Regional differences in leaf evolution facilitate photosynthesis following severe drought
Data files
Jul 12, 2024 version files 318.06 MB
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0.1_map.R
972 B
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0.5_bio15.R
1.73 KB
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1.0_clim.R
2.02 KB
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2.0_aci_fit.R
5.02 KB
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3.0_vcmax.R
4.18 KB
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4.0_Assim.R
7.62 KB
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5.0_gsw.R
8.69 KB
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6.0_mesophyll.R
3.94 KB
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6.5_thickness.R
5.10 KB
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7.0_stomtrich.R
15.20 KB
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aci_data_all.csv
32.26 KB
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all_stom_trich.csv
50.27 KB
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chl_fl_all.csv
34.37 KB
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climate.csv
214 B
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gsw_400.csv
40.74 KB
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gsw_50.csv
41.11 KB
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hbPopulations.csv
526 B
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Mesophyll_proportions_all.csv
34.96 KB
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RandomID.csv
8.60 KB
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README.md
17.23 KB
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sites.csv
655 B
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timeSer3.csv
317.75 MB
Abstract
Characterizing physiological and anatomical changes that underlie rapid evolution following climatic perturbation can broaden our understanding of how climate change is affecting biodiversity. It can also provide evidence of cryptic adaptation despite stasis at higher levels of biological organization.
Here we compared evolutionary changes in populations of Mimulus cardinalis from historically different climates in the north and south of the species’ range following an exceptional drought. We grew seeds produced from pre-drought ancestral plants alongside peak-drought descendants in a common greenhouse and exposed them to wet and dry conditions.
Prior to the drought, northern ancestral populations expressed traits contributing to drought escape, while southern ancestral populations expressed drought avoidance. Following the drought, both regions evolved to reduce water loss and maintain photosynthesis in dry treatments (drought avoidance), but via different anatomical alterations in stomata, trichomes, and palisade mesophyll. Additionally, southern populations lost the ability to take advantage of wet conditions.
These results reveal rapid evolution towards drought avoidance at an anatomical level following an exceptional drought, but suggest that differences in the mechanisms between regions incur different trade-offs. This sheds light on the importance of characterizing underlying mechanisms for downstream life-history and macromorphological traits.
https://doi.org/10.5061/dryad.x3ffbg7th
We use Mimulus cardinalis (scarlet monkeyflower) to ask the following questions:
- Are there differences in ancestral (2010-2011) leaf trait means and plasticity between regions with distinct historical climates?
- Are these differences maintained at the peak of the drought (2014-2015) or do populations from different historical climates evolve to drought stress differently?
- If so, via what type of leaf changes (those that promote escape or those that promote avoidance)?
We conducted this experiment on plants from six populations (three from north and three from the southern part of the range) with different climates. To obtain the differences in climate between the north and south, we first obtained 30-year-averages for mean annual precipitation and mean annual temperature from ClimateWNA. The precipitation seasonality was obtained from the biovars function from 'dismo' package in R. Seeds were collected from the field during 2010 and 2011, which was prior to a severe drought, and then were also collected from the same populations during the peak of the drought. All seeds were then refreshed in a common greenhouse. These refreshed seeds (maternal lines) were then planted in wet and dry treatments to conduct the experiment. Data from running A/Ci curves with the LI-6800 were cleaned to obtain the carboxylation rate, RuBP-regeneration rate, CO2 concentration when Vcmax switches to Jmax (Ci transition point), stomatal conductance, leaf temperature. The anatomical traits were gathered by making nail polish peels to count stomata and trichome densities and cross-sections for mesophyll layers and leaf thickness. All traits measured were run against a correlation and those with greater than 0.60 were removed as traits to continue to examine. This only excluded Jmax and the Ci transition point.
Description of the data and file structure
Data:
aci_data_all
vcmax = carboxylation rate (µmol per m-squared per second) values obtained from calculations in the
plantecophys R package from raw data from LICOR 6800 photosynthetic instrument.
Jmax = RuBP regeneration rate (µmol per m-squared per second) values obtained from calculations in the
plantecophys R package from raw data from LICOR 6800 photosynthetic instrument.
Rd = respiration rate (µmol per m-squared per second) values obtained from calculations in the
plantecophys R package from raw data from LICOR 6800 photosynthetic instrument.
