databaseUtils/R/importcommunity.r
In Between-the-Fjords/seedclim-data: Code for Cleaning SeedClim data
####################
#todo############
#check species in taxon table before inserting
#merge subturf taxa
####################
#for loop
import_data <- function(file, con, merge_dictionary){
#browser()
print(file)
chkft <- c("pleuro","acro", "liver", "lichen", "litter" ,"soil", "rock", "totalVascular", "totalBryophytes", "totalLichen", "vegetationHeight", "mossHeight")
f <- readLines(file, warn = FALSE) %>%
if_else(condition = substring(., 1, 1) == "\"", true = {
gsub(pattern = "^\"", replacement = "", x = .) %>% #replace starting quote
gsub(pattern = "\"\"", replacement = "\"", x = .) %>% #replace double quotes
gsub(pattern = "\"\"$", replacement = "\"", x = .) %>% #replace double quotes that was part of a triple at end
#gsub(pattern = "(?<!\\)),\"$", replacement = ",", x = ., perl = TRUE) #-ve look behind fixes Veskre comment problem
gsub(pattern = ",\"$", replacement = ",", x = .) #-ve remove end quote
}, false = .) %>%
paste(collapse = "\n")
dat <- read.delim(text = f, sep = ";", dec = ",", stringsAsFactors = FALSE)#sep = ";", dec = ","
if(ncol(dat) > 10){
if(any(sapply(dat[, chkft], class) == "character"))
dat <- read.delim(text = f, sep = ";", dec = ".", stringsAsFactors = FALSE)#sep = ";", dec = "."
}else{
dat <- read.delim(text = f, sep = ",", dec = ".", stringsAsFactors = FALSE)
}
names(dat) <- make.names(names(dat))
dat <- dat %>%
filter(!is.na(turfID), turfID != "", turfID != "turfID") %>%
mutate(
turfID = trimws(turfID),
comment = as.character(comment),
year = as.integer(year)
)
head(dat)
names(dat)
Encoding(dat$comment) <- "latin1"
#remove numeric suffix on duplicates
names(dat) <- gsub("_\\d$", "", names(dat))
#extract turf data####
#fix typos in turfID
dat <- dat %>%
mutate(turfID = recode(turfID,
"515 TT4 247" = "515 TT4 274",
"277 TTC" = "286 TTC",
"192 TT4 29" = "192 TT4 299"))
turf <- dat %>%
select(turfID, matches("treat$"), one_of(c("originPlotID", "destinationPlotID"))) %>%
distinct() %>%
mutate_all(trimws)
turf
names(turf)
alreadyIn <- dbGetQuery(con,"select turfID from turfs")
newTurfs <- turf %>%
anti_join(alreadyIn) %>% #find which turfs IDs are not already in database
select(where(~!(all(is.na(.x))))) #remove empty columns to avoid type conflicts
if(nrow(newTurfs) > 0) {
message("adding ", paste(newTurfs$turfID, collapse = " "), " new turfs" )
db_pad_write_table(con, "turfs", newTurfs, row.names = FALSE, append = TRUE)
}
message("done turfs")
#subTurf env ####
subturfEnv <- dat %>%
filter(Measure != "Cover") %>%
select(turfID, subturf = subPlot, year, pleuro, acro, liver, lichen, litter, soil, rock, comment) %>%
mutate(subturf = as.integer(subturf))
if(!is.null(dat$missing)){
bad = dat$missing[dat$Measure != "Cover"]
bad[is.na(bad)] <- ""
subturfEnv <- subturfEnv %>% mutate(bad = bad)
} else{
subturfEnv <- subturfEnv %>% mutate(bad = "")
}
subturfEnv
db_pad_write_table(con, "subturf_environment", subturfEnv, row.names = FALSE, append = TRUE)
nrow(subturfEnv)
#TurfEnv ####
turfEnv <- dat %>%
filter(Measure == "Cover") %>%
select(turfID, year, pleuro, acro, liver, lichen, litter, soil, rock,
