BUG: behaviour of skipna=None changed on master
### 

- [X] I have checked that this issue has not already been reported.
- [X] I have confirmed this bug exists on the [latest version](https://pandas.pydata.org/docs/whatsnew/index.html) of pandas.
- [X] I have confirmed this bug exists on the master branch of pandas.


### Reproducible Example

```python
import pandas as pd
import numpy as np
pd.Series([1.7, 0.5, np.nan]).sum(skipna=None)
```


### Issue Description

In pandas 1.3.4 the example returns `2.2` on nightly it returns `nan`.

This lead to a test failure in xarray (we use pandas to double check a result - so we get a wrong `expected` value & could fix this but I still think this should not change silently).

### Expected Behavior

I think this should still return 2.2 or raise a deprecation warning or an error.

### Installed Versions

pandas was installed from scipy-wheels-nightly:

```bash
python -m pip install -i https://pypi.anaconda.org/scipy-wheels-nightly/simple --no-deps --pre --upgrade --force-reinstall  pandas
```


<details>

INSTALLED VERSIONS
------------------
commit           : 9018d327defbe4d397eadc342e489e79bbc14b71
python           : 3.9.7.final.0
python-bits      : 64
OS               : Linux
OS-release       : 5.11.0-38-generic
Version          : #42~20.04.1-Ubuntu SMP Tue Sep 28 20:41:07 UTC 2021
machine          : x86_64
processor        : x86_64
byteorder        : little
LC_ALL           : None
LANG             : en_US.UTF-8
LOCALE           : en_US.UTF-8

pandas           : 1.4.0.dev0+972.g9018d327de
numpy            : 1.20.3
pytz             : 2021.3
dateutil         : 2.8.2
pip              : 21.3.1
setuptools       : 58.2.0
Cython           : None
pytest           : 6.2.5
hypothesis       : 6.24.0
sphinx           : None
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : 4.6.3
html5lib         : None
pymysql          : None
psycopg2         : None
jinja2           : 3.0.2
IPython          : 7.28.0
pandas_datareader: None
bs4              : 4.10.0
bottleneck       : 1.3.2
fsspec           : 2021.10.1
fastparquet      : None
gcsfs            : None
matplotlib       : 3.4.3
numexpr          : 2.7.3
odfpy            : None
openpyxl         : None
pandas_gbq       : None
pyarrow          : None
pyxlsb           : None
s3fs             : None
scipy            : 1.7.1
sqlalchemy       : None
tables           : None
tabulate         : None
xarray           : 0.19.1.dev89+gfdabf3be
xlrd             : None
xlwt             : None
numba            : 0.54.1


</details>
