Data and code for: Adaptive evolution of freezing tolerance in oaks is key to their dominance in North America
Data files
Oct 17, 2024 version files 137.80 KB
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Critical_temperature_for_MN-NY_dataset.csv
9.14 KB
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MN_NY_Index_of_injury_mean_se_climatic_variables.csv
7.46 KB
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README.md
8.82 KB
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RGR_cylinder_cold_all_data.csv
92.35 KB
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sp_means_bio6_min_temp_se.csv
6.29 KB
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Species_section_phenology.csv
2.02 KB
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Trait_data_RGR_bio6.csv
9.53 KB
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tree_MN_NY_spp
2.19 KB
Abstract
Freezing tolerance plays a pivotal role in shaping the distribution and diversification of organisms across diverse habitats and was likely crucial to the expansion and adaptive radiation of the American oaks. We investigated the dynamics of adaptation to climate and potential trade-offs between stem freezing tolerance and growth rate in 48 Quercus species from five genus sections grown under temperate and tropical conditions. Species from colder regions exhibit higher freezing tolerance, lower growth rates and higher acclimation potential compared to species from warmer climates, suggesting evolutionary adaptations to seasonal climate fluctuations. Deciduous species show marked variability in freezing tolerance across their broad climatic range while evergreen species, confined to warm climates, display low freezing tolerance. While annual growth rates are constrained in deciduous species, we found no direct trade-off between freezing tolerance and growth because deciduous species that evolved in warm latitudes lost freezing tolerance. Despite an evolutionary lag, freezing tolerance in Quercus species is closely aligned with its optimal state. The capacity to withstand cold and adapt to a wide range of thermal environments was likely critical to adaptive radiation and current dominance of the North American oaks. Data and code are provided here.
https://doi.org/10.5061/dryad.547d7wmhm
Description of the data and file structure
Files and variables
File: Critical_temperature_for_MN-NY_dataset.csv
Description: Mean and SD for critical freezing temperatures and climate variables for each species
Variables
- species: Latin binomial
- Dataset: plants grown in NY or MN greenhouses
- critical_temp_25: critical freezing temperature at which 25% of cells have lysed
- critical_temp_50: critical freezing temperature at which 50% of cells have lysed
- Section: Section or major lineage within the genus -> Cerris, Lobatae, Quercus, Virentes
- LP: Leaf phenology -> Evergreen or Deciduous
- min_min_temp: mean minimum temperature, averaged across the distribution for each species
- sd_min_temp: SD of the minimum temperature, across the distribution for each species
- se_min_temp: SE of the minimum temperature, across the distribution for each species
- mean_bio6c: bioclim variable 6, which is the mean minimum temperature of the coldest month, averaged across the distribution for each species
- sd_bio6c: SD of bioclim variable 6 across the distribution for each species
- se_bio6c: SE of bioclim variable 6 across the distribution for each species
File: Species_section_phenology.csv
Description: Phylogenetic section each species belongs to
Variables
- species: Latin binomial
- Section: Section or major lineage within the genus -> Cerris, Lobatae, Quercus, Virentes
- LP: Leaf phenology -> Evergreen or Deciduous
File: MN_NY_Index_of_injury_mean_se_climatic_variables.csv
Description: Mean, SD, and SE for the Index of injury after freezing for each species and the greenhouse location
Variables
- species: Latin binomial
- Location: plants grown in NY or MN greenhouses -> NY or MN
- IJ_mean: mean index of injury after freezing at -15 degrees C for each species
- log_IJ_mean: log (base 10) of the index of injury after freezing at -15 degrees C, calculated from the mean of each species
- IJ_sd: SD of the index of injury after freezing at -15 degrees C for each species
- IJ_se: SE of the index of injury after freezing at -15 degrees C for each species
- mean_min_temp: mean minimum temperature of the coldest month, averaged across the distribution for each species
- min_min_temp: minimum temperature, averaged across the distribution for each species
- log_min_min_temp: log (base 10) of the minimum temperature for each species
- sd_min_temp: SD of the minimum temperature, across the distribution for each species
- se_min_temp: SE of the minimum temperature, across the distribution for each species
- mean_bio6c: bioclim variable 6, which is the mean minimum temperature of the coldest month, averaged across the distribution for each species
- sd_bio6c: SD of bioclim variable 6 across the distribution for each species
