knitr::opts_chunk$set( collapse = TRUE, comment = "#>", fig.width = 6, fig.height = 2.25 )
library(isocalcR) library(tidyr) library(dplyr) library(ggplot2)
|isocalcR
Function | Description |
|-------------------- |----------------------------------------------------------------------------------------------------------------|
|d13C.to.D13C
| Calculate leaf carbon isotope discrimination (∆^13^C) given plant tissue δ^13^C signature (‰) |
|d13C.to.Ci
| Calculate leaf intercellular CO~2~ concentration (ppm) given plant tissue δ^13^C signature (‰) |
|d13C.to.CiCa
| Calculate the ratio of leaf intercellular CO~2~ to atmospheric CO~2~ concentration (ppm) given plant tissue δ^13^C signature (‰) |
|d13C.to.diffCaCi
| Calculate the difference between atmospheric CO~2~ concentration (ppm) and leaf intercellular CO~2~ concentration (ppm) given plant tissue δ^13^C signature (‰) |
|d13C.to.iWUE
| Calculate leaf intrinsic water use efficiency (µmol CO~2~ mol H~2~O^-1^) given plant tissue δ^13^C signature (‰) |
|custom.calc
| Calculate ∆^13^C, Ci, CiCa, diffCaCi, or iWUE given plant tissue δ^13^C signature (‰) |
Data for atmospheric CO~2~ and atmospheric δ^13^CO~2~ for the period 0 C.E. to 2021 C.E. can be loaded and viewed. Data are from Belmecheri and Lavergne (2020).
data(CO2data) #Load CO2data into your environment head(CO2data, 10) #View initial CO2data observations tail(CO2data, 10) #View most recent CO2data observations
Data for piru13C can loaded and viewed.
data(piru13C) head(piru13C)
Calculate leaf intrinsic water use efficiency from leaf δ^13^C:
library(isocalcR) #Load the package #Calculate iWUE from leaf organic material with a δ13C signature of -27 ‰ for the year 2015, #300 meters above sea level at 25°C. d13C.to.iWUE(d13C.plant = -27, year = 2015, elevation = 300, temp = 25) #Use custom.calc to calculate iWUE from the same leaf sample as above. custom.calc(d13C.plant = -27, d13C.atm = -8.44, outvar = "iWUE", Ca = 399.62, elevation = 300, temp = 25) #Calculate the ratio of leaf intercellular to atmospheric CO2 (Ci/Ca) using the simple #formulation for leaf and wood. Internally updates apparent fractionation by Rubisco, b, #according to Cernusak and Ubierna 2022. d13C.to.CiCa(d13C.plant = -27, year = 2015, elevation = 300, temp = 25, tissue = "leaf") d13C.to.CiCa(d13C.plant = -27, year = 2015, elevation = 300, temp = 25, tissue = "wood") #Calculate iWUE using the "simple", "photorespiration", and "mesophyll" formulations. d13C.to.iWUE(d13C.plant = -28, year = 2015, elevation = 300, temp = 15, method = "simple") d13C.to.iWUE(d13C.plant = -28, year = 2015, elevation = 300, temp = 15, method = "photorespiration") d13C.to.iWUE(d13C.plant = -28, year = 2015, elevation = 300, temp = 15, method = "mesophyll") #Calculate iWUE from tree ring (wholewood) d13C from Mathias and Thomas (2018) #using previously loaded piru13C data #First drop years where there are no data piru13C <- piru13C %>% drop_na() #Calculate iWUE for each case using 'mapply' piru13C$iWUE_simple <- mapply(d13C.to.iWUE, #Call the function d13C.plant = piru13C$wood.d13C, #Assign the plant d13C value year = piru13C$Year, #Assign the year to match atmospheric CO2 and atmospheric d13CO2 elevation = piru13C$Elevation_m, #Assign the elevation temp = piru13C$MGT_C, #Assign the temperature method = "simple", #Specify the method tissue = "wood") #Specify which tissue the sample is from piru13C$iWUE_photorespiration <- mapply(d13C.to.iWUE, #Call the function d13C.plant = piru13C$wood.d13C, #Assign the plant d13C value year = piru13C$Year, #Assign the year to match atmospheric CO2 and atmospheric d13CO2 elevation = piru13C$Elevation_m, #Specify elevation temp = piru13C$MGT_C, #Specify the temperature during tissue formation method = "photorespiration", #Specify the iWUE calculation formulation frac = piru13C$frac) #Specify any post-photosynthetic fractionations. In this case 2 permille to