What statistical test to use for species abundance between wet and dry season?

#1
Sorry if this question is trivial,

I have a collection of camera trap data of recorded species during the rainy season and the dry season.

I am confused how to lay out a table to import to R, do I have species down the left (then counts of how many of that species) and columns of wet season and dry season?

Also, I am confused on what statistical test to use :(


I've read so many books and websites and every thing seems to be contradicting each other, please can anyone help!
 

gianmarco

TS Contributor
#3
Just to complement rogojel's advice, my guess is that you are seeking to assess if there is a significant difference between rainy and dry season; put in another way, you may want to test if there is a "correlation" between species and season.
I think that the first step would be building a cross-tabulation of species against season. Depending on the number of species you are studying, you would end up building a Rx2 table, where R is the number of species, 2 is the number of seasons.

Should this be the case, you may want to use something like Pearson's chi-square test.
 
#4
Just to complement rogojel's advice, my guess is that you are seeking to assess if there is a significant difference between rainy and dry season; put in another way, you may want to test if there is a "correlation" between species and season.
I think that the first step would be building a cross-tabulation of species against season. Depending on the number of species you are studying, you would end up building a Rx2 table, where R is the number of species, 2 is the number of seasons.

Should this be the case, you may want to use something like Pearson's chi-square test.
Hi, thanks for the reply, at the moment my data is laid out like this;

Species Wet Season Dry Season
Jaguar 6 4
Ocelot 3 2
currassow 17 14
etc...

I want to find out that if there is a significant difference between the abundance of all species in wet and dry seasons. I hope to find out that as the wet season is likely to be more profitable for both predators and prey so most of the species should be more abundant?

Would it still be using a test for two samples? e.g. wilcoxon or t-test.

thanks
 
#5
Hi, you can investigate if your data are normally distributed (i.e., the data for "wet season" as well as for "dry season" separately, e.g. using a QQ-plot or a Shapiro-Wilk-Test). If tey are normally distributed you can use a T-test to asses your question. If not, you can use a Wilcoxon rank sum test.
 

gianmarco

TS Contributor
#6