DOI: 10.5061/dryad.qv9s4mwn9
title: Leaf-level resistance to frost, drought and heat covaries across European temperate tree seedlings

description: Most trees die as seedlings, with harsh environmental conditions, such as
 early-spring frosts and summer heat waves, being important drivers of
 early mortality. However, it remains unclear whether tolerance to
 different environmental extremes (e.g. frost vs. heat) trades-off, or
 covaries synergistically and how stress tolerances relate to growth rates
 and life history strategies. Given the likely role of extreme
 environmental conditions as environmental filters, the ability to tolerate
 different stressors at the seedling stage could shape the occurrence and
 composition of present and future forests. We explored the relationships
 between different leaf-level stress tolerances, functional traits and
 geographic distributions across 22 species of temperate European tree
 seedlings. We measured indicators of tolerance to frost, drought and heat
 and related these values to growth rates and to important functional
 traits (e.g., leaf mass per area, stem specific density). Finally, we
 explored the links between measured seedling stress tolerances and
 climatic niche limits inferred from adult trees’ distributions. We found
 that seedlings of most species were either moderately tolerant to all
 three stressors, or susceptible to all of them. Moreover, higher stress
 tolerances were associated with traits describing slower growth and lower
 competitive ability. However, seedling tolerances to climatic factors were
 unrelated to the environmental limits of their adult geographic
 distributions. Synthesis. Our results suggest that temperate tree
 seedlings might not experience trade-offs when facing an increase in
 multiple extreme climate stressors, but may experience trade-offs related
 to growth rate and competitive ability in the establishment phase. The
 lack of correlation between leaf-level stress tolerances and the
 environmental limits of adult geographic distributions suggests that
 predicting species’ current or future geographic distributions in Europe
 will require a more nuanced understanding of how climatic tolerances at
 juvenile and adult stages influence range limits. A better understanding
 of the interaction between survival in extreme climate, leaf-level stress
 tolerances of seedlings, and the factors driving species distributions is
 needed to understand future forest responses to climate change.
description: # Leaf-level resistance to frost, drought and heat covaries across
 European temperate tree seedlings
 This is metadata for the
 dataset linked to the following publication: Visakorpi K., Manzanedo R.,
 Görlich A. S., Schiendorfer K., Altermatt Bieger A., Gates E. and Hille
 Ris Lambers J. Leaf-level resistance to frost, drought and heat covaries
 across European temperate tree seedlings. Journal of Ecology, 2023. The
 dataset consists of seven .csv files which contain the data, and one .R
 file which contains the R code to reproduce the analyses and figures. In
 all datafiles, species are identified with code of three first letters of
 genus name + three first letters of species name. The full species names
 are: Abialb = Abies alba Acecam = Acer campestre Acepla = Acer platanoides
 Acepse = Acer pseudoplatanus Alnglu = Alnus glutinosa Alninc = Alnus
 incana Betpen = Betula pendula Carbet = Carpinus betulus Fagsyl = Fagys
 sylvatica Lardec = Larix decidua Picabi = Picea abies Pincem = Pinus
 cembra Pinmug = Pinus mugo Pinnig = Pinus nigra Pinsyl = Pinus sylvestris
 Pruavi = Prunus avium Quepet = Quercus petrea Querob = Quercus robur
 Sorauc = Sorbus aucuparia Sortor = Sorbus torminalis Tilcor = Tilia
 cordata Ulmgla = Ulmus glabra Explanations of the specific datafiles are
 below: **##Visakorpietal2023_heat_tolerance.csv** This datafile contains
 the species-specific heat tolerance parameters and can be used to
 reproduce the analyses in the manuscript. The columns are as follows:
 \#Species = see above for the species full names \#Tcrit.lci = lower 95%
 confidence interval for the parameter Tcrit \#Tcrit.mn = mean Tcrit
 \#Tcrit.uci = upper 95% confidence interval for the parameter Tcrit
 \#T50.lci = lower 95% confidence interval for the parameter T50 \#T50.mn =
 mean T50 \#T50.uci = upper 95% confidence interval for the parameter T50
 \#T95.lci = lower 95% confidence interval for the parameter T95 \#T95.mn =
 mean T95 \#T95.uci = upper 95% confidence interval for the parameter T95
 \#n = sample size (seedlings per species)
 **##Visakorpietal2023_frost_tolerance.csv** This datafile contains the
 species-specific frost tolerance values and can be used to reproduce the
 analyses in the manuscript. The columns are as follows: \#Species = see
 above for the species full names \#Replicate = idenitifies a replicate
 pair of seedlings (i.e. frost + control) \#Frost.treatment = identifies
 whether the treated seedling exprienced -4C or -7C frost
 \#Control.before.boiling = electrolyte leakeage in the control sample
 before boiling \#Frost.before.boiling = electrolyte leakeage in the
 treatment sample after experiencing frost, before boiling
 \#Control.after.boiling = conductivity in the control sample after boiling
