"0","```r
# pollen.datasets <- get_dataset(datasettype=\"pollen\", loc=c(-105, 40, -86, 49), ageyoung = 8000)
# browse(pollen.datasets)
# 
# # pollen.downloads <- get_download(pollen.datasets)
# # save(pollen.downloads, file=\"data/pollen.downloads.RData\")
# load(\"data/pollen.downloads.RData\")
# 
# # Standardize the taxonomy
# pollen.whit <- compile_taxa(pollen.downloads, list.name=\"WhitmoreSmall\")
# pollen.ages <- ages(pollen.whit)
# 
# # find the closest sample to the focal time and save the pollen counts for that sample
# # Note: the loop code not working yet.
# focalTime <- 12000
# pollen.whit.focal <- matrix(nrow=length(pollen.ages), ncol= ncol(pollen.whit[[i]]$counts))
# for (i in 1:length(pollen.ages)){
#   sampleRow <- which.min(abs(focalTime - pollen.ages[[i]]$age))
#   pollen.whit.focal[i,] <- pollen.whit[[i]]$counts[sampleRow,]
# }
# 
# #Stratiplot(pollen.whit[[1]]$counts, pollen.whit[[1]]$chronologies[[1]]$age, ylab=\"Age (cal BP)\", sort=\"wa\", c(\"poly\",\"g\"))
# 
# whit.counts <- lapply(pollen.whit, '[[', 4) 
# whit.S.obs <- lapply(whit.counts, specnumber)
# whit.shannon <- lapply(whit.counts, diversity, \"shannon\")
```"
