Clark-Wolf, K.D., Higuera, P.E., Davis, K.T., In Press. Conifer seedling demography reveals mechanisms of initial forest resilience to wildfires in the northern Rocky Mountains. Forest Ecology and Management. Dryad repository DOI: Contact: Kyra D. Wolf, kyra.clark-wolf@umontana.edu University of Montana 32 Campus Dr. Missoula, MT, 59812 Philip E. Higuera, philip.higuera@umontana.edu University of Montana 32 Campus Dr. Missoula, MT, 59812 Overview: This archive includes field measurements, climate/microclimate data, and soil data needed to reproduce the results presented in Clark-Wolf et al. (2022). The archive contains eight .csv files and two .R scripts. Methods for the collection of these data are described in Clark-Wolf et al. (2022). (1) ClarkWolf_et_al_2022_PlotData.csv – This includes site data and field measurements for each plot and derived (e.g., plot-averaged) variables used in statistical models. ‘Plot’ – unique plot identifier ‘Fire’ – wildfire identifier: LPK = Lolo Peak Fire; SUR = Sunrise Fire ‘Severity’ – fire severity classification from soil burn severity maps used in site selection ‘LON_WGS1984’ – longitude of plot location in decimal degrees ‘LAT_WGS1984’ – latitude of plot location in decimal degrees ‘Date_1’ – date of first sampling in 2018 ‘Date_2’ – date of sampling in 2019 ‘Date_3’ – date of sampling in 2020 ‘TransectSize’ – area of transect used for seedling count at last sampling time (2020), in square meters ‘Regen_AllSpp_ct’ – count of post-fire seedlings in transect at last sampling time, all species combined ‘Regen_Spp_ct’ – count of post-fire seedlings in transect at last sampling time by species PSME = Pseudotsuga menziesii PIPO = Pinus ponderosa LAOC = Larix occidentalis PICO = Pinus contorta PIEN = Picea engelmannii UNKN = unidentified Abies = Abies lasiocarpa and Abies grandis combined ‘Mort_seedlings_tot’ – total mortality rate of all seedlings marked in subplots across the 3 study years ‘Elev’– elevation of plot in m ‘slope’ – slope calculated from a digital elevation model in percent ‘aspect’ – aspect calculated from a digital elevation model in degrees ‘HLI’ – heat load index, unitless ‘DEF’ – 35-year average climatic water deficit (mm), 250-m resolution ‘ppt_ann’ – 35-year average annual precipitation (mm), scale-free ‘ppt_JJAS’ – 35-year average JJAS precipitation (mm), scale-free ‘ppt_pf’ – 2-year post-fire average JJAS precipitation (mm), scale-free ‘Tmax_abs’ – maximum JJAS microclimate temperature, predicted from statistical microclimate models ‘Tmax_avg’ – average daily maximum JJAS microclimate temperature, predicted from statistical microclimate models ‘dnbr’ – plot-averaged dNBR value derived from MTBS data (30-m resolution) ‘Axis1’ – field-based fire severity metric derived from PCA, reflecting variability in tree mortality and live canopy cover, with positive values associated with higher overstory fire severity ‘Axis2’ – field-based fire severity metric derived from PCA, reflecting variability in understory vegetation and bare ground cover among plots, with positive values associated with less vegetation cover ‘DSS’ – plot averaged distance to the nearest live mature tree (“distance to seed source”) in meters ‘PP’ – average percent cover of live trees within a 200 m radius of plot center identified from aerial imagery (“propagule pressure”) ‘PP_dWt’ – distance-weighted propagule pressure ‘cover.XX_Avg’ – variables describing ground cover (%), averaged within plots and across sample years ‘BG’ = bare ground and rock ‘Wood’ = coarse woody debris ‘Litter’ = litter and fine wood ‘Moss’ = moss and lichen ‘Grass’ = graminoid ‘Forb’ = herbaceous ‘Shrub’ = woody shrub ‘SeedlingSapling’ = cover of seedlings and juvenile trees <1.37 m height (not included in canopy cover measurements) ‘Canopy.tot_Avg’ – total live and dead canopy cover, averaged within plots and across sample years ‘Canopy.green_Avg’ – green canopy cover, averaged within plots and across sample years ‘Canopy.dead_Avg’ – dead canopy cover, averaged within plots and across sample years ‘SH’ – plot average char height in meters measured at 6 to 10 trees ‘NH4’ – plot-average ammonium availability in