Why are different base learners used in mboost package in R




While using the mboost package,the code below implements three different base-learners in the same model:

model <- mboost(DEXfat ~
                  bols(age) +                 ### a linear function of age
                  btree(hipcirc, waistcirc) + ### a non-linear interaction of hip and waist circumference
                  bbs(kneebreadth),           ### a smooth function of kneebreadth
                  data = bodyfat, control = boost_control(mstop = 100))

I understand that DeXfat is predicted based on three different functions(bols,btree,bbs).
What is the purpose of combining three different models and I also could not understand how to interpret the output of such a model.
Also after creating the model,to visualize the output:

cvm <- cvrisk(model, papply = lapply)
### restrict model to mstop(cvm)
model[mstop(cvm), return = FALSE]
### plot age and kneebreadth
layout(matrix(1:2, nc = 2))
plot(model, which = c("age", "kneebreadth"))

In this output,what is the f-partial in the y-axis??
I know these questions might be quite basic,but can somebody please help me understand this!