Ci.transition = the point where vcmax and jmax flip (ppm)
Treatment = wet or dry treatment experienced by plants
Year = year of collection
Site = ID for the location where the seeds were collected
Rep = temporal replicate number
ID = Individual maternal line name
PrePeak = the time that the seeds were collected relative to the drought event
Region = north or south
all_stom_trich
Rep = temporal replicate number
Placement = ab for above leaf and be for below leaf
Stomata = total number of stomata counted from microscope images
Trichome = total number of trichomes counted from microscope images
Name = the site name
Site = the ID of the site location
Year = year of collection
ID = Individual maternal line name
Treatment = wet or dry treatment experienced by plants
PrePeak = the time that the seeds were collected relative to the drought event (pre- or peak- drought)
Region = north or south
Trich_mm = number of trichomes standardized for mm-squared
Stom_mm = number of stomata standardized for mm-squared
chl_fl_all
Treatment = wet and dry
Rep = temporal replicate number
Timeline = name of maternal plant
Fs = steady state fluorescence
Fm’ = maximal F, dark-adapted
PhiPS2 = 1-Fs/Fm’
ETR = electron transport rate in micromole per second (µmol/s)
A = assimilation rate (µmol per m-squared per second)
Year = year of collection
PrePeak = the time that the seeds were collected relative to the drought event (pre- or peak- drought)
Site = ID for the location where the seeds were collected
Fv.Fm. = 1-Fo(minimal F, dark adapted)/Fm’
Region = north or south
Climate
Region = north or south
Site = the site name
MAP = mean annual precipitation obtained from climateWNA
MAT = mean annual temperature obtained from climateWNA
CVI = coefficient of covariance for precipitation seasonality obtained from the biovars package using
climateNA in R
gsw_50
A = carbon assimilation rate value obtained from LICOR-6800 (µmol per m-squared per second)
Ca = ambient carbon dioxide concentration value obtained from LICOR-6800 (ppm)
Ci = intercellular carbon dioxide concentration value obtained from LICOR-6800 (ppm)
gsw = gas exchange value obtained from LICOR-6800 (µmol per m-squared per second)
Tleaf = leaf temperature value obtained from LICOR-6800 (celsius)
ID = Individual maternal line name
Treatment = wet or dry treatment experienced by plants
Rep = temporal replicate number
Year = year of collection
Site = ID for the location where the seeds were collected
PrePeak = the time that the seeds were collected relative to the drought event (pre- or peak- drought)
Region = north or south
gsw_400
A = carbon assimilation rate value obtained from LICOR-6800 (µmol per m-squared per second)
Ca = ambient carbon dioxide concentration value obtained from LICOR-6800 (ppm)
Ci = intercellular carbon dioxide concentration value obtained from LICOR-6800 (ppm)
gsw = gas exchange value obtained from LICOR-6800 (µmol per m-squared per second)
Tleaf = leaf temperature value obtained from LICOR-6800 (celsius)
ID = Individual maternal line name
Treatment = wet or dry treatment experienced by plants
Rep = temporal replicate number
Year = year of collection
Site = ID for the location where the seeds were collected
PrePeak = the time that the seeds were collected relative to the drought event (pre- or peak- drought)
Region = north or south
hbPopulations
Site = name of the location where populations are
Group = letter ID for each location
ID = site numerical ID
Lat = latitude
Lon = longitude
Mesophyll_proportions_all
Rep = temporal replicate number
Treatment = wet or dry treatment experienced by plants
ID = maternal seed line identification number
PrePeak = the time that the seeds were collected relative to the drought event (pre- or peak- drought)
Region = north or south
Site = ID for the location where the seeds were collected
Length 1 = measure (of mesophyll thickness total (including palisade and spongy) (µm)
Length 2 = 2nd measure of mesophyll thickness total (including palisade and spongy) (µm)
Length 3 = 3rd measure of mesophyll thickness total (including palisade and spongy) (µm)
Palisade 1 = measure of palisade thickness (µm)
Palisade 2 = 2nd measure of palisade thickness (µm)
Palisade 3 = 3rd measure of palisade thickness (µm)
Ratio 1 = proportion between total length and first palisade thickness
Ratio 2 = proportion between total length and second palisade thickness
Ratio 3 = proportion between total length and third palisade thickness
Average_prop = average ratio number
Thickness 1 = thickness of leaf including epidermal pavement cells (not trichomes) (µm)
Thickness 2 = 2nd thickness of leaf including epidermal pavement cells (not trichomes) (µm)
Thickness 3 = 3rd thickness of leaf including epidermal pavement cells (not trichomes) (µm)
Average_thick = average leaf thickness (µm)
Palisade_length = average palisade thickness (µm)
RandomID
Name = population site location
Site = numerical site name
Year = year of collection
Timelines = name of maternal plant
