Simulated calibration dataset
This dataset contains simulated hydrogen delta values for corresponding locations
based on an assumed linear relationship between the animal tissue value and the
hydrogen delta values in the environment.
The data can be used as an example to fit a calibration model using the
function calibfit
.
A dataframe with x observations on 6 variables:
[, 1] | site_ID | (Factor) | Identification of the sampling site |
[, 2] | long | (numeric) | Longitude coordinate [decimal degrees] |
[, 3] | lat | (numeric) | Latitude coordinate [decimal degrees] |
[, 4] | elev | (numeric) | Elevation asl [m] |
[, 5] | sample_ID | (Factor) | Identification of the sampled animal |
[, 6] | tissue.value | (numeric) | Hydrogen delta value of the tissue |
Users who wish to use their own dataset for calibration should create a
dataframe of similar structure than this one. The columns should possess
the same names as the ones described above. If the elevation is unknown at the
sampling sites, elevation information can be extracted from a high resolution elevation
raster using the function extract
. In this dataset, we
retrieved elevations from the Global Multi-resolution Terrain Elevation Data
2010.
calibfit
to fit a calibration model
head(CalibDataAlien) str(CalibDataAlien) ## The examples below will only be run if sufficient time is allowed ## You can change that by typing e.g. options_IsoriX(example_maxtime = XX) ## if you want to allow for examples taking up to ca. XX seconds to run ## (so don't write XX but put a number instead!) if(getOption_IsoriX("example_maxtime") > 30) { ## We prepare the precipitation data GNIPDataDEagg <- prepsources(data = GNIPDataDE) ## We fit the models for Germany GermanFit <- isofit(data = GNIPDataDEagg) ## We build the isoscape GermanScape <- isoscape(raster = ElevRasterDE, isofit = GermanFit) ## We create a simulated dataset with 50 site and 10 observations per site set.seed(2L) CalibDataAlien <- create_aliens(calib_fn = list(intercept = 3, slope = 0.5, resid_var = 5), isoscape = GermanScape, raster = ElevRasterDE, n_sites = 50, min_n_samples = 10, max_n_samples = 10) plot(sample_value ~ source_value, data = CalibDataAlien) abline(3, 0.5) CalibDataAlien$source_value <- NULL ## Uncomment the following to store the file as we did #save(CalibDataAlien, file = "CalibDataAlien.rda", compress = "xz") }
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