Merge branch 'main' of https://github.com/NEFSC/EAD-ASEB_EPA_LISS_Dis…

…ease_Surveillance

Lab_Data_RFTM/code/RFTM_QAQC.Rmd

@@ -6,7 +6,7 @@ output: html_document
 
 description: This R code is used to import and summarize RFTM (Rays Fluid Thioglycollate Medium) intensity scoring from the LISS Oyster Health Project's monthly sampling at Ash Creek and Fence Creek intertidal sites in Connecticut and Goldstar beach and Laurel Hollow subtidal sites on Long Island, NY. The scale used to score intensity for individuals is the Mackins Scale (citation). This score can be used to calculate prevalence, weighted prevalence and intensity across the population. 
 ---
-Last updated 1/17/25 by K. Lenderman
+Last updated 2/12/25 by K. Lenderman
   - Added code for 2025 data changed graph formats
   - Accuracy 80.8%
   - Master file and Completeness file are up to date.

Lab_Data_RFTM/output/Completeness_RFTM_intensity_data.csv

@@ -18,6 +18,7 @@
 "ASHC",2024-11-13,30,1.16666666666667,1.00286944635719,0.183098072667517,0.374477605636974,1
 "ASHC",2024-12-09,29,0.982758620689655,0.761609651385632,0.141427361772962,0.289700817900994,0.966666666666667
 "ASHC",2025-01-06,30,0.6,0.593063350689481,0.108278058400742,0.221453494633773,1
+"ASHC",2025-02-05,29,0.362068965517241,0.375512785690113,0.0697309737285323,0.142837424589862,0.966666666666667
 "FENC",2023-04-27,30,0.533333333333333,0.392457626382451,0.0716526316115342,0.146546086108725,1
 "FENC",2023-05-15,30,0.433333333333333,0.217086242727652,0.0396343440219923,0.0810613352402638,1
 "FENC",2023-06-14,30,0.45,0.634496813937274,0.115842739219534,0.23692500407764,1
@@ -37,6 +38,7 @@
 "FENC",2024-11-12,30,0.65,0.645274600728114,0.117810484867976,0.240949495806011,1
 "FENC",2024-12-10,30,0.833333333333333,0.854333106856608,0.155979171416279,0.319013224935871,1
 "FENC",2025-01-08,30,0.783333333333333,0.582552844033873,0.10635911120538,0.217528806948133,1
+"FENC",2025-02-04,30,0.3,0.534983080621924,0.0976741003800776,0.19976596536598,1
 "GOLD",2023-05-25,30,0.1,0.203419051086243,0.0371390676354104,0.0759579220091126,1
 "GOLD",2023-06-20,30,0.25,0.254273813857804,0.046423834544263,0.0949474025113908,1
 "GOLD",2023-07-17,30,0.233333333333333,0.739679955644067,0.135046465680225,0.276201034674454,1

