - Number of tree species. * diversity.shrubs - Inverse Simpson's index for shrubs. * richness.shrubs - Number of shrub species. "_df_sapling_quad_all_sites_050820.csv" - 2019 quadrat-based sampling of woody species in the sapling layer (woody species &gt;1 m tall and &lt;2.5 cm DBH). * site - Fellenz Woods Park (data not reported in this manuscript, see Hovick and Reinartz 2007), Winker Property (data not reported in this manuscript, see Hovick and Reinartz 2007), or Huiras Lake State Natural Area. * block - Experimental block. See Figure S1 for experimental design layout. * plot - Experimental plot. See Figure S1 for experimental design layout. * area - Plot area in sq m. * elevation_f - Plot elevation in ft. * elevation_m - Plot elevation in m. * treat - Phalaris removal treatment. (P)–herbicide+plow; (B)–herbicide+burn; (M)–mow+herbicide; (H)–herbicide-only; and (C)–control. * quad - Sampling quadrat. * to_include - Identifier denoting quadrat samples to omit due to being counted twice. * sp_name - Sapling species common name abbreviation. Blank if the quadrat had no saplings. See Table 1 for additional species details. * cat - Identifier to denote tree vs. shrub (See Table 1 for additional species details). NA if the quadrat had no saplings. * sapling - Identifier to denote saplings. * sapling_count - Count of saplings of that species within the quadrat. * notes - additional details such as species ID or information about data transcription from physical data sheets. "_df_small_trees_050520.csv" - 2019 quadrat-based sampling of woody species in the seedling layer (&lt;1 m but &gt;30 cm in height). * site - Fellenz Woods Park (data not reported in this manuscript, see Hovick and Reinartz 2007), Winker Property (data not reported in this manuscript, see Hovick and Reinartz 2007), or Huiras Lake State Natural Area. * block - Experimental block. See Figure S1 for experimental design layout. * plot - Experimental plot. See Figure S1 for experimental design layout. * area - Plot area in sq m. * elevation_f - Plot elevation in ft. * elevation_m - Plot elevation in m. * treat - Phalaris removal treatment. (P)–herbicide+plow; (B)–herbicide+burn; (M)–mow+herbicide; (H)–herbicide-only; and (C)–control. * quad - Sampling quadrat. * sp_name - Seedling species common name abbreviation. NA if the quadrat had no seedlings. See Table 1 for additional species details. * status - a=alive, d=dead. NA if the quadrat had no seedlings. * sll_tree_count - Count of seedlings of that species within the quadrat. * notes - additional details about data transcription from physical data sheets. "_df_soilmoist_light_rcg_elevation_treat_quad_050320.csv" - 2019 quadrat-based sampling of vegetation and environmental variables. * site - Fellenz Woods Park (data not reported in this manuscript, see Hovick and Reinartz 2007), Winker Property (data not reported in this manuscript, see Hovick and Reinartz 2007), or Huiras Lake State Natural Area. * block - Experimental block. See Figure S1 for experimental design layout. * plot - Experimental plot. See Figure S1 for experimental design layout. * area - Plot area in sq m. * elevation_f - Plot elevation in ft. * elevation_m - Plot elevation in m. * treat - Phalaris removal treatment. (P)–herbicide+plow; (B)–herbicide+burn; (M)–mow+herbicide; (H)–herbicide-only; and (C)–control. * quad - Sampling quadrat. * mean_soil_moist - Per-plot mean soil moisture. * light - Total light availability above the herbaceous level estimated as percent canopy openness using hemispherical photos. * v_cover_rcg - Visually estimated Phalaris cover via modified Daubenmire cover classes: &lt;5%, 5-24%, 25-49%, 50-74%, and 75-100% (Daubenmire, 1959), allowing the sum of Phalaris and non-Phalaris cover to exceed 100%. Cover estimates were transformed to the midpoint of each cover class (restricting midpoints to minimum 2.5%, maximum 87.5%). * v_cover_no_rcg - Visually estimated cover of species other than Phalaris, via modified Daubenmire cover classes: &lt;5%, 5-24%, 25-49%, 50-74%, and 75-100% (Daubenmire, 1959), allowing the sum of Phalaris and non-Phalaris cover to exceed 100%. Cover estimates were transformed to the midpoint of each cover class (restricting midpoints to minimum 2.5%, maximum 87.5%). * bare - Visually estimated cover of bare ground, via modified Daubenmire cover classes: &lt;5%, 5-24%, 25-49%, 50-74%, and 75-100% (Daubenmire, 1959), constraining the summed estimates of litter, vegetation, and bare soil to equal 100%. * litter - Visually estimated cover of litter, via modified Daubenmire cover classes: &lt;5%, 5-24%, 25-49%, 50-74%, and 75-100% (Daubenmire, 1959), constraining the summed estimates of litter, vegetation, and bare soil to equal 100%. * veg - Visually estimated cover of vegetation, via modified Daubenmire cover classes: &lt;5%, 5-24%, 25-49%, 50-74%, and 75-100% (Daubenmire, 1959), constraining