Main question: "What are the contributing variates to daily movement distances?"

Specifically my question today relates to:

"What is the contribution related to gender, and then within female what are the effects related to those females having young?"

I have multiple readings per animal (hundreds per individual), with 13 individuals (5 females and 8 males). The females sometimes have young with them, and I know this contributes to the distance they move.

I have several contributing factors in a GLMM; I am using the nlme::lme function. The current form is:

lm1 <- lme(movedistance ~ Gender+YoungPresent+x3+x4+x5+x6, random  = ~1|AnimalID/Month, data = df1)

There is no significant gender effect in this current model; however I know that this is mis-specified, because males never have young; but I don't know how to fix it. "YoungPresent" is a binary term, it is always 0 for males, and 0 or 1 for females, 1 when they have young. What I want is to somehow remove the attribution of variation by "YoungPresent" to males in the "Gender" term, but not from females.

Please let me know what is the correct term for what I am looking for (Crossed? Nested?), and how I can correctly specify this structure in lme.