Hi
see inline
>
> Hello,
>
> I've got a small dataset on box turtle shell measurements that I would
> like to perform a detrended correspondence analysis on. I thought that
it > would be interesting to examine the morphometrics for each species in
the > area of overlap and in areas where neither species occurs.
>
> I've taken a look at the dune and dune.env datasets in vegan. Using the
> str() command gives me
>
> > str(dune)
> 'data.frame': 20 obs. of 30 variables:
> $ Belper: num 3 0 2 0 0 0 0 2 0 0 ...
> $ Empnig: num 0 0 0 0 0 0 0 0 0 0 ...
> $ Junbuf: num 0 3 0 0 0 0 0 0 0 0 ...
> $ Junart: num 0 0 0 3 0 0 4 0 0 3 ...
> ...
>
> However, when I try looking directly at the data frame using the edit
> command I see that there is a column called "row.names" to the
left of
"Belper".>
> Likewise, when I use the str() command on dune.env I get
>
> > str(dune.env)
> 'data.frame': 20 obs. of 5 variables:
> $ A1 : num 3.5 6 4.2 5.7 4.3 2.8 4.2 6.3 4 11.5 ...
> $ Moisture : Ord.factor w/ 4 levels
"1"<"2"<"4"<"5": 1 4 2 4 1 1 4
1 2
4 ...> $ Management: Factor w/ 4 levels
"BF","HF","NM",..: 1 4 4 4 2 4 2 2 3 3
...> $ Use : Ord.factor w/ 3 levels
"Hayfield"<"Haypastu"<..: 2 2 2 3
2 > 2 3 1 1 2 ...
> $ Manure : Ord.factor w/ 5 levels
"0"<"1"<"2"<"3"<..: 3 4 5 4
3 5 4
3 1 1 ...>
> but using the edit() command shows a column named "row.names".
No. This is not a column but it is what it says row.names
> str(rosin)
'data.frame': 10 obs. of 5 variables:
$ pytel: int 1 2 3 4 5 6 7 8 9 10
$ rstr : num 1.022 0.981 0.992 1.01 0.976 ...
$ gama : num 1.4 1.44 1.41 1.43 1.39 ...
$ cas : int 0 3 6 9 12 15 18 21 24 27
$ typ : chr "anatas" "anatas" "anatas"
"anatas"
> head(rosin)
pytel rstr gama cas typ
1 1 1.0216621 1.397885 0 anatas
2 2 0.9809663 1.442439 3 anatas
3 3 0.9916211 1.411767 6 anatas
^^ these are row names
>
> I assume that the the "row.names" column is used to link the two
files
together.
If you are in doubt, recommended way is to consult documentation.
?row.names
All data frames have a row names attribute, a character vector of length
the number of rows with no duplicates nor missing values.
>
> My turtle data is saved as a *.csv, and I've added a column called
> "row.names", so that it looks like this
>
> row.names,CL,CCL,CW,CCW,CH,CCH
> 1,104.4,131.8,89.887,137.4,43.391,89.7
> 2,108.79,135.9,87.78,118.1,50.72,71.2
> 3,114.12,126.1,89.33,132.8,142.39,78.3
> 4,102.87,128.2,84.2,125,45.42,72.4
> 5,84.6,104.8,72.61,111.8,41.1,57.3
>
> I've called this file "turtles_dca.csv". I've also
created a file called
> "turtles_dca_env.csv" that looks like this
>
> row.names,Species,Sex,Distribution,Concatenated,Species_overlap
> 1,Terrapene_ornata,Female,overlap,TO_F_Overlap,TO_Overlap
> 2,Terrapene_ornata,Female,overlap,TO_F_Overlap,TO_Overlap
> 3,Terrapene_ornata,Female,overlap,TO_F_Overlap,TO_Overlap
> 4,Terrapene_ornata,Female,overlap,TO_F_Overlap,TO_Overlap
> 5,Terrapene_ornata,Female,overlap,TO_F_Overlap,TO_Overlap
>
> However, when I read the data into R using this command
>
> turtles.env = read.csv("turtles_dca_env.csv", header = TRUE)
>
>
> and then using the str() command I get
>
>
> > str(turtles)
> 'data.frame': 67 obs. of 7 variables:
> $ row.names: int 1 2 3 4 5 6 7 8 9 10 ...
> $ CL : num 104.4 108.8 114.1 102.9 84.6 ...
> $ CCL : num 132 136 126 128 105 ...
> $ CW : num 89.9 87.8 89.3 84.2 72.6 ...
> $ CCW : num 137 118 133 125 112 ...
> $ CH : num 43.4 50.7 142.4 45.4 41.1 ...
> $ CCH : num 89.7 71.2 78.3 72.4 57.3 73.4 67 57 68.8 68 ...
>
> When I run decorana() on this dataset, it appears that the column
> "row.names" is included in the analysis, which isn't what
I'm looking
for.
Then why you added this column to your data?
>
> If I go ahead and delete the column "row.names" from my data
frames
(i.e. > removing it from turtles and turtles.env), I don't believe that the
> analysis is performed correctly. The two species differ significantly in
> most of their measurements, but the ordihull() and ordispider() commands
> show them overlapping almost completely.
>
> I think that I'm missing something pretty basic about inputting and
> formatting this data for this analysis. Can anyone offer a suggestion on
> where I'm going astray? I can send a copy of the data if anyone wants
to
look at it.
I am not familiar with functions you use. However you probably want to
link those 2 files together. If they both are in the same order you can
just do
turtles.complet <- cbind(turtles, turtles.env)
Or if they are in different order you need to find some common column(s)
and
?merge
those two files.
Regards
Petr
>
> Best wishes,
> Chris
> University of Central Oklahoma
> [[alternative HTML version deleted]]
>
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