total_vascular = totalVascular,
total_bryophytes = totalBryophytes,
total_lichen = totalLichen,
vegetation_height = vegetationHeight,
moss_height = mossHeight,
comment, recorder, date)
# harmonise recorder names (supposed to be botanist but sometimes scribe)
turfEnv <- turfEnv %>%
mutate(
recorder = case_when(
recorder %in% c("", "not noted") | is.na(recorder) ~ "Not noted",
recorder %in% c("VV", "vv", "W") ~ "Vigdis",
recorder == "KK" ~ "Kari",
recorder == "SO" ~ "Siri",
TRUE ~ recorder
),
recorder = str_replace(recorder, "W(?![:alpha:])", "Vigdis"),
recorder = str_replace(recorder, "KK(?![:alpha:])", "Kari")
)
if(mode(turfEnv$moss_height) == "character"){
turfEnv <- turfEnv %>%
mutate(moss_height = gsub(",", ".", moss_height),
moss_height = as.numeric(moss_height))
}
if(any(nchar(as.character(turfEnv$comment)) > 255, na.rm = TRUE)) {
stop ("more than 255 characters in a comment field in turfEnv")
}
db_pad_write_table(con, "turf_environment", turfEnv, row.names = FALSE, append = TRUE)
nrow(turfEnv)
#TurfCommunity ####
spp <- dat %>%
filter(Measure == "Cover") %>%
select(turfID, year, (which(names(dat) == "recorder") + 1):(which(names(dat) == "pleuro") - 1)) %>%
gather(key = species, value = cover, -turfID, -year) %>%
filter(!is.na(cover), cover != 0) %>% #remove absent taxa
mutate(
cf = grepl("cf", cover, ignore.case = TRUE),
cover = gsub("cf", "", cover, ignore.case = TRUE) #move any CF to new column
)
#oddity search
spp %>% filter(is.na(as.numeric(cover))) %>% count(cover)
#merge synonyms
spp <- spp %>%
left_join(merge_dictionary, by = c("species" = "oldID")) %>%
mutate(newID = coalesce(newID, species)) %>%
select(turfID, year, species = newID, cover, cf) %>%
mutate(cover = as.numeric(cover)) %>%
filter(!is.na(cover)) %>%
group_by(year, turfID, species) %>%
summarise(cover = sum(cover), .groups = "drop") %>% #aggregate taxa
filter(cover > 0)
#check_new_taxa
spp_list <- dbGetQuery(conn = con, statement = "select species from taxon")
spp %>% anti_join(spp_list) %>% verify(nrow(.) == 0)
#inject
initNrowTurfCommunity <- dbGetQuery(con, "select count(*) as n from turf_community")
db_pad_write_table(con, "turf_community", spp)
finalNrowTurfCommunity <- dbGetQuery(con, "select count(*) as n from turf_community")
stopifnot(nrow(spp) == finalNrowTurfCommunity - initNrowTurfCommunity)
#subTurfCommunity ####
message("subturf_community")
subspp <- dat %>%
filter(Measure != "Cover") %>%
select(turfID, year, subturf = subPlot, (which(names(dat) == "recorder") + 1):(which(names(dat) == "pleuro") -1)) %>%
mutate(subturf = as.integer(subturf)) %>%
gather(key = species, value = presence, -turfID, -subturf, -year) %>%
filter(!is.na(presence), presence != 0, presence != "") #remove absent taxa
# #oddity search
subspp %>% count(presence)
# #merge synonyms
subspp <- subspp %>%
left_join(merge_dictionary, by = c("species" = "oldID")) %>%
mutate(newID = coalesce(newID, species)) %>%
select(turfID, subturf, year, species = newID, presence) %>%
group_by(year, turfID, subturf, species) %>%
summarise(presence = paste0(presence, collapse = ""), .groups = "drop") #aggregate taxa
#check_new_taxa
subspp %>% anti_join(spp_list) %>% verify(nrow(.) == 0)
