Below I have pasted the outputs of an ordistep() on an rda()

I noticed in the final fitting of the ordistep() that two terms 
"mydata$TreeCov" and "mydata$HabConfig" were still included but had variance of 
0 and therefore P was not calculated.

Why are they still included in the final model?  

thanks

Nevil Amos


> myOrdistepBoth
Call: rda(formula = mygenind@tab ~ mds3dCS_NULL + mds3dTRE_25_2_CS25 + 
mydata$LAT.x + mydata$Hab_Config + mds3dTRE_25_100_CS25 + mydata$TreeCov +
mydata$Site_No + mds3dSFW_EO_100_CS25 + mds3dSFW_EO_5000_CS25 + 
mydata$Landscape + mds3dSFW_TH_10_CS25 + mydata$LONG.x, scale = T, na.action = 
"na.omit")

               Inertia Proportion Rank
Total         160.0000     1.0000     
Constrained    45.3560     0.2835   32
Unconstrained 114.6440     0.7165  139
Inertia is correlations 
Some constraints were aliased because they were collinear (redundant)

Eigenvalues for constrained axes:
  RDA1   RDA2   RDA3   RDA4   RDA5   RDA6   RDA7   RDA8   RDA9  RDA10  RDA11  
RDA12  RDA13  RDA14  RDA15  RDA16  RDA17  RDA18  RDA19  RDA20  RDA21  RDA22  
RDA23  RDA24  RDA25 
3.3489 3.2291 2.8211 2.5129 2.2606 2.1062 2.0834 1.8720 1.7727 1.6680 1.6072 
1.5512 1.5100 1.4314 1.3802 1.2427 1.1497 1.1153 1.0547 1.0287 0.9814 0.9361 
0.9168 0.8851 0.7577 
 RDA26  RDA27  RDA28  RDA29  RDA30  RDA31  RDA32 
0.7150 0.7056 0.6436 0.6098 0.5643 0.4806 0.4140 

Eigenvalues for unconstrained axes:
  PC1   PC2   PC3   PC4   PC5   PC6   PC7   PC8 
3.433 3.098 3.057 2.912 2.866 2.743 2.669 2.586 
(Showed only 8 of all 139 unconstrained eigenvalues)



> anova(myOrdistepBoth,by="term")
Permutation test for rda under reduced model
Terms added sequentially (first to last)

Model: rda(formula = mygenind@tab ~ mds3dCS_NULL + mds3dTRE_25_2_CS25 + 
mydata$LAT.x + mydata$Hab_Config + mds3dTRE_25_100_CS25 + mydata$TreeCov + 
mydata$Site_No + mds3dSFW_EO_100_CS25 + mds3dSFW_EO_5000_CS25 + 
mydata$Landscape + mds3dSFW_TH_10_CS25 + mydata$LONG.x, scale = T, na.action = 
"na.omit")
                       Df     Var      F N.Perm Pr(>F)   
mds3dCS_NULL            3   6.527 2.6380     99   0.01 **
mds3dTRE_25_2_CS25      3   5.596 2.2616     99   0.01 **
mydata$LAT.x            1   1.892 2.2939     99   0.01 **
mydata$Hab_Config       2   2.858 1.7325     99   0.01 **
mds3dTRE_25_100_CS25    3   4.314 1.7435     99   0.01 **
mydata$TreeCov          1   1.238 1.5008     99   0.01 **
mydata$Site_No          1   1.304 1.5806     99   0.01 **
mds3dSFW_EO_100_CS25    3   3.834 1.5497     99   0.01 **
mds3dSFW_EO_5000_CS25   3   3.344 1.3515     99   0.01 **
mydata$Landscape        8   9.711 1.4717     99   0.01 **
mds3dSFW_TH_10_CS25     3   3.702 1.4961     99   0.01 **
mydata$LONG.x           1   1.037 1.2569     99   0.06 . 
Residual              139 114.644                        
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 



> anova(myOrdistepBoth,by="margin")
Permutation test for rda under reduced model
Marginal effects of terms

Model: rda(formula = mygenind@tab ~ mds3dCS_NULL + mds3dTRE_25_2_CS25 + 
mydata$LAT.x + mydata$Hab_Config + mds3dTRE_25_100_CS25 + mydata$TreeCov + 
mydata$Site_No + mds3dSFW_EO_100_CS25 + mds3dSFW_EO_5000_CS25 + 
mydata$Landscape + mds3dSFW_TH_10_CS25 + mydata$LONG.x, scale = T, na.action = 
"na.omit")
                       Df     Var      F N.Perm  Pr(>F)   
mds3dCS_NULL            3   3.519 1.4222    199 0.00500 **
mds3dTRE_25_2_CS25      3   3.663 1.4805    199 0.00500 **
mydata$LAT.x            1   1.185 1.4364    199 0.00500 **
mydata$Hab_Config       0   0.000 0.0000      0           
mds3dTRE_25_100_CS25    3   3.569 1.4423    199 0.00500 **
mydata$TreeCov          0   0.000 0.0000      0           
mydata$Site_No          1   1.251 1.5170    199 0.00500 **
mds3dSFW_EO_100_CS25    3   3.303 1.3348    199 0.00500 **
mds3dSFW_EO_5000_CS25   3   3.395 1.3721    199 0.01000 **
mydata$Landscape        8   9.573 1.4508    199 0.00500 **
mds3dSFW_TH_10_CS25     3   3.658 1.4785    199 0.00500 **
mydata$LONG.x           1   1.037 1.2569   1399 0.03571 * 
Residual              139 114.644                         
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 
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