You sound like a R user, if so, every package of R comes with a pdf file associated with it. For example for the R package "sp" one just need to look for the document "sp.pdf" which you can get through google or "R-seek" site. If you still cannot get what you want, contact the writer(s) of the package their address or e-mail is usually obtainable from the help "pdf" document (i.e. "sp.pdf" for "sp"). By reading blogs for R groups too you may also get what you want.     

Many thanks for your thoughtful response Abayomi. I have looked at many forums/blogs and in the manual, but could not find an answer to my question. It seems that it is not possible with the fe.slope function to plot non-linearity. However, I did find out in the meanwhile that with the type = "eff" function it is possible, even for non-linearity modeled with splines, so that is what I ended up going for!

If you want to plot the "marginal effects" of the polynomial term (not just the estimates), you can use either the ggeffects-package (https://cran.r-project.org/package=ggeffects), which comes with a vignette that describes how to plot splines and polynomial terms (https://cran.r-project.org/web/packages/ggeffects/vignettes/marginaleffects.html).

Or you use the (latest) version of sjPlot and use the function plot_model(), which now replaces the former sjp.lmer(), sjp.glmer() etc. There you can define the plot-type, e.g. type = "pred" and then specify your poly-term in terms = "x1", so it would look like:

plot_model(model, type = "pred", terms = "x1")

The sjPlot-package simply wraps the ggeffects-package for marginal-effects plots.