µg-N day-1, measured using resin capsules ‘NH4’ – plot-average nitrate availability in µg-N day-1, measured using resin capsules ‘soilN’ – plot-average total inorganic nitrogen availability in µg-N day-1, measured using resin capsules ‘LiveBA’ – plot-average live basal area in ft-sq per acre ‘DeadBA’ – plot-average dead basal area in ft-sq per acre ‘ba_PICO’ – plot-average total (live and dead) basal area of P. contorta ‘ba_PICO_L’ – live basal area of P. contorta ‘ba_PSME_L’ – live basal area of P. menziesii ‘ba_LAOC_L’ – live basal area of L. occidentalis ‘Spp_present’ – binary, 1 if focal species (PICO, PSME, LAOC) was identified in the overstory or nearby as a seed source, 0 otherwise ‘Mat_mort’ – mortality rate (%) of mature trees (>1.37 m height) ‘Sap_mort’ – mortality rate (%) of pre-fire sapling trees (<1.37 m height) ‘mort’ – total mortality rate of pre-fire trees (%) ‘Sapling_AllSpp’ – reconstructed total density of pre-fire sapling trees ‘Mature_AllSpp’ – reconstructed total density of pre-fire mature trees ‘n_live_V1_c1’ – total number of live seedlings in the first post-fire cohort (germinated in 2018) identified within subplots at the first sampling time (2018) ‘n_live_V2_c1’ – total number of live seedlings in the first post-fire cohort (germinated in 2018) identified within subplots at the second sampling time (2019) ‘n_live_V2_c2’ – total number of live seedlings in the second post-fire cohort (germinated in 2019) identified within subplots at the second sampling time (June 2019) ‘n_live_V3_c1’ – total number of live seedlings in the first post-fire cohort (germinated in 2018) identified within subplots at the third sampling time (Aug/Sept 2019) ‘n_live_V3_c2’ – total number of live seedlings in the second post-fire cohort (germinated in 2019) identified within subplots at the third sampling time (Aug/Sept 2019) ‘n_live_V4_c1’ – total number of live seedlings in the first post-fire cohort (germinated in 2018) identified within subplots at the fourth sampling time (Aug/Sept 2020) ‘n_live_V4_c1’ – total number of live seedlings in the second post-fire cohort (germinated in 2019) identified within subplots at the fourth sampling time (Aug/Sept 2020) ‘germ_2019_tot_c2’ – total number of seedlings that germinated in the summer of 2019 (2) ClarkWolf_et_al_2022_OverstoryData.csv – This includes raw overstory tree data for each plot. ‘Plot’ – unique plot identifier ‘Species’ – four-letter species code PSME = Pseudotsuga menziesii PIPO = Pinus ponderosa LAOC = Larix occidentalis PICO = Pinus contorta PIEN = Picea engelmannii ABLA = Abies lasiocarpa ABGR = Abies grandis TSME = Tsuga mertensiana THPL = Thuja plicata PIAL = Pinus albicaulis UNKN = unidentified ‘dens_Mature_Live’ = density of live mature trees (>1.37 m height), in # ha-1 ‘dens_Mature_Dead’ = density of dead mature trees (>1.37 m height), in # ha-1 ‘dens_Sapling_Live’ = density of live sapling trees (<1.37 m height), in # ha-1 ‘dens_Sapling_Dead’ = density of dead sapling trees (<1.37 m height), in # ha-1 ‘Live.BA’ = live basal area, average of three measurements per plot ‘Dead.BA = dead basal area, average of three measurements per plot (3) ClarkWolf_et_al_2022_SubplotData.csv – This includes raw ground cover measurements and other field data collected in subplots in all three sample years. ‘Plot’ – unique plot identifier ‘Subplot’ – subplot identifier ‘Postfire_year’ – sampling year ‘Date’ – sampling date ‘Cover.xx’ – estimated ground cover of different types ‘BG’ = bare ground and rock cover (%) ‘Wood’ = coarse woody debris cover (%) ‘Litter’ = litter and fine wood cover (%) ‘Moss’ = moss and lichen cover (%) ‘Grass’ = graminoid cover (%) ‘Forb’ = herbaceous cover (%) ‘Shrub’ = woody shrub cover (%) ‘Seedling’ = cover of seedlings (<10 cm height, %) Sapling’ = cover of juvenile trees <1.37 m height (%, not included in canopy cover) ‘Canopy.tot’ – total live and dead canopy cover (%) measured using a spherical densiometer ‘Canopy.Green’ – green canopy cover (%), not measured in year 1 ‘Canopy.Dead’– dead canopy cover (%), not measured in year 1 (4) ClarkWolf_et_al_2022_RecruitmentData.csv – This includes annual seedling counts of