Dear everyone,
I want to compared the relative abundances of two bird counting methods. I
am using the proportions instead of the numbers itself, because i dont want
to argue that one method have the same effort or chance to capture the same
amount of information, just want to know if the structure and composition of
the data are similar. I am going to use several methods to compare the
composition and in the case of structure basically the diversities with
grades of significance. The problem is that i also want to compare the
structure of two samples and choose a good statistical test. Anova and other
tests have some asummptions that i dont think im going to fulfill for all my
samples. All that kind of tests compare means so i have to use proportions
or densities but make a lot of data standarized (arbitrary). For example i
have read some papers that compare point counts and mist nets using an
analizing unit like species counts per 4 point counts or 100 mistnet/hours.
In such cases i have lot of data for each species to compare the means but
you have to much arbitrary or unconscious assumptions like "each point or
mist net study area at any time have to represent what the second round of
count is going to have". I will be very thankful if anyone can help me
selecting a simple method to compare the abundances between two samples. For
data like this

sp. Sample 1 Sample 2
1 65 30
2 0 1
3 20 3
4 5 0
5 12 13

Because sample 1 and 2 are data from different census techniques i am going
to use proportions. Then i want to compare not the means but the proportions
of each species so i can have a significance of the similarity or
dissimilarity of the tendency of the proportions based on the comparisons of
the values between the species. At last i can say if sample 1 have the same
results or not from number 2. Starting with this i can use another methods
just to corroborate this at a level of comparing different places with
different census method ( more than 2 samples) with ordination graphs like
deternded correspondence analysis, just to be more easy to visualize and
understand the conclusions.

Best Regards,

Eveling T fernandez
Lima - Peru