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spatial correlation

Andrew Halford 
Hi Listers,

I am trying to better understand how spatial autocorrelation is determined.
I have attached 2 txt files one is a fish species x sites abundance table
and the other is a distance file with the lat and longs for each site
(converted to cartesian coords). I have run the tests for spatial
correlation using the methodology from the Borcard et al. Use R! book.

The result was no significant spatial correlation. However an nmds
ordination of the fish data shows 3 very strongly clustered groups of sites
which corresponds to 3 oceanic islands. A permutation analysis of the fish
resemblance matrix with a distance matrix was also highly significant with
a rho=0.646 spearmans rank correlation. To my mind I would have thought
that with such strong groupings in the data that spatial correlation would
be present at the scale of islands? Can someone help me explain this result?

My analysis below

fish_hellinger <- decostand (fish,"hellinger")
fish.xy # spatial dataset space_ed.txt

#test for overall trend
lineartest <- anova(rda(fish_hellinger,fish.xy))

Permutation test for rda under reduced model

Model: rda(X = fish_hellinger, Y = fish.xy)
         Df     Var      F N.Perm Pr(>F)
Model     2 0.17148 8.6098    199  0.005 ** ##significant linear trend
Residual 14 0.13942
---
Signif. codes:  0 ?***? 0.001 ?**? 0.01 ?*? 0.05 ?.? 0.1 ? ? 1

 # fit linear trend to the fish data and then extract residuals for
subsequent use in spatial analysis
.,data=fish.xy))

# make a distance matrix from the residuals data for input to the
correlogram call
# perform the mantel-based test for spatial correlation
mantel.correlog(fish_hellinger_D1,XY=fish.xy,nperm=99))

Mantel Correlogram Analysis

Call:

mantel.correlog(D.eco = fish_hellinger_D1, XY = fish.xy, nperm = 99)

        class.index      n.dist  Mantel.cor Pr(Mantel) Pr(corrected)
D.cl.1   118.013676  462.000000   -0.042424       0.11          0.11
D.cl.2   352.037024    0.000000          NA         NA            NA
D.cl.3   586.060371    0.000000          NA         NA            NA
D.cl.4   820.083719    0.000000          NA         NA            NA
D.cl.5  1054.107067  384.000000    0.033639       0.30            NA
D.cl.6  1288.130414    0.000000          NA         NA            NA
D.cl.7  1522.153762    0.000000          NA         NA            NA
D.cl.8  1756.177109  320.000000          NA         NA            NA
D.cl.9  1990.200457    0.000000          NA         NA            NA
D.cl.10 2224.223804    0.000000          NA         NA            NA
D.cl.11 2458.247152  240.000000          NA         NA            NA

Thread (2 messages)

Andrew Halford spatial correlation Nov 20 Tim Richter-Heitmann spatial correlation Nov 21