I have a dataset of monthly hydrologic parameters by year, including this
year, with a matrix of 48r x 24c.

> my.data
         Octinflow    Novinflow . . . OctPrecip . . .
1963     400             357                 0.25
1964     567             429                 0.89
.
.
.
2010     150             210                 0.12


I would like to use NMDS to rank years based on similarity to 2010.

>library(vegan)
>my.model <- metaMDS(my.data, distance='euclidean', autotransform=T, k=6)

Is it possible to use the euclidean distance of the points to determine the
overall (dis)similarity of years...

> dist(my.model$points)

And then from this extract the values of interest (i.e. the last row) and
rank these values?

Any direction is greatly appreciated.

Pura Vida,

Josh

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