Lab_Data_RFTM/raw_data/Files_by_Month/0225ASHC_RFTM - Master.csv

@@ -0,0 +1,31 @@
+lab_id,date_collected,site,lab_sample,date_rftmread1,rftm_reader1,rftm_intensity_read1,duplicate_read,date_rftmread2,rftm_reader2,rftm_intensity_read2,rftm_notes,rftm_final
+0225ASHC_01,2025-02-05,ASHC,1,2025-02-12,Kyra Lenderman,0.5,FALSE,,,,,0.5
+0225ASHC_02,2025-02-05,ASHC,2,2025-02-12,Kyra Lenderman,0.5,FALSE,,,,,0.5
+0225ASHC_03,2025-02-05,ASHC,3,2025-02-12,Mariah Kachmar,0,TRUE,2025-02-12,Isaiah Mayo,0,,0
+0225ASHC_04,2025-02-05,ASHC,4,2025-02-12,Mariah Kachmar,0,FALSE,,,,,0
+0225ASHC_05,2025-02-05,ASHC,5,2025-02-12,Kyra Lenderman,0.5,FALSE,,,,,0.5
+0225ASHC_06,2025-02-05,ASHC,6,2025-02-12,Kyra Lenderman,0.5,FALSE,,,,,0.5
+0225ASHC_07,2025-02-05,ASHC,7,2025-02-12,Isaiah Mayo,0.5,TRUE,2025-02-12,Kyra Lenderman,0.5,,0.5
+0225ASHC_08,2025-02-05,ASHC,8,2025-02-12,Isaiah Mayo,1,TRUE,2025-02-12,Kyra Lenderman,0.5,,0.5
+0225ASHC_09,2025-02-05,ASHC,9,2025-02-12,Kyra Lenderman,1,FALSE,,,,,1
+0225ASHC_10,2025-02-05,ASHC,10,2025-02-12,Kyra Lenderman,0.5,FALSE,,,,,0.5
+0225ASHC_11,2025-02-05,ASHC,11,2025-02-12,Isaiah Mayo,0,FALSE,,,,,0
+0225ASHC_12,2025-02-05,ASHC,12,2025-02-12,Isaiah Mayo,0.5,FALSE,,,,,0.5
+0225ASHC_13,2025-02-05,ASHC,13,2025-02-12,Isaiah Mayo,0,FALSE,,,,,0
+0225ASHC_14,2025-02-05,ASHC,14,2025-02-12,Isaiah Mayo,0,FALSE,,,,,0
+0225ASHC_15,2025-02-05,ASHC,15,2025-02-12,Kyra Lenderman,0.5,FALSE,,,,,0.5
+0225ASHC_16,2025-02-05,ASHC,16,2025-02-12,Kyra Lenderman,1,FALSE,,,,,1
+0225ASHC_17,2025-02-05,ASHC,17,2025-02-12,Isaiah Mayo,0,FALSE,,,,,0
+0225ASHC_18,2025-02-05,ASHC,18,2025-02-12,,,,,,,no tissue present,
+0225ASHC_19,2025-02-05,ASHC,19,2025-02-12,Isaiah Mayo,1,FALSE,,,,,1
+0225ASHC_20,2025-02-05,ASHC,20,2025-02-12,Isaiah Mayo,1,FALSE,,,,,1
+0225ASHC_21,2025-02-05,ASHC,21,2025-02-12,Kyra Lenderman,0,FALSE,,,,,0
+0225ASHC_22,2025-02-05,ASHC,22,2025-02-12,Kyra Lenderman,0,FALSE,,,,,0
+0225ASHC_23,2025-02-05,ASHC,23,2025-02-12,Kyra Lenderman,0,FALSE,,,,,0
+0225ASHC_24,2025-02-05,ASHC,24,2025-02-12,Kyra Lenderman,0,FALSE,,,,,0
+0225ASHC_25,2025-02-05,ASHC,25,2025-02-12,Isaiah Mayo,1,FALSE,,,,,1
+0225ASHC_26,2025-02-05,ASHC,26,2025-02-12,Isaiah Mayo,0,FALSE,,,,,0
+0225ASHC_27,2025-02-05,ASHC,27,2025-02-12,Kyra Lenderman,0.5,FALSE,,,,,0.5
+0225ASHC_28,2025-02-05,ASHC,28,2025-02-12,Kyra Lenderman,0.5,FALSE,,,,,0.5
+0225ASHC_29,2025-02-05,ASHC,29,2025-02-12,Isaiah Mayo,0,FALSE,,,,,0
+0225ASHC_30,2025-02-05,ASHC,30,2025-02-12,Isaiah Mayo,0,FALSE,,,,,0

