I am designing an experiment to test density effects of interacting species. The real example is quite complicated to explain, so I'll give a simplified example - I want to test whether the density of herbivores effects plant growth.
I am planning on using regression to test for any effect of density on growth. I have enough plants for 12 treatments and I'm wondering how best to design the spread of density treatments. Would it be better to have evenly spaced treatments e.g. herbivore densities of 0, 10, 20, 30, 40, 50 etc. Or should I space them widely over a greater scale e.g. 0, 10, 20, 40, 80, 160 etc ?
This is the first experiment on this system, so I have no idea about the natural variation in productivity between plants, or how they will likely respond to the treatments, or if there is a threshold at which they start to respond.
Ideally, I would like this experiment to test an interesting hypothesis suitable for publication (ie. does growth decline as herbivore density increases?), but also provide information about the shape of the relationship that will help inform future experiments (ie. how many herbivores do we need to use to show an effect in subsequent studies?).
I wondered if there was guidance on the spread of explanatory variables in regression or experimental design? Or if it just comes down to judgement/guesswork.