Hi Joseph,

Apologies fr the delay.

You are asking a compendium question.

My first point is that it is terribly easy to over-think or ascribe too much respect to climate matching tools.

I published a method using CLIMEX Match Climates (Regional) to tackle the problem that you are tackling: Kriticos, D. J. 2012. Regional climate-matching to estimate current and future biosecurity threats. Biological Invasions 14:1533-1544.

Every one of these methods will require you to set an arbitrary threshold, which dictates the specificity of the result.

Using all 16 Bioclim variables is, ahem,

not

a good idea. Typically, 4-5 variables is the best if you want to use a climate matching or correlative method. Given that you are trying to identify risk areas (in general) you should focus on variables that indicate stressful conditions. No plant or animal ever persisted or died depending on the mean annual temperature or total precipitation.

Correlation of your variables is the least of your worries. In fact, the opposite is the problem if you are wanting to use all of the first 16 BC variables you will be over-fitting the model extremely.

10 min spatial resolution is fine (possibly even over-kill) foor this challenge.

Kind regards,
Darren