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7a_WORMS_R3.1.2
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## Script Info
## Purpose: Compiling the Species lists of all datras datasets
## to get the Aphia Codes for the complete species lists
## Author: Meadhbh Moriarty
## Reviewers:
## Date: 23/05/2016
## some general housekeeping
## remove objets stored in R environment
rm(list=ls())
## set working directory
setwd("~/MSFD-QA-GFSM-A-DP/Data_Cleaning_Process")
## check proxy settings
Sys.getenv("http_proxy")
## fix ";" to ":" to allow connection be established
Sys.setenv(http_proxy="http://192.168.41.8:80")
# proxy for france
# Sys.setenv(http_proxy="http://134.246.166.17:3128")
#################
# LOAD PACKAGES #
#################
library(doParallel)
library(data.table)
library(SSOAP)
library(plyr)
#############
# LOAD DATA #
#############
MySpeciesList<-read.csv("MySpeciesList_23-05-2016.csv")
names(MySpeciesList)
#-------------------------------------------#
# Quick check that function is doing its job#
#-------------------------------------------#
w = processWSDL("http://www.marinespecies.org/aphia.php?p=soap&wsdl=1")
iface = genSOAPClientInterface(, w)
AphiaID = iface@functions$getAphiaID("Solea solea",1,('http://www.marinespecies.org/aphia.php?p=soap'))
print(AphiaID)
# should output '[0] 127160'
#------------------------------------------------------------------#
# Get original AphiaID's for specieslist only is names not for IDs #
#------------------------------------------------------------------#
# AphiaMatch <- function(x) {
# result<-NULL
# for (i in 1:length(x)) {
# AphiaRecord <- iface@functions$getAphiaID(x[i],1,('http://www.marinespecies.org/aphia.php?p=soap'))
# result<-c(result, AphiaRecord)
# }
# return(result)
# }
#------------------------------------------------#
# Get accepted synonym AphiaID's for specieslist #
#------------------------------------------------#
SynResolv <- function(x) {
result<-NULL
for (i in 1:length(x)) {
AphiaRecord <- iface@functions$getAphiaRecordByID(x[i],('http://www.marinespecies.org/aphia.php?p=soap'))
result<-c(result, slot(AphiaRecord, "valid_AphiaID"))
}
return(result)
}
AccTaxID<-SynResolv(MySpeciesList$list_unique)
#---------------------------------------------------------------------
# Add full record information (classification, ranking, authority,...)
#---------------------------------------------------------------------
getFullRecord <- function(x) {
result<-NULL
for (i in 1:length(x)) {
AphiaRecord <- iface@functions$getAphiaRecordByID(x[i],('http://www.marinespecies.org/aphia.php?p=soap'))
slotnames <- slotNames(AphiaRecord)
slotlist <- data.frame(rbind(1:length(slotnames)))
names(slotlist) <- slotnames
for(y in slotnames) {
#R cannot handle a slot name "class"
if (y == "CLASS") {slotlist[1,y] <- '(empty)'}
else {slotlist[1, y] <- slot(AphiaRecord, y)}
}
result<-rbind(result, slotlist)
}
return(result)
}
# get full taxonomic record for the 1049 aphia id records
AphiaRecords<-getFullRecord(AccTaxID)
head(AphiaRecords)
# write a table to save the information
write.table(AphiaRecords, "AphiaRecords_23_05_2016.csv", sep=",")
# attach the Aphia records to the biological data
# change the AphiaID to Valid_Aphia to merge the two dataframes
bio$AphiaID<-bio$Valid_Aphia
MySpecList<-merge(bio, AphiaRecords, by="AphiaID")
head(MySpecList)
# write a table to save the all the information
write.table(MySpecList, "Species_Data_09_12_2015.csv", sep=",")
# Delete non fish records from bio file (MySpecList)
MyFishList<-subset(MySpecList, phylum=="Chordata")
MyFishList$totalno<-(as.numeric(MyFishList$TotalNo))
# Delete Country DUM - not used in HL file
keep<-c("DEN", "ENG", "FRA", "GFR", "IRL", "NED", "NI", "POR", "SCO", "SPA", "SWE")
MyFishList<-subset(MyFishList, Country==keep)
summaryfish<-ddply(MyFishList, c( "Country", "Survey", "Quarter", "Year",
