Hello Waqas,

In R, you can calculate

- the pairwise Pearson/Spearman/Kendall correlations with cor() or with Hmisc::rcorr() if you need the significance values as well,

- the Variance Inflation Factor (VIF) with usdm::vif(), and

- the Condition Number (CN) with kappa().

I recommend package 'corrplot' for displaying the correlation matrix.

HTH,

Ákos

Hello Waqas,

But please do not use only the correlation values for selecting from the bioclimatic variables. Several other characteristics of the BCVs are to be taken into account if selecting some of them as predictors in an SDM. Please refer to this paper:

Article The way bioclimatic variables are calculated has impact on p...

HTH,

Ákos

You can use the VIF approach preseneted in the 'sdm'

package in R

(Naimi and Araújo 2016)

Naimi B, Araújo MB (2016) Sdm: A reproducible and extensible R platform for species distribution modelling. Ecography 39:368–375. https://doi.org/10.1111/ecog.01881