I am conducting a research project on the vegetation composition of an abandoned mine site to determine the environmental factors that influence species abundance (cover) and composition.
Study Design: I have 10 sites, within each site 10 randomly placed 1x1m quadrats were sampled for plant species percent cover (abundance) along with a soil sample that was tested for heavy metals concentration(Pb, As, Cu, Zn), pH, NPK, and OM. Factors such as slope, aspect were also recorded.
Analysis: From species abundance data I created the response variables: total cover, exotic cover, native cover, and species richness. I would like to investigate if my environmental variables are influencing the response variables I described above. I have tried using
lm in R but my response variables are not normally distributed and therefore I believe violate the assumptions of linear modeling. I have also tried
glm but since my cover abundance data contains many 0's and is not bounded at 100%, as there can be more than 100% cover in a quadrat, I don't think any of the error distribution families of
glm can accommodate this.
So, I would appreciate any input on selecting an appropriate model for my response variables. If possible I would like to see the size of the effect or r2 rather than just a P value. Thank you very much for your time. If you would be interested in the data I could provide it.