"Valid_Aphia","rank","scientificname" ),
summarise, sumtotalno=sum(totalno))
nospecies<-ddply(summaryfish, c("Country", "Survey", "Quarter",
"rank", "Year"), summarise,
countofspecies=length(Valid_Aphia) )
nospeciescountryyear<-ddply(summaryfish, c("Country", "Survey",
"rank", "Year"), summarise,
countofspecies=length(Valid_Aphia) )
library(ggplot2)
k<-ggplot(nospecies, aes(x=Year, y=countofspecies, colour=Quarter, group=Quarter))
k + geom_line(aes(fill=rank)) +facet_grid(rank~Country+Survey, margins=F, drop=T)
k + geom_bar(aes(fill=factor(rank))) +facet_grid(.~Country+Survey, margins=F, drop=T)
k<-ggplot(nospeciescountryyear, aes(x=Year, y=countofspecies, colour=rank, group=rank))
k + geom_line(aes(fill=rank)) +facet_grid(rank~Survey+Country, margins=F, drop=T)
k1<-ggplot(subset(nospecies, rank%in%"Species"))
k2<-k1 + geom_line(aes(x=Year, y=countofspecies, colour=Quarter, group=Quarter, size=rank)) + facet_wrap(~Survey+Country, ncol=3, drop=T)
k2 + theme(axis.text.x = element_text(angle=90, vjust=1))
l1<-ggplot(subset(nospeciescountryyear, rank%in%"Species"))
l2<-l1 + geom_line(aes(x=Year, y=countofspecies, colour=rank, group=rank, size=rank)) + facet_wrap(~Survey+Country, ncol=3, drop=T)
l2 + theme(axis.text.x = element_text(angle=90, vjust=1))
#---------------------------------------------------------------------
# Get full record information for all other surveys eg Spanish?
#---------------------------------------------------------------------
library(rfishbase)
MyFishDistribution<-distribution("Clupea harengus")
MyFishLW<-length_weight("Clupea harengus")
Denmark83_86<-subset(MyFishList, Year<1987 & Survey%in%"NS-IBTS" & Country%in%"DEN")
head(Denmark83_86)
write.csv(Denmark83_86, "denmarkDATRASDATA.csv")
herring<-species("Clupea harengus")
tables<-docs()
faoareas<-faoareas("Clupea harengus")
#--------------------------------
# Whats the story with the gobies in each survey? #
#-------------------------------
names(MyFishList)
levels(as.factor(MyFishList$family))
gobies<-subset(MyFishList, family%in%"Gobiidae")
summarygobies<-ddply(gobies, c("Country", "Survey",
"rank", "Year"), summarise,
countofspecies=length(Valid_Aphia) )
k<-ggplot(summarygobies, aes(x=Year, y=countofspecies, colour=rank, group=rank))
kk<-k + geom_line(aes(fill=rank)) + facet_wrap(~Survey+Country, ncol=3, drop=T)
kk + theme(axis.text.x = element_text(angle=90, vjust=1))
k1<-ggplot(subset(nospecies, rank%in%"Species"))
k2<-k1 + geom_line(aes(x=Year, y=countofspecies, colour=Quarter, group=Quarter, size=rank)) + facet_wrap(~Survey+Country, ncol=3, drop=T)
k2 + theme(axis.text.x = element_text(angle=90, vjust=1))
l1<-ggplot(subset(nospeciescountryyear, rank%in%"Species"))
l2<-l1 + geom_line(aes(x=Year, y=countofspecies, colour=rank, group=rank, size=rank)) + facet_wrap(~Survey+Country, ncol=3, drop=T)
l2 + theme(axis.text.x = element_text(angle=90, vjust=1))
--------------
summarygear<-ddply(MyFishList, c("Gear", "Country",
"Survey"), summarise,
count=length(Gear) )
# My species list
head(AphiaRecords)
# reduce file to Chordata Only
MyAphiaFishList<-subset(AphiaRecords, phylum=="Chordata")
names(MyAphiaFishList)
write.csv(MyAphiaFishList, "WoRMS_Corrected_FishList.csv")
# load rfishbase lib
library(rfishbase)
MyFishBaseFishList<-species(MyAphiaFishList$scientificname)
write.csv(MyFishBaseFishList, "FishBaseSpeciesData.csv")
MyFishBaseFishDistribution<-distribution(MyFishBaseFishList$sciname)
MyFishBaseLengthWeight<-length_weight(MyFishBaseFishList$sciname)
# Simons species list
simonsspplist<-read.csv("speciesdata.csv")
names(simonsspplist)
AMspplist<-AphiaMatch(simonsspplist$CorrSciName)
simonsspplist$AMspplist<-AMspplist
write.csv(simonsspplist,"speciesdata_with_AphiaMatch.csv")
#-------------------------------------------
# Get accepted synonym AphiaID's for specieslist
synRes_sppList<-SynResolv(AMspplist)
