This repository contains data and code for the paper "Forest recovery following extreme drought in California, USA: natural patterns and effects of pre-drought management" by Young et al., published in Ecological Applications. The abstract of the paper is as follows.

Rising temperatures and more frequent and severe droughts are driving increases in tree mortality in forests around the globe. However, in many cases, the likely trajectories of forest recovery following drought-related mortality are poorly understood. In many fire-suppressed western U.S. forests, management is applied to reverse densification and restore natural forest structure and composition, but it is unclear how such management affects post-mortality recovery. We addressed these uncertainties by examining forest stands that experienced mortality during the severe drought of 2012-2016 in California, USA. We surveyed post-drought vegetation along a gradient of overstory mortality severity in paired treated (mechanically thinned or prescribed-burned) and untreated areas in the Sierra Nevada. Treatment substantially reduced tree density, particularly in smaller tree size classes, and these effects persisted through severe drought-related overstory mortality. However, even in treated areas with severe mortality (> 67% basal area mortality), the combined density of residual (surviving) trees (mean 44 trees ha^-1) and saplings (mean 189 saplings ha^-1) frequently (86% of plots) fell within or exceeded the natural range of variation (NRV) of tree density, suggesting little need for reforestation intervention to increase density. Residual tree densities in untreated high-mortality plots were significantly higher (mean 192 trees ha^-1 and 506 saplings ha^-1), and 96% of these plots met or exceeded the NRV. Treatment disproportionately removed shade-tolerant conifer species, while mortality in the drought event was concentrated in pines (Pinus ponderosa and P. lambertiana); as a consequence, the residual trees, saplings, and seedlings in treated areas, particularly those that had experienced moderate or high drought-related mortality, were more heavily dominated by broadleaf (“hardwood”) trees (particularly Quercus kelloggii and Q. chrysolepis). In contrast, residual trees and regeneration in untreated stands were heavily dominated by shade-tolerant conifer species (Abies concolor and Calocedrus decurrens), suggesting a need for future treatment. Because increased dominance of hardwoods brings benefits for plant and animal diversity and stand resilience, the ecological advantages of mechanical thinning and prescribed-fire treatments may, depending on the management perspective, extend even to stands that ultimately experience high drought-related mortality following treatment.

See the associated paper for a detailed description of data colleciton methods. Some raw plot data have been processed to a certain degree, following the methods described in the paper. For example, field-based counts of dead, down woody fuels have been converted to toal fuel density estimates.

Description of code and data files accompanying Young et al. (2019) "Forest recovery following extreme drought in California, USA: natural patterns and effects of pre-drought management" published in Ecological Applications

 

Analysis code

File: Young_etal_analysis.R

R code for fitting the Bayesian models and extracting 95% credible intervals for the effect of treatment on each response variable for each mortality severity level.

 

Plot-level biotic and abiotic data

File: Young_etal_plot_data.csv

Each row of this table provides values of various biotic and abiotic attributes of a given study plot. There is one row per study plot. The meaning of each column is as follows.

PlotName: The unique identifier of the plot.

Forest: The National Forest or National Park (or “BLM” for Bureau of Land Management land) within which the plot was located.

Treated: The status of the plot as treated (“Y”) or not treated (“N”).

MortClass: The identity of the plot category with respect to its drought-associated mortality severity. Options are “low” (0-33% basal area mortality), “moderate” (33-67% basal area mortality), and “high” (67-100% basal area mortality).

LiveOverstory: Ocularly estimated percent cover of the study plot, looking directly down from above, by biomass belonging to live trees.

ShrubCover: Ocularly estimated percent cover of the study plot, looking directly down from above, by biomass belonging to shrubs.

ShrubSp: The USDA PLANTS database code for the shrub species with greatest cover within the plot.

fuel_mass_total: The estimated total density (in kg / ha) of dead, down woody fuels, estimated as described in the Methods section of the manuscript this data file accompanies.

Remaining columns:

The remaining columns have three-part names in the format X_Y_Z (for example, "BA_Pines_L”). These columns present specific attributes of forest stand structure within each study plot. The meaning of the three components (X, Y, and Z) of the column names are as follows.

X: The structure metric reported. Options are “BA” (basal area in sq. m / ha), “Sapling” (the number of saplings in the plot), “Seedling” (the number of seedlings in the plot), “Stems” (the total number of tree stems in the plot, including seedlings, saplings, and trees), “TREES” (the number of adult trees—i.e., trees larger than saplings—within the plot), “TREESsmall” (the number of small adult trees—i.e., trees smaller than 30 cm DBH), “TREESmed” (the number of medium-sized adult trees—i.e., trees above 30 cm DBH but below 70 cm DBH), “TREESlarge” (the number of large-sized adult trees—i.e., trees larger than 70 cm DBH).

Y: The species group for which the structure metric is reported. Options are “Hdwds” for angiosperm (or “hardwood” or “broadleaf”) trees; “Pines” for Pinus spp., “ShadeTols” for Abies concolor and Calocedrus decurrens, and “Trees” for all tree species.

Z: The category of trees for which the structure metric is reported. Options are “DS” (all dead trees, including recent, drought-associated mortality and trees dead prior to the drought), “L” (trees that were alive at the time of survey), and “T” (trees that were alive at the time of survey plus recent, drought-associated mortality). Dead trees were considered to reflect “recent, drought-associated mortality” if they had some dead needles and fine branches (see the Methods section of the manuscript this data file accompanies).

 

Tree size distribution data

File: Young_etal_tree_size_distribution.csv

Each row of this table provides mean live tree density for a specfiic combination of time period (pre-drought or post-drought), treatment status (treated or untreated), mortality severity (low, moderate, or high), tree size class, and species group. The meaning of each column is as follows.

Period: Time period for which trees were considered “live”. Options are “Pre-drought” and “Post-drought.” Post-drought live trees reflect all trees that were alive at the time of survey. Pre-drought live trees reflect all trees that were alive at the time of survey plus all trees that were recently-dead at the time of survey (i.e., dead trees that still had some needles and fine branches intact).

Treated: Identity of plot category with respect to whether it was treated (“Y”) or not treated (“N”).

BAmort_class: The identity of the plot category with respect to its drought-associated mortality severity. Options are “low” (0-33% basal area mortality), “moderate” (33-67% basal area mortality), and “high” (67-100% basal area mortality).

DBH_cat: The diameter at breast height (DBH) category for which tree density is reported. Values (in cm) reflect the middle of a 10-cm-wide range of DBH values. For example, the value 35 reflects trees between 30 and 40 cm in DBH.

SpeciesCat: The species group for which tree density is reported. Options are “Hardwoods” (all angiosperm trees), “Pines” (all Pinus spp.), and “Shade tolerants” (Abies concolor and Calocedrus decurrens).

TPH: Tree density (in trees per hectare) for the specified plot category (e.g., untreated, low-mortality), time period, diameter category, and species group. Values reflect means across all plots representing the specified plot category.