Dear Friends, I have a data set of a cyclone impacted estuary. This dataset involve bunch of physical-chemical variables and copepod density data of multiple species. I have collected the data immediate after a cyclone so species no expanded from few to 16 in 7 days and I stopped the study. I had collected data from three sites.
I have tested site specific variations that is not significant for physical-chemical parameters and diversity indices. A reviewer recently wrote back to me " I am therefore, left wondering: why did you not consider multivariate analysis to assess the sequential change in copepod species/abunance dynamics following the impact of Cyclone...? An ordination protocol for example could show how either sites or sampling periods".
Doing multivariate is not a problem for me but I refrained from it seeing the community is unstable therefore CCA type analysis may over look many details of changes. I instead have done univariate following GLMS. What is your theoretical or philosophical opinion on this issue.
Thanks
Dr. Sourav Paul
University of Calcutta
Multivariate analysis will give you a more conceptual perspective on which variables are driving the Copepods' community, therefore you can run a Spearman correlation ranking using PRIMER based on p-values to opt for combination of variables that have significant impact in the Copepods' biomass. Or else do an Ecosim with Ecopath model. I hope I make sense.
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