Leaf-level resistance to frost, drought and heat covaries across European temperate tree seedlings
Data files
Dec 27, 2023 version files 3.28 MB
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README.md
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Visakorpietal2023_frost_tolerance.csv
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Visakorpietal2023_heat_tolerance.csv
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Visakorpietal2023_rawdata_heat_recovery.csv
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Visakorpietal2023_rawdata_heat_response.csv
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Visakorpietal2023_rawdata_whole_seedlings_heat.csv
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Visakorpietal2023_tlp.csv
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Visakorpietal2023_traits.csv
Abstract
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.
README: Leaf-level resistance to frost, drought and heat covaries across European temperate tree seedlings
https://doi.org/10.5061/dryad.qv9s4mwn9
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
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