- se_bio6c: SE of bioclim variable 6 across the distribution for each species
File: RGR_cylinder_cold_all_data.csv
Description: relative growth rate and other growth related variables for all species in tropical and temperate treatments
Variables
- species: specific epithet
- ID: Individual plant identification number or code
- zone: greenhouse room in which plants were grown – climatic regimes in zones were set to simulate tropical (zones 3,4,5) or temperate (zones 1,2,6) growth environments
- d0: stem basal diameter at time zero (start of growth; first measurement) in mm
- d1: stem basal diameter at time one (end of growing season; second measurement) in mm
- h0: stem height at time zero (start of growth; first measurement) in cm
- h1: stem height at time one (end of growing season; second measurement) in cm
- t0: time 0 (in units of days)
- t1: time 1 (in units of days)
- v0: calculated cylindrical plant volume at time 0 in units of cm^3
- v1: calculated cylindrical plant volume at time 1 in units of cm^3
- biom0: estimated dry plant biomass at time 0 in units of g
- biom1: estimated dry plant biomass at time 1 in units of g
- rgr_cyl: relative growth rate calculated based on the cylindrical volume of the plant in units of cm^3 per cm^3 per day
- rgr_biom: relative growth rate calculated based on the estimated biomass in units of g per g per day
- rgr_h: relative growth rate calculated based on height in units of cm per cm per day
- rgr_d: relative growth rate calculated based on stem basal diameter in units of mm per mm per day
- rgr_av: average of all of the relative growth rate calculations
File: tree_MN_NY_spp
Description: Phylogeny of the 48 oak species in the dataset
File: Trait_data_RGR_bio6.csv
Description: mean trait values, growth related traits, acclimation potential and climate variables
Missing data codes: NA
Variables
- Species: Latin binomial
- Section: Section or major lineage within the genus Cerris, Lobatae, Quercus, Virentes
- Leaf_P: leaf phenology
- Vess_Diam: average vessel diameter
- Wood_Density: stem specific density (g per cm^3)
- Habit: tree or shrub
- Region: Tropical, Temperate or Mediterranean
- critical_temp_25: critical freezing temperature at which 25% of cells have lysed
- critical_temp_50: critical freezing temperature at which 50% of cells have lysed
- IJ: index of injury when stems were frozen at -15 degrees C
- cold: index of injury when stems were frozen at -15 degrees C for plants grown in temperate conditionsindex of injury when stems were frozen at -15 degrees C for plants grown in temperate conditions
- warm: index of injury when stems were frozen at -15 degrees C for plants grown in tropical conditions
- mean_rgr_cold: relative growth rate for plants grown in temperate conditions
- sd_rgr_cold: SD of relative growth rate for plants grown in temperate conditions
- mean_rgr_warm: relative growth rate for plants grown in tropical conditions
- sd_rgr_warm: SD of relative growth rate for plants grown in tropical conditions
- bio6c: bioclim variable 6, which is the mean minimum temperature of the coldest month, averaged across the distribution for each species
- diff_RGR: difference between rgr in temperate and tropical conditions
- min_min_temp: minimum temperature averaged across the distribution for each species
- acclimation: cold acclimation capacity based on the difference in index of injury in temperate and tropical growth conditions
File: sp_means_bio6_min_temp_se.csv
Description: freezing vulnerability and mean minimum temperatures in source locations for each species
Variables
- species: Latin binomial
- cold: mean index of injury at -15 degrees C after growth in temperate treatment
- warm: mean index of injury at -15 degrees C after growth in tropical treatment
- cold_se: standard error of index of injury at -15 degrees C after growth in temperate treatment
- warm_sd: standard deviation of index of injury at -15 degrees C after growth in tropical treatment
- warm_se: standard error of index of injury at -15 degrees C after growth in tropical treatment
- mean_min_temp: mean minimum temperature in source location
- min_min_temp: minimum temperature in source location
- sd_min_temp: standard deviation of minimum temperature in source location
- se_min_temp: standard error of minimum temperature in source location
- mean_bio6c: mean minimum temperature of coldest month
- sd_bio6c: standard deviation of minimum temperature of coldest month
- se_bio6c: standard error of minimum temperature of coldest month
- diff_mean: difference in index of injury between seedlings of the same mother grown in temperate and tropical environments
- diff_sd: standard deviation of difference in index of injury between seedlings of the same mother grown in temperate and tropical environments
- diff_se: standard error of difference in index of injury between seedlings of the same mother grown in temperate and tropical environments
- Section: Section or major lineage within the genus Cerris, Lobatae, Quercus, Virentes
- LP: Leaf phenology, Evergreen or Deciduous
