R/biomassData.R
In dempseydanielle/SSdata: Extracts Fishery Independent and Commercial Landings Data for the Scotian Shelf from DFO-Maritimes Databases
Defines functions
biomassData
Documented in
biomassData
#'@title Extracts and exports fishery independent biomass and abundance data
#'@description Extracts and exports annual q-adjusted and not q-adjusted,
#' length-based (separated into 1 cm length classes) and not length-based
#' (aggregated over length) biomass and abundance data from the Scotian Shelf
#' summer research vessel surveys. q-adjustments are applied at the set level
#' (before stratification).
#'@details User must define \code{channel = odbcConnect("ptran", uid = ###, pwd
#' = ###)} in the global environment. This channel must have access to the
#' gscat, gsdet, gsinf, and gs_lengths tables from the groundfish database and
#' the nafo_strat table from the mfd_stomach database.
#'
#' Units: biomass - kg; abundance - numbers; length - cm.
#'
#' If \code{BIOMASS} or \code{ABUNDANCE} data is missing when the other is
#' present, the missing field is filled in based on the relationship
#' \eqn{Weight_{Avg} = \code{BIOMASS}/\code{ABUNDANCE}}. \eqn{Weight_{Avg}} is
#' from a sql call to "mean_wts_for_fill_in." If \eqn{Weight_{Avg}} is not
#' available for a species, it is assumed that \eqn{Weight_{Avg} = 0.5}.
#'
#' Abnormally high dogfish biomass estimates (> 8000 kg at the set level) are
#' replaced with \code{BIOMASS = 0} kg.
#'
#' Abundance estimates of \code{Inf} in 2012 are replaced with \code{ABUNDANCE
#' = 1}.
#'
#' Code will stop if any \code{BIOMASS} or \code{ABUNDANCE} estimates are
#' \code{NA}.
#'
#' Estimates of zero are replaced with small values: \code{BIOMASS = 0} is
#' replaced with \code{BIOMASS = 0.01}; \code{ABUNDANCE = 0} is replaced with
#' \code{ABUNDANCE = 1}.
#'@param path Filepath indicating where to create folders to store the extracted
#' data.
#'@param s.strat Stratum for which to begin data extraction. Default is
#' \code{s.strat = 440}. Code will stop with an error message if \code{s.strat
#' < 440} or \code{s.strat > 495}.
#'@param e.strat Stratum for which to end data extraction. Default is
#' \code{e.strat = 495}. Code will stop with an error message if \code{e.strat
#' < 440} or \code{e.strat > 495}.
#'@param s.year Year for which to begin data extraction.
#'@param e.year Year for which to end data extraction.
#'@param vessel.correction Logical value indicating whether to apply vessel
#' correction to \code{BIOMASS} and \code{ABUNDANCE}. Default is
#' \code{vessel.correction} = TRUE.
#'@return Creates directories to store extracted data.
#'
#' Not length-based data are stored in path/data/aggregate/. This folder
#' includes an RData file for each year called year.RData (object name
#' \code{dat}). \code{dat} has 9 columns: \code{MISSION}, \code{SETNO},
#' \code{SPECIES}, \code{YEAR}, \code{STRAT}, \code{BIOMASS}, \code{ABUNDANCE},
#' \code{QBIOMASS} and \code{QABUNDANCE}.
#'
#' Length-based data is stored in path/data/length/. This folder includes an
#' RData file for each year called num_biom_at_length_year.RData (object name
#' \code{out}). \code{out} has 10 columns: \code{MISSION}, \code{SETNO},
#' \code{SPECIES}, \code{YEAR}, \code{STRAT}, \code{BIOMASS}, \code{ABUNDANCE},
#' \code{QBIOMASS} and \code{QABUNDANCE}, and \code{FLEN}, where \code{FLEN} is
#' length in 1 cm increments.