#---------------------------------------------------------------------
# Add full record information (classification, ranking, authority,...)
#---------------------------------------------------------------------
SppList_full<-getFullRecord(synRes_sppList)
names(SppList_full)
write.csv(SppList_full, "spp_list_Worms.csv")
simonsspplistfishbase<-species(SppList_full$scientificname)
write.csv(simonsspplistfishbase, "spp_list_fishbase.csv")
simonsspplenghtsfishbase<-length_weight(SppList_full$scientificname)
write.csv(simonsspplenghtsfishbase, "spp_lenghts_fishbase.csv")
# ----------------------------------
# Explore the species data in europe
# ----------------------------------
head(MySpecList)
killer<-subset(MySpecList, Valid_Aphia==137102,)
bad_range<-subset(MySpecList, scientificname=='Nettastoma melanurum',)
bad_range<-subset(MySpecList, scientificname=='Ephippion guttifer',)
bad_range<-subset(MySpecList, scientificname=='Deania profundorum',)
bad_range<-subset(MySpecList, scientificname=='Benthodesmus elongatus',)
bad_range<-subset(MySpecList, scientificname=='Lestidiops jayakari jayakari',)
bad_range<-subset(MySpecList, scientificname=='Gasterosteus aculeatus williamsoni',)
bad_range<-subset(MySpecList, scientificname=='Solea senegalensis',)
bad_range<-subset(MySpecList, scientificname=='Monochirus hispidus',)
skate<-subset(MySpecList, scientificname=='Bathyraja brachyurops',)
library(plyr)
str(MyFishList)
summary_fish_numbers<-ddply(MyFishList, c("Country","Survey", "Quarter",
"Year", "Ship", "HaulNo",
"scientificname", "Sex", "SpecVal",
"totalno"), summarise,
sumnoatlngt=sum(as.numeric(HLNoAtLngt)*as.numeric(SubFactor)))
291990
114038+
177904
str(summary_fish_numbers)
match<-subset(summary_fish_numbers,
sumnoatlngt=totalno, )
nomatch_fish_numbers<-subset(summary_fish_numbers,
sumnoatlngt>totalno,
)
nomatch_fish_numbers<-subset(nomatch_fish_numbers,
totalno>0,
)
nomatch_fish_numbers1<-subset(summary_fish_numbers,
sumnoatlngt<totalno,
)
274473+20
levels(as.factor(nomatch_fish_numbers1$Survey))
levels(as.factor(nomatch_fish_numbers$Survey))
write.csv(nomatch_fish_numbers1, "nomatch_fish_numbers1.csv")
write.csv(nomatch_fish_numbers, "nomatch_fish_numbers.csv")
summaryfish<-ddply(MyFishList, c( "Country", "Survey", "Quarter", "Year",
"Valid_Aphia","rank","scientificname" ),
summarise, sumtotalno=sum(totalno))
head(summaryfish)
write.csv(summaryfish, "summary_of_fish_per_country_per_Year.csv")