How did using a pedigree influence the degrees of freedom available to test fixed effects in asreml-R?

Question

I am using a half-sibling pedigree (individuals, Sires, Dams and groups (populations) assigned). When I run the model I received the message “Terms with zero df listed …” and when I ask for the wald test of fixed effect one of my effects is missing. How does assigning a pedigree to my data effect the degrees of freedom available to test my fixed effects? Below is my code. “sacode” and “treatcode” are my fixed effects I’m interested in. When I run the model and produce the Wald tests “sacode” is not included. I am using asreml-R4 in R studio.

Example pedigree:

> ped2[1:10,]
   ID Sire Dam
1   1    0   0
2   2    0   0
3   3    0   0
4   4    0   0
5   5    1   1
6   6    1   1
7   7    1   1
8   8    1   1
9   9    1   1
10 10    1   1
> ped2[515:525,]
     ID Sire Dam
515 515    4   4
516 516    4   4
517 517   10 148
518 518   11 152
519 519    9 145
520 520    5 133
521 521   10 149
522 522    7 139
523 523    6 138
524 524   11 151
525 525    9 145

Example code:

> m1 <- asreml(Zlg_1 ~ 
+       1 + treatcode + sacode + treatcode:sacode + Age + Mated + 
+         Block , 
+         random = ~ vm(ID, ped_ai2) + Dam,
+         data = dat) 
Model fitted using the gamma parameterization.
ASReml 4.1.0 Mon Feb 22 11:34:24 2021
          LogLik        Sigma2     DF     wall    cpu
 1     -1816.164      0.442551   2112 11:34:24    0.0
 2     -1744.799      0.379880   2112 11:34:24    0.0
 3     -1681.384      0.307075   2112 11:34:24    0.0
 4     -1649.280      0.235116   2112 11:34:24    0.0
 5     -1637.209      0.159875   2112 11:34:24    0.0
 6     -1634.396      0.104286   2112 11:34:24    0.0
 7     -1633.798      0.070116   2112 11:34:24    0.0
 8     -1633.701      0.052888   2112 11:34:24    0.0
 9     -1633.693      0.046869   2112 11:34:24    0.0
10     -1633.693      0.046003   2112 11:34:24    0.0
Terms with zero df listed in attribute 'zerodf' of the wald table.

> wald.asreml(m1)
Wald tests for fixed effects.
Response: Zlg_1
Terms added sequentially; adjusted for those above.

                 Df Sum of Sq Wald statistic Pr(Chisq)
treatcode         1  0.001408         0.0306    0.8611
Age               1  0.053934         1.1729    0.2788
Mated             1  0.019122         0.4159    0.5190
Block             3  0.228305         4.9650    0.1744
treatcode:sacode  1  0.034669         0.7539    0.3852
residual (MS)        0.045983 

I have tried adding and removing different variables to see if any particular variable is creating an issue but the zerodf message comes up no matter what combination of variables are in the model.