#'
#'@references Modified code from AC's ExtractIndicators/R/biomassData.R
#'@importFrom stats aggregate
#'@importFrom reshape melt
#'@importFrom RODBC sqlQuery
#'@family RV functions
#'@export
biomassData <- function(path, s.strat = 440, e.strat = 495, s.year, e.year,
vessel.correction = TRUE) {
# display error message if s.strat or e.start are < 440 or > 495
if(s.strat < 440 | s.strat > 495 | e.strat < 440 | e.strat > 495) {
stop("error: s.strat or e.strat is outside of the Scotian Shelf")
}
# vector of years of interest
yr <- s.year:e.year
# start loop over years
for(i in 1:length(yr)) {
# At Length ---------------------------------------------------------------
# Table with "SPECIES", "FUNGROUP", "Q", "LENCORR" (88 observations)
catch_coefs <- sqlQuery(channel, paste('select * from gomezc.indiseas_catchability_coeffs'))
catch_coefs[catch_coefs == 'NULL'] <- NA
outputs <- list()
m = 0
# Extract table with 12 columns:
## YEAR, STRAT, MISSION, YYDDMMSS, XDDMMSS, SETNO, FLEN,
## ABUNDANCE, QABUNDANCE, QBIOMASS, BIOMASS, SPECIES
# QABUNDANCE and QBIOMASS are q-adjusted at the set level (BEFORE stratification).
for (j in 1:nrow(catch_coefs)) {
outputs[[j]] <- qBiomass(species = catch_coefs[j, 1], fun_group = catch_coefs[j, 2],
q = catch_coefs[j, 3], len_corr = catch_coefs[j, 4], year = yr[i])
}
out <- as.data.frame(do.call(rbind, outputs))
out <- out[, -which(names(out) %in% c('YDDMMSS', 'XDDMMSS'))] # remove lat/long columns
if(vessel.correction) out <- vesselCorr(out) # apply vessel correction
# Export length based data (biomass and abundance at 1 cm intervals)
fna <- paste(path,"/data/length/",sep="")
dir.create(fna, recursive = T, showWarnings = F)
fna <- paste(fna, "num_biom_at_length", yr[i], ".RData", sep = "")
save(out, file = fna, compress = T)
# End of At Length ------------------------------------------------------
# Begin aggregate ---------------------------------------------------------
# Sum over length (aggregated biomass & abundance of species that have length-based q)
ag.out <- aggregate(cbind(QBIOMASS, BIOMASS, QABUNDANCE, ABUNDANCE) ~
YEAR + STRAT + MISSION + SETNO + SPECIES,
data = out, FUN = sum)
# Extract table with 7 columns:
## MISSION, SETNO, STRAT, YEAR, SPEC, ABUNDANCE, BIOMASS
dat <- sqlQuery(channel,paste("select distinct i.mission,i.setno,i.strat, to_char(sdate,'yyyy') year, spec,sum(nvl(totno,0)*1.75/i.dist) Abundance,sum(nvl(totwgt,0)*1.75/i.dist) biomass from
groundfish.gsinf i, groundfish.gscat c, mfd_stomach.nafo_strat sg where i.mission=c.mission and i.setno=c.setno and i.strat=sg.strat and to_char(sdate,'mm') in ('06','07','08') and
i.strat between '",s.strat,"' and '",e.strat,"' and type=1 and spec<9000 and to_char(sdate,'yyyy')=",yr[i],"
group by i.mission,i.setno,i.strat,slat , slong ,to_char(sdate,'yyyy'), spec;",sep=""))
# Fix high biomass estimate(s) for dogfish
dat[dat$BIOMASS > 8000 & dat$SPEC != 220,'BIOMASS'] <- 0 # added in November 08, 2013
# Change NA for abundance or biomass based on mean size of animals captured (for invs only)
dat[is.na(dat$ABUNDANCE), 'ABUNDANCE'] <- 0
dat[is.na(dat$BIOMASS), 'BIOMASS'] <- 0
# Handle the missing biomass or abudance data where the other is present
# by using mean weight = biomass/abundance
if(any(dat$ABUNDANCE == 0 | dat$BIOMASS==0)) {
wt <- sqlQuery(channel, paste("select * from mean_wts_for_fill_in;",sep="")) # table of mean fish weight ("SPEC" and "MEAN_WT_FISH", 640 observations)
dat <- merge(dat, wt, by = c('SPEC'), all.x = T) # merge dat and wt
dat[is.na(dat$MEAN_WT_FISH), 'MEAN_WT_FISH'] <- 0.5 # if mean fish weight is NA, assign mean weight of 0.5
if(any(dat$ABUNDANCE == 0)) {
dat$ABUNDANCE[dat$ABUNDANCE == 0] <- dat$BIOMASS[dat$ABUNDANCE==0]/dat$MEAN_WT_FISH[dat$ABUNDANCE==0] # abundance = biomass/mean weight
} # DD added this bracket so that biomass correction is OUTSIDE of the if statement for abundance
if(any(dat$BIOMASS == 0)) {
dat$BIOMASS[dat$BIOMASS == 0] <- dat$ABUNDANCE[dat$BIOMASS==0]*dat$MEAN_WT_FISH[dat$BIOMASS==0]
}
}
# Change ABUNDANCE = inf to ABUNDANCE = 1
if(unique(dat$YEAR)==2012 & any(!is.finite(dat$ABUNDANCE))) dat[which(!is.finite(dat$ABUNDANCE)),'ABUNDANCE'] <- 1
# If any biomass or abundance is still NA, stop code
if(any(is.na(dat[,c('BIOMASS','ABUNDANCE')]))) browser()
# Replace 0's with small values
dat[dat$BIOMASS == 0 ,'BIOMASS'] <- 0.01
dat[dat$ABUNDANCE == 0 ,'ABUNDANCE'] <- 1
dat$QABUNDANCE <- dat$ABUNDANCE
dat$QBIOMASS <- dat$BIOMASS
dat$SPECIES <- dat$SPEC # need this line? Drop SPECIES column at line 145
if(vessel.correction) dat <- vesselCorr(dat) # Apply vessel correction
dat <- dat[, -which(names(dat) == 'SPECIES')]
