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

[Tim O'Connor]

Thanks Gavin! It helps enormously.
Best,
Tim

> On Jan 19, 2017, at 6:39 PM, Gavin Simpson <ucfagls at gmail.com> wrote:
> 
> Hi Tim,
> 
> It sounds like you'd be best served by modelling the transect spatial
> position and using free permutations. Spatial eigenvectors could be
> used for example to model the transect position effect if you need a
> more complex effect than a simple linear or polynomial function.
> 
> HTH
> 
> G
> 
> On 13 January 2017 at 22:53, Tim O'Connor <tko2 at berkeley.edu> wrote:
>> 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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>> 
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> 
> 
> 
> -- 
> Gavin Simpson, PhD

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