[R-sig-eco] accounting for linear sampling structure using PERMANOVA or dbRDA

[Tim O'Connor]

Hello everyone, 

I’m trying to assess the effect of a factor on community structure while controlling for confounded spatial effects.

I sampled herbivorous insect communities along transects spanning a contact zone between two host plants, A and B, with 6 sites per transect (e.g., start-A-A-A-B-B-B-end) and 10 plants per site. Each plant was censused for insects separately, so I began with 60 total communities per transect. The transects are basically linear, but sites are irregularly spaced. I would like to quantify the effect of plant type on insect community while controlling for possible environmental or spatial effects due to transect position. 

At the moment I attempt this with a PERMANOVA (or equivalently, dbRDA), permuting plant type among sites and finding the marginal effect of plant in a model that includes position.

ctrl <- how(complete = T, 
	within = Within(type = "none"), 
	plots = Plots(type = “free", strata = site))
perms <- shuffleSet(nobs(communities), control = ctrl)
adonis2(vegdist(communities) ~ position + plant, permutations = perms, by = “margin")

Although a linear permutation scheme seems most justified and would account for the adjacency of sites, there are only 5 such permutations for a transect of 6 sites (aside from the observed arrangement). Allowing free permutation of sites improves total permutations (up to 719) but no longer includes spatial information.

I have two questions. First, is this approach correct in principle? Does it seem overly or underly conservative? Second, are there other approaches I should consider, especially those that allow uneven observations among sites? The challenge with the method I describe is that my final data set includes different numbers of plants per site due to data cleaning. The constrained permutations require me to sacrifice at least 1/3 of my cleaned data to ensure the same number of observations per site.

Thanks for any suggestions.

Best,
Tim

-------------------
Tim O'Connor
PhD Student
Whiteman Laboratory
Integrative Biology
University of California, Berkeley
http://noahwhiteman.org/tim-oconnor.html


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