Message-ID: <5657247A.60708@gmail.com>
Date: 2015-11-26T15:25:46Z
From: Ben Bolker
Subject: Mixed modelling and Species Area Relationship (SAR)
In-Reply-To: <CAFPRYfCev4UPecF7ud7K8mu2P8q-8czX13zUFTMoFSFSQAYRyw@mail.gmail.com>
On 15-11-26 09:09 AM, Gitu wa Mbui wrote:
> How does one account for the species area relationship in a mixed model of
> predicting species richness?
>
> Sampling was carried out using different methods - photoquadrats, transects
> etc ( five different methods).
>
> The area of the sampled plots differed and there were hundreds of plots. I
> am constructing a glmm for predicting the species richness, overall, and
> have configured the Method of sampling as a random intercept in the model.
> I am wondering how I should construct the model such the influence of SAR
> is taken into account - considering that SAR can not be a random factor.
>
> ~Gitu
This is probably a little bit too vague for most of the people on the
list (who are not ecologists).
Supposing that you're using a log link for the response (which would
make sense if you plan to treat species richness as Poisson or negative
binomial), try incorporating log(Area) as a covariate. Then (ignoring
all the other stuff in your model for the moment)
log(mu) = b0 + b1*log(area)
or
mu = exp(b0)*exp(b1*log(area)) = C*area^b1
which looks like a pretty respectable model for the species-area
relationship.
Ben Bolker