Lab_Data_RFTM/raw_data/Files_by_Month/0225FENC_RFTM - Master.csv

@@ -0,0 +1,31 @@
+lab_id,date_collected,site,lab_sample,date_rftmread1,rftm_reader1,rftm_intensity_read1,duplicate_read,date_rftmread2,rftm_reader2,rftm_intensity_read2,rftm_notes,rftm_final
+0225FENC_01,2025-02-04,FENC,1,2025-02-11,Mariah Kachmar,0.5,FALSE,,,,,0.5
+0225FENC_02,2025-02-04,FENC,2,2025-02-11,Mariah Kachmar,0,FALSE,,,,,0
+0225FENC_03,2025-02-04,FENC,3,2025-02-11,Kyra Lenderman,1,FALSE,,,,,1
+0225FENC_04,2025-02-04,FENC,4,2025-02-11,Kyra Lenderman,0,FALSE,,,,,0
+0225FENC_05,2025-02-04,FENC,5,2025-02-11,Isaiah Mayo,0.5,FALSE,,,,,0.5
+0225FENC_06,2025-02-04,FENC,6,2025-02-11,Isaiah Mayo,0,FALSE,,,,,0
+0225FENC_07,2025-02-04,FENC,7,2025-02-11,Mariah Kachmar,0,FALSE,,,,,0
+0225FENC_08,2025-02-04,FENC,8,2025-02-11,Mariah Kachmar,0,FALSE,,,,,0
+0225FENC_09,2025-02-04,FENC,9,2025-02-11,Isaiah Mayo,0,FALSE,,,,,0
+0225FENC_10,2025-02-04,FENC,10,2025-02-11,Isaiah Mayo,0.5,FALSE,,,,,0.5
+0225FENC_11,2025-02-04,FENC,11,2025-02-11,Isaiah Mayo,0,FALSE,,,,,0
+0225FENC_12,2025-02-04,FENC,12,2025-02-11,Isaiah Mayo,0,FALSE,,,,,0
+0225FENC_13,2025-02-04,FENC,13,2025-02-11,Isaiah Mayo,0.5,TRUE,2025-02-11,Kyra Lenderman,0.5,,0.5
+0225FENC_14,2025-02-04,FENC,14,2025-02-11,Isaiah Mayo,0,TRUE,2025-02-11,Kyra Lenderman,0,,0
+0225FENC_15,2025-02-04,FENC,15,2025-02-11,Mariah Kachmar,0.5,FALSE,,,,,0.5
+0225FENC_16,2025-02-04,FENC,16,2025-02-11,Mariah Kachmar,0,FALSE,,,,,0
+0225FENC_17,2025-02-04,FENC,17,2025-02-11,Mariah Kachmar,0,FALSE,,,,,0
+0225FENC_18,2025-02-04,FENC,18,2025-02-11,Mariah Kachmar,0,FALSE,,,,,0
+0225FENC_19,2025-02-04,FENC,19,2025-02-11,Isaiah Mayo,0.5,FALSE,,,,,0.5
+0225FENC_20,2025-02-04,FENC,20,2025-02-11,Isaiah Mayo,0,FALSE,,,,,0
+0225FENC_21,2025-02-04,FENC,21,2025-02-11,Mariah Kachmar,0.5,FALSE,,,,,0.5
+0225FENC_22,2025-02-04,FENC,22,2025-02-11,Mariah Kachmar,0,FALSE,,,,,0
+0225FENC_23,2025-02-04,FENC,23,2025-02-11,Isaiah Mayo,0,FALSE,,,,,0
+0225FENC_24,2025-02-04,FENC,24,2025-02-11,Isaiah Mayo,2,TRUE,2025-02-11,Kyra Lenderman,2,,2
+0225FENC_25,2025-02-04,FENC,25,2025-02-11,Isaiah Mayo,2,FALSE,,,,,2
+0225FENC_26,2025-02-04,FENC,26,2025-02-11,Isaiah Mayo,0,FALSE,,,,,0
+0225FENC_27,2025-02-04,FENC,27,2025-02-11,Kyra Lenderman,0.5,FALSE,,,,,0.5
+0225FENC_28,2025-02-04,FENC,28,2025-02-11,Kyra Lenderman,0,FALSE,,,,,0
+0225FENC_29,2025-02-04,FENC,29,2025-02-11,Mariah Kachmar,0,FALSE,,,,,0
+0225FENC_30,2025-02-04,FENC,30,2025-02-11,Mariah Kachmar,0,FALSE,,,,,0

