I made a series of posts of how to get BBS data and import it into R, as well as an example of predictor data for a model, and how to get that into R. Here I’ll collect it all into a step-by-step by linking to those posts.
- How to get BBS data
- Importing BBS data into R
- Getting predictor data (in my case, remote sensing imagery)
- Summarizing images for BBS routes
- Making a data frame for a single species analysis (zero-filling)
Here’s the total script at the end of all the posts: bbs_species
To get started, pick a Bird Conservation Region of interest, and a species. Take the BCR specification line out of comment (remove the #) and specify the number(s) of the BCR(s) within the empty vector. Set the “bird” variable to be the AOU code of your chosen species from the species list (if you choose from that link, remember to remove the leading zero). For instance, to look at eastern wood-pewees in the Blue Ridge…
BBS <- BBS[BBS$BCR %in% c(28), ] bird <- 4610
Another thought is how to handle nuisance effects. I consider route and observer to be linked, so that I concatenate them for a random effect.
vars$rteobs <- paste(vars$rteno,vars$ObsN,sep="_")
You now have a data frame of BBS data for a single species matched up with remotely sensed data (i.e. ready for an analysis). Half the battle is the data acquisition, cleaning and shaping! 🙂
Now try an example analysis.