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Small sample Size; repeated measurements binomial glmer

Hello,

I searched a lot in the internet, but i didn't find sufficient information.
I believe I've got a very simple study design, however there are some 
characteristics taking me to the brink of possible.

I have two sampling campaigns, autumn year 1 and autumn year 2,
I sampled five agricultural fields of different ages, but each age_class 
has got only 3 repetitions.
My response is proportion of fungal feeding species.

I am interested in the effect of age classes (increase over time) and if 
this effect is reflected during the time of sampling.
Since i should be able to observe an increase during a 1 year time 
interval, then.

My Model is:
glmer(response ~ age_class*autumn + (1|field), family="binomial", 
weights=total number of Individuals, data)

However, I have the following problems:

1 - My N = 30, but my N(group) = 3
1 - I don't know the power of my analysis
2 - I'm not able to drop Outliers from the data (or am I?)
3 - my random factor has only 2 levels, so N(random) = 2

I think in Bolker et al. (2008) und Zuur et al. (2009) st. is said about 
that there is no need to use random factors when N(random) = 2

Since I am quite confused about my opportunities to handle patterns in 
residuals of the above model, I'm asking you about your opinions. Have i 
chosen the right Model formulation?

I think I'd feel more confident with a non parametric test, sth. like a 
rank based estimation of mixed effects nested models (rlme package), for 
which i found not a single example how to use them with repeated 
measures (also for PERMANOVA), or sth. else.
At least i need to report an Anova table and pairwise comparisons

yours sincerely,
Quentin