Lab_Data_Reproduction/code/ReproductiveScoring.Rmd

@@ -108,6 +108,17 @@ data_all
 ```
 
 ```{r}
+#Creating count graph for stage and sex of each site
+LAUR_repro <- data_all%>% filter(Site == "LAUR")
+ggplot(LAUR_repro, aes(x=Stage_final, fill=Sex_final))+
+  labs(title = "Gonadal Scoring - LAUR")+
+  geom_histogram(stat = "count")
+
+GOLD_repro <- data_all%>% filter(Site == "GOLD")
+ggplot(GOLD_repro, aes(x=Stage_final, fill=Sex_final))+
+  labs(title = "Gonadal Scoring - GOLD")+
+  geom_histogram(stat = "count")
+
 ASHC_repro <- data_all%>% filter(Site == "ASHC")
 ggplot(ASHC_repro, aes(x=Stage_final, fill=Sex_final))+
   labs(title = "Gonadal Scoring - ASHC")+
@@ -119,7 +130,7 @@ ggplot(FENC_repro, aes(x=Stage_final, fill=Sex_final))+
   geom_histogram(stat = "count")
 ```
 ```{r}
-#Creating proportions
+#Creating proportions for stages and sex
 df_score_proportions<- data_all %>%
   mutate(stage_final_numeric = as.factor(Stage_final),stage_bin = case_when(Stage_final == 0 ~ "0_Castrated", Stage_final == 1 ~ "1_Inactive_Indeterminate", Stage_final == 2 ~"2_Developing",Stage_final == 3 ~ "3_Early_Active", Stage_final == 4 ~"4_Late_Mature",Stage_final == 5 ~ "5_Spawning", Stage_final == 6 ~ "6_Post_Spawning", Stage_final == 7 ~ "7_Reabsorbing", TRUE ~ as.character(Stage_final))) %>%
   group_by(Site, month,year, stage_bin) %>%
@@ -143,14 +154,14 @@ df_sex_proportions
 ```
 
 ```{r}
-#Proportion graphs of just scores
+#Proportion graphs of scores
 #will need to separate by years, once we have 2024 reproductive data
 ggplot(data=df_score_proportions, aes(x=month, y= Proportion, fill=stage_bin)) +
   geom_bar(width = .5, stat="identity", position = "fill",colour = "black")+  
    theme_bw() +  theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank())+ 
   theme(axis.text.x = element_text(angle = 45, vjust = 1, hjust=1))+
   labs(fill ="Gonadal Score")+
-  labs(title="Proportion of gonadal scores", x ="month", y = "Proportion")+ theme(axis.title.y = element_text(size = rel(1.3), angle =90), axis.title.x = element_text(size = rel(1.3), angle = 0))+
+  labs(title="Proportion of gonadal scores - 2023", x ="month", y = "Proportion")+ theme(axis.title.y = element_text(size = rel(1.3), angle =90), axis.title.x = element_text(size = rel(1.3), angle = 0))+
   theme(axis.text=element_text(size=12))+
 scale_fill_brewer(palette = "YlGnBu")+
    scale_x_continuous("Month", breaks = c(3,4,5,6,7,8,9,10,11))+ 
@@ -169,16 +180,17 @@ scale_fill_brewer(palette = "Pastel1")+
    scale_x_continuous("Month", breaks = c(3,4,5,6,7,8,9,10,11))+ 
   facet_wrap(~Site)
 ```
+#Need to determine code for having two points summarizing spawning (4 & 5)
 #ASHC Summary
 ```{r}
 df_ASHC<- data_all%>%
   filter(Site=="ASHC")
 df_ASHC
 
 ASHC_mature_spawning <- df_ASHC %>%
-  dplyr::mutate(stage = recode(Stage_final, "0_Castrated" = 0, "1_Inactive_Inderterminate" = 1, "2_Developing" = 2, "3_Early_Active" = 3, "4_Late_Mature" = 4, "5_Spawning" = 5, "6_Post_Spawning" = 6, "7_Reabsorbing" = 7)) %>%
+  dplyr::mutate(stage = recode(Stage_final, "0_Castrated" = 0, "1_Inactive_Indeterminate" = 1, "2_Developing" = 2, "3_Early_Active" = 3, "4_Late_Mature" = 4, "5_Spawning" = 5, "6_Post_Spawning" = 6, "7_Reabsorbing" = 7)) %>%
   dplyr::group_by(month, Site, year) %>%
-  dplyr::summarise(Percentage = mean(stage == 4)*100)
+  dplyr::summarise(Percentage = mean(stage == 5)*100)
 ASHC_mature_spawning
 