ID = new ID made for each maternal plant for randomization
Treatment = wet or dry treatments
Unique = combination of ‘Site’, ‘Timeline’, ‘Year’, and ‘Treatment’
PrePeak = collection year relative to drought timing
sites
ID = numerical name for each site
Name = population site name
Latitude = latitude
Longitude = longitude
Elevation = elevation
Region = South, Centre, and North
timeSer3
Year = the year the weather data is from climateNA
ID1 = name of site
ID2 = each site by year combination has 1000 weather points within a 62km radius
Latitude = latitude location of weather site near the ID1 population location
Longitude = longitude location of weather site near the ID1 population location
Elevation = elevation location of weather site near the ID1 population location
Tmax = maximum temperature (kelvin)
01-12 = month of the year
Tmin = minimum temperature (kelvin)
01-12 = month of the year
Tave = average temperature (kelvin)
01-12 = month of the year
PPT = precipitation amount (mm)
01-12 = amount of precipitation within each month
Columns BC-ET = parameters generated by climateNA that are not used
CMD = climate moisture deficit
01-12 = month of the year
RH = relative humidity
01-12 = month of the year
Bio1 = mean annual temperature (kelvin)
Bio2 = mean diurnal range (mean of max temp – min temp)
Bio3 = Isothermality (bio2/bio7)*(100)
Bio4 = temperature seasonality
Bio5 = Max temperature of warmest month
Bio6 = min temperature of coldest month
Bio7 = temperature annual range (bio5-bio6)
Bio8 = mean temperature of wettest quarter
Bio9 = mean temperature of driest quarter
Bio10 = mean temperature of warmest quarter
Bio11 = mean temperature of coldest quarter
Bio12 = total annual precipitation
Bio13 = precipitation of wettest month
Bio14 = precipitation of driest month
Bio15 = precipitation seasonality (coefficient of variation)
Bio16 = precipitation of wettest quarter
Bio17 = precipitation of driest quarter
Bio18 = precipitation of warmest quarter
Bio19 = Precipitation of coldest quarter
PopID = site number
Script file structure:
0.1_map.R = generate a map of Oregon and California with the six focal populations.
0.5_bio15.R = first grab precipitation seasonality. This is obtained from calculating the weather averages for precipitation and temperatures for each year across the 30 years of interest and using the* biovars* function from 'dismo'.
1.0_clim.R = Graphical representation of the 30 year climate averages for the two regions.
2.0_aci_fit.R = using the 'plantecophys' package to generate the ACi curve fitting and grab all variables of interest to create new dataframes of the ACi variables for each replicate. Merge all files together.
3.0_vcmax.R = run a mixed-effects model with a type 3 ANOVA using the 'lme4' package. The effect sizes are generated using* omega_squared* from the 'effectsize' spackage and following Field (2013). To compare the contrasts of interest, use 'emmeans' and specify the 12 contrasts wished to examine and posthoc with a Benjamini Hochberg analysis to reduce type-2 error. Generate a graphical representation of the residuals of the data using 'ggplot2'.
4.0_Assim.R = same as 3.0 but with assimilation data for max assimilation rate and net assimilation rate at 400ppm CO2 concentration.
5.0_gsw.R = same as 3.0 but with max stomatal conductance at 50 ppm CO2 concentration and net stomatal conductance at 400ppm CO2 concentration.
6.0_mesophyll.R = same as 3.0 but with average proportion of the palisade mesophyll layer relative to the spongy mesophyll layer.
6.5_thickness.R = same as 3.0 but with leaf thickness.
7.0_stomtrich.R = same as 3.0 but with stomatal and trichome densities. Each model is made for the above and below densities.
Sharing/Access information
Links to other publicly accessible locations of the data:
Data was derived from the following sources:
- ClimateNA, ClimateWNA, biovars, seed collections, demography data, LI-6800 portable photosynthetic instruments, microscopy
Code/Software
R version 4.0.4
Packages required in alphabetical order:
car
cowplot
dismo
dplyr
effectsize
emmeans
ggplot2
Hmisc
lme4
lmerTest
multtest
MuMIn
plantecophys
tidyverse
visreg
Climate data was collected from ClimateWNA. Seeds of Mimulus cardinalis (scarlet monkeyflower) were originally field collected prior to a severe drought (2010 and 2011) and during the peak drought (2014 and 2015) that occurred throughout the range . Following a refresher generation, the seeds were grown in a common garden experiment and exposed to either wet or dry treatments. Plants were monitored to maintain a similar drought across all plants. Leaves were sampled with a licor 6800 photosynthetic instrument for physiological traits. The leaves were collected and sectioned to examin leaf cell layers and epidermal peels were made using nail polish to examine leaf surface architecture. Data was directly input into a spreadsheet for anatomical traits. Data from Licor instrument was imported into Excel and cleaned for just the variables of interest using R software.
