fillna on dataset converts all variables to float

MCVE Code Sample

xr.Dataset(
     {
         "A": ("x", [np.nan, 2, np.nan, 0]),
         "B": ("x", [3, 4, np.nan, 1]),
         "C": ("x", [True, True, False, False]),
         "D": ("x", [np.nan, 3, np.nan, 4])
     },
     coords={"x": [0, 1, 2, 3]}
).fillna(value={"A": 0})

<xarray.Dataset>
Dimensions:  (x: 4)
Coordinates:
  * x        (x) int64 0 1 2 3
Data variables:
    A        (x) float64 0.0 2.0 0.0 0.0
    B        (x) float64 3.0 4.0 nan 1.0
    C        (x) float64 1.0 1.0 0.0 0.0
    D        (x) float64 nan 3.0 nan 4.0

Expected Output

<xarray.Dataset>
Dimensions:  (x: 4)
Coordinates:
  * x        (x) int64 0 1 2 3
Data variables:
    A        (x) float64 0.0 2.0 0.0 0.0
    B        (x) float64 3.0 4.0 nan 1.0
    C        (x) bool True True False False
    D        (x) float64 nan 3.0 nan 4.0

Problem Description

I'd like to use fillna to replace NaN's in some of a Dataset's variables.
However, fillna unexpectably converts all variables to float, even if they are boolean or integers.

Would it be possible to apply fillna only on float / object types and consider the value argument, if I only want to apply fillna to a subset of the dataset?

Output of xr.show_versions()

Start from the Dataset.fillna entry point and reproduce the supplied MCVE with the listed Python, NumPy, pandas, and xarray versions. Check how applying a value to variable A affects the other variables, then add coverage for the expected result: A is filled while boolean C remains boolean and unrelated variables retain their types.