 ASHC_spawning <- ASHC_mature_spawning%>% 
@@ -211,7 +223,7 @@ df_FENC<- data_all%>%
 df_FENC
 
 FENC_mature_spawning <- df_FENC %>%
-  dplyr::mutate(stage = recode(Stage_final, "0_Castrated" = 0, "1_Inactive_Inderterminate" = 1, "2_Developing" = 2, "3_Early_Active" = 3, "4_Late_Mature" = 4, "5_Spawning" = 5, "6_Post_Spawning" = 6, "7_Reabsorbing" = 7)) %>%
+  dplyr::mutate(stage = recode(Stage_final, "0_Castrated" = 0, "1_Inactive_Indeterminate" = 1, "2_Developing" = 2, "3_Early_Active" = 3, "4_Late_Mature" = 4, "5_Spawning" = 5, "6_Post_Spawning" = 6, "7_Reabsorbing" = 7)) %>%
   dplyr::group_by(month, Site, year) %>%
   dplyr::summarise(Percentage = mean(stage >= 4)*100)
 #need to try an just have 4 and 5 be the scores for percentage because that is when spawning is happening
@@ -240,7 +252,78 @@ FENC_spawning <- FENC_mature_spawning%>%
 
 FENC_spawning
 ```
+#LAUR Summary
+```{r}
+df_LAUR<- data_all%>%
+  filter(Site=="LAUR")
+df_LAUR
+
+LAUR_mature_spawning <- df_LAUR %>%
+  dplyr::mutate(stage = recode(Stage_final, "0_Castrated" = 0, "1_Inactive_Indeterminate" = 1, "2_Developing" = 2, "3_Early_Active" = 3, "4_Late_Mature" = 4, "5_Spawning" = 5, "6_Post_Spawning" = 6, "7_Reabsorbing" = 7)) %>%
+  dplyr::group_by(month, Site, year)%>%
+  dplyr::summarise(Percentage = mean(stage >= 4)*100)
+#need to try an just have 4 and 5 be the scores for percentage because that is when spawning is happening
+LAUR_mature_spawning
+
+LAUR_spawning <- LAUR_mature_spawning%>% 
+  #filter(year =="2024")%>%
+  ggplot(aes(x = month, y = Percentage)) +
+  #geom_bar(width = 0.5, stat = "identity", position = "fill") +
+    geom_col()+
+  theme_bw() +
+  theme(
+    panel.grid.major = element_blank(),
+    panel.grid.minor = element_blank(),
+    axis.text.x = element_text(angle = 45, vjust = 1, hjust = 1),
+    axis.title.y = element_text(size = rel(1.3), angle = 90),
+    axis.title.x = element_text(size = rel(1.3), angle = 0),
+    axis.text = element_text(size = 12)
+  ) +
+  labs(
+    title = "Laurel Hollow % of spawning",
+    x = "month",
+    y = "Percentage of spawning scores 4 & 5"
+  ) + ylim(0,100)
+    #facet_wrap(~year)
 
+LAUR_spawning
+```
+#GOLD Summary
+```{r}
+df_GOLD<- data_all%>%
+  filter(Site=="GOLD")
+df_GOLD
+
+GOLD_mature_spawning <- df_GOLD %>%
+  dplyr::mutate(stage = recode(Stage_final, "0_Castrated" = 0, "1_Inactive_Indeterminate" = 1, "2_Developing" = 2, "3_Early_Active" = 3, "4_Late_Mature" = 4, "5_Spawning" = 5, "6_Post_Spawning" = 6, "7_Reabsorbing" = 7)) %>%
+  dplyr::group_by(month, Site, year)%>%
+  dplyr::summarise(Percentage = mean(stage >= 4)*100)
