Biometric sampling overview and subsets
Naomi Bakken
2024-08-15
This RMarkdown file includes the analysis on the snappers sampled overall for biometric measurements. Additionally, The brms package will not run when the conflicted package is installed, which is needed for certain functions in the dpylr package to work. So in this line of code I will do all the df subsetting steps which will be saved in the environment and can be used in the other scripts.
Load libraries
library(ggplot2)
library(conflicted)## Warning: package 'conflicted' was built under R version 4.4.1library(cowplot)
library(patchwork)## Warning: package 'patchwork' was built under R version 4.4.1library(summarytools)## Warning: package 'summarytools' was built under R version 4.4.1library(tidyverse)## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
## ✔ dplyr 1.1.4 ✔ readr 2.1.5
## ✔ forcats 1.0.0 ✔ stringr 1.5.1
## ✔ lubridate 1.9.3 ✔ tibble 3.2.1
## ✔ purrr 1.0.2 ✔ tidyr 1.3.1library(viridis)## Loading required package: viridisLiteDefine color palettes
safe_colorblind_palette <- c("#88CCEE", "#CC6677", "#DDCC77", "#117733", "#332288", "#AA4499", "#44AA99", "#999933", "#882255", "#661100", "#6699CC", "#888888")Load data file
“snapperdata_250624.csv” is the “WorkBook_OtolithProject_June_V1.9” file filtered to only include snappers.
snappers_df2506 <- read.csv("snapperdata_250624.csv")
#class categorical data as nominal factors
snappers_df2506$catch_month <- factor(snappers_df2506$catch_month)
snappers_df2506$year <- factor(snappers_df2506$year)
snappers_df2506$species <- factor(snappers_df2506$species)
snappers_df2506$common_name <- factor(snappers_df2506$common_name)
snappers_df2506$frozen <- factor(snappers_df2506$frozen)
snappers_df2506$catch_method <- factor(snappers_df2506$catch_method)
snappers_df2506$bait <- factor(snappers_df2506$bait)
snappers_df2506$area <- factor(snappers_df2506$area)
snappers_df2506$finclip <- factor(snappers_df2506$finclip)
snappers_df2506$otoliths <- factor(snappers_df2506$otoliths)
snappers_df2506$gutted <- factor(snappers_df2506$gutted)
snappers_df2506$gonads_present <- factor(snappers_df2506$gonads_present)
snappers_df2506$sex <- factor(snappers_df2506$sex)
snappers_df2506$maturity <- factor(snappers_df2506$maturity)
summary(snappers_df2506)
View(snappers_df2506)Overall sampling length overview
plot_species_FL <-ggplot(snappers_df2506, aes(x = species, y = FL_CM)) +
geom_boxplot() +
geom_jitter(aes(fill = frozen, color = frozen),
size = 1.8,
alpha = 0.6,
pch = 21) + #show individual occurences
theme_classic() +
coord_flip() +
scale_x_discrete(name = "Species",
labels = rev(str_wrap(c("E. oculatus (n=7)",
"L. bucanella (n=85)",
"L. synagris (n=31)",
"L. vivanus (n=88)",
"P. aquilonaris (n=24)",
"R. aurorubens (n=71)"), width = 14)),
limits = rev) +
scale_y_continuous(name = "Fork Length in cm", limits = c(10,70))+
scale_fill_viridis_d(name = "Frozen",
option = "D",
begin = 0.2,
end = 0.8,
labels = c("Yes", "No")) +
scale_color_viridis_d(guide = "none",
option = "D",
begin = 0.2,
end = 0.8) +
theme(axis.text.y=element_text(face = "italic")) +
labs(title = "Sampled snappers (May 2023 to June 2024)")