# subspp[subspp == 0] <- NA
# subsppX <- lapply(unique(mergedNames), function(sppname){
# species <- subspp[, names(subspp) == sppname, drop = FALSE]
# if (ncol(species) == 1) {
# return(species)
# } else {
# apply (species, 1, function(r) {
# occurence <- which(!is.na(r))
# if(length(occurence) == 0) return(NA)
# if(length(occurence) == 1) return(r[occurence])
# else {
# warning(paste("more than one species observation in same subplot!"))
# write.csv(data.frame(filename = n, species = sppname, occurence = r[occurence]), file = "cooccurence_log.csv", append = TRUE)
# return(r[occurence][1])
# }
# })
# }
# })
#
#
# subsppX <- setNames(as.data.frame(subsppX), unique(mergedNames))
# subspp <- cbind(subspp[, 1:3], subsppX)
#euphrasia rule adults=adults+juvenile+seedling, j=j+s, s=s
seedlingSp <- c("Euph.fri", "Eup.fri","Eup.sp","Eup.str","Euph.fri","Euph.sp", "Euph.str","Euph.str.1", "Euph.wet", "Poa.ann","Thlaspi..arv","Com.ten","Gen.ten", "Rhi.min", "Cap.bur", "Mel.pra","Mel.sp","Mel.syl","Noc.cae","Ste.med","Thl.arv","Ver.arv")
subspp <- subspp %>%
mutate(
cf = grepl("cf", presence, ignore.case = TRUE),
fertile = grepl("F",presence, ignore.case = FALSE),
dominant = grepl("D",presence, ignore.case = TRUE),
vegetative = grepl("V",presence, ignore.case = TRUE),
seedling_1 = grepl("S",presence, ignore.case = TRUE),
seedling_n = stringr::str_extract(presence, pattern = "(?<=Sx)\\d+|\\d+(?=xS)"),
seedling_n = as.integer(seedling_n),
seedlings = case_when(
!is.na(seedling_n) ~ seedling_n,
seedling_1 ~ 1L,
TRUE ~ 0L
),
juvenile_1 = grepl("J",presence, ignore.case = TRUE),
juvenile_n = stringr::str_extract(presence, pattern = "(?<=Jx)\\d+|\\d+(?=xJ)"),
juvenile_n = as.integer(juvenile_n),
juvenile = case_when(
!is.na(juvenile_n) ~ juvenile_n,
juvenile_1 ~ 1L,
TRUE ~ 0L
),
adult = fertile|dominant|vegetative|grepl("1", presence) ) %>%
select(-c(seedling_1, seedling_n, juvenile_1, juvenile_n)) %>%
#########more annuals?
mutate(
juvenile = if_else(species %in% seedlingSp & juvenile == 0L & adult, 1L, juvenile),
seedlings = if_else(species %in% seedlingSp & seedlings == 0L & juvenile > 0L, juvenile, seedlings)
) %>%
mutate_at(vars(cf, fertile, dominant, vegetative, adult), as.integer)
#inject
initNrowSubTurfCommunity <- dbGetQuery(con, "select count(*) as n from subturf_community")
db_pad_write_table(con, "subturf_community", subspp)
finalNrowSubTurfCommunity <- dbGetQuery(con, "select count(*) as n from subturf_community")
stopifnot(nrow(subspp) == finalNrowSubTurfCommunity - initNrowSubTurfCommunity)
############### Vigdis seedling problem #only for 2011 data #############################
