[R-sig-eco] Presence-absence to Occurrence Dataset?

[Peter Solymos]

Hi Elyse,

Tom referred to the mefa package, I'd like to draw the attention to
the mefa4 package which is more efficient and can handle large data
since it uses sparse matrices through the Matrix package. The Melt()
function is the inverse operation to xtabs() or its modified version
Xtabs() in mefa4. It can take a matrix, sparse matrix, S3 mefa or S4
Mefa object as its argument:

library(mefa4)

y <- matrix(sample(0:4, 12, replace=TRUE, prob=c(0.5, rep(0.5/4, 4))), 4, 3)
x <- data.frame(x=runif(4), y=runif(4))
colnames(y) <- LETTERS[1:3]
rownames(y) <- rownames(x) <- paste("row", 1:4, sep="_")

z <- Melt(y)
data.frame(z, x[z$rows,])

There is also the (relatively) new multitable package by Steve Walker
with similar functionality. Lots of ways to do it -- the problem must
bother many of us :)

Cheers,

Peter

Péter Sólymos
Alberta Biodiversity Monitoring Institute
and Boreal Avian Modelling project
Department of Biological Sciences
CW 405, Biological Sciences Bldg
University of Alberta
Edmonton, Alberta, T6G 2E9, Canada
Phone: 780.492.8534
Fax: 780.492.7635
email <- paste("solymos", "ualberta.ca", sep = "@")
http://www.abmi.ca
http://www.borealbirds.ca
http://sites.google.com/site/psolymos



On Fri, Apr 20, 2012 at 1:06 PM,  <Tom_Philippi at nps.gov> wrote:
> Elyse--
>
> For the first step of converting your community matrix to triplets of
> {site, species, presence}, you can use melt() from the flexible & powerful
> reshape package as David suggested, or dematrify() from Dave Roberts'
> labdsv package, which was built specifically for this task and has simpler
> syntax than melt.  The second step is to then merge your location dataframe
> with the long-format occurrence data by sitenames.
>
> Do you need coordinates for only presences, or for presences and absences?
> If you need only presences, dematrify() with thresh=0.5 would automatically
> drop absences, while melt() would require a second step LongOccurrences <-
> LongOccurrences[Freq>0,]
>
> So, (untested code) for dataframes named CommMatrix and SiteCoords and
> sitenames as Site:
> LongOccurrences <- dematrify(CommMatrix,thresh=0.5)
> Presences <- merge(LongOccurrences,SiteCoords,by="Site",all.x=TRUE)
>
> If you have more complex needs for handling community and environmental
> data, you might consider the mefa package.
>
> Tom
> -------------------------------------------
> Tom Philippi
> Quantitative Ecologist
> Inventory and Monitoring Program
> National Park Service
> c/o Cabrillo National Monument
> 1800 Cabrillo Memorial Dr
> San Diego, CA 92106
> (619) 523-4576
> Tom_philippi at NPS.gov
> http://science.nature.nps.gov/im/monitor
> -------------------------------------------
>
>
>
>
>             David Valentim
>             Dias
>             <dvdscripter at gmai                                          To
>             l.com>                    "r-sig-ecology at r-project.org"
>             Sent by:                  <r-sig-ecology at r-project.org>
>             r-sig-ecology-bou                                          cc
>             nces at r-project.or
>             g                                                     Subject
>                                       Re: [R-sig-eco] Presence-absence to
>                                       Occurrence Dataset?
>             04/20/2012 01:32
>             PM AST
>
>
>
>
>
>
>
>
> You can check melt() (from reshape2) and reshape() functions.
>
>
> 2012/4/20 Coffey, Elyse D. (UMSL-Student) <edc6cb at mail.umsl.edu>
>
>> Hello everyone,
>>
>> I am working with a large community dataset where column names are
> species
>> and rows are filled with either 1s or 0s (presence absence of the
> species)
>> and each row corresponds to a site name.  I have long and lati
> coordinates
>> for each site in a separate datasheet.
>>
>> I am trying to use a program called Maxent in order model species
>> distributions. The program requires a specific occurrence dataset with
>> columns in this format: species, Long, Lati.
>>
>> It is very difficult and time consuming to create such a dataset by hand!
>> I was wondering if anyone had any ideas as to how I can use R to
> manipulate
>> my original community dataset in order to create the occurrence dataset I
>> described above?
>>
>> Any suggestions would be greatly appreciated!
>>
>> Thanks,
>>
>> Elyse Coffey
>> Biology (B.S.) student
>> University of Missouri-St. Louis
>>
>>
>>        [[alternative HTML version deleted]]
>>
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>
>
>
> --
> Currículo: http://lattes.cnpq.br/7541377569511492
>
>             [[alternative HTML version deleted]]
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