+#need to try an just have 4 and 5 be the scores for percentage because that is when spawning is happening
+GOLD_mature_spawning
+
+GOLD_spawning <- GOLD_mature_spawning%>% 
+  #filter(year =="2024")%>%
+  ggplot(aes(x = month, y = Percentage)) +
+  #geom_bar(width = 0.5, stat = "identity", position = "fill") +
+    geom_col()+
+  theme_bw() +
+  theme(
+    panel.grid.major = element_blank(),
+    panel.grid.minor = element_blank(),
+    axis.text.x = element_text(angle = 45, vjust = 1, hjust = 1),
+    axis.title.y = element_text(size = rel(1.3), angle = 90),
+    axis.title.x = element_text(size = rel(1.3), angle = 0),
+    axis.text = element_text(size = 12)
+  ) +
+  labs(
+    title = "Gold Star % of spawning",
+    x = "month",
+    y = "Percentage of spawning scores 4 & 5"
+  ) + ylim(0,100)
+    #facet_wrap(~year)
+
+GOLD_spawning
+```
 
 ## R Markdown
 

Lab_Data_Reproduction/raw_data/0523LAUR_Gonad_Scoring.csv

@@ -0,0 +1,31 @@
+Sample_ID,Date_collected,Site,Lab_sample,Date_read1,reader1,Sex1,Stage1,Duplicate_read,Date_read2,reader2,Sex2,Stage2,Notes,Sex_final,Stage_final,Column 1
+0523LAUR_01,05-25-2023,LAUR,1,01-02-2025,Kyra Lenderman,Female,5_Spawning,TRUE,,Mariah Kachmar,Female,5_Spawning,,Female,5_Spawning,
+0523LAUR_02,05-25-2023,LAUR,2,01-02-2025,Kyra Lenderman,Female,4_Late_Mature,,,,,,May be spawning,Female,4_Late_Mature,
+0523LAUR_03,05-25-2023,LAUR,3,01-02-2025,Kyra Lenderman,Female,5_Spawning,,,,,,,Female,5_Spawning,
+0523LAUR_04,05-25-2023,LAUR,4,01-02-2025,Kyra Lenderman,Female,3_Early_Active,,,,,,"found spots that are 3, but more spots with 4",Female,4_Late_Mature,
+0523LAUR_05,05-25-2023,LAUR,5,01-02-2025,Kyra Lenderman,Female,3_Early_Active,,,,,,partially full but gonads are mature/developed,Female,3_Early_Active,
+0523LAUR_06,05-25-2023,LAUR,6,01-02-2025,Kyra Lenderman,Female,4_Late_Mature,,,,,,"outer layer of mantle is not there, so it may be spawning or may just be mature",Female,4_Late_Mature,
+0523LAUR_07,05-25-2023,LAUR,7,01-02-2025,Kyra Lenderman,NA,1_Inactive_Indeterminate,TRUE,,Mariah Kachmar,NA,1_Inactive_Indeterminate,no gonads present,NA,1_Inactive_Indeterminate,
+0523LAUR_08,05-25-2023,LAUR,8,01-02-2025,Kyra Lenderman,Female,5_Spawning,TRUE,,Mariah Kachmar,Female,5_Spawning,,Female,4_Late_Mature,
+0523LAUR_09,05-25-2023,LAUR,9,01-02-2025,Kyra Lenderman,Male,4_Late_Mature,,,,,,potentially hermaphrodite but it may be feeding on eggs that is why they are present,Male,4_Late_Mature,
+0523LAUR_10,05-25-2023,LAUR,10,01-02-2025,Kyra Lenderman,Female,3_Early_Active,,,,,,,Female,3_Early_Active,
