R/data download/ellison_2018.r

In chase-lab/BioTIMEx: Aggregating long-term ecological communities data

## ellison_2018


# Package ID: knb-lter-hfr.160.20 Cataloging System:https://pasta.edirepository.org.
# Data set title: Ants and Ecosystem Function in Hemlock Removal Experiment at Harvard Forest since 2006.
# Data set creator:  Aaron Ellison -
# Contact:  Aaron Ellison -  Harvard Forest  - aellison@fas.harvard.edu
# Stylesheet v2.10 for metadata conversion into program: John H. Porter, Univ. Virginia, jporter@virginia.edu

infile1 <- 'data/raw data/ellison_2018/hf160-01-ibuttons.csv'
if(!dir.exists('data/raw data/ellison_2018/') || !file.exists(infile1))   {
   dir.create('data/raw data/ellison_2018/',  showWarnings = FALSE)
   inUrl1  <- "https://pasta.lternet.edu/package/data/eml/knb-lter-hfr/160/20/b1610a7d2f2a95a509af82a7bd01a108"
   download.file(inUrl1, infile1, method="curl")
}


dt1 <-read.csv(infile1,header=F
               ,skip=1
               ,sep=","
               , col.names=c(
                  "datetime",
                  "date",
                  "time.24hr",
                  "soilt",
                  "block",
                  "treatment",
                  "plot",
                  "subplot",
                  "subplot.t"    ), check.names=TRUE)


# Fix any interval or ratio columns mistakenly read in as nominal and nominal columns read as numeric or dates read as strings

# attempting to convert dt1$datetime dateTime string to R date structure (date or POSIXct)
tmpDateFormat<-"%Y-%m-%dT%H:%M"
tmp1datetime<-as.POSIXct(dt1$datetime,format=tmpDateFormat)
# Keep the new dates only if they all converted correctly
if(length(tmp1datetime) == length(tmp1datetime[!is.na(tmp1datetime)])){dt1$datetime <- tmp1datetime } else {print("Date conversion failed for dt1$datetime. Please inspect the data and do the date conversion yourself.\nIssue resolved at data wrangling step.")}
rm(tmpDateFormat,tmp1datetime)
# attempting to convert dt1$date dateTime string to R date structure (date or POSIXct)
tmpDateFormat<-"%Y-%m-%d"
tmp1date<-as.Date(dt1$date,format=tmpDateFormat)
# Keep the new dates only if they all converted correctly
if(length(tmp1date) == length(tmp1date[!is.na(tmp1date)])){dt1$date <- tmp1date } else {print("Date conversion failed for dt1$date. Please inspect the data and do the date conversion yourself.\nIssue resolved at data wrangling step.")}
rm(tmpDateFormat,tmp1date)
if (class(dt1$soilt)=="factor") dt1$soilt <-as.numeric(levels(dt1$soilt))[as.integer(dt1$soilt) ]
if (class(dt1$soilt)=="character") dt1$soilt <-as.numeric(dt1$soilt)
if (class(dt1$block)!="factor") dt1$block<- as.factor(dt1$block)
if (class(dt1$treatment)!="factor") dt1$treatment<- as.factor(dt1$treatment)
if (class(dt1$plot)!="factor") dt1$plot<- as.factor(dt1$plot)
if (class(dt1$subplot)!="factor") dt1$subplot<- as.factor(dt1$subplot)
if (class(dt1$subplot.t)!="factor") dt1$subplot.t<- as.factor(dt1$subplot.t)

# Convert Missing Values to NA for non-dates

dt1$soilt <- ifelse((trimws(as.character(dt1$soilt))==trimws("NA")),NA,dt1$soilt)


infile2 <- 'data/raw data/ellison_2018/hf160-02-subplots.csv'
if(!dir.exists('data/raw data/ellison_2018/') || !file.exists(infile2))   {
   dir.create('data/raw data/ellison_2018/',  showWarnings = FALSE)
   inUrl2  <- "https://pasta.lternet.edu/package/data/eml/knb-lter-hfr/160/20/4b3cebe94958392ef8cff25409565fa1"
   download.file(inUrl2, infile2, method="curl")
}


dt2 <-read.csv(infile2,header=F
               ,skip=1
               ,sep=","
               , col.names=c(
                  "treatment",
                  "block",
                  "plot",
                  "subplot",
                  "subplot.t",
                  "x.m",
                  "y.m",
                  "elevation"    ), check.names=TRUE)


# Fix any interval or ratio columns mistakenly read in as nominal and nominal columns read as numeric or dates read as strings

if (class(dt2$treatment)!="factor") dt2$treatment<- as.factor(dt2$treatment)
if (class(dt2$block)!="factor") dt2$block<- as.factor(dt2$block)
if (class(dt2$plot)!="factor") dt2$plot<- as.factor(dt2$plot)
if (class(dt2$subplot)!="factor") dt2$subplot<- as.factor(dt2$subplot)
if (class(dt2$subplot.t)!="factor") dt2$subplot.t<- as.factor(dt2$subplot.t)
if (class(dt2$x.m)=="factor") dt2$x.m <-as.numeric(levels(dt2$x.m))[as.integer(dt2$x.m) ]
if (class(dt2$x.m)=="character") dt2$x.m <-as.numeric(dt2$x.m)
if (class(dt2$y.m)=="factor") dt2$y.m <-as.numeric(levels(dt2$y.m))[as.integer(dt2$y.m) ]
if (class(dt2$y.m)=="character") dt2$y.m <-as.numeric(dt2$y.m)
if (class(dt2$elevation)=="factor") dt2$elevation <-as.numeric(levels(dt2$elevation))[as.integer(dt2$elevation) ]
if (class(dt2$elevation)=="character") dt2$elevation <-as.numeric(dt2$elevation)

