How to categorize/classify functional relationships? [R] I have a dataset of bacterial abundance at specific degrees of temperature. Each line is a different bacterial species and each column is the abundance at a specific temperature.
My dataset includes some taxa increasing with temperature, some decreasing, some having plateau at certain values and so on, with several different functional responses of bacterial abundance to temperature.
The question is: how can I classify my bacterial species according to their relationships with temperature? e.g.

*

*cluster 1 = all species linearly decreasing with temperature;

*cluster 2 = all species linearly increasing with temperature;

*cluster 3 = all species increasing according to a sigmoidal curve;

*cluster 4 = all species increasing according to a saturation curve;

and so on.
Any cool method in R you would suggest?

I would:

*

*define a set of temperature-dependence models that you want to test, e.g. linear; exponential, after Brown et al. (2004); Lactin-2; etc. (see Clarke's and/or Angilletta's books);

*code them in your favourite modelling software: in R you can use nls(), but there might be R packages with ready-to-use implementations of some thermal dependence models;

*fit each model to the data for each of your study species;

*select the best model for each study species via AIC, BIC, or other model-selection methods.

You can automate the process using loops.
Here is a blog post I wrote some time ago that might provide some help. It includes a worked example in R.
