Message-ID: <C99BF09C.15A2B%jari.oksanen@oulu.fi>
Date: 2011-03-08T12:41:32Z
From: Jari Oksanen
Subject: null models for a single species
In-Reply-To: <134087CA64D9E745A66170FFAAA29F9940A797@mfns13.naturkundemuseum-berlin.de>
On 8/03/11 10:54 AM, "Penner, Johannes" <Johannes.Penner at mfn-berlin.de>
wrote:
> Dear List members,
>
> I would like to test whether an observed occupancy of lakes in a landscape has
> occurred randomly (by chance) or not.
>
> How can I do that? The problem is that it concerns only a single species and I
> would like to use binary data only.
>
> At first I thought of generating null models and test the observed occupancy
> against the randomly generated one. However, this needs more than one
> species...
>
> Any hints are highly appreciated!
>
Johanne,
Actually many of the null models as defined in vegan would work here: you
only provide a one-column matrix. Although they work, they would not make
much sense: null models of type "r00" and "c0" would only give you random
permutation of your data (and "c0" would give you the data). Naturally, this
is one way to go: just permute your observations. For simple permutations
you can use sample() function of base R, and for constrained permutation you
can download Gavin Simpson's 'permute' package from
http://www.r-forge.r-project.org/. However, if you have a structured model
and a structured hypothesis you can do much better than have a simple
permutation. I have no idea of your hypothesis, though, and I can't help
here.
Cheers, Jari Oksanen