#
# id_seedling <- subspp %>%
# filter(year == 2011, species != "seedling") %>%
# group_by(turfID) %>%
# summarise(n_seedlings = sum(seedling))
#
# uid_seedlings <- subspp %>%
# filter(year == 2011, species == "seedling") %>%
# full_join(id_seedlings, by = turfID) %>%
# left_join(dat %>%
# filter(year == 2011, measure == "cover") %>%
# select(turfID, recorder))
#
#
# if(dat$year[1] == 2011 & FALSE){ #disable seedling error <---- FIX THIS!!!
# seed <- dat[dat$TTtreat != "" & dat$Measure != "Cover", c("turfID","subPlot", "year", "seedlings", "recorder")] #get data.frame of seedlings N1
# seed$subPlot <- as.integer(as.character(seed$subPlot))
# seed$turfID <- factor(seed$turfID)
# seedsum <- dbGetQuery(con, paste("select * from [number identified seedlings by subplot] where siteID='",dat$DestinationSite[1], "' and Year=2011", sep="")) #sqlQuery database for number of seedlings per subplot N2
# seed <- seed[order(seed$turfID, seed$subPlot),]
#
# head(seed)
# head(seedsum)
#
# seed <- seed[!paste(seed$turf, seed$subPlot) %in% setdiff(paste(seed$turf, seed$subPlot), paste(seedsum$turf, seedsum$subTurf)),]# then remove any missing rows as they have no species
#
# seed$seedlings[is.na(seed$seedlings)] <- 0
#
# seed$seedlings2 <- seed$seedlings
# seed$seedlings2[seed$recorder == "W"]<-seed$seedlings[seed$recorder == "W"]-seedsum$SumOfseedlings[seed$recorder == "W"]#for VV /W subplots n seedlings N1 = N1 - N2
#
# data.frame(seed$recorder, seed$seedlings, seedsum$SumOfseedlings, seed$seedlings2)
#
# #insert N1 into subturf_community as unident seedling
#
# seed <- seed[seed$seedlings2 > 0,]
# seed <- data.frame(turfID = seed$turfID, year = seed$year, subTurf = seed$subPlot, species = "seed.unid", seedlings = seed$seedlings2, juvenile = 0,adult = 0,fertile = 0,vegetative = 0,dominant = 0, cf = 1)
# dbWriteTable(con, "subturf_community", seed, row.names=FALSE, append = TRUE)
# }
# ######################### vigdis seedling problem fixed
}
Between-the-Fjords/seedclim-data documentation built on March 6, 2023, 7:53 a.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
####################
#todo############
#check species in taxon table before inserting
#merge subturf taxa
####################
#for loop
import_data <- function(file, con, merge_dictionary){
#browser()
print(file)
chkft <- c("pleuro","acro", "liver", "lichen", "litter" ,"soil", "rock", "totalVascular", "totalBryophytes", "totalLichen", "vegetationHeight", "mossHeight")
f <- readLines(file, warn = FALSE) %>%
if_else(condition = substring(., 1, 1) == "\"", true = {
gsub(pattern = "^\"", replacement = "", x = .) %>% #replace starting quote
gsub(pattern = "\"\"", replacement = "\"", x = .) %>% #replace double quotes
gsub(pattern = "\"\"$", replacement = "\"", x = .) %>% #replace double quotes that was part of a triple at end
#gsub(pattern = "(?<!\\)),\"$", replacement = ",", x = ., perl = TRUE) #-ve look behind fixes Veskre comment problem
gsub(pattern = ",\"$", replacement = ",", x = .) #-ve remove end quote
}, false = .) %>%
paste(collapse = "\n")
dat <- read.delim(text = f, sep = ";", dec = ",", stringsAsFactors = FALSE)#sep = ";", dec = ","
if(ncol(dat) > 10){
if(any(sapply(dat[, chkft], class) == "character"))
dat <- read.delim(text = f, sep = ";", dec = ".", stringsAsFactors = FALSE)#sep = ";", dec = "."
