Hello,
I have what should be an easy question to answer I hope. I am using
Capscale and anovs.cca in vegan to examine relationship between genetic
distance among individuals to be predicted by several ecological niche
model distance matrices generated from Circuitscape and partialing out
distance in space (from lat/lon). I have done the following:
Converted all of the distances on the RHS using PCNM and used ?scores? to
pull the scores from the PCNM results. My genetic distance is formatted as
a ?dist? object on the LHS. The model looks as follows:
capscale(gendist~scores(cur)+scores(ms)+scores(el)+scores(lgm)+scores(lig)+scores(mis19)+Condition(scores(dist2)),sqrt.dist=T)->try
This works and so does:
anova(try, by=?terms)
However, when I used anova(try, by=?margin) I get this error:
Error in X[, ass != i, drop = FALSE] :
(subscript) logical subscript too long
If I chose a smaller number of axes, then it will work but seems unstable
(P values change from significant to non-significant and vice versa) given
the number of axes I choose. This model works with anova(try, by=?margin?)
for instance:
capscale(gendist~scores(cur,choices=1:20)+scores(ms,choices=1:20)+scores(el,choices=1:20)+scores(lgm,choices=1:20)+scores(lig,choices=1:20)+scores(mis19,choices=1:20)+Condition(scores(dist2,choices=1:20))->try
If I increase the number axes to 50 then I get the same error as above.
What could be causing this error and is there way to get a stable answer
using anova.cca with margins?
I thank you very much in advance!
Frank
P.S.
Here are some outputs from the reduced to the full axes model:
Call: capscale(formula = gendist ~ scores(cur) + scores(ms) + scores(el) +
scores(lgm) + scores(lig) + scores(mis19) +
Condition(scores(dist2)), sqrt.dist = T)
Inertia Proportion Rank
Total 30.3890110 1.0000000
Conditional 20.2125899 0.6651283 115
Constrained 9.9498632 0.3274165 118
Unconstrained 0.2551651 0.0083966 4
Imaginary -0.0286072 -0.0009414 5
Inertia is Nei distance
Call: capscale(formula = gendist ~ scores(cur, choices = 1:20) + scores(ms,
choices = 1:20) + scores(el, choices = 1:20) +
scores(lgm, choices = 1:20) + scores(lig, choices = 1:20) + scores(mis19,
choices = 1:20) + Condition(scores(dist2, choices
= 1:20)))
Inertia Proportion Rank
Total 10.1488 1.0000
Conditional 6.9685 0.6866 20
Constrained 3.1599 0.3114 120
Unconstrained 1.9522 0.1924 97
Imaginary -1.9319 -0.1904 88
Inertia is squared Nei distance
Some constraints were aliased because they were collinear (redundant)
--
*__________________________________*
*Frank T. Burbrink, Ph.D.*
*Curator in Charge*
*Department of Herpetology*
*American Museum of Natural History*
*Central Park West at 79th Street*
*New York, NY 10024-5192*
*Website: https://sites.google.com/view/frank-burbrink-website/
<https://sites.google.com/view/frank-burbrink-website/>*
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