Rising temperatures are amplifying drought-induced stress and mortality in forests globally. It remains uncertain, however, whether tree mortality across drought-stricken landscapes will be concentrated in particular climatic and competitive environments. We investigated the effects of long-term average climate [i.e. 35-year mean annual climatic water deficit (CWD)] and competition (i.e. tree basal area) on tree mortality patterns, using extensive aerial mortality surveys conducted throughout the forests of California during a 4-year statewide extreme drought lasting from 2012 to 2015. During this period, tree mortality increased by an order of magnitude, typically from tens to hundreds of dead trees per km2, rising dramatically during the fourth year of drought. Mortality rates increased independently with average CWD and with basal area, and they increased disproportionately in areas that were both dry and dense. These results can assist forest managers and policy-makers in identifying the most drought-vulnerable forests across broad geographic areas.
Young_et_al_Data
Gridded tree mortality data based on annual aerial surveys conducted from 2009 to 2015, along with environmental variables used to explain mortality patterns. The data file contains one row per unique 3.5 km grid cell & year combination. The data frame covers all grid cells within the state of California where at least one Aerial Detection Survey (ADS) flight was taken between 2009 and 2015, so each grid cell position has between 1 and 7 years of data (reflected as 1 to 7 rows in the data file per grid cell position). The main response variables are mort.bin (presence of any mortality) and mort.tph (number of dead trees/ha reported for the given grid cell & year combination). The main predictor variables are a set of climatic and forest structure variables at the same spatial scale, as described in the primary publication. This file is an Excel workbook with two worksheets: the first worksheet describes the variables, and the second worksheet contains the data. This data file was created by compiling and processing various publicly-available data sources into a standardized grid; the R code used for this is included in this repository as "Young_et_al_Data_preparation.R". The code used for statistical analyses and plots based on this data file ("Young_et_al_Analysis.R") is included as well.
Young_et_al_Data_preparation
Code for generating the data file (also contained in this repository) by compiling and processing publicly-available data sources.
Young_et_al_Analysis
Code for performing statistical analyses and producing plots based on the gridded mortality data (also included in this repository).