germination-year seedlings in each plot. ‘Plot’ – unique plot identifier ‘Postfire_year’ – sampling year ‘Spp’ – seedling species (includes “AllSpp” for all species combined), see above for codes ‘Germ’ – count of germination-gear seedlings within transect ‘TransectSize’ – transect area used for seedling count, in square meters (5) ClarkWolf_et_al_2022_RegenMonitoring.csv – This includes monitoring data for individual seedlings marked in subplots and tracked across sample years. ‘Seedling_ID’ – unique identifier for individual marked seedlings ‘Plot’ – unique plot identifier ‘Subplot’ – subplot number ‘Num_subplots’ – number of subplots used for seedling monitoring in that plot ‘ID.conf’ – binary, 1 if species identification is fully confident, 0 if ambiguous ‘Age.conf’ – binary, 1 if age estimate is confident, 0 if ambiguous ‘Postfire_year’ – sampling year ‘Spp’ – species, see above for species codes ‘Age’ – seedling age in years, where 1 is the germination year ‘Alive’ – binary, 1 if alive (any green needles present) at sampling time ‘Ht’ – Height in cm at sampling time ‘n_seedlings’ – number of seedlings of the same age and species found in the same subplot ‘Ht_y1_Avg’ – average height (cm) of equivalent seedlings in the same subplot in year 1 ‘Ht_y2_Avg’ – average height (cm) of equivalent seedlings in the same subplot in year 2 ‘Ht_y3_Avg’ – average height (cm) of equivalent seedlings in the same subplot in year 3 (6) ClarkWolf_et_al_2022_SoilData.csv – This includes all soil measurements for each plot. ‘Plot’ – unique plot identifier ‘soil_NH4.N.day’ – plot-average resin-sorbed ammonium in µg-N day-1 ‘soil_NO3.N.day’ – plot-average resin-sorbed nitrate in µg-N day-1 ‘soil_ph’ – soil pH ‘soil_M_2018_NH4’ – mineral soil ammonium concentration in µg-N g soil-1 in 2018 (year 1) ‘soil_M_2018_NO3’ – mineral soil nitrate concentration in µg-N g soil-1 in 2018 (year 1) ‘soil_M_2019_NH4’ – mineral soil ammonium concentration in µg-N g soil-1 in 2019 (year 2) ‘soil_M_2019_NO3’ – mineral soil nitrate concentration in µg-N g soil-1 in 2019 (year 2) ‘soil_O_2018_NH4’ – organic soil ammonium concentration in µg-N g soil-1 in 2018 (year 1) ‘soil_O_2018_NO3’ – organic soil nitrate concentration in µg-N g soil-1 in 2018 (year 1) ‘soil_O_2019_NH4’ – organic soil ammonium concentration in µg-N g soil-1 in 2019 (year 2) ‘soil_O_2019_NO3’ – organic soil nitrate concentration in µg-N g soil-1 in 2019 (year 2) ‘soil_M_perc_C’ – mineral soil carbon content (% by mass) ‘soil_M_perc_N’ – mineral soil total nitrogen content (% by mass) ‘soil_ug.N.day’ – plot-average resin-sorbed total inorganic nitrogen in µg-N day-1 (7) ClarkWolf_et_al_2022_Microclimate.csv – This includes modeled and raw daily microclimate data. ‘Plot’ – unique plot identifier ‘Date’ – date in M/D/YYYY ‘Year’ – calendar year ‘Month’ – month ‘Day’ – day ‘fitted_Tmax’ – modeled daily maximum microclimate temperature (°C), predicted based on statistical microclimate models ‘fitted_Vmax’ – modeled daily maximum microclimate vapor pressure deficit (VPD, kPa), predicted based on statistical microclimate models ‘fitted_Vmean’ – modeled daily mean microclimate VPD (kPa), predicted based on statistical microclimate models ‘Meas_Tmin’ – measured daily minimum temperature (°C) in a subset of sites ‘Meas_Vmin’ – measured daily minimum VPD (kPa) in a subset of sites ‘Meas_Tavg’ – measured daily mean temperature (°C) in a subset of sites ‘Meas_Vavg’ – measured daily mean VPD (kPa) in a subset of sites ‘Meas_Tmax’ – measured daily maximum temperature (°C) in a subset of sites ‘Meas_Vmax’ – measured daily maximum VPD (kPa) in a subset of sites (8) ClarkWolf_et_al_2022_gridMET.csv – This includes daily maximum temperature estimates derived from GridMet (Abatzoglou 2013) for all plots. ‘Plot’ – unique plot identifier ‘Date’ – date (m/d/Y) ‘Tmax.gm’ – daily maximum temperature estimate from GridMet ‘vpd.gm’ – daily average VPD estimate from GridMet (9) Clark-Wolf_et_al_2022_code.R – This R script contains code to recreate the main text figures in the manuscript. (10) Clark-Wolf_et_al_2022_supplemental.R – This R script contains additional code to recreate supplemental figures.