Is there a way to add species to an ISOMAP plot in R?

Question

I am using the isomap-function from vegan package in R to analyse community data of epiphytic mosses and lichens. I started analysing the data using NMDS but due to the structure of the data ran into problems which is why I switched to ISOMAP which works perfectly well and returns very nice results. So far so good... However, the output of the function does not support plotting of species within the ISOMAP plot as species scores are not available. Anyway, I would really like to add species information to enhance the interpretability of the output.

Does anyone of you has a solution or hint to this problem? Is there a way to add species kind of post hoc to the plot as it can be done with environmental data?

I would greatly appreciate any help on this topic!

Thank you and best regards, Inga

Answer 1

No, there is no function to add species scores to isomap. It would look like this:

`sppscores<-.isomap` <-
    function(object, value)
{
    value <- scale(value, center = TRUE, scale = FALSE)
    v <- crossprod(value, object$points)
    attr(v, "data") <- deparse(substitute(value))
    object$species <- v
    object
}

Or alternatively:

`sppscores<-.isomap` <-
    function(object, value)
{
    wa <- vegan::wascores(object$points, value, expand = TRUE)
    attr(wa, "data") <- deparse(substitute(value))
    object$species <- wa
    object
}

If ord is your isomap result and comm are your community data, you can use these as:

sppscores(ord) <- comm # either alternative

I have no idea (yet) which of these alternatives is more correct. The first adds species scores as vectors of their linear increase, the second as their weighted averages in ordination space, but expanded so that we allow some species be more extreme than the site units where they occur.

These will add new element species to the result object ord. However, using these in vegan would need more coding, but you can extract the species scores with vegan::scores, but their scaling is based on the original scale of community data, and may be badly scaled with respect to points of site units, and working on this would require more work. However, you can plot them separately, or then multiply with a constant giving similar scaling as site unit scores.

sp <- scores(ord, display="species", choices=1:2)
plot(sp, type = "n", asp = 1) # does not allow plotting text
text(sp, labels = rownames(sp)) # so we must add text