# Convert Missing Values to NA for non-dates

dt2$x.m <- ifelse((trimws(as.character(dt2$x.m))==trimws("NA")),NA,dt2$x.m)
dt2$y.m <- ifelse((trimws(as.character(dt2$y.m))==trimws("NA")),NA,dt2$y.m)
dt2$elevation <- ifelse((trimws(as.character(dt2$elevation))==trimws("NA")),NA,dt2$elevation)





infile3 <- 'data/raw data/ellison_2018/hf160-03-ants.csv'
if(!dir.exists('data/raw data/ellison_2018/') || !file.exists(infile3))   {
   dir.create('data/raw data/ellison_2018/',  showWarnings = FALSE)
   inUrl3  <- "https://pasta.lternet.edu/package/data/eml/knb-lter-hfr/160/20/8821e0b89318cfb2204f9acc17287e0f"
   download.file(inUrl3, infile3, method="curl")
}

dt3 <-read.csv(infile3, header=F
               ,skip=1
               ,sep=","
               , col.names=c(
                  "date",
                  "treatment",
                  "block",
                  "plot",
                  "subplot",
                  "subplot.t",
                  "vial.num",
                  "subfamily",
                  "genus",
                  "species",
                  "spec.code",
                  "count"    ), check.names=TRUE)


# Fix any interval or ratio columns mistakenly read in as nominal and nominal columns read as numeric or dates read as strings

# attempting to convert dt3$date dateTime string to R date structure (date or POSIXct)
tmpDateFormat<-"%Y-%m-%d"
tmp3date<-as.Date(dt3$date,format=tmpDateFormat)
# Keep the new dates only if they all converted correctly
if(length(tmp3date) == length(tmp3date[!is.na(tmp3date)])){dt3$date <- tmp3date } else {print("Date conversion failed for dt3$date. Please inspect the data and do the date conversion yourself.")}
rm(tmpDateFormat,tmp3date)
if (class(dt3$treatment)!="factor") dt3$treatment<- as.factor(dt3$treatment)
if (class(dt3$block)!="factor") dt3$block<- as.factor(dt3$block)
if (class(dt3$plot)!="factor") dt3$plot<- as.factor(dt3$plot)
if (class(dt3$subplot)!="factor") dt3$subplot<- as.factor(dt3$subplot)
if (class(dt3$subplot.t)!="factor") dt3$subplot.t<- as.factor(dt3$subplot.t)
if (class(dt3$vial.num)!="factor") dt3$vial.num<- as.factor(dt3$vial.num)
if (class(dt3$subfamily)!="factor") dt3$subfamily<- as.factor(dt3$subfamily)
if (class(dt3$genus)!="factor") dt3$genus<- as.factor(dt3$genus)
if (class(dt3$species)!="factor") dt3$species<- as.factor(dt3$species)
if (class(dt3$spec.code)!="factor") dt3$spec.code<- as.factor(dt3$spec.code)
if (class(dt3$count)=="factor") dt3$count <-as.numeric(levels(dt3$count))[as.integer(dt3$count) ]
if (class(dt3$count)=="character") dt3$count <-as.numeric(dt3$count)

# Convert Missing Values to NA for non-dates
dt3$count <- ifelse((trimws(as.character(dt3$count))==trimws("NA")),NA,dt3$count)

ddata <- dt3
save(ddata, file='data/raw data/ellison_2018/ddata')



if(FALSE) {
   # Nitrogen data

   infile4 <- 'data/raw data/ellison_2018/hf160-04-nitrogen.csv'
   if(!dir.exists('data/raw data/ellison_2018/') || !file.exists(infile4))   {
      dir.create('data/raw data/ellison_2018/',  showWarnings = FALSE)
      inUrl4  <- "https://pasta.lternet.edu/package/data/eml/knb-lter-hfr/160/20/ae3924330258eef88d26f8abe7cdf4d1"
      download.file(inUrl4, infile4, method="curl")
   }


   dt4 <-read.csv(infile4, header=F
                  ,skip=1
                  ,sep=","
                  , col.names=c(
                     "year",
                     "quarter",
                     "treatment",
                     "block",
                     "plot",
                     "subplot",
                     "subplot.t",
                     "res.mass",
                     "tot.nh4",
                     "tot.no3",
                     "res.nh4",
                     "res.no3",
                     "tot.n",
                     "res.n",
                     "daily.nh4",
                     "daily.no3",
                     "daily.n"    ), check.names=TRUE)