}else{
dat <- read.delim(text = f, sep = ",", dec = ".", stringsAsFactors = FALSE)
}
names(dat) <- make.names(names(dat))
dat <- dat %>%
filter(!is.na(turfID), turfID != "", turfID != "turfID") %>%
mutate(
turfID = trimws(turfID),
comment = as.character(comment),
year = as.integer(year)
)
head(dat)
names(dat)
Encoding(dat$comment) <- "latin1"
#remove numeric suffix on duplicates
names(dat) <- gsub("_\\d$", "", names(dat))
#extract turf data####
#fix typos in turfID
dat <- dat %>%
mutate(turfID = recode(turfID,
"515 TT4 247" = "515 TT4 274",
"277 TTC" = "286 TTC",
"192 TT4 29" = "192 TT4 299"))
turf <- dat %>%
select(turfID, matches("treat$"), one_of(c("originPlotID", "destinationPlotID"))) %>%
distinct() %>%
mutate_all(trimws)
turf
names(turf)
alreadyIn <- dbGetQuery(con,"select turfID from turfs")
newTurfs <- turf %>%
anti_join(alreadyIn) %>% #find which turfs IDs are not already in database
select(where(~!(all(is.na(.x))))) #remove empty columns to avoid type conflicts
if(nrow(newTurfs) > 0) {
message("adding ", paste(newTurfs$turfID, collapse = " "), " new turfs" )
db_pad_write_table(con, "turfs", newTurfs, row.names = FALSE, append = TRUE)
}
message("done turfs")
#subTurf env ####
subturfEnv <- dat %>%
filter(Measure != "Cover") %>%
select(turfID, subturf = subPlot, year, pleuro, acro, liver, lichen, litter, soil, rock, comment) %>%
mutate(subturf = as.integer(subturf))
if(!is.null(dat$missing)){
bad = dat$missing[dat$Measure != "Cover"]
bad[is.na(bad)] <- ""
subturfEnv <- subturfEnv %>% mutate(bad = bad)
} else{
subturfEnv <- subturfEnv %>% mutate(bad = "")
}
subturfEnv
db_pad_write_table(con, "subturf_environment", subturfEnv, row.names = FALSE, append = TRUE)
nrow(subturfEnv)
#TurfEnv ####
turfEnv <- dat %>%
filter(Measure == "Cover") %>%
select(turfID, year, pleuro, acro, liver, lichen, litter, soil, rock,
total_vascular = totalVascular,
total_bryophytes = totalBryophytes,
total_lichen = totalLichen,
vegetation_height = vegetationHeight,
moss_height = mossHeight,
comment, recorder, date)
# harmonise recorder names (supposed to be botanist but sometimes scribe)
turfEnv <- turfEnv %>%
mutate(
recorder = case_when(
recorder %in% c("", "not noted") | is.na(recorder) ~ "Not noted",
recorder %in% c("VV", "vv", "W") ~ "Vigdis",
recorder == "KK" ~ "Kari",
recorder == "SO" ~ "Siri",
TRUE ~ recorder
),
recorder = str_replace(recorder, "W(?![:alpha:])", "Vigdis"),
recorder = str_replace(recorder, "KK(?![:alpha:])", "Kari")
)
if(mode(turfEnv$moss_height) == "character"){
turfEnv <- turfEnv %>%
mutate(moss_height = gsub(",", ".", moss_height),
moss_height = as.numeric(moss_height))
}
if(any(nchar(as.character(turfEnv$comment)) > 255, na.rm = TRUE)) {
stop ("more than 255 characters in a comment field in turfEnv")
}
db_pad_write_table(con, "turf_environment", turfEnv, row.names = FALSE, append = TRUE)
nrow(turfEnv)
#TurfCommunity ####
spp <- dat %>%
filter(Measure == "Cover") %>%
select(turfID, year, (which(names(dat) == "recorder") + 1):(which(names(dat) == "pleuro") - 1)) %>%
gather(key = species, value = cover, -turfID, -year) %>%
filter(!is.na(cover), cover != 0) %>% #remove absent taxa
mutate(
cf = grepl("cf", cover, ignore.case = TRUE),
cover = gsub("cf", "", cover, ignore.case = TRUE) #move any CF to new column
)
#oddity search
spp %>% filter(is.na(as.numeric(cover))) %>% count(cover)
#merge synonyms
spp <- spp %>%
left_join(merge_dictionary, by = c("species" = "oldID")) %>%
mutate(newID = coalesce(newID, species)) %>%
