IsoriX can be used for building isoscapes using mixed models and inferring the geographic origin of organisms based on their isotopic signature. This package is essentially a simplified interface combining several other packages. It uses the package spaMM for fitting and predicting isoscapes, and for performing the assignment. IsoriX also heavily relies on the package rasterVis for plotting the maps using the powerful lattice visualization system.
We describe below, step-by-step, the general work-flow that aims at performing the construction of an isoscape and the assignment of organisms of unknown geographic origin(s) based on their isotopic signature. We advise you to also read the vignettes provided with this package, which essentially cover the same material in a more practical and detailed manner. You should also read the dedicated help pages of the functions you are using.
The statistical methods will not be detailed in this document but should soon be available as publications (we are currently working on it).
Fitting the isoscape model with isofit:
The function isofit fits a geostatistical model, which
approximates the relationship between the topographic features of a location
and its isotopic signature (see isofit for details). The model
fits observations of isotopic delta values at several geographic locations
(hereafter, called sources). One common type of sources used in
ecology is the delta values for deuterium in precipitation water collected at
weather stations, but one may also use measurements performed on sedentary
organisms. In either case, the accuracy of the isoscape (and thereby the
accuracy of assignments) increases with the number and spatial coverage of
the sources. The function isofit is designed to fit the model
on data aggregated per location across all measurements. If instead you want
to fit the model on measurements split per time intervals (e.g. per month),
within each location, you should use the alternative function
isomultifit.
Preparing the elevation raster with relevate:
Building isoscapes and assigning organisms to their origin requires an
adequate elevation raster, i.e. a matrix representing altitude data on a
spatial grid. The function relevate allows restricting the
extent of the raster to the area covered by isoscape data (in order to avoid
extrapolation) and to reduce the resolution of the original elevation raster
(in order to speed up computation in all following steps). Note that
aggregating the raster may lead to different results for the assignment,
because the elevation of raster cells changes depending on the aggregation
function, which in turn will affect model predictions.
We provide the function getelev to download an elevation raster
for the entire world at a resolution of one altitude per square-km, and other
rasters may be used. We have also stored a low resolution raster for Germany
in our package (see ElevRasterDE) for users to try things out,
but we do not encourage its use for real application.
Predicting the isoscape across the area covered by the elevation
raster with isoscape:
The function isoscape generates the isoscape: it uses the
fitted geostatistical model to predict the isotopic values for each raster
cell defined by the elevation raster. If the model has been fitted with
isomultifit, you should use the alternative function
isomultiscape to generate the isoscape.
Our package allows the production of fine-tuned isoscape figures (using the
function plot.isoscape). Alternatively, the isoscape rasters
can be exported as ascii raster and edited in any Geographic Information
System (GIS) software (see isoscape and the vignette
exportGIS for details).
Fitting the calibration model with calibfit:
In most cases, organisms are of another kind than the sources used to build
the isoscape (e.g. the isoscape is built on precipitation isotopic values
and organisms are not water drops, i.e. the deuterium values of their
keratin structures were modulated by their distinct physiology). In this
situation, one must use sedentary organisms to study the relationship
between the isotopic values in organisms and that of their environment. The
function calibfit fits a statistical model on such a
calibration dataset.
If the isoscape is directly built from isotopic values of organisms, there is no need to fit a calibration model.
Inferring spatial origins of organisms with isofind:
The function isofind tests for each location across the
isoscape if it presents a similar isotopic signature than the unknown origin
of a given individual(s). This assignment procedure considered the
uncertainty stemming from the model fits (geostatistical model and
calibration model). The function plot.isorix then draws such
assignment by plotting the most likely origin with the prediction region
around it. When several organisms are being assigned, both individual
assignments and a single assignment for the whole group can be performed.
Bowen, G. J., Wassenaar, L. I., Hobson, K. A. (2005). Global application of stable hydrogen and oxygen isotopes to wildlife forensics. Oecologia, 143(3): 337-348.
# NOT RUN {
### A simple workflow for IsoriX
### is provided in a vignette:
### vignette("Workflow", "IsoriX")
# }
Run the code above in your browser using DataLab