Hello,
I have a large data set which consists of ~24,000 identified beetle specimens, which were collected weekly over the course of a few weeks at a dozen sites.
My goal is to quantify how many types of communities were collected at collection week 1, collection week 2, 3, etc. A hypothetical example would be at collection week 1, we identified two types of communities, one dominated by species A, and one dominated by species A & B. And so on for the other time periods. Then I'd like to connect natural history with this. Is there a way to mathematically quantify the number of types of communities, instead of just describing the observed data? I imagine this is something done with plant succession post fires, or something along those lines, but I haven't found anything.
I use R program as well.
Thank you.
You must to use principal component analysis (PCA) and then cluster analysis (CA) with the principal components.
Miguel Angel García-Alvarado Thank you -- you are absolutely right. Then I could see which beetle species have the largest loading score magnitudes on community structure.
I would try various multi-variate ordination methods – PCA, DCA, CA, NMDS
Thank you. but I think statics method will be helpful here and Math-cad program will come very handy.
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