plot_species_FL
ggsave("snapperFLplot_2506.png", plot = plot_species_FL, width = 7.2, height = 3.8, dpi = 400)Catch method overview
plot_species_method <- ggplot(snappers_df2506, aes(catch_method)) +
theme_classic() +
geom_bar(aes(fill = catch_method)) +
scale_fill_viridis_d(option = "C", guide = "none", begin = 0, end = 0.4) +
scale_x_discrete(name = "Catch Method", labels =str_wrap(c("Not recorded", "Dropline", "Lobster trap", "Redfish trap"),width = 10)) +
scale_y_continuous(name = "Number of Individual Fish")+
labs(title = "Snapper Sample Catch Methods") +
theme(axis.text=element_text(size=12),
axis.title=element_text(size=14),
plot.title = element_text(size=16))
plot_species_method
ggsave("plot_species_method.png", plot = plot_species_method, width = 4, height = 3.4, dpi = 400)Bait overview
plot_species_bait <- ggplot(snappers_df2506, aes(bait)) +
theme_classic() +
geom_bar(aes(fill = bait)) +
scale_fill_viridis_d(option = "C", guide = "none", begin = 0.6, end = 1.0) +
scale_x_discrete(name = "Bait Type", labels =str_wrap(c("Not recorded", "Cowskin", "Japanese bait", "Japanese bait/squid"), width = 10)) +
scale_y_continuous(name = "Number of Individual Fish") +
labs(title = "Snapper Sample Bait Types") +
theme(axis.text=element_text(size=12),
axis.title=element_text(size=14),
plot.title = element_text(size=16))
plot_species_bait
ggsave("plot_species_bait.png", plot = plot_species_bait, width = 4, height = 3.4, dpi = 400)# Combine plots using plot_grid from cowplot
catchoverview_plot <- plot_grid(plot_species_method, plot_species_bait,
ncol = 2,
align = "v")
# Display the combined plot
print(catchoverview_plot)
#save high res plot
ggsave("catchoverviewplot.png", plot = catchoverview_plot, width = 8, height = 4, dpi = 400)Overall sex and maturity
conflicts_prefer(dplyr::filter)## [conflicted] Will prefer dplyr::filter over any other package.summary(snappers_df2506)## catch_date catch_month landing_time dissection_date
## Length:309 Sep :103 Length:309 Length:309
## Class :character Jun : 76 Class :character Class :character
## Mode :character May : 55 Mode :character Mode :character
## Jul : 34
## Apr : 15
## : 14
## (Other): 12
## dissection_time year month observer
## Length:309 2023:207 Length:309 Length:309
## Class :character 2024:102 Class :character Class :character
## Mode :character Mode :character Mode :character
##
##
##
##
## species common_name fish_code
## Etelis oculatus : 7 Blackfin Snapper :85 Length:309
## Lutjanus buccanella :85 Lane Snapper :31 Class :character
## Lutjanus synagris :31 Queen Snapper : 7 Mode :character
## Lutjanus vivanus :91 Vermilion Snapper:71
## Pristipomoides aquilonaris:24 Wenchman Snapper :24
## Rhomboplites aurorubens :71 Yelloweye Snapper:91
##
## frozen catch_method bait area
## N: 99 :174 :180 :105
## Y:210 Dropline : 31 Cowskin : 31 C2 : 71
## Lobster trap: 31 Japanese bait : 66 B4 : 46
## Redfish trap: 73 Japanese bait; Squid: 32 D5 : 31
## A3/A4 : 22
## D3 : 20
## (Other): 14
## SL_CM FL_CM TL_CM HH_CM
## Min. :13.70 Min. :14.00 Min. :14.90 Min. :2.900
## 1st Qu.:23.35 1st Qu.:21.60 1st Qu.:23.50 1st Qu.:4.725
## Median :27.00 Median :25.80 Median :28.50 Median :5.850
## Mean :27.36 Mean :27.02 Mean :29.78 Mean :6.026
## 3rd Qu.:31.20 3rd Qu.:30.70 3rd Qu.:33.80 3rd Qu.:6.975
## Max. :61.10 Max. :65.50 Max. :78.50 Max. :9.900
## NA's :173 NA's :14 NA's :227
## ED_CM W_G finclip otoliths gutted gonads_present
## Min. :0.800 Min. : 52.7 :146 N : 6 N:302 : 6
## 1st Qu.:1.425 1st Qu.: 163.5 N: 21 y : 2 Y: 7 N: 55
## Median :1.800 Median : 296.0 Y:142 Y :300 y: 2
## Mean :1.828 Mean : 437.8 Y : 1 Y:246
## 3rd Qu.:2.200 3rd Qu.: 486.8
## Max. :3.000 Max. :4118.8
## NA's :227 NA's :6
## sex maturity G1L_CM G2L_CM GW_G
## :100 :207 Min. : 1.000 Min. : 0.000 Length:309
## F:117 A: 32 1st Qu.: 2.600 1st Qu.: 2.500 Class :character
## M: 92 B: 34 Median : 3.750 Median : 3.700 Mode :character
## C: 34 Mean : 4.196 Mean : 4.204
## D: 2 3rd Qu.: 5.000 3rd Qu.: 5.200
## Max. :21.100 Max. :22.800
## NA's :63 NA's :73
## stomach._sample
## Length:309
## Class :character
## Mode :character
##
##
##
## #drop the columns with neither sex nor maturity measurements
snappers_reproduction <- snappers_df2506 %>%
filter(maturity != "" | sex != "")
summary(snappers_reproduction)## catch_date catch_month landing_time dissection_date
## Length:213 Sep :68 Length:213 Length:213
## Class :character May :55 Class :character Class :character
## Mode :character Jun :38 Mode :character Mode :character
## Jul :21
## Apr :15
## : 5
## (Other):11
## dissection_time year month observer
## Length:213 2023:111 Length:213 Length:213
## Class :character 2024:102 Class :character Class :character
## Mode :character Mode :character Mode :character
##
##
##
##
## species common_name fish_code
## Etelis oculatus : 4 Blackfin Snapper :55 Length:213
## Lutjanus buccanella :55 Lane Snapper :31 Class :character
## Lutjanus synagris :31 Queen Snapper : 4 Mode :character
## Lutjanus vivanus :44 Vermilion Snapper:55
## Pristipomoides aquilonaris:24 Wenchman Snapper :24
## Rhomboplites aurorubens :55 Yelloweye Snapper:44
##
## frozen catch_method bait area
## N: 99 :82 :88 :45
## Y:114 Dropline :28 Cowskin :31 B4 :42
## Lobster trap:31 Japanese bait :66 C2 :39
## Redfish trap:72 Japanese bait; Squid:28 D5 :31
## A3/A4 :22
## D3 :20
## (Other):14
## SL_CM FL_CM TL_CM HH_CM
## Min. :13.70 Min. :14.50 Min. :15.80 Min. :2.900
## 1st Qu.:23.35 1st Qu.:21.80 1st Qu.:23.48 1st Qu.:4.725
## Median :27.00 Median :27.00 Median :29.60 Median :5.850
## Mean :27.41 Mean :27.68 Mean :30.42 Mean :6.026
## 3rd Qu.:31.23 3rd Qu.:32.40 3rd Qu.:35.42 3rd Qu.:6.975
## Max. :61.10 Max. :65.50 Max. :78.50 Max. :9.900
## NA's :81 NA's :9 NA's :131
## ED_CM W_G finclip otoliths gutted gonads_present
## Min. :0.800 Min. : 52.7 : 60 N : 5 N:211 : 1
## 1st Qu.:1.425 1st Qu.: 164.7 N: 21 y : 2 Y: 2 N: 1
## Median :1.800 Median : 334.6 Y:132 Y :205 y: 2
## Mean :1.828 Mean : 468.7 Y : 1 Y:209
## 3rd Qu.:2.200 3rd Qu.: 566.5
## Max. :3.000 Max. :4118.8
## NA's :131 NA's :5
## sex maturity G1L_CM G2L_CM GW_G
## : 4 :111 Min. : 1.000 Min. : 0.000 Length:213
## F:117 A: 32 1st Qu.: 2.800 1st Qu.: 2.675 Class :character
## M: 92 B: 34 Median : 3.900 Median : 3.950 Mode :character
## C: 34 Mean : 4.361 Mean : 4.398
## D: 2 3rd Qu.: 5.125 3rd Qu.: 5.400
## Max. :21.100 Max. :22.800
## NA's :1 NA's :9
## stomach._sample
## Length:213
## Class :character
## Mode :character
##
##
##
## #drop the columns without sex measurements
snappers_sex <- snappers_df2506 %>%
