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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