Sure, a 1D solution can be fine. Most ecological data sets are complex
enough that multiple dimensions are helpful, but some datasets simply
have only one dominant gradient in the species data.
On the other hand, 1D solutions are common when there is a problem. For
example, a single, very strong outlier will be represented by a 1D
solution. Or consider a data set where there is one species with
overwhelming abundance compared to the other species. That single species
dominates the signal in the distance matrix, so that all that NMS needs
to do to get low stress is to represent that one species. But if your 1D
pattern is well distributed across species and sample units, it should be
ok.
As for overlays, the envelope curves are a good way to go, both for
species and environmental variables. These curves are made by
nonparametric regression, using a kernel smoother, so they don't assume a
straight-line response. The "envelope" comes from being able to
fit the curve to the upper side of the point cloud so that the line
includes most of the points rather than bisecting it. Gaps in the curves
are places where you have insufficient data to estimate the curve, or
where the envelope extends off the top of the graph panel. If you have
the latter problem, try changing the standard deviation parameter for the
envelope function to zero, so that the line goes through the central
tendency of the points.
I'm not sure what is happening, when you say you have to overlay a
categorical variable, nor do understand what you wrote about the species
names outside the graph.
Note that for 1D graphs there are several basic options on how they are
displayed. See under the "Axis" menu: jittered/not, rank vs.
not, Here is an example that is not jittered, not on rank order, and
"1 only horizontal" selected.

Hope this helps.
Bruce McCune