# Add in zero sets.
# These are needed to calculate the stratified means
extra.sets <- sqlQuery(channel,paste("select distinct i.mission,i.setno,i.strat,to_char(sdate,'yyyy') year from groundfish.gsinf i, nafo_strat sg where
i.strat=sg.strat and to_char(sdate,'yyyy') =",yr[i]," and to_char(sdate,'mm') in ('06','07','08') and i.strat between '",s.strat,"' and '",e.strat,"' and type=1;",sep=""))
s <- unique(dat$SPEC)
m <- matrix(0, nrow = dim(extra.sets)[1], ncol=length(s),
dimnames = list(c(1:nrow(extra.sets)), s))
m <- cbind(extra.sets, m)
h <- melt(m, id = c("MISSION", "SETNO", "STRAT", "YEAR"))
names(h)[which(names(h) %in% c('variable','value'))] <- c('SPECIES','BIOMASS')
h$QBIOMASS <- h$QABUNDANCE <- h$MEAN_WT_FISH <- h$ABUNDANCE <- 0
names(dat)[1] <- 'SPECIES'
l <- rbind(dat, h, all = T) # not sure why need all = T. This adds an extra
# row where MISSION = TRUE and SPECIES = TRUE (other columns = 1).
# I remove this row below
dat <- l[!duplicated(l[,c('MISSION','SETNO','SPECIES')], fromLast = F),]
dat <- dat[-which(dat$MISSION == TRUE), ] # remove row where MISSION == TRUE
# Add in the qadjusted data
dat1 <- dat
w <- merge(dat, ag.out, by = c('MISSION','SETNO','STRAT','SPECIES','YEAR'), all.x = T)
# Add columns for ABUNDANCE, QABUNDANCE, BIOMASS, and QBIOMASS
w$ABUNDANCE <- 0
w$QABUNDANCE <- 0
w$BIOMASS <- 0
w$QBIOMASS <- 0
# Fill in columns for ABUNDANCE, QABUNDANCE, BIOMASS, and QBIOMASS with appropriate data
# .x is from dat (not q adj); .y is from ag.out (qadj)
w$ABUNDANCE <- ifelse(is.na(w$ABUNDANCE.y), w$ABUNDANCE.x, w$ABUNDANCE.y)
w$BIOMASS <- ifelse(is.na(w$BIOMASS.y), w$BIOMASS.x, w$BIOMASS.y)
w$QABUNDANCE <- ifelse(is.na(w$QABUNDANCE.y), w$QABUNDANCE.x, w$QABUNDANCE.y)
w$QBIOMASS <- ifelse(is.na(w$QBIOMASS.y), w$QBIOMASS.x, w$QBIOMASS.y)
# Export aggregated data
dat <- w[, c('MISSION','SETNO','SPECIES','YEAR','STRAT','ABUNDANCE','BIOMASS','QABUNDANCE','QBIOMASS')]
fna <- paste(path,"/data/aggregate/",sep="")
dir.create(fna, recursive = T, showWarnings = F)
save(dat, file = paste(fna, "num_biom", yr[i], ".RData", sep=""))
rm(dat, w)
print(paste("biomassData() function: finished year", yr[i]))
} # end of loop over years
} # end of function
dempseydanielle/SSdata documentation built on May 3, 2020, 5:09 p.m.