filter(sex != "")
summary(snappers_sex)## catch_date catch_month landing_time dissection_date
## Length:209 Sep :68 Length:209 Length:209
## Class :character May :54 Class :character Class :character
## Mode :character Jun :36 Mode :character Mode :character
## Jul :21
## Apr :14
## : 5
## (Other):11
## dissection_time year month observer
## Length:209 2023:111 Length:209 Length:209
## Class :character 2024: 98 Class :character Class :character
## Mode :character Mode :character Mode :character
##
##
##
##
## species common_name fish_code
## Etelis oculatus : 4 Blackfin Snapper :53 Length:209
## Lutjanus buccanella :53 Lane Snapper :31 Class :character
## Lutjanus synagris :31 Queen Snapper : 4 Mode :character
## Lutjanus vivanus :43 Vermilion Snapper:55
## Pristipomoides aquilonaris:23 Wenchman Snapper :23
## Rhomboplites aurorubens :55 Yelloweye Snapper:43
##
## frozen catch_method bait area
## N: 96 :82 :88 :45
## Y:113 Dropline :28 Cowskin :30 B4 :41
## Lobster trap:30 Japanese bait :63 C2 :39
## Redfish trap:69 Japanese bait; Squid:28 D5 :30
## A3/A4 :22
## D3 :19
## (Other):13
## SL_CM FL_CM TL_CM HH_CM
## Min. :13.70 Min. :14.50 Min. :15.80 Min. :2.900
## 1st Qu.:23.55 1st Qu.:22.00 1st Qu.:23.57 1st Qu.:4.800
## Median :27.25 Median :27.20 Median :29.60 Median :6.000
## Mean :27.60 Mean :27.76 Mean :30.50 Mean :6.097
## 3rd Qu.:31.32 3rd Qu.:32.60 3rd Qu.:35.52 3rd Qu.:7.000
## Max. :61.10 Max. :65.50 Max. :78.50 Max. :9.900
## NA's :81 NA's :9 NA's :130
## ED_CM W_G finclip otoliths gutted gonads_present
## Min. :0.800 Min. : 52.7 : 60 N : 5 N:207 : 1
## 1st Qu.:1.500 1st Qu.: 169.2 N: 21 y : 2 Y: 2 N: 0
## Median :1.800 Median : 334.6 Y:128 Y :201 y: 2
## Mean :1.844 Mean : 472.7 Y : 1 Y:206
## 3rd Qu.:2.250 3rd Qu.: 578.7
## Max. :3.000 Max. :4118.8
## NA's :130 NA's :5
## sex maturity G1L_CM G2L_CM GW_G
## : 0 :111 Min. : 1.000 Min. : 0.000 Length:209
## F:117 A: 28 1st Qu.: 2.800 1st Qu.: 2.700 Class :character
## M: 92 B: 34 Median : 3.900 Median : 4.000 Mode :character
## C: 34 Mean : 4.387 Mean : 4.412
## D: 2 3rd Qu.: 5.200 3rd Qu.: 5.400
## Max. :21.100 Max. :22.800
## NA's :7
## stomach._sample
## Length:209
## Class :character
## Mode :character
##
##
##
## #drop the columns without maturity measurements
snappers_maturity <- snappers_df2506 %>%
filter(maturity != "")
summary(snappers_maturity)## catch_date catch_month landing_time dissection_date
## Length:102 May :55 Length:102 Length:102
## Class :character Jun :27 Class :character Class :character
## Mode :character Apr :15 Mode :character Mode :character
## Mar : 5
## : 0
## Aug : 0
## (Other): 0
## dissection_time year month observer
## Length:102 2023: 0 Length:102 Length:102
## Class :character 2024:102 Class :character Class :character
## Mode :character Mode :character Mode :character
##
##
##
##
## species common_name fish_code
## Etelis oculatus : 0 Blackfin Snapper :33 Length:102
## Lutjanus