Added 2019 SHR data and script to create 2019 SHR and STTD data table…

… csv and moved some files into the zoop folder

Zoop_code/Zoop_2019_SHR_STTD.R

@@ -0,0 +1,29 @@
+#2019 SHR and STTD zoop for contaminants manuscript
+
+library(tidyverse)
+
+#zooplankton data from Mallory and Nicole (biomass)
+zoopNDFAv2.1<-read.csv("Zoop_code/zoop_NDFA_v2_copy.csv", stringsAsFactors = FALSE)
+#data organization and cleanup
+
+zoopNDFAv2.1$StationCode <- factor(zoopNDFAv2.1$StationCode)
+
+zoopNDFAv2.1 <-  zoopNDFAv2.1%>% filter(Year=="2019")
+zoopNDFAv3.1 <- zoopNDFAv2.1 
+zoopNDFAv3.1$Year <- as.character(zoopNDFAv3.1$Year)
+
+
+zoopNDFAv3.1 <- zoopNDFAv3.1 %>% filter(StationCode!="RMB")
+zoopNDFAv3.1 <- zoopNDFAv3.1 %>% filter(StationCode!="RD22")
+zoopNDFAv3.1 <- zoopNDFAv3.1 %>% filter(StationCode!="RCS")
+zoopNDFAv3.1 <- zoopNDFAv3.1 %>% filter(StationCode!="I80")
+zoopNDFAv3.1 <- zoopNDFAv3.1 %>% filter(StationCode!="BL5")
+zoopNDFAv3.1 <- zoopNDFAv3.1 %>% filter(StationCode!="RYI")
+zoopNDFAv3.1 <- zoopNDFAv3.1 %>% filter(StationCode!="LIB")
+zoopNDFAv3.1 <- zoopNDFAv3.1 %>% filter(StationCode!="RVB")
+zoopNDFAv3.1 <- zoopNDFAv3.1 %>% filter(StationCode!="LIS")
+
+zoopNDFA4.1 <- zoopNDFAv3.1[,c("Year","Date","StationCode","Classification","Organism","CPUEZoop")] #new table with relevant columns
+
+zoopNDFA4.1$StationCode <- as.character(zoopNDFA4.1$StationCode)
+#write.csv(zoopNDFA4.1, file = "C:/Users/jadams/Documents/DES docs and forms/NDFA/Manuscript/ND-FASTR/Zoop_code/zoop_2019_SHR_STTD.csv")

Zoop_code/ted-zoop-analyses/zoop-data-processing-FASTRv2.R

@@ -401,6 +401,7 @@ for (year in years) {
   anosim_r$p_value[which(anosim_r$Year == year)] <- test$signif
 
 }
+anosim_r
 
 # Calculate ANOSIM comparisons for zoop communities by Sample Period
 anosim_S <- data.frame(Year = years, 
@@ -421,7 +422,7 @@ for (year in years) {
   anosim_S$p_value[which(anosim_S$Year == year)] <- testS$signif
 
 }
-
+anosim_S
 
 ####recreating Ted's plots####