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Defines functions biomassData
Documented in biomassData
#'@title Extracts and exports fishery independent biomass and abundance data
#'@description Extracts and exports annual q-adjusted and not q-adjusted,
#' length-based (separated into 1 cm length classes) and not length-based
#' (aggregated over length) biomass and abundance data from the Scotian Shelf
#' summer research vessel surveys. q-adjustments are applied at the set level
#' (before stratification).
#'@details User must define \code{channel = odbcConnect("ptran", uid = ###, pwd
#' = ###)} in the global environment. This channel must have access to the
#' gscat, gsdet, gsinf, and gs_lengths tables from the groundfish database and
#' the nafo_strat table from the mfd_stomach database.
#'
#' Units: biomass - kg; abundance - numbers; length - cm.
#'
#' If \code{BIOMASS} or \code{ABUNDANCE} data is missing when the other is
#' present, the missing field is filled in based on the relationship
#' \eqn{Weight_{Avg} = \code{BIOMASS}/\code{ABUNDANCE}}. \eqn{Weight_{Avg}} is
#' from a sql call to "mean_wts_for_fill_in." If \eqn{Weight_{Avg}} is not
#' available for a species, it is assumed that \eqn{Weight_{Avg} = 0.5}.
#'
#' Abnormally high dogfish biomass estimates (> 8000 kg at the set level) are
#' replaced with \code{BIOMASS = 0} kg.
#'
#' Abundance estimates of \code{Inf} in 2012 are replaced with \code{ABUNDANCE
#' = 1}.
#'
#' Code will stop if any \code{BIOMASS} or \code{ABUNDANCE} estimates are
#' \code{NA}.
#'
#' Estimates of zero are replaced with small values: \code{BIOMASS = 0} is
#' replaced with \code{BIOMASS = 0.01}; \code{ABUNDANCE = 0} is replaced with
#' \code{ABUNDANCE = 1}.
#'@param path Filepath indicating where to create folders to store the extracted
#' data.
#'@param s.strat Stratum for which to begin data extraction. Default is
#' \code{s.strat = 440}. Code will stop with an error message if \code{s.strat
#' < 440} or \code{s.strat > 495}.
#'@param e.strat Stratum for which to end data extraction. Default is
#' \code{e.strat = 495}. Code will stop with an error message if \code{e.strat
#' < 440} or \code{e.strat > 495}.
#'@param s.year Year for which to begin data extraction.
#'@param e.year Year for which to end data extraction.
#'@param vessel.correction Logical value indicating whether to apply vessel
#' correction to \code{BIOMASS} and \code{ABUNDANCE}. Default is
#' \code{vessel.correction} = TRUE.
#'@return Creates directories to store extracted data.
#'
#' Not length-based data are stored in path/data/aggregate/. This folder
#' includes an RData file for each year called year.RData (object name
#' \code{dat}). \code{dat} has 9 columns: \code{MISSION}, \code{SETNO},
#' \code{SPECIES}, \code{YEAR}, \code{STRAT}, \code{BIOMASS}, \code{ABUNDANCE},
#' \code{QBIOMASS} and \code{QABUNDANCE}.
#'
#' Length-based data is stored in path/data/length/. This folder includes an
#' RData file for each year called num_biom_at_length_year.RData (object name
#' \code{out}). \code{out} has 10 columns: \code{MISSION}, \code{SETNO},
#' \code{SPECIES}, \code{YEAR}, \code{STRAT}, \code{BIOMASS}, \code{ABUNDANCE},
#' \code{QBIOMASS} and \code{QABUNDANCE}, and \code{FLEN}, where \code{FLEN} is
#' length in 1 cm increments.
