SDM (MaxEnt) per Species, package dismo
Hi, I would like to know this answer as well as I am doing a very similar thing. I am currently working with enfa (package adehabitat) for Species Distribution Models but will also look at the results with maxent. I also have multiple species on my site and was thinking of doing a loop, but if there is a way of doing them together I would be very interested! Best, Mieke Mieke Zwart PhD student Room 4.53 School of Biology Ridley 2 Newcastle University Newcastle upon Tyne NE1 7RU United Kingdom Tel extension: 5952 -----Original Message----- From: r-sig-ecology-bounces at r-project.org [mailto:r-sig-ecology-bounces at r-project.org] On Behalf Of Johannes Radinger Sent: 30 January 2012 11:25 To: r-sig-ecology at r-project.org Subject: [R-sig-eco] SDM (MaxEnt) per Species, package dismo Hello SIG-ECO list, I am want to perform Species Distribution Models with R's dismo package (function: maxent()). Of course this topic is a spatial topic (R-SIG-GEO related) but I think it fits better to the ECO list. For my analysis (MaxEnt)I have a Rasterstack of predictor variables and the species occurence points as spatial points (sp-class). My list of observations has several different species. And I divided the list into a training and testing dataset with: kfold(occ.points, k = 5, by = occ.points$Species) As I read in the orig. MaxEnt tutorial, it should be possible to use an input file with multiple species. I'd like to know: Does that accuatlly work also in the R-Maxent setup? Can a provide maxent() spatial points of different species, or do I have to fit the model manually for each species (resp. in a loop?) How can I access the results of the single species (like the 'me' in the examples of maxent). Another maxent related question: What happens if one of the predictor rasters is not entirely populated with values resp. shows NA's? Are these cells just excluded from the model fit and prediction or will there be a problem with the entire model? Thank you for your help, Best regards, Johannes -------- Original-Nachricht --------
Datum: Fri, 27 Jan 2012 09:06:44 -0800 Von: "Robert J. Hijmans" <r.hijmans at gmail.com> An: Johannes Radinger <JRadinger at gmx.at> Betreff: Re: kfold question
Johannes, An error occurs when you request a kfold for a single observation. I will fix that, but the request obviously makes no sense. It is straightforward to count the number of observations by species with something like table(data$species) Best, Robert On Fri, Jan 27, 2012 at 1:56 AM, Johannes Radinger <JRadinger at gmx.at> wrote:
Dear Mr Hijmans, I tried to use your package dismo's function: kfold() I want to split my dataset into 5 parts by species. Of course it is not possible to split records of a species with less the 5 observation into 5 parts... That is the reason why I get a warning message... It'd be okay when these species are devided by their maximum number of records (1,2,3,4). But somehow I also get an error message. I think that might be related to that. Of course it doesn't make sense to devide a species with 1 record by 1. Is this the reason for the error message (sorry it is in German) or is it just something totally different? Fehler in rep(j, times = times[j]) : ung?ltiges 'times' Argument Zus?tzlich: Warnmeldungen: 1: In kfold(occ.fish, k = 5, by = occ.fish$Species) : lowered k for by group: N.Gesamt.Amerikanischer.Hundsfisch because the number of observations was 4 2: In kfold(occ.fish, k = 5, by = occ.fish$Species) : lowered k for by group: N.Gesamt.Flunder because the number of observations was 3 3: In kfold(occ.fish, k = 5, by = occ.fish$Species) : lowered k for by group: N.Juvenil.Flunder because the number of observations was 1
...which would mean Error in rep(j, times = times[j]) : invalid 'times' argument How do you usually handle such datasets?Probably excluding these species at all and subsetting the dataset (I have to think how to do that in R). best regards, johannes -- "Feel free" - 10 GB Mailbox, 100 FreeSMS/Monat ... Jetzt GMX TopMail testen: http://www.gmx.net/de/go/topmail
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