rm(list = ls()) 
setwd("") #set your working directory
library(foreign) 
library(data.table)
library(reshape2)
library(stringr)
library(ggplot2)

BBS <- rbindlist(lapply(list.files("",full.names=TRUE),read.csv)) #this needs to have the full path name to your folder of all the BBS CSV files
BBS$rteno <- paste(BBS$statenum,formatC(BBS$Route, width=3, flag="0"),sep="") 
speciesnames <- read.csv("SpeciesList.csv") 

routeinfo <- read.csv("weather.csv") 
routeinfo$rteno <- paste(routeinfo$statenum,formatC(routeinfo$Route, width=3, flag="0"),sep="") 
routeinfo <- routeinfo[c("RouteDataId","Year","ObsN","rteno","EndWind","StartWind","RunType","RPID")]
routeinfo$firstyear <- c(1L,routeinfo$ObsN[-1]!=routeinfo$ObsN[-nrow(routeinfo)])

BBS$countrynum <- NULL
BBS$rteno <- paste(BBS$statenum,formatC(BBS$Route, width=3, flag="0"),sep="") 
BBS$StopTotal <- NULL
BBS <- merge(BBS,routeinfo,by=c("rteno","Year"))

route_data <- read.csv("routes.csv")
route_data$rteno <- paste(route_data$statenum,formatC(route_data$Route, width=3, flag="0"),sep="") 
route_data <- route_data[c("BCR","rteno")]

BBS <- merge(BBS,route_data,by="rteno")
#if you only want to keep data from a certain BCR...
#BBS <- BBS[BBS$BCR %in% c(), ]

vcf <- read.dbf("landcover/bbs_buffers.dbf")
vcf <- vcf[,c("rteno",grep("[[:digit:]]", names(vcf), perl=TRUE, value=TRUE))]
vcf <- melt(vcf,id=c("rteno","interval"))
vcf$variable <- as.character(vcf$variable)
vcf$Year <- str_extract(vcf$variable,"[[:digit:]]+")
vcf$var <- sapply(strsplit(vcf$variable, "[[:digit:]]+"),"[[",2)
vcf$variable <- NULL
vcf <- dcast(vcf,rteno ~ var,fun.aggregate=mean)

vcf$rteno <- as.character(vcf$rteno)
vars <- merge(vcf,routeinfo,by="rteno")

#set bird to the AOU code of your species of interest
dataperspecies <- subset(BBS[which(BBS$Aou == bird),]) 
vars$abundance <- dataperspecies$count[match(vars$rteno, dataperspecies$rteno)]
vars[is.na(vars)] <- 0

assess <- data.table(vars)
whattodrop <- assess[,list(abundance=sum(abundance)),by='rteno']
droprtes <- whattodrop$rteno[whattodrop$abundance==0]
vars <- vars[!(vars$rteno %in% droprtes),]
vars <- vars[vars$RunType > 0,]
vars <- vars[vars$RPID < 102]