Determining an optimum and distribution range from species abundance vs environmental gradient data

Determining an optimum and distribution range from species abundance vs
environmental gradient data

Hi and thanks for any help re the below
This is a fairly complex question so I will attempt to ask it in a fairly
basic manor.
I have data on the abundance of 99 different species of estuarine
macroinvertebrate species and the sediment mud content (0 - 100 %) in
which each observation was obtained. I have a total of 1402 observations
for each species (i.e. a massive dataset).
Here is a subset of the raw data for one species to give you an idea of
the data I'm working with (if I had 10 reputation points i'd upload a plot
of real raw data:
Abundance:
10,14,10,3,3,3,3,4,5,5,0,0,0,0,0,0,0,0,0,0,0,0,0,6,6,6,0,0,0,0,12,0,0,0,34,0,0
Mud %:
0.9,4,2,10,13,14,6,5,5,7,22,27,34,37,47,58,54,70,54,80,90,65,56,7,8,34,67,54,32,1,57,45,49,4,78,65
The primary aim of my research is to determine an "optimum mud % range"
(e.g. 15 - 45 %) and "distribution mud % range" (e.g. 0 - 80 %) for each
of the 99 invertebrate species.
As you can see the abundance data for the above species contains a
significant number of zero values. Although this significantly skews any
sort of model that I run on the data (i.e. GLM, GAM), even if I model the
non-zero data only, the model for this particular species does not
represent what is seemingly a bell-shaped response.
So, my question is: what would be the best, most robust way to determine
an "optimum" and "distribution" mud range for each species, given that
responses vary significantly between species?