Master Post: BBS 10-Stop Data

This one may not be as step-by-step, because the GIS layer of BBS routes I have may not have been published yet. Nonetheless, here’s what I did.

1. Cleaning up the spatial data and splitting routes
2. Assigning segment order once the routes are split
3. Summarizing spatial covariates by segment
4. Determining which segments can be considered the same
5. Importing BBS and spatial data into R at the segment level

The final step looks similar to the route-level tutorial, but with pieceID being the variable to match on. Set “bird” to the AOU code of your species of interest.

dataperspecies <- subset(BBS[which(BBS$Aou == bird),]) 
vars$abundance <- dataperspecies$count[match(vars$pieceID, dataperspecies$pieceID)]
vars[is.na(vars)] <- 0

assess <- data.table(vars)
whattodrop <- assess[,list(abundance=sum(abundance)),by='rteno']
droprtes <- whattodrop$rteno[whattodrop$abundance==0]
perspp <- vars[!(vars$rteno %in% droprtes),]
perspp$Year <- as.integer(perspp$Year)
perspp$yearfix <- perspp$Year
perspp <- perspp[perspp$RunType > 0,]
#vars <- vars[vars$RPID < 102]
perspp <- perspp[c("Year","MN","firstyear","rteno","ObsN","abundance")]

Here is the full script: bbs_10stop_species