buccanella :33 Lane Snapper :19 Class :character
## Lutjanus synagris :19 Queen Snapper : 0 Mode :character
## Lutjanus vivanus :29 Vermilion Snapper:13
## Pristipomoides aquilonaris: 8 Wenchman Snapper : 8
## Rhomboplites aurorubens :13 Yelloweye Snapper:29
##
## frozen catch_method bait area
## N:99 : 0 : 5 D5 :31
## Y: 3 Dropline : 0 Cowskin :31 A3/A4 :22
## Lobster trap:31 Japanese bait :66 D3 :19
## Redfish trap:71 Japanese bait; Squid: 0 B4 :13
## D4 : 4
## : 3
## (Other):10
## SL_CM FL_CM TL_CM HH_CM
## Min. :13.70 Min. :16.10 Min. :16.90 Min. :2.900
## 1st Qu.:21.85 1st Qu.:25.00 1st Qu.:27.18 1st Qu.:4.725
## Median :25.40 Median :29.05 Median :31.30 Median :5.850
## Mean :25.88 Mean :29.48 Mean :31.87 Mean :6.026
## 3rd Qu.:29.32 3rd Qu.:33.17 3rd Qu.:36.40 3rd Qu.:6.975
## Max. :38.60 Max. :44.10 Max. :47.60 Max. :9.900
## NA's :20
## ED_CM W_G finclip otoliths gutted gonads_present
## Min. :0.800 Min. : 65.7 : 0 N : 0 N:100 : 0
## 1st Qu.:1.425 1st Qu.: 238.9 N:18 y : 2 Y: 2 N: 1
## Median :1.800 Median : 401.4 Y:84 Y :100 y: 2
## Mean :1.828 Mean : 516.7 Y : 0 Y:99
## 3rd Qu.:2.200 3rd Qu.: 632.8
## Max. :3.000 Max. :1714.7
## NA's :20
## sex maturity G1L_CM G2L_CM GW_G
## : 4 : 0 Min. : 1.000 Min. : 1.000 Length:102
## F:47 A:32 1st Qu.: 2.800 1st Qu.: 2.700 Class :character
## M:51 B:34 Median : 3.900 Median : 4.000 Mode :character
## C:34 Mean : 4.399 Mean : 4.521
## D: 2 3rd Qu.: 5.300 3rd Qu.: 5.800
## Max. :11.500 Max. :11.600
## NA's :1 NA's :5
## stomach._sample
## Length:102
## Class :character
## Mode :character
##
##
##
## Filter the data into counts
female_counts <- snappers_reproduction %>%
filter(sex == "F") %>%
group_by(species, maturity) %>%
summarize(count = n(), .groups = 'drop') %>%
mutate(sex = "Female")
# Calculate counts for males
male_counts <- snappers_reproduction %>%
filter(sex == "M") %>%
group_by(species, maturity) %>%
summarize(count = n(), .groups = 'drop') %>%
mutate(sex = "Male")
# Calculate counts for N/A
na_counts <- snappers_reproduction %>%
filter(sex == "") %>%
group_by(species, maturity) %>%
summarize(count = n(), .groups = 'drop') %>%
mutate(sex = "N/A")
# Combine the counts into one dataframe
summary_reproduction <- bind_rows(female_counts, male_counts, na_counts)
# View the combined dataframe
View(summary_reproduction)Plot
plasma_colors_5 <- rev(viridis_pal(option = "plasma", begin = 0.1, end = 0.9)(5))
plasma_colors_5## [1] "#FCCE25FF" "#F1844BFF" "#CC4678FF" "#900DA4FF" "#42049EFF"# First plot with the first three species
reproduction_top_plot <- ggplot(summary_reproduction %>% filter(species %in% c("Etelis oculatus", "Lutjanus buccanella", "Lutjanus synagris"))) +
geom_bar(aes(x = sex, y = count, fill = maturity),
position = "stack",
stat = "identity") +
facet_grid(~ species, switch = "x") +
theme_minimal() +
theme(strip.placement = "outside",
strip.background = element_rect(fill = NA, color = "transparent"),
panel.spacing = unit(-.01, "cm"),
strip.text = element_text(face = "italic")) +
scale_fill_manual(values = c("#FCCE25FF", "#F1844BFF", "#CC4678FF", "#900DA4FF"),
label = c("N/A", "A", "B", "C")) +
labs(x = "",
y = "Count",
fill = "Maturity stage")