the summed estimates of litter, vegetation, and bare soil to equal 100%. * note - additional information about data transcription from physical data sheets. * plot_quad - Identifier combining experimental plot and sampling quadrat. * sap_all - count of saplings of all woody individuals (trees and shrubs) within the quadrat. * sap_tree - count of all tree species saplings within the quadrat. * sap_shrub - count of all shrub species saplings within the quadrat. * sap_ash - count of all ash tree saplings within the quadrat. * sap_dogwood - count of dogwood shrub saplings within the quadrat. * sap_elderberry - count of all elderberry shrub saplings within the quadrat. * sap_blackraspberry - count of all raspberry shrub saplings within the quadrat. "_df_trees_shrub_no_sapling_050620.csv" - 2019 per-plot census of all large woody individuals (≥2.5 cm diameter at breast height (DBH)). * page - Physical data sheet source. * to_include - Identifier denoting quadrat samples to omit due to being counted twice. * site - Fellenz Woods Park (data not reported in this manuscript, see Hovick and Reinartz 2007), Winker Property (data not reported in this manuscript, see Hovick and Reinartz 2007), or Huiras Lake State Natural Area. * block - Experimental block. See Figure S1 for experimental design layout. * plot - Experimental plot. See Figure S1 for experimental design layout. * area - Plot area in sq m. * treat - Phalaris removal treatment. (P)–herbicide+plow; (B)–herbicide+burn; (M)–mow+herbicide; (H)–herbicide-only; and (C)–control. * sp_name - Woody species common name abbreviation. NA if the plot had no large woody individuals. See Table 1 for additional species details. * cat - Identifier to denote tree vs. shrub (See Table 1 for additional species details). NA if the plot had no large woody individuals. * sapling - Identifier to denote sapling or not (nosap). * dbh - Diameter at breast height, cm. * dbh_old - See note for these observations, error in collection of some DBHs. * canopy_area - Dimension of canopy area (m2) for shrubs. * wrong_canopy_area - See note for these observations, error in collection of some areas. * basal_area - Basal area (m2) for trees calculated from DBH. * status - a=alive, d=dead, r=resprout. NA if the plot had no large woody individuals. * note - additional information about data transcription from physical data sheets. "data_survival_all_years_edited_111320.csv" - per-plot counts of woody individuals at planting, in 2003 census, 2004 census, and as large woody individuals in 2019. * plot - Experimental plot. See Figure S1 for experimental design layout. * treat - Phalaris removal treatment. (P)–herbicide+plow; (B)–herbicide+burn; (M)–mow+herbicide; (H)–herbicide-only; and (C)–control. * cat - Identifier to denote tree vs. shrub (See Table 1 for additional species details). * identifier - Identifier combining plot and species name. * sp_name - Woody species common name abbreviation. See Table 1 for additional species details. * sum_of_n Rows - Data validation column. Column not used in the analysis. Column shows the total rows in which a species appears in a previous file. * n_planted - number of individuals planted of a species in that plot. * sum_n_03_S - sum per species found in spring 2003 * sum_n_03_F_original_noused - data not used in the analysis. Sum per species found in fall 2003 * sum_n_03_F - sum per species found in fall 2003 * sum_n_04 - sum per species found in 2004 * n_19_origin - sum per species found in 2019 * n_19 - sum per species found in 2019 omitting dead and resprout * status_2019 - a=alive, d=dead, r=resprout. NA if the plot had no large woody individuals. * subs_03F-04F - Data validation column. Column not used in the analysis. Column shows the difference in the number of species planted in fall 2003 and 2004. * note - notes about calculations. "ECxs 5_18_23.csv" - percent target calculations. Output from "ECxs 5_18_23.Rmd" * Percent_target - target/threshold percent of y variable. * x - x variable that is being manipulated to achieve the target. * y - y variable that is being targeted. * Estimate - curve-estimated value of x required to achieve target y. * Lower 95 - lower 95% confidence bound around estimate. * Upper 95 - upper 95% confidence bound around estimate. * figure - manuscript figure plotting the estimates. "Hill slopes and EC50s 5_18_23.csv" - curve model parameter estimates. Output of "Hill slopes and EC50s 5_18_23.Rmd" * parameter - curve model parameter: slope or asymptote (e:1:50). * x - x variable that is being manipulated to achieve the target. * y - y variable that is being targeted. * Estimate - estimated value of parameter. * Std.Error - standard error around parameter estimate. * Lower 95 - lower 95% confidence bound around estimate. * Upper 95 - upper 95% confidence bound around estimate. * t-value - t statistic of estimate. * p-value - significance of estimate. * figure - manuscript figure plotting the curve. "mean_quad_data.csv" - per-plot means of key environmental and vegetation variables. * plot - Experimental plot. See Figure S1 for experimental design layout. * block - Experimental block. See Figure S1 for experimental design layout. * treat - Phalaris removal treatment. (P)–herbicide+plow; (B)–herbicide+burn; (M)–mow+herbicide; (H)–herbicide-only; and (C)–control. * area - Plot area in sq m. * elev_m - Plot elevation in m. * mean_soil_moist - Per-plot mean soil moisture. * mean_light - per-plot mean light availability above the herbaceous level estimated as percent canopy openness using hemispherical photos. * mean_v_cover_no_rcg - per-plot mean of visually estimated cover of species other than Phalaris, via modified Daubenmire cover classes: &lt;5%, 5-24%, 25-49%, 50-74%, and 75-100% (Daubenmire, 1959). Within a sampling quadrat, we allowed the sum of Phalaris and non-Phalaris cover to exceed 100%. Cover estimates were transformed to the midpoint of each cover class (restricting midpoints to minimum 2.5%, maximum 87.5%). * mean_v_cover_rcg - per-plot mean of visually estimated cover of Phalaris, via modified Daubenmire cover classes: &lt;5%, 5-24%, 25-49%, 50-74%, and 75-100% (Daubenmire, 1959). Within a sampling quadrat, we allowed the sum of Phalaris and non-Phalaris cover to exceed 100%. Cover estimates were transformed to the midpoint of each cover class (restricting midpoints to minimum 2.5%, maximum 87.5%). * mean_sap_all - per-plot mean count of saplings of all woody individuals (trees and shrubs). * mean_sap_tree - per-plot mean count of all tree species saplings. * mean_sap_shrub - per-plot mean count of all shrub species saplings. * mean_sap_ash - per-plot mean count of all ash saplings. "treatment_reference.csv" - summary of experimental design variables. * site_num - number to differentiate the 3 sites. * site - Fellenz Woods Park (data not reported in this manuscript, see Hovick and Reinartz 2007), Winker Property (data not reported in this manuscript, see Hovick and Reinartz 2007), or Huiras Lake State Natural Area. * plot - Experimental plot. See Figure S1 for experimental design layout. * treatment - Long descriptive names for Phalaris removal treatments. * treat - Abbreviated names for Phalaris removal treatments. (P)–herbicide+plow; (B)–herbicide+burn; (M)–mow+herbicide; (H)–herbicide-only; and (C)–control. * area_m2 - Plot area in sq m. * block - Experimental block. See Figure S1 for experimental design layout. "z_abundance_ash_05_27_21.csv" - change in ash abundance over time from planting to 2019 survey. * time - 0=at planting, 0.5=survey in 2003, 1.5=survey in 2004, 16=2019 survey after 16 years. * treat - Phalaris removal treatment. (P)–herbicide+plow; (B)–herbicide+burn; (M)–mow+herbicide; (H)–herbicide-only; and (C)–control. * freq - abundance of ashes. ## Sharing/Access information Other publicly accessible locations of the data will include being linked by the journal, Journal of Applied Ecology. ## Code/Software "DRM plots KZM 5_18_23.R" This R script loads data and required packages and creates curve and correlation figures (Figure 3, 4, 5, and Supplemental Figure S4). The script was developed in R v. 4.2.1. "ECxs 5_18_23.Rmd" This R script loads data and required packages, fits the curve models, then prints to "ECxs 5_18_23.csv" the estimates at the 10, 25, and 50% threshold levels of restoration targets. The script was developed in R v. 4.2.1. "Figure 2 overstory sapl seedl density 1_30_23.R" This R script loads data and required packages and creates figure 2 (comparison of woody densities in each vegetation layer). The script was developed in R v. 4.2.1. "Figure S2 density diff w ANOVA 11_8_23.R" This R script loads data and required packages and creates figure S2 plus relevant ANOVA (shows changes over time in woody densities, comparing across treatments). The script was developed in R v. 4.2.1. "Figure S3 woody rich div w ANOVA 11_8_23.R" This R script loads data and required packages and creates figure S3 plus relevant ANOVA (shows richness and diversity of different layers of woody vegetation, comparing across treatments). The script was developed in R v. 4.2.1. "Figure S5 ash over time 1_31_23.R" This R script loads data and required packages and creates figure S5 (change over time in ash density, separated by treatment). The script was developed in R v. 4.2.1. "Hill slopes and EC50s 5_18_23.Rmd" This R script loads data and required packages, fits the curve models, then prints to "Hill slopes and EC50s 5_18_23.csv" the curve model parameters. The script was developed in R v. 4.2.1. "Tukeys among trts Table S1 11_20_23.R" This R script loads data and required packages and performs analyses reported in table S1 (comparisons across treatments of main focal variables). The script was developed in R v. 4.2.1.