+0523LAUR_11,05-25-2023,LAUR,11,01-02-2025,Kyra Lenderman,Female,4_Late_Mature,TRUE,,Mariah Kachmar,Female,4_Late_Mature,"barely any outer layer of the mantle, may be spawning",Female,4_Late_Mature,
+0523LAUR_12,05-25-2023,LAUR,12,01-02-2025,Kyra Lenderman,NA,2_Developing,,,,,,msx,NA,7_Reabsorbing,
+0523LAUR_13,05-25-2023,LAUR,13,01-02-2025,Kyra Lenderman,Male,4_Late_Mature,,,,,,,Male,4_Late_Mature,
+0523LAUR_14,05-25-2023,LAUR,14,01-02-2025,Kyra Lenderman,Male,3_Early_Active,,,,,,"do not see tails, is that from the staining?",Male,3_Early_Active,
+0523LAUR_15,05-25-2023,LAUR,15,01-02-2025,Kyra Lenderman,Male,4_Late_Mature,,,,,,,Male,4_Late_Mature,
+0523LAUR_16,05-25-2023,LAUR,16,01-02-2025,Kyra Lenderman,NA,1_Inactive_Indeterminate,,,,,,msx,NA,7_Reabsorbing,
+0523LAUR_17,05-25-2023,LAUR,17,01-02-2025,Kyra Lenderman,NA,1_Inactive_Indeterminate,,,,,,,NA,7_Reabsorbing,
+0523LAUR_18,05-25-2023,LAUR,18,01-02-2025,Kyra Lenderman,Female,5_Spawning,TRUE,,Mariah Kachmar,Female,5_Spawning,,Female,5_Spawning,
+0523LAUR_19,05-25-2023,LAUR,19,01-02-2025,Kyra Lenderman,Male,4_Late_Mature,TRUE,,Mariah Kachmar,Male,4_Late_Mature,,Male,5_Spawning,
+0523LAUR_20,05-25-2023,LAUR,20,01-02-2025,Kyra Lenderman,Male,4_Late_Mature,,,,,,,Male,5_Spawning,
+0523LAUR_21,05-25-2023,LAUR,21,01-02-2025,Kyra Lenderman,Male,4_Late_Mature,TRUE,,Mariah Kachmar,Male,4_Late_Mature,,Male,5_Spawning,
+0523LAUR_22,05-25-2023,LAUR,22,01-02-2025,Kyra Lenderman,Male,4_Late_Mature,TRUE,,Mariah Kachmar,Male,4_Late_Mature,,Male,4_Late_Mature,
+0523LAUR_23,05-25-2023,LAUR,23,01-02-2025,Kyra Lenderman,Female,4_Late_Mature,,,,,,eaten eggs,Female,5_Spawning,
+0523LAUR_24,05-25-2023,LAUR,24,01-02-2025,Kyra Lenderman,Female,5_Spawning,TRUE,,Mariah Kachmar,Female,5_Spawning,poor cut only half visible,Female,5_Spawning,
+0523LAUR_25,05-25-2023,LAUR,25,01-02-2025,Kyra Lenderman,Female,5_Spawning,,,,,,,Female,5_Spawning,
+0523LAUR_26,05-25-2023,LAUR,26,01-02-2025,Kyra Lenderman,Male,4_Late_Mature,,,,,,,Male,4_Late_Mature,
+0523LAUR_27,05-25-2023,LAUR,27,01-02-2025,Kyra Lenderman,Male,4_Late_Mature,,,,,,Bad cut,Male,4_Late_Mature,
+0523LAUR_28,05-25-2023,LAUR,28,01-02-2025,Kyra Lenderman,Female,3_Early_Active,,,,,,there are very mature eggs but not many,Female,4_Late_Mature,
+0523LAUR_29,05-25-2023,LAUR,29,01-02-2025,Kyra Lenderman,Female,4_Late_Mature,TRUE,,Mariah Kachmar,Female,4_Late_Mature,"some underdeveloped eggs are in different spots on the other layer of mantle. Clean up from spawning, but still many eggs present.",Female,5_Spawning,
+0523LAUR_30,05-25-2023,LAUR,30,01-02-2025,Kyra Lenderman,Male,4_Late_Mature,TRUE,,Mariah Kachmar,Male,4_Late_Mature,,Male,4_Late_Mature,