   # Fix any interval or ratio columns mistakenly read in as nominal and nominal columns read as numeric or dates read as strings

   if (class(dt4$quarter)!="factor") dt4$quarter<- as.factor(dt4$quarter)
   if (class(dt4$treatment)!="factor") dt4$treatment<- as.factor(dt4$treatment)
   if (class(dt4$block)!="factor") dt4$block<- as.factor(dt4$block)
   if (class(dt4$plot)!="factor") dt4$plot<- as.factor(dt4$plot)
   if (class(dt4$subplot)!="factor") dt4$subplot<- as.factor(dt4$subplot)
   if (class(dt4$subplot.t)!="factor") dt4$subplot.t<- as.factor(dt4$subplot.t)
   if (class(dt4$res.mass)=="factor") dt4$res.mass <-as.numeric(levels(dt4$res.mass))[as.integer(dt4$res.mass) ]
   if (class(dt4$res.mass)=="character") dt4$res.mass <-as.numeric(dt4$res.mass)
   if (class(dt4$tot.nh4)=="factor") dt4$tot.nh4 <-as.numeric(levels(dt4$tot.nh4))[as.integer(dt4$tot.nh4) ]
   if (class(dt4$tot.nh4)=="character") dt4$tot.nh4 <-as.numeric(dt4$tot.nh4)
   if (class(dt4$tot.no3)=="factor") dt4$tot.no3 <-as.numeric(levels(dt4$tot.no3))[as.integer(dt4$tot.no3) ]
   if (class(dt4$tot.no3)=="character") dt4$tot.no3 <-as.numeric(dt4$tot.no3)
   if (class(dt4$res.nh4)=="factor") dt4$res.nh4 <-as.numeric(levels(dt4$res.nh4))[as.integer(dt4$res.nh4) ]
   if (class(dt4$res.nh4)=="character") dt4$res.nh4 <-as.numeric(dt4$res.nh4)
   if (class(dt4$res.no3)=="factor") dt4$res.no3 <-as.numeric(levels(dt4$res.no3))[as.integer(dt4$res.no3) ]
   if (class(dt4$res.no3)=="character") dt4$res.no3 <-as.numeric(dt4$res.no3)
   if (class(dt4$tot.n)=="factor") dt4$tot.n <-as.numeric(levels(dt4$tot.n))[as.integer(dt4$tot.n) ]
   if (class(dt4$tot.n)=="character") dt4$tot.n <-as.numeric(dt4$tot.n)
   if (class(dt4$res.n)=="factor") dt4$res.n <-as.numeric(levels(dt4$res.n))[as.integer(dt4$res.n) ]
   if (class(dt4$res.n)=="character") dt4$res.n <-as.numeric(dt4$res.n)
   if (class(dt4$daily.nh4)=="factor") dt4$daily.nh4 <-as.numeric(levels(dt4$daily.nh4))[as.integer(dt4$daily.nh4) ]
   if (class(dt4$daily.nh4)=="character") dt4$daily.nh4 <-as.numeric(dt4$daily.nh4)
   if (class(dt4$daily.no3)=="factor") dt4$daily.no3 <-as.numeric(levels(dt4$daily.no3))[as.integer(dt4$daily.no3) ]
   if (class(dt4$daily.no3)=="character") dt4$daily.no3 <-as.numeric(dt4$daily.no3)
   if (class(dt4$daily.n)=="factor") dt4$daily.n <-as.numeric(levels(dt4$daily.n))[as.integer(dt4$daily.n) ]
   if (class(dt4$daily.n)=="character") dt4$daily.n <-as.numeric(dt4$daily.n)

   # Convert Missing Values to NA for non-dates

   dt4$res.mass <- ifelse((trimws(as.character(dt4$res.mass))==trimws("NA")),NA,dt4$res.mass)
   dt4$tot.nh4 <- ifelse((trimws(as.character(dt4$tot.nh4))==trimws("NA")),NA,dt4$tot.nh4)
   dt4$tot.no3 <- ifelse((trimws(as.character(dt4$tot.no3))==trimws("NA")),NA,dt4$tot.no3)
   dt4$res.nh4 <- ifelse((trimws(as.character(dt4$res.nh4))==trimws("NA")),NA,dt4$res.nh4)
   dt4$res.no3 <- ifelse((trimws(as.character(dt4$res.no3))==trimws("NA")),NA,dt4$res.no3)
   dt4$tot.n <- ifelse((trimws(as.character(dt4$tot.n))==trimws("NA")),NA,dt4$tot.n)
   dt4$res.n <- ifelse((trimws(as.character(dt4$res.n))==trimws("NA")),NA,dt4$res.n)
   dt4$daily.nh4 <- ifelse((trimws(as.character(dt4$daily.nh4))==trimws("NA")),NA,dt4$daily.nh4)
   dt4$daily.no3 <- ifelse((trimws(as.character(dt4$daily.no3))==trimws("NA")),NA,dt4$daily.no3)
   dt4$daily.n <- ifelse((trimws(as.character(dt4$daily.n))==trimws("NA")),NA,dt4$daily.n)
}