eee2eye

Calculating E:I Values from δ¹⁸O-H~2~O (‰)

Please see ‘EI-Calculations.pdf’ in the ‘man/ei_calcs’ folder for a step-by-step description of the Isotope Mass Balance used to calculate E:I.

Briefly, this function calculates E:I ratios, based on δ18O-H~2~O data. Environmental conditions (i.e. evaporation rate, humidity, temperatures, etc.) are set for the sub-arctic around Yellowknife, NT.

The function is based on a table with the following input parameters per sample:

• dL (‰) = -11.77, steady-state lake isotope value (measured value from field)
• dI (‰) = -20.7, source water, likely precipitation (value from Gibson 2001 and GNIP 1999)
• dP (‰) = -23, average value during evaporation season (signal of rain)
• temp (C) = 14.3, average temp. on lake (from Gibson & Reid, 2010)
• humid (dec) = 0.68, relative humidity (from Gibson & Reid, 2010)
• k = 0.7, estimated for our area (see ‘Note’ at bottom to calculate an approximate value)

Installation

remotes::install_github("paukes/eee2eye")

Example E:I Calculation

Load the package

library(eee2eye)

Add E:I ratios to the data.frame of field data:

# create example database
ei_input <- data.frame(dL_permille = c(-11.77, -15.67, -18.23),
                       dI_permille = c(-20.7, -18.2, -20.2),
                       dP_permille = c(-23, -28, -32), 
                       temp_C = c(14.3, 12.1, 8.9), 
                       h_dec = c(0.68, 0.71, 0.58), 
                       k = c(0.7, 0.72, 0.65))

# add calculated E:I values
ei_input <- eee2eye(ei_input, 'dL_permille', 'dI_permille', 'dP_permille', 'temp_C', 'h_dec', 'k')

Add E:I ratios to a data.frame of field data when not all input values are known or estimated for each field site so common values can be specified:

ei_input <- eee2eye(ei_input, 'dL_permille', -20.7, 'dP_permille', 14.3, 0.68, 0.7)

See the vignette for more information.

Example WRT Calculation

# create example database
ei_input <- data.frame(E.I = c(0.2042, 0.3138, 0.1838),
                      e_myr = c(0.3965, 0.3965, 0.3965),
                      SA_m2 = c(315900, 300825, 589950),
                      V_m3 = c(2466000, 3004064, 5712829))

# add calculated WRT values
ei_input <- eee2eye_WRT(ei_input, 'E.I', 'e_myr', 'SA_m2', 'V_m3')

A Note About the Seasonality Value (k):

k is a very difficult parameter to quantify in that we don’t know much about it. For this reason we created a small function that you could approximate a k value based on the decimal latitude of your sampling site:

k_season <- function(x) {
  k <- (((90 - x) / 90 ) * 0.5) + 0.5
  return(k)
}