In short, my experimental design involves sampling along multiple transects in a pond.

Along these transects, I've established THREE depth zones from which samples are taken: (1) Edge, (2) Shallow, and (3) Deep. So, for every transect (n=5) there are three zones (k=3), giving a total sample size of 15. A sampling tube of known area is pushed through the water column into the substrate to isolate all macro organisms in the water column. Once a sampling column is established, temp (at the bottom of the column), D.O., depth, and pH are measured. Then, tadpoles and dragonfly nymphs are collected from the tube sampler and counted. THESE variables are killing me.

So - in theory, this design should allow me to assess the fine spatial distribution of tadpoles based on how many were found in the three depth zones - as well as relate the non-uniform distribution to variations in abiotic and biotic factors.

Are my data referring to the number of tadpoles and dragonfly larvae collected from the tube sampler considered a measurement variable (meristic) or categorical?

So far, I have used a One-Way Anova with Tuk's HSD to determine if the average number of tadpoles collected across the three depth zones are significantly different, followed by Tuk's to determine which one is significantly different.

Is my use of the ANOVA invalid considering the nature of my variable, or should I just use the Chi square test where the null: the number of tadpoles found in the three depth zones are uniform, OR can i add a constant to my data (I do have zeros for some values) and use a square root transformation to strengthen the results of the ANOVA? I could also convert the number of tadpoles found to density of tadpoles because I am sampling with a tube of known area (BUT VARYING VOLUME), but would this frowned upon?

Thank you for all you help, I am really struggling with this and will appreciate any type of contribution.