10.5061/DRYAD.7VT36
Young, Derek J. N.
University of California, Davis
Stevens, Jens T.
University of California, Davis
Earles, J. Mason
Yale University
Moore, Jeffrey
United States Department of Agriculture
Ellis, Adam
United States Department of Agriculture
Jirka, Amy L.
United States Department of Agriculture
Latimer, Andrew M.
University of California, Davis
Data from: Long-term climate and competition explain forest mortality
patterns under extreme drought
Dryad
dataset
2017
climatic water deficit
tree
Holocene
National Science Foundation
https://ror.org/021nxhr62
2011124066
2017-11-14T00:00:00Z
2017-11-14T00:00:00Z
en
https://doi.org/10.1111/ele.12711
15405784 bytes
1
CC0 1.0 Universal (CC0 1.0) Public Domain Dedication
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_DataGridded 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_preparationCode for generating the data file (also
contained in this repository) by compiling and processing
publicly-available data sources.Young_et_al_AnalysisCode for performing
statistical analyses and producing plots based on the gridded mortality
data (also included in this repository).
USA
California