DOI: 10.5061/dryad.sbcc2frds
title: Data from: Drought and heat-induced mortality of conifer trees is explained by leaf and growth legacies

description: An increased frequency and severity of droughts and heatwaves have
 resulted in increased tree mortality and forest dieback across the world
 but underlying mechanisms are poorly understood. We used a common garden
 experiment with 20 conifer tree species to quantify mortality after three
 consecutive hot, dry summers and tested whether mortality could be
 explained by putative underlying mechanisms, such as stem hydraulics and
 legacies affected by leaf lifespan and stem growth responses to previous
 droughts. Mortality varied from 0-79% across species and was,
 surprisingly, not affected by hydraulic traits. Mortality increased with
 the species’ leaf lifespan, probably because leaf damage caused crown
 dieback and contributed to carbon depletion and sensitivity to bark beetle
 damage. Mortality also increased with lower growth resilience, which may
 exacerbate the contribution of carbon depletion and bark beetle
 sensitivity to tree mortality. Our study highlights how ecological
 legacies at different time scales can explain tree mortality in response
 to hot, dry periods and climate change.
description: # Data from: Drought and heat-induced mortality of conifer trees is
 explained by leaf and growth legacies
 [https://doi.org/10.5061/dryad.sbcc2frds](https://doi.org/10.5061/dryad.sbcc2frds) This dataset contains resilience, mortality, and all functional trait data to produce all figures and tables in the published paper "Drought and heat-induced mortality of conifer trees is explained by leaf and growth legacies". ## Description of the data and file structure Species-specific data are provided. This dataset contains four Excel files named "data", "SPEI4", "dailyCWB" and "hist". * **data**: Fig 2, Fig S3, Fig S4, Fig S5, Fig S6, Fig S7, Fig S8, Fig S10, Table 2, Table S2, Table S3, * **SPIE4** (Fig S1): the monthly Standardized Precipitation Evapotranspiration Index from 1970 to 2020. * **dailyCWB** (Fig S2): annual development of the cumulative water balance visualised for 12 years with the Standardized Precipitation Evapotranspiration Index SPEI&lt;-1. * **hist** (Fig S9): relationships between the presence of bark beetle exit holes on tree stems (on x-axis: no, yes) for different species. #### For trait abbreviations in 'data' file, see below: * DBH: diameter at the breast height (cm) * Age: tree age (yrs) * DOY: day of year * BAI: basal area increment (cm^2/year) * Mortality: mortality rate * Resistance6, recovery6 and Resilience6: resilience indexes collected for 6 drought years preceding the 2018 drought year (from 1986 onwards), see Figure 2. * HSM: hydraulic safety margin (MPa) * TLP_P50: TLP minus P50 (MPa) * |P50|: the absolute value of xylem potential inducing 50% loss of hydraulic conductivity (MPa) * TLP: tugor loss point (MPa) * |Pmin|: absolute minimum water potential (MPa) * |Ppre|: absolute predawn water potential (MPa) * DPA: pit aperture diameter (µm) * WD: wood density (g cm-3) * LLS: leaf lifespan (yrs) * LTD: leaf tissue density (g cm-3) * LDMC: leaf dry matter content (g g-1) * SLA: specific leaf area (cm^2 g-2) * Resistance, Recovery and Resilience: resilience indexes collected for 8 drought years preceding the 2018 drought, thus adding the 1975-1976 and 1982-1983 droughts to the series from 1986 (see Figure 2c), see Figure S8. * Pmin_TLP: Pmin minus TLP (MPa) * 90MAT, 50MAT and 10MAT: 90%, 50% and 10% quantile of mean annual temperature (C°) * 90Tmax, 50Tmax, 10Tmax: 90%, 50% and 10% quantile of maximum monthly temperature (C°) * 90MAP, 50MAP, 10MAP: 90%, 50% and 10% quantile of mean annul precipitation (mm) * 90PRmin, 50PRmin, 10PRmin: 90%, 50% and 10% quantile of minimum monthly precipitation (mm) * 90PET, 50PET, 10PET,: 90% , 50% and 10% of quantile of potential evapotranspiration (mm) * 90PETmax, 50PETmax, 10PETmax: 90% , 50% and 10% of quantile of maximum monthly potential evapotranspiration (mm) The authors request that users of this data kindly cite their published paper (doi: 10.1126/sciadv.adl4800). You can contact the corresponding author at yanjun.song@2021@gmail.com.