- diff: difference in mean index of injury in temperate and tropical treatment for each species
Code/software
R (R Core Team 2018)
Acclimation potential.R
Critical temperature MN and NY data.R
Extracting climatic variables.R
Index of injury - MN_NY - Phylo regression.R
RGR-Mixed Models.R
Slouch-evolutionary model.R
Access information
Other publicly accessible locations of the data:
- WorldClim database (http://www.worldclim.org/) for climatic variables
We examined 48 species of Quercus from 5 different sections: Cerris (3 species), Lobatae (19), Protobalanus (1), Quercus (26), and Virentes (3 species; Table S1). The species are characterized by different growth forms, leaf phenology (34 deciduous and 14 evergreen species), ecological niches, and distribution ranges. Acorns were collected from one to five populations within each of the 48 oak species in the fall of 2010 or 2011 to capture variation across the range of the species and to maximize the phylogenetic coverage of the oaks within North America. Acorns from the Cerris section were gathered from locations outside North America, as these species are not indigenous to the region. Seeds were collected from California, Florida, Illinois, Michigan, Minnesota, North Carolina, New York, Ohio, Utah, and Wyoming from trees occurring in natural areas within each population. The length and width of each acorn were measured, and the acorns were stored for several months at 4ºC at the University of Minnesota until synchronous planting (25 to 40 seedlings per species) in glasshouse facilities at the Franklinville Experimental Research Station in Franklinville, New York or at the University of Minnesota (UMN).
Seeds were germinated and grown in two replicated climate treatments in each of the two greenhouse locations for two years in (1) a tropical treatment, in which daytime temperature was maintained between 30 and 35ºC, and night-time temperature between 22º and 26ºC; and (2) a temperate treatment, in which winter growth temperatures (mid-November to March) reached a minimum night-time temperature of 4ºC with a minimum daytime temperature of 15ºC, simulating species’ range limits. Plants in the temperate treatment were acclimated to the winter temperature regime approximately 3 months prior to measurement. In New York, each climate regime was replicated in three independently controlled glasshouse rooms (for a total of six rooms) and in Minnesota, each climate regime was replicated in two independently controlled rooms (total of four). Summer photoperiods were left at ambient levels with a maximum of 15.4 hours in Minnesota and 15.16 in New York. The photoperiod was extended to 12 hours during the winter. These climate treatments were repeated every year for three subsequent years.
Three months after the start of the winter climate treatment, all individuals were monitored for maximum height (h; root collar to apex of tallest stem), the number of leaves (total leaves on all stems), and stem diameter (d; measured at the root collar). Allometric equations used to estimate the biomass for each species. Above-ground biomass was estimated using the maximum height, total number of leaves, and stem diameter. Acorn mass was estimated using the acorn volume. Absolute growth rate (AGR; g yr-1) was calculated as AGR = (Vfinal -Vinitial) ⁄ (Tfinal - Tinitial), and Relative growth rate (RGR; mm3 mm-3 yr-1) was calculated as RGR= [loge(Vfinal) - loge(Vinitial)] ⁄ (Tfinal - Tinitial). Where Vfinal and Vinitial were calculated as the volume of a cylinder: Vfinal/initial = (dfinal/initial/2)2 x P x hfinal/initial. Tinitial is the approximate date plants were measured in March 2012 and Tfinal is the date plants.
We used the most comprehensive phylogenetic tree for the genus Quercus and performed a comparative analysis using the ‘SLOUCH’ package in R. SLOUCH models traits as evolving under an Ornstein-Uhlenbeck (OU) model of evolution in a maximum likelihood framework. Traits are modeled as evolving toward a primary optimum, which is influenced by a continuous, randomly changing predictor variable, in our case, minimum temperature. Estimates of the phylogenetic signal or phylogenetic inertia are given by the phylogenetic half-life (t1/2) and are interpreted relative to the absolute time associated with the phylogeny. When t1/2 is close to 0, the trait is evolving under strong selection by the predictors included in the model, without any influence from the ancestral trait value, whereas increasing values of t1/2 reflect an increasing effect of the ancestral trait value on present-day trait values.
We used index of injury measured at -15oC as the response variable of the model, while minimum temperature of the coldest month in the native climate was treated as a predictor variable modeled as evolving according to a Wiener (Brownian motion) process. We compared models with and without the predictor variable to test the role of climatic niche in freezing tolerance evolution. For all statistical analyses, we used R v.3.4.2 with base packages R core Team (2018).