select(turfID, year, species = newID, cover, cf) %>%
mutate(cover = as.numeric(cover)) %>%
filter(!is.na(cover)) %>%
group_by(year, turfID, species) %>%
summarise(cover = sum(cover), .groups = "drop") %>% #aggregate taxa
filter(cover > 0)
#check_new_taxa
spp_list <- dbGetQuery(conn = con, statement = "select species from taxon")
spp %>% anti_join(spp_list) %>% verify(nrow(.) == 0)
#inject
initNrowTurfCommunity <- dbGetQuery(con, "select count(*) as n from turf_community")
db_pad_write_table(con, "turf_community", spp)
finalNrowTurfCommunity <- dbGetQuery(con, "select count(*) as n from turf_community")
stopifnot(nrow(spp) == finalNrowTurfCommunity - initNrowTurfCommunity)
#subTurfCommunity ####
message("subturf_community")
subspp <- dat %>%
filter(Measure != "Cover") %>%
select(turfID, year, subturf = subPlot, (which(names(dat) == "recorder") + 1):(which(names(dat) == "pleuro") -1)) %>%
mutate(subturf = as.integer(subturf)) %>%
gather(key = species, value = presence, -turfID, -subturf, -year) %>%
filter(!is.na(presence), presence != 0, presence != "") #remove absent taxa
# #oddity search
subspp %>% count(presence)
# #merge synonyms
subspp <- subspp %>%
left_join(merge_dictionary, by = c("species" = "oldID")) %>%
mutate(newID = coalesce(newID, species)) %>%
select(turfID, subturf, year, species = newID, presence) %>%
group_by(year, turfID, subturf, species) %>%
summarise(presence = paste0(presence, collapse = ""), .groups = "drop") #aggregate taxa
#check_new_taxa
subspp %>% anti_join(spp_list) %>% verify(nrow(.) == 0)
# subspp[subspp == 0] <- NA
# subsppX <- lapply(unique(mergedNames), function(sppname){
# species <- subspp[, names(subspp) == sppname, drop = FALSE]
# if (ncol(species) == 1) {
# return(species)
# } else {
# apply (species, 1, function(r) {
# occurence <- which(!is.na(r))
# if(length(occurence) == 0) return(NA)
# if(length(occurence) == 1) return(r[occurence])
# else {
# warning(paste("more than one species observation in same subplot!"))
# write.csv(data.frame(filename = n, species = sppname, occurence = r[occurence]), file = "cooccurence_log.csv", append = TRUE)
# return(r[occurence][1])
# }
# })
# }
# })
#
#
# subsppX <- setNames(as.data.frame(subsppX), unique(mergedNames))
# subspp <- cbind(subspp[, 1:3], subsppX)
#euphrasia rule adults=adults+juvenile+seedling, j=j+s, s=s
seedlingSp <- c("Euph.fri", "Eup.fri","Eup.sp","Eup.str","Euph.fri","Euph.sp", "Euph.str","Euph.str.1", "Euph.wet", "Poa.ann","Thlaspi..arv","Com.ten","Gen.ten", "Rhi.min", "Cap.bur", "Mel.pra","Mel.sp","Mel.syl","Noc.cae","Ste.med","Thl.arv","Ver.arv")
subspp <- subspp %>%
mutate(
cf = grepl("cf", presence, ignore.case = TRUE),
fertile = grepl("F",presence, ignore.case = FALSE),
dominant = grepl("D",presence, ignore.case = TRUE),
vegetative = grepl("V",presence, ignore.case = TRUE),
seedling_1 = grepl("S",presence, ignore.case = TRUE),
seedling_n = stringr::str_extract(presence, pattern = "(?<=Sx)\\d+|\\d+(?=xS)"),
seedling_n = as.integer(seedling_n),
seedlings = case_when(
!is.na(seedling_n) ~ seedling_n,
seedling_1 ~ 1L,
TRUE ~ 0L
),
juvenile_1 = grepl("J",presence, ignore.case = TRUE),
juvenile_n = stringr::str_extract(presence, pattern = "(?<=Jx)\\d+|\\d+(?=xJ)"),
juvenile_n = as.integer(juvenile_n),
juvenile = case_when(
!is.na(juvenile_n) ~ juvenile_n,
juvenile_1 ~ 1L,
TRUE ~ 0L
),
adult = fertile|dominant|vegetative|grepl("1", presence) ) %>%
select(-c(seedling_1, seedling_n, juvenile_1, juvenile_n)) %>%
#########more annuals?
