Derive common shape parameters from the different model types. Calculate a set of parameters (see values below) from eHOF models.
Para(resp, ...)# S3 method for HOF
Para(resp, model, newdata = NULL, ...)
* species Name or abbreviat of the species.
* abund sum Abundance sum, i.e. sum of all response values divided by M.
* range Range of x values.
* model Model type, if not specified the result of [pick.model].
* para Model parameters (a to d).
* M Maximum response value, specified in the HOF function call.
* mini Location of the minimum, i.e. the gradient value, where the response is lowest, for model VI and VII the lowest response between the two optima.
* pess Lowest estimated response value.
* top Highest estimated response value(s).
* opt Location of the optimum, i.e. the gradient value, where the species response is highest. NA for model I and an optimum interval for model type III.
* expect Expectancy value, i.e. average x value under the model curve).
* max slope Highest slope, i.e. maximum of the first derivation of the curve.
* centralBorder Following Heegard, the central borders are calculated as the gradient values, where the response reaches "exp(-1/2)" of the top.
* outerBorder Following Heegard, the outer borders of the species niche are calculated as the gradient values, where the response reaches exp(-2) of the top.
* raw mean Average of measured x values.
response model results, see [HOF()]
further arguments passed to or from other methods, e.g. for [pick.model()]
response model type. If not specified, the output of [pick.model()] will be used
vector of gradient values to use
Florian Jansen
For models VI and VII Para will give you two expectancy values for the ranges left and right of the pessimum between the model optima. If you want to have the overall expectancy value, use:
gradient <- seq(min(Para(resp)$range), max(Para(resp)$range), length.out=10000)
weighted.mean(gradient, predict(resp, newdata=gradient))
Heegard, E. (2002) The outer border and central border for species-environmental relationships estimated by non-parametric generalised additive models. Ecological Modelling, 157, 131-139.
Damgaard, C. (2006) Modelling ecological presence-absence data along an environmental gradient: threshold levels of the environment. Environ Ecol Stat 13:229-236.