README.Rmd

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output: 
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# eee2eye <img src="man/figures/eee2eye_logo.png" width="120" align="right"/>

## Calculating E:I Values from δ^18^O-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

```{r, eval = FALSE}
remotes::install_github("paukes/eee2eye")
```

## Example E:I Calculation

Load the package

```{r}
library(eee2eye)
```

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

```{r}
# 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:

```{r}
ei_input <- eee2eye(ei_input, 'dL_permille', -20.7, 'dP_permille', 14.3, 0.68, 0.7)
```

See the [vignette](https://github.com/paukes/eee2eye/blob/master/man/ei_calc/EI-Calculations.pdf) for more information.

## Example WRT Calculation

```{r}
# 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:

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