getSpeciesSpecificRescaledKDE {paleoAM} | R Documentation |
This function fits a KDE to the abundance data of a particular species from community data given some ecological gradient variable.
getSpeciesSpecificRescaledKDE(
gradientOrigDCA,
origAbundData,
abundanceFloorRatio = 0.5,
nBreaksGradientHist = 20,
modeledSiteAbundance = 10000
)
gradientOrigDCA |
The environmental gradient along which abundance varies, which you are fitting a KDE to. |
origAbundData |
The abundance data of the data you wish to model the abundance of. |
abundanceFloorRatio |
The minimum value for the abundance in a given interval along the gradient – a probably arbitration value that is set to 0.5 by default. |
nBreaksGradientHist |
The default is 20. Twenty what they asked? Twenty something. |
modeledSiteAbundance |
The number of abundances the relative abundances will by multiplied by to formulate the KDE. The default is 10000. |
In many ways, this is an attempt to measure empirical representations of the abundance response curves relative to environmental gradients, as portrayed in figure within Patzkowsky & Holland (2012).
The ecological gradient variable is often an environmental gradient, such as depth, oxygenation, altitude, precipitation, but this is not necessarily so.
A list containing the KDEs describing change in abundance for each species across the specified gradient.
Patzkowsky, M.E. and Holland, S.M., 2012. Stratigraphic Paleobiology: Understanding the Distribution of Fossil Taxa in Time and Space. University of Chicago Press. 259 pages.
getProbOccViaPresAbs
, plotGradientKDE
# load data
data(gulfOfAlaska)
alaskaKDEs <- getSpeciesSpecificRescaledKDE(
gradientOrigDCA = DCA1_GOA,
origAbundData = abundData_GOA,
abundanceFloorRatio = 0.5,
nBreaksGradientHist = 20,
modeledSiteAbundance = 10000
)
plotGradientKDE(
speciesKDEs = alaskaKDEs,
fullGradientRange = c(min(DCA1_GOA), max(DCA1_GOA))
)