Mixed modelling and Species Area Relationship (SAR)
Dear Gitu, If the area is constant within each method, then the random effect of method will model the area effect. If not you can add area to the fixed effects of the model. You have several options: as an offset, as a (log)linear trend, as a smoother, ... Much will depend on your assumption on the relation between species richness and sample area. Best regards, ir. Thierry Onkelinx Instituut voor natuur- en bosonderzoek / Research Institute for Nature and Forest team Biometrie & Kwaliteitszorg / team Biometrics & Quality Assurance Kliniekstraat 25 1070 Anderlecht Belgium To call in the statistician after the experiment is done may be no more than asking him to perform a post-mortem examination: he may be able to say what the experiment died of. ~ Sir Ronald Aylmer Fisher The plural of anecdote is not data. ~ Roger Brinner The combination of some data and an aching desire for an answer does not ensure that a reasonable answer can be extracted from a given body of data. ~ John Tukey 2015-11-26 15:09 GMT+01:00 Gitu wa Mbui <gitumbui at gmail.com>:
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
[[alternative HTML version deleted]]
_______________________________________________ R-sig-mixed-models at r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models