 \#Frost.after.boiling = conductivity in the treatment sample after
 experiencing frost, after boiling \#PEL.control = percentage of damaged
 cells in the control sample (i.e. conductivity before boiling /
 conductivity after boiling) \#PEL.Frost = percentage of damaged cells in
 the frost-treated samples (i.e. i.e. conductivity before boiling /
 conductivity after boiling) \#PELeff = difference between PEL.Frost -
 PEL.control \#FReff100 = the estimated frost tolerance, as 100-PELeff
 (with 100% set as the max value) \#AgeEstW = age of the seedling estimated
 in weeks \#MeasuringDate = date of the electrolyte leakege measurements
 (DD.MM.YYYY) **##Visakorpietal2023_tlp.csv** This datafile contains the
 species-specific drought tolerance values (as turgor loss point at
 wilting) and can be used to reproduce the analyses in the manuscript. The
 columns are as follows: \#Species = see above for the species full names
 \#Replicate = identifies each individual replicate \#Extraction_date =
 date when sap extraction was carried out (DD.MM.YYYY) \#Measuring_date =
 date when tlp measurements were carried out \#Temperature = temperature
 (in Celsius) during the measurements \#Age_days = age of the seedling in
 days at the time of the sap extraction \#Tlp = turgor loss point at
 wilting, as MPa **##Visakorpietal2023_traits.csv** This datafile contains
 the species-specific functional trait values and can be used to reproduce
 the analyses in the manuscript. The columns are as follows: \#Species =
 see above for the species full names \#Replicate = identifies replicate
 per species \#Harvest_date = date when the seedling was harvested for
 biomass (DD.MM.YYYY) \#Leaf_fresh_weight_g = weigth of the harvested leaf
 when fresh, g \#Diameter_base_mm = diameter of the stem at the base, mm
 \#Diameter_top_mm = diameter at the top of the stem, mm \#Stem_height_cm =
 height of the stem from base to the top, cm \#Leaf_dry_weight_g = weight
 of the harvested leaf after drying (Xh in XC), g
 \#Rest_of_leaves_dry_weight_g = Combined weight of all the other leaves of
 the seedling \#Stem_dry_weight_g = weight of the stem after drying (Xh in
 XC), g \#Bg_dry_weight_g =weight of the root system after drying (Xh in
 XC), g \#Leaf_area_lma = area of the leaf harvested and weighted
 individually to calculate LMA, cm2 \#Rest_of_leaves_area_cm2 = area of all
 the other leaves per seedling combined, cm2 \#Biomass_type = Categorical,
 whether seedling was harvested in June-July ("summer) or September
 ("autumn) **##Visakorpietal2023_rawdata_heat_response.csv** This
 datafile contains the raw chlorophyll fluorescence measurements taken from
 leaf discs to estimate heat tolerance parameters. The species-specific
 heat tolerance metrics estimated from this raw data can be found in the
 datafile "Visakorpietal2023_heat_tolerance.csv" The columns are
 as follows: \#ID = unique identifier for each row \#Heat_treatment =
 temperature of the water bath in which the leaf discs were treated,
 Celsius \#Replicate = identifies replicate per species \#Species = see
 above for the species full names \#Date = date of the measurement,
 DD.MM.YYYY \#Time = time of the measurement, as decimal Columns
 thereafter: point measurement values to create the trace plots
 **##Visakorpietal2023_rawdata_heat_recovery.csv** This datafile contains
 the raw chlorophyll fluorescence measurements taken from whole leaves to
 estimate whether leaves can recover from heat stress. These data can be
 used to reproduce the analyses in the Supplementary information of the
 manuscript. The columns are as follows: \#ID = unique identifier for each
 row \#LeafID = identifies the leaf per seedling \#Species = see above for
 the species full names \#Time_after_treatment = categorica variable that
 separates the different measurement times after the heat treatment was
 carried out. "Before" refers to the measurements taken before
 the heat treatment. \#Date = date of the measurement, DD.MM.YYYY \#Time =
 time of the measurement, as decimal Columns thereafter: point measurement
 values to create the trace plots
 **##Visakorpietal2023_rawdata_whole_seedlings_heat.csv** This datafile
 contains the raw chlorophyll fluorescence measurements taken from whole
 leaves to estimate whether whole seedlings react to heat stress similarly
 than leaf discs. These data can be used to reproduce the analyses in the
 Supplementary information of the manuscript. The columns are as follows:
 \#ID = unique identifier for each row \#LeafID = identifies the leaf per
 seedling \#Species = see above for the species full names \#Replicate =
 identifies replicate per species \#Time_after_treatment = categorica
 variable that separates the different measurement times after the heat
 treatment was carried out. "Before" refers to the measurements
 taken before the heat treatment. "24h after second" refers to
 measurements taken 24h of the second heat treatment. \#Watering_level =
 whether the seedking was well watered before the treatment, or let to dry
 our for couple of days. \#Date = date of the measurement, DD.MM.YYYY
 \#Time = time of the measurement, as decimal Columns thereafter: point
 measurement values to create the trace plots ##