Hi, I could use your help to analyze with R software my data investigating the effects of environmental parameters and parasite species on growth rates.
I measured the length and width of 3 species of plants every 2 weeks for 6 months. I did it in 2 different sites. In each site, I had 6 quadrats as a unite of replication, with 4 plants of each species per quadrat.
As environmental variables, I have: the temperature at each site for the whole period and the relative covers of two unwanted plant species (assessed every 2 weeks).
First of all, should I work on the raw data of length and width or on growth rates (mm/day) or on another variable combining those two apparied measures?
Next, how to test the effect of the time and of the 3 environmental variables (temperature, growth unwanted plant 1, growth unwanted plant 2)? I was thinking of doing GLMMs and maybe use a multi model inference procedure (like MuMin) to select the model taking into account the variables really having an effect?
Thanks a lot for your advice.
Regarding your 1st question: by reading your main question ("...the influence of environmental parameters on growth rates") I find that the response/dependent variable is growth rate; but you as the researcher should define and decide which one is or which ones are your variable/s of interest as dependent variable/s.
Regarding your next question: yes, using GLM in R you could ask software to calculate the effects of each of the independent variables you've listed as well as their possible interactions on the dependent variable/s (e.g., growth rate).
Then following book is highly recommended with respect to Design of Experiments (2 links):
1
https://www.researchgate.net/deref/https%3A%2F%2Fwww.amazon.com%2FDesign-Analysis-Experiments-Douglas-Montgomery%2Fdp%2F1119589061%2Fref%3Dsr_1_1%3Fkeywords%3DMontgomery%2BDesign%2Bof%2Bexperiments%26qid%3D1567108971%26s%3Dbooks%26sr%3D1-1
2
https://www.researchgate.net/deref/https%3A%2F%2Fb-ok.cc%2Fbook%2F3591248%2F4df2ac
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