account for leaf to wood. piru13C$iWUE_mesophyll <- mapply(d13C.to.iWUE, #Call the function d13C.plant = piru13C$wood.d13C, #Assign the plant d13C value year = piru13C$Year, #Assign the year to match atmospheric CO2 and atmospheric d13CO2 elevation = piru13C$Elevation_m, #Specify elevation temp = piru13C$MGT_C, #Specify the temperature during tissue formation method = "mesophyll", #Specify the iWUE calculation formulation frac = piru13C$frac) #Specify any post-photosynthetic fractionations. In this case 2 permille to account for leaf to wood. #Create dataframe for visualizing differences in computed iWUE among the three formulations piru13C_long <- piru13C %>% select(Year, Site, iWUE_simple, iWUE_photorespiration, iWUE_mesophyll) %>% #Select only columns of interest rename(Simple = iWUE_simple, Photorespiration = iWUE_photorespiration, Mesophyll = iWUE_mesophyll) %>% pivot_longer(names_to = "Formulation", values_to = "iWUE", -c(Year, Site)) #Visually examine differences in iWUE based on the formulation used for each study location ggplot(data = piru13C_long, aes(x = Year, y = iWUE, color = Formulation)) + geom_point(alpha = 0.5) + geom_smooth(aes(group = Formulation), color = "gray30") + theme_classic() + facet_wrap(~Site) + ylab(expression("iWUE (µmol mol"^{-1}*")"))
Badeck, F.-W., Tcherkez, G., Nogués, S., Piel, C. & Ghashghaie, J. (2005). Post-photosynthetic fractionation of stable carbon isotopes between plant organs—a widespread phenomenon. Rapid Commun. Mass Spectrom., 19, 1381–1391.
Belmecheri, S. & Lavergne, A. (2020). Compiled records of atmospheric CO~2~ concentrations and stable carbon isotopes to reconstruct climate and derive plant ecophysiological indices from tree rings. Dendrochronologia, 63, 125748.
Bernacchi, C.J., Singsaas, E.L., Pimentel, C., Portis Jr, A.R. & Long, S.P. (2001). Improved temperature response functions for models of Rubisco-limited photosynthesis. Plant, Cell Environ., 24, 253–259.
Craig, H. (1953). The geochemistry of the stable carbon isotopes. Geochim. Cosmochim. Acta, 3, 53–92.
Cernusak, L. A. & Ubierna, N. Carbon Isotope Effects in Relation to CO~2~ Assimilation by Tree Canopies. in Stable Isotopes in Tree Rings: inferring physiological, climatic, and environmental responses 291–310 (2022).
Davies, J.A. & Allen, C.D. (1973). Equilibrium, Potential and Actual Evaporation from Cropped Surfaces in Southern Ontario. J. Appl. Meteorol., 12, 649–657.
Farquhar, G., O’Leary, M. & Berry, J. (1982). On the relationship between carbon isotope discrimination and the intercellular carbon dioxide concentration in leaves. Aust. J. Plant Physiol., 9, 121–137.
Frank, D.C., Poulter, B., Saurer, M., Esper, J., Huntingford, C., Helle, G., et al. (2015). Water-use efficiency and transpiration across European forests during the Anthropocene. Nat. Clim. Chang., 5, 579–583.
Gong, X. Y. et al. Overestimated gains in water‐use efficiency by global forests. Glob. Chang. Biol. 1–12 (2022)
Lavergne, A. et al. Global decadal variability of plant carbon isotope discrimination and its link to gross primary production. Glob. Chang. Biol. 28, 524–541 (2022).
Ma, W. T. et al. Accounting for mesophyll conductance substantially improves ^13^C-based estimates of intrinsic water-use efficiency. New Phytol. 229, 1326–1338 (2021).
Mathias, J. M. & Thomas, R. B. Disentangling the effects of acidic air pollution, atmospheric CO2 , and climate change on recent growth of red spruce trees in the Central Appalachian Mountains. Glob. Chang. Biol. 24, 3938–3953 (2018).
Tsilingiris, P.T. (2008). Thermophysical and transport properties of humid air at temperature range between 0 and 100°C. Energy Convers. Manag., 49, 1098–1110.
Ubierna, N. & Farquhar, G.D. (2014). Advances in measurements and models of photosynthetic carbon isotope discrimination in C~3~ plants. Plant. Cell Environ., 37, 1494–1498.
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