#'
#'@references Modified code from AC's ExtractIndicators/R/biomassData.R
#'@importFrom stats aggregate
#'@importFrom reshape melt
#'@importFrom RODBC sqlQuery
#'@family RV functions
#'@export
biomassData <- function(path, s.strat = 440, e.strat = 495, s.year, e.year,
vessel.correction = TRUE) {
# display error message if s.strat or e.start are < 440 or > 495
if(s.strat < 440 | s.strat > 495 | e.strat < 440 | e.strat > 495) {
stop("error: s.strat or e.strat is outside of the Scotian Shelf")
}
# vector of years of interest
yr <- s.year:e.year
# start loop over years
for(i in 1:length(yr)) {
# At Length ---------------------------------------------------------------
# Table with "SPECIES", "FUNGROUP", "Q", "LENCORR" (88 observations)
catch_coefs <- sqlQuery(channel, paste('select * from gomezc.indiseas_catchability_coeffs'))
catch_coefs[catch_coefs == 'NULL'] <- NA
outputs <- list()
m = 0
# Extract table with 12 columns:
## YEAR, STRAT, MISSION, YYDDMMSS, XDDMMSS, SETNO, FLEN,
## ABUNDANCE, QABUNDANCE, QBIOMASS, BIOMASS, SPECIES
# QABUNDANCE and QBIOMASS are q-adjusted at the set level (BEFORE stratification).
for (j in 1:nrow(catch_coefs)) {
outputs[[j]] <- qBiomass(species = catch_coefs[j, 1], fun_group = catch_coefs[j, 2],
q = catch_coefs[j, 3], len_corr = catch_coefs[j, 4], year = yr[i])
}
out <- as.data.frame(do.call(rbind, outputs))
out <- out[, -which(names(out) %in% c('YDDMMSS', 'XDDMMSS'))] # remove lat/long columns
if(vessel.correction) out <- vesselCorr(out) # apply vessel correction
# Export length based data (biomass and abundance at 1 cm intervals)
fna <- paste(path,"/data/length/",sep="")
dir.create(fna, recursive = T, showWarnings = F)
fna <- paste(fna, "num_biom_at_length", yr[i], ".RData", sep = "")
save(out, file = fna, compress = T)
# End of At Length ------------------------------------------------------
# Begin aggregate ---------------------------------------------------------
# Sum over length (aggregated biomass & abundance of species that have length-based q)
ag.out <- aggregate(cbind(QBIOMASS, BIOMASS, QABUNDANCE, ABUNDANCE) ~
YEAR + STRAT + MISSION + SETNO + SPECIES,
data = out, FUN = sum)
# Extract table with 7 columns:
## MISSION, SETNO, STRAT, YEAR, SPEC, ABUNDANCE, BIOMASS
dat <- sqlQuery(channel,paste("select distinct i.mission,i.setno,i.strat, to_char(sdate,'yyyy') year, spec,sum(nvl(totno,0)*1.75/i.dist) Abundance,sum(nvl(totwgt,0)*1.75/i.dist) biomass from
groundfish.gsinf i, groundfish.gscat c, mfd_stomach.nafo_strat sg where i.mission=c.mission and i.setno=c.setno and i.strat=sg.strat and to_char(sdate,'mm') in ('06','07','08') and
i.strat between '",s.strat,"' and '",e.strat,"' and type=1 and spec<9000 and to_char(sdate,'yyyy')=",yr[i],"
group by i.mission,i.setno,i.strat,slat , slong ,to_char(sdate,'yyyy'), spec;",sep=""))
# Fix high biomass estimate(s) for dogfish
dat[dat$BIOMASS > 8000 & dat$SPEC != 220,'BIOMASS'] <- 0 # added in November 08, 2013
# Change NA for abundance or biomass based on mean size of animals captured (for invs only)
dat[is.na(dat$ABUNDANCE), 'ABUNDANCE'] <- 0
dat[is.na(dat$BIOMASS), 'BIOMASS'] <- 0
# Handle the missing biomass or abudance data where the other is present
# by using mean weight = biomass/abundance
if(any(dat$ABUNDANCE == 0 | dat$BIOMASS==0)) {
wt <- sqlQuery(channel, paste("select * from mean_wts_for_fill_in;",sep="")) # table of mean fish weight ("SPEC" and "MEAN_WT_FISH", 640 observations)
dat <- merge(dat, wt, by = c('SPEC'), all.x = T) # merge dat and wt
dat[is.na(dat$MEAN_WT_FISH), 'MEAN_WT_FISH'] <- 0.5 # if mean fish weight is NA, assign mean weight of 0.5
if(any(dat$ABUNDANCE == 0)) {
dat$ABUNDANCE[dat$ABUNDANCE == 0] <- dat$BIOMASS[dat$ABUNDANCE==0]/dat$MEAN_WT_FISH[dat$ABUNDANCE==0] # abundance = biomass/mean weight
} # DD added this bracket so that biomass correction is OUTSIDE of the if statement for abundance
if(any(dat$BIOMASS == 0)) {
dat$BIOMASS[dat$BIOMASS == 0] <- dat$ABUNDANCE[dat$BIOMASS==0]*dat$MEAN_WT_FISH[dat$BIOMASS==0]
}
}
# Change ABUNDANCE = inf to ABUNDANCE = 1
if(unique(dat$YEAR)==2012 & any(!is.finite(dat$ABUNDANCE))) dat[which(!is.finite(dat$ABUNDANCE)),'ABUNDANCE'] <- 1
# If any biomass or abundance is still NA, stop code
if(any(is.na(dat[,c('BIOMASS','ABUNDANCE')]))) browser()
# Replace 0's with small values
dat[dat$BIOMASS == 0 ,'BIOMASS'] <- 0.01
dat[dat$ABUNDANCE == 0 ,'ABUNDANCE'] <- 1
dat$QABUNDANCE <- dat$ABUNDANCE
dat$QBIOMASS <- dat$BIOMASS
dat$SPECIES <- dat$SPEC # need this line? Drop SPECIES column at line 145
if(vessel.correction) dat <- vesselCorr(dat) # Apply vessel correction
dat <- dat[, -which(names(dat) == 'SPECIES')]