mutate(
juvenile = if_else(species %in% seedlingSp & juvenile == 0L & adult, 1L, juvenile),
seedlings = if_else(species %in% seedlingSp & seedlings == 0L & juvenile > 0L, juvenile, seedlings)
) %>%
mutate_at(vars(cf, fertile, dominant, vegetative, adult), as.integer)
#inject
initNrowSubTurfCommunity <- dbGetQuery(con, "select count(*) as n from subturf_community")
db_pad_write_table(con, "subturf_community", subspp)
finalNrowSubTurfCommunity <- dbGetQuery(con, "select count(*) as n from subturf_community")
stopifnot(nrow(subspp) == finalNrowSubTurfCommunity - initNrowSubTurfCommunity)
############### Vigdis seedling problem #only for 2011 data #############################
#
# id_seedling <- subspp %>%
# filter(year == 2011, species != "seedling") %>%
# group_by(turfID) %>%
# summarise(n_seedlings = sum(seedling))
#
# uid_seedlings <- subspp %>%
# filter(year == 2011, species == "seedling") %>%
# full_join(id_seedlings, by = turfID) %>%
# left_join(dat %>%
# filter(year == 2011, measure == "cover") %>%
# select(turfID, recorder))
#
#
# if(dat$year[1] == 2011 & FALSE){ #disable seedling error <---- FIX THIS!!!
# seed <- dat[dat$TTtreat != "" & dat$Measure != "Cover", c("turfID","subPlot", "year", "seedlings", "recorder")] #get data.frame of seedlings N1
# seed$subPlot <- as.integer(as.character(seed$subPlot))
# seed$turfID <- factor(seed$turfID)
# seedsum <- dbGetQuery(con, paste("select * from [number identified seedlings by subplot] where siteID='",dat$DestinationSite[1], "' and Year=2011", sep="")) #sqlQuery database for number of seedlings per subplot N2
# seed <- seed[order(seed$turfID, seed$subPlot),]
#
# head(seed)
# head(seedsum)
#
# seed <- seed[!paste(seed$turf, seed$subPlot) %in% setdiff(paste(seed$turf, seed$subPlot), paste(seedsum$turf, seedsum$subTurf)),]# then remove any missing rows as they have no species
#
# seed$seedlings[is.na(seed$seedlings)] <- 0
#
# seed$seedlings2 <- seed$seedlings
# seed$seedlings2[seed$recorder == "W"]<-seed$seedlings[seed$recorder == "W"]-seedsum$SumOfseedlings[seed$recorder == "W"]#for VV /W subplots n seedlings N1 = N1 - N2
#
# data.frame(seed$recorder, seed$seedlings, seedsum$SumOfseedlings, seed$seedlings2)
#
# #insert N1 into subturf_community as unident seedling
#
# seed <- seed[seed$seedlings2 > 0,]
# seed <- data.frame(turfID = seed$turfID, year = seed$year, subTurf = seed$subPlot, species = "seed.unid", seedlings = seed$seedlings2, juvenile = 0,adult = 0,fertile = 0,vegetative = 0,dominant = 0, cf = 1)
# dbWriteTable(con, "subturf_community", seed, row.names=FALSE, append = TRUE)
# }
# ######################### vigdis seedling problem fixed
}
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.