I have formatted my abundance data for 138 vegetation plots of paired pre-fire and post-fire data for iNEXT by collapsing my count data into counts for all pre-fire and post-fire plots. Counts are in numbers per ha because the plot sizes differed between the pre- and post-fire sampling interval. When I run iNEXT and specify se=T and conf=0.95, I end up with very small confidence intervals that don't show up at all when I plot them using the ggiNEXT command. I am writing to know if I'm doing something wrong, or if these results are correct.
calculate the rarefaction/extrapolation curve (R/E)
out <- iNEXT(master, q=c(0, 1, 2), se=T,conf = 0.95,datatype="abundance") out
Now plot sample-size-based R/E curves, separating by "time-step""
and plotting the curve with 95% confidence intervals
ggiNEXT(out, type=1, facet.var="order", se=T,color.var="order") + theme_bw(base_size=8)
calculate the rarefaction/extrapolation curve (R/E)
out <- iNEXT(master, q=c(0, 1, 2), se=T,conf = 0.95,datatype="abundance") out
Now plot sample-size-based R/E curves, separating by "time-step""
and plotting the curve with 95% confidence intervals
ggiNEXT(out, type=1, facet.var="order", se=T,color.var="order") + theme_bw(base_size=8)
I would expect that these CIs would be larger, as they were when I did these analyses via Rob Colwell's EstimateS GUI software in which I was able to specify the results without collapsing the data into two columns of species counts (pre- vs. post-fire). I.E, in EstimateS, I was able to use all plot count data for all plots to construct the rarefaction curves and CIs. Any idea if these iNEXT results are plausible?