# Add in zero sets.
# These are needed to calculate the stratified means
extra.sets <- sqlQuery(channel,paste("select distinct i.mission,i.setno,i.strat,to_char(sdate,'yyyy') year from groundfish.gsinf i, nafo_strat sg where
i.strat=sg.strat and to_char(sdate,'yyyy') =",yr[i]," and to_char(sdate,'mm') in ('06','07','08') and i.strat between '",s.strat,"' and '",e.strat,"' and type=1;",sep=""))
s <- unique(dat$SPEC)
m <- matrix(0, nrow = dim(extra.sets)[1], ncol=length(s),
dimnames = list(c(1:nrow(extra.sets)), s))
m <- cbind(extra.sets, m)
h <- melt(m, id = c("MISSION", "SETNO", "STRAT", "YEAR"))
names(h)[which(names(h) %in% c('variable','value'))] <- c('SPECIES','BIOMASS')
h$QBIOMASS <- h$QABUNDANCE <- h$MEAN_WT_FISH <- h$ABUNDANCE <- 0
names(dat)[1] <- 'SPECIES'
l <- rbind(dat, h, all = T) # not sure why need all = T. This adds an extra
# row where MISSION = TRUE and SPECIES = TRUE (other columns = 1).
# I remove this row below
dat <- l[!duplicated(l[,c('MISSION','SETNO','SPECIES')], fromLast = F),]
dat <- dat[-which(dat$MISSION == TRUE), ] # remove row where MISSION == TRUE
# Add in the qadjusted data
dat1 <- dat
w <- merge(dat, ag.out, by = c('MISSION','SETNO','STRAT','SPECIES','YEAR'), all.x = T)
# Add columns for ABUNDANCE, QABUNDANCE, BIOMASS, and QBIOMASS
w$ABUNDANCE <- 0
w$QABUNDANCE <- 0
w$BIOMASS <- 0
w$QBIOMASS <- 0
# Fill in columns for ABUNDANCE, QABUNDANCE, BIOMASS, and QBIOMASS with appropriate data
# .x is from dat (not q adj); .y is from ag.out (qadj)
w$ABUNDANCE <- ifelse(is.na(w$ABUNDANCE.y), w$ABUNDANCE.x, w$ABUNDANCE.y)
w$BIOMASS <- ifelse(is.na(w$BIOMASS.y), w$BIOMASS.x, w$BIOMASS.y)
w$QABUNDANCE <- ifelse(is.na(w$QABUNDANCE.y), w$QABUNDANCE.x, w$QABUNDANCE.y)
w$QBIOMASS <- ifelse(is.na(w$QBIOMASS.y), w$QBIOMASS.x, w$QBIOMASS.y)
# Export aggregated data
dat <- w[, c('MISSION','SETNO','SPECIES','YEAR','STRAT','ABUNDANCE','BIOMASS','QABUNDANCE','QBIOMASS')]
fna <- paste(path,"/data/aggregate/",sep="")
dir.create(fna, recursive = T, showWarnings = F)
save(dat, file = paste(fna, "num_biom", yr[i], ".RData", sep=""))
rm(dat, w)
print(paste("biomassData() function: finished year", yr[i]))
} # end of loop over years
} # end of function
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