Dear All,
Perhaps, there is another way of approaching this problem: the
Monmonier's maximum-difference barriers algorithm.
Monmonier, M. (1973) Maximum-difference barriers: an alternative
numerical regionalization method. Geographic Analysis, 3, 245?261.
Manni, F., Guerard, E. and Heyer, E. (2004) Geographic patterns of
(genetic, morphologic, linguistic) variation: how barriers can be
detected by "Monmonier's algorithm". Human Biology, 76, 173?190
Nice documantation and a free software Barrier here:
http://www.mnhn.fr/mnhn/ecoanthropologie/software/barrier.html
The R implementation has been done by Thibaut Jombart in the adegenet
package (function monmonier), that is slightly different in handling
tessellation at the margin. Permutation test are discussed in the
Manni paper as I recall and implemented in Barrier. This is especially
useful for genetic distances (and NOT for biotic data, because of
profoundly different dispersal mechanisms involved in shaping genetic
vs. community structures).
Yours,
Peter
P?ter S?lymos
Alberta Biodiversity Monitoring Institute
Department of Biological Sciences
CW 405, Biological Sciences Bldg
University of Alberta
Edmonton, Alberta, T6G 2E9, Canada
Phone: 780.492.8534
Fax: 780.492.7635
email <- paste("solymos", "ualberta.ca", sep = "@")
On Tue, Oct 13, 2009 at 10:07 AM, Jari Oksanen <jari.oksanen at oulu.fi> wrote:
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 55:1703?1705
Castellano, S. and E. Balletto. 2002. Is the partial Mantel test
inadequate? Evolution 56:1871?1873.
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