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Data from: A trait-based approach to assessing resistance and resilience to wildfire in two iconic North American conifers

Citation

Rodman, Kyle et al. (2020), Data from: A trait-based approach to assessing resistance and resilience to wildfire in two iconic North American conifers, Dryad, Dataset, https://doi.org/10.5061/dryad.cz8w9gj1b

Abstract

  1. Ongoing changes in fire activity have the potential to drive widespread shifts in Earth’s vegetation. Plant traits and vital rates can be indicators of the ability of individuals to survive fire (resistance) and populations to persist (resilience) following fire and provide a method to assess vulnerability to fire-driven vegetation shifts.
  2. In 15 study sites spanning climatic gradients in the southern Rocky Mountains, U.S.A., we quantified variation in key traits and vital rates of two co-occurring, widely-distributed conifers (Pinus ponderosa Douglas ex. P. Lawson & C. Lawson and Pseudotsuga menziesii (Mirb.) Franco). We used mixed models to explain inter- and intraspecific variation in tree growth, survival, bark thickness, and seed cone production, as a function of species, tree life stage (i.e., diameter, height, and age), average climate, local competition, and site conditions.
  3. P. ponderosa was predicted to survive low-severity fire at a 23% earlier age than P. menziesii. P. ponderosa had thicker bark and more rapid juvenile height growth, traits conferring greater fire resistance. In contrast, P. menziesii was predicted to produce seed cones at a 28% earlier age than P. ponderosa. For both species, larger individuals were more likely to survive fire and to produce cones. For P. ponderosa, cone production increased where average actual evapotranspiration (AET) was higher and local competition was lower. More frequent cone production on productive sites with higher AET is an important and underappreciated mechanism that may help to explain greater resilience to fire in these areas.
  4. Synthesis:  Our analyses indicated that many plant traits and vital rates related to fire differed between P. ponderosa and P. menziesii, with trade-offs between investment in traits that promote individual defence to fire and those that promote recolonization of disturbed sites. Future changes in fire activity will act as a filter throughout North American forests, with our findings providing insight into which individuals and populations of two iconic species are most vulnerable to future change and offering a framework for future inquiry in other forests facing an uncertain future.

Methods

Datasets included in the final archive file are stored within the following subfolders. Brief descriptions are included below, but more detailed descriptions are provided in .docx files within each subfolder.

1) "AET and CWD": This folder includes two c. 250m climate grids used in the study. These data were clipped to bounds of the Southern Rocky Mountains Ecoregion (EPA Level III Ecoregion #21). Each dataset was initially calculated at 4km using the water balance equations of Dobrowski et al. (2013) and spatially downscaled using GIDS interpolation (Flint and Flint 2012). For a further description of processing, see Rodman et al. (2020; Global Ecology and Biogeography). AET is total actual evapotranspiration (evaporation constrained by moisture availability) for the calendar year. CWD is total climatic water deficit (unmet evaporative demand of the atmosphere) for the calendar year. All units are in mm/year in an average year in the 1981-2010 period. These data were extracted to field plot locations and used in statistical models

2) "Fires_SpatialData": Contains a raster grid of Landsat-derived fire severity (Relative differenced Normalized Burn Ratio following Miller and Thode, 2007) clipped to the perimeters of the 15 studied wildfires, as well as a shape file of perimeters of each fire, obtained from the Monitoring Trends in Burn Severity program (Eidenshink et al. 2007)

3) "Post-Fire Seedling Data": Includes three individual .csv files that contain much of the field data describing juveniles in "burned plots" included in this study. Briefly, these data include post-fire seedling abundances of coniferous tree species throughout each of 15 studied fires, site-level variables such as fire severity (percent basal area mortality), ground cover, forest structure, as well as the age, height, and bark thickness of individual juveniles of Pinus ponderosa, Pseudotsuga menziesii, and a few other species. For additional information on field collection protocol and data processing, see Rodman et al. (2020, J. Ecology). 

4) "Resistance": Contains two individual .csv files with descriptions of trees that survived or died during each of the 15 fire events. Plot information within these data correspond to .csv files in "Post-Fire Seedling Data." For additional information on field collection protocol and data processing, see Rodman et al. (2020, J. Ecology)

5) "Ring Widths": Includes raw and processed ring width data from scans of increment cores, processed using WinDendro software. Data is primarily for Pinus ponderosa and is at 17 individual stands in southern Colorado and northern New Mexico, USA. For additional information on field collection protocol and data processing, see Rodman et al. (2020, J. Ecology)

6) "Trees and Cone Scars": Includes one .csv that describes tree-level variables related to tree size, cone production, bark thickness, and other traits related to wildfire. All surveyed trees in this .csv were in stands that were unburned or burned at low severity. For additional information on field collection protocol and data processing, see Rodman et al. (2020, J. Ecology)

Usage Notes

See "Rodman_J_Ecol_2020.html" in data archive for examples of use. See "README.txt" and metadata within the compressed archive files for usage notes. We encourage the user to contact the corresponding author (Kyle Rodman, Kyle.Rodman@colorado.edu) with any additional questions regarding data usage.

Funding

Australian Research Council, Award: DP170101288

Joint Fire Science Program, Award: 17-2-01-4

National Science Foundation, Award: DEB-1833529