[R-sig-eco] using two distance metrices in formula

[Jari Oksanen]

On 13/10/09 18:44 PM, "Jens Oldeland" <oldeland at gmx.de> wrote:

> Hi again,
> 
> our distance matrices are 1) genetic distance (Jaccard) and 2)
> 3D-Euclidean Distance and the question we want to solve is if there is
> an effect called "Isolation by Distance" (IBD) in our data (genetic and
> "real"-distances of snails on the island of crete) or not. There was a
> debate on the topic if the mantel test or the partial mantel test (isn´t
> this similar to MRM?) in several papers mainly in evolution-journals:
> 
> Raufaste, N. and F. Rousset. 2001. Are partial Mantel tests adequate?
> Evolution 55:1703­1705
> Castellano, S. and E. Balletto. 2002. Is the partial Mantel test
> inadequate? Evolution 56:1871­1873.
> 
> 
> Geffen, E., Anderson, M.J., & Wayne, R.K. (2004). Climate and habitat
> barriers to dispersal in the highly mobile grey wolf. Molecular Ecology,
> 13, 2481-2490
> explain it nicely on page p.2483 (LHS)
> 
> "The problem arises due to the lack of independence of individual
> distances in a distance matrix. Although a simple Mantel test overcomes
> this issue by the
> use of permutations, a permutational approach does not necessarily solve
> problems introduced by several uncontrolled nuisance parameters in the
> case of more than one
> regressor (i.e. partial tests). Thus, we do not use a Mantel approach
> here, but rather use the distance-based multivariate approach of McArdle
> & Anderson (2001). The important point is that, for dbRDA, the
> individual distances are not treated as a single univariate response
> variable, as in the Mantel test, but rather the individual sites are the
> units of observation for analysis, about which we have calculated
> distances using an entire set of genetic variables. The distance matrix
> is therefore treated as information regarding multivariate
> response.Taking this multivariate approach avoids the problems
> associated with the partial Mantel test."

Jens,

There has been a very similar discussion in the Ecology recently between my
good friends, Hanna Tuomisto & co vs. Pierre Legendre & co. However, the
point here and above exactly was that you cannot use dissimilarities on the
RHS (lack of independence), but you must use rectangular data in dbRDA. If
you use distances on the RHS you won't have dbRDA but you get Mantel family
methods (like MRM in ecodist). The problem, of course, is how to map
distances onto Euclidean space (= rectangular data) *and* still study the
effects of the distances instead of the effects of *location*. I don't know
any really good solution here, but all proposed solutions have their
problems. Pierre Legendre, Daniel Borcard and Hanna Tuomisto have all tried
to convince me of their point of view, and while all their conflicting
arguments make sense, they are not yet an optimal solution.

Cheers, Jari Oksanen
> 
> so we thought it would be a good idea not to use mantel and friends
> since the problem of IBD seems to need a different approach here.
> 
> best,
> Jens
> 
> 
> 
> 
> 
> Sarah Goslee schrieb:
>> That doesn't make much sense to me. You'd need an entirely different method
>> than capscale.
>> 
>> Perhaps what you're looking for is more like multiple regression on distance
>> matrices (implemented in MRM in ecodist)?
>> 
>>      Lichstein, J. 2007. Multiple regression on distance matrices: A
>>      multivariate spatial analysis tool. Plant Ecology 188: 117-131.
>> 
>>      Legendre, P.; Lapointe, F. and Casgrain, P. 1994. Modeling brain
>>      evolution from behavior: A permutational regression approach.
>>      Evolution 48: 1487-1499.
>> 
>> Sarah
>> 
>> On Tue, Oct 13, 2009 at 11:13 AM, Jens Oldeland <oldeland at gmx.de> wrote:
>>   
>>> Dear Sarah dear Jari,
>>> 
>>> many thanks for your explanations. However, it wasnt what I thought about,
>>> sorry I definitely have to be more specific about the problem.
>>> 
>>> Okay I try be more precise:
>>> 
>>> the problem was that for example  capscale accepts   "capscale(dist.matrix.1
>>> ~ N + P + K *Ag, data=varechem)"
>>> but I need  "capscale(dist.matrix.1 ~ dist.matrix.2, data=dist.matrix.2)"
>>>  so the trick was not on how to create a distance matrix but how to use a
>>> second on in a formula.
>>> 
>>> We are trying a similar analysis like the the "distlm" program by Marti
>>> Anderson does, however we had a problem with that and wanted to try the
>>> analysis in R.
>>> 
>>> thanks already for all your comments !
>>> 
>>> best
>>> Jens
>>>     
>> 
>> 
>> 
>>   
>