Thank you Staasis for taking the time to explain again, I assure you, the form changes a lot. Thanks aslo for others to take time,

for the latter it's almost how i understand my problem but i doesn't find adequat statistical test witch excludes/controls the prorata time factor

For Staasis

I am well aware that there are only 3 classes but statistically, regularly 2 percentages for example - so 2 modalities between them - are compared with robust methods. This distribution in 3 modalities, could return in 3 tests of each of the modalities transformed into % versus its opposite (% of 1 and % non-1; % of 2 and % non-2,...). So three modes is not necessarily unquestionable? No?

I could increase the number of modalities (for example, from small/medium/large to small/medium/medium-high/high) but this brings little, what is interesting is the effect of extreme modalities where the counted numbers are already the lowest.

(I deliberately disguised a quantitative variable as a categorical variable by grouping values together, hence the trace in the ordering of the 3 modalities small/medium/large).

I am also aware that the time factor (hence my initial title prorata temporis) is a problem but I do not control it, the modality occurs in the year in an uneven way, I can only measure their effect on the fish stock.

I'm giving you another lead, can you tell me what you think? If I artificially free myself from the time factor, for example by levelling it by drawing the same number of hours of observations within each of the modalities, there would be an appropriate statistical test on these three values (sum of fish), type Chi2, other ?

Does that make sense?

I lose information but I remove a variable, duration, which parasitizes me:

1 single factor tested, of 3 - possibly 4- modalities (of the same collection effort, duration), high numbers of fish per modality (well over 5), possibly 2 series of values (2 potentially possible random draws in each modality) ? or again "a naivety"?

thank you in advance,