The problem: I calculated the root of the sum of squares of all 8 CCA scores of the explanatory variables. However, it turns out that the lengths of the explanatory variables equal the root of the sum of squares of only CCA scores of the first two (canonical) axes in the graph. As a result, I have two vectors in my graph of which the smallest is almost half of the bigger one, while when I calculate their length by taking the square root of the sum of the squares of their CCA scores (over al 8 canonical axes):

Precip -0,1315 0,074613 -0,00788 -0,40556 0,077369 0,144983 0,021653 -0,04012

Open area -0,23588 0,144588 0,18441 -0,09637 -0,01802 0,174098 -0,25398 -0,02785

Result 1: length of resp. Open area over all 8 (canonical) dimensions 0,465282326 0,464494416

Result 2 length of resp. Precip over the first 2 (canonical) dimensions.: 0,151190429 0,276666081

That seems strange: the lengths of the vectors actually only represents the impact of the explanatory variables over the first two (strongest) canonical axes it seems. As a result, the impact given to precipitation is much smaller as when all 8 dimensions are included.