# Second plot with the next three species
reproduction_bottom_plot <- ggplot(summary_reproduction %>% filter(species %in% c("Lutjanus vivanus", "Pristipomoides aquilonaris", "Rhomboplites aurorubens"))) +
geom_bar(aes(x = sex, y = count, fill = maturity),
position = "stack",
stat = "identity") +
facet_grid(~ species, switch = "x") +
theme_minimal() +
theme(strip.placement = "outside",
strip.background = element_rect(fill = NA, color = "transparent"),
panel.spacing = unit(-.01, "cm"),
strip.text = element_text(face = "italic")) +
scale_fill_manual(values = c("#FCCE25FF", "#F1844BFF", "#CC4678FF", "#900DA4FF", "#42049EFF"),
label = c("N/A", "A", "B", "C", "D")) +
labs(x = "",
y = "Count",
fill = "Maturity stage")
# Combine the two plots vertically
reproduction_plot <- reproduction_top_plot / reproduction_bottom_plot
# View the combined plot
reproduction_plot
# Save the plot
ggsave("reproduction_plot.png", plot = reproduction_plot, width = 7.2, height = 6, dpi = 400)Subset the BS data into a new df
conflicts_prefer(dplyr::filter)## [conflicted] Removing existing preference.
## [conflicted] Will prefer dplyr::filter over any other package.bsdf_2506 <- subset(filter(snappers_df2506, species == "Lutjanus buccanella"))
#save the df as a csv for further steps
write.csv(bsdf_2506, "bs2506df.csv")Subset the YS data into a new df
ysdf_2506 <- filter(snappers_df2506, species == "Lutjanus vivanus")
View(ysdf_2506)
#remove gutted samples
ysdf_2506 <- subset(filter(ysdf_2506, gutted == "N"))
summary(ysdf_2506)## catch_date catch_month landing_time dissection_date
## Length:86 Sep :32 Length:86 Length:86
## Class :character Jun :19 Class :character Class :character
## Mode :character May :14 Mode :character Mode :character
## Jul : 9
## Mar : 5
## : 3
## (Other): 4
## dissection_time year month observer
## Length:86 2023:57 Length:86 Length:86
## Class :character 2024:29 Class :character Class :character
## Mode :character Mode :character Mode :character
##
##
##
##
## species common_name fish_code
## Etelis oculatus : 0 Blackfin Snapper : 0 Length:86
## Lutjanus buccanella : 0 Lane Snapper : 0 Class :character
## Lutjanus synagris : 0 Queen Snapper : 0 Mode :character
## Lutjanus vivanus :86 Vermilion Snapper: 0
## Pristipomoides aquilonaris: 0 Wenchman Snapper : 0
## Rhomboplites aurorubens : 0 Yelloweye Snapper:86
##
## frozen catch_method bait area
## N:26 :48 :54 :25
## Y:60 Dropline : 8 Cowskin : 1 C2 :24
## Lobster trap: 1 Japanese bait :23 B4 :13
## Redfish trap:29 Japanese bait; Squid: 8 D5 :13
## D3 : 6
## A3/A4 : 5
## (Other): 0
## SL_CM FL_CM TL_CM HH_CM ED_CM
## Min. :16.00 Min. :17.20 Min. :18.30 Min. :3.600 Min. :1.20
## 1st Qu.:24.68 1st Qu.:21.73 1st Qu.:23.20 1st Qu.:5.250 1st Qu.:1.65
## Median :29.20 Median :26.15 Median :28.60 Median :6.600 Median :1.90
## Mean :28.70 Mean :27.57 Mean :29.77 Mean :6.317 Mean :1.87
## 3rd Qu.:32.10 3rd Qu.:33.08 3rd Qu.:36.08 3rd Qu.:7.450 3rd Qu.:2.10
## Max. :40.40 Max. :45.90 Max. :49.20 Max. :9.400 Max. :3.00
## NA's :48 NA's :63 NA's :63
## W_G finclip otoliths gutted gonads_present sex maturity
## Min. : 83.9 :47 N : 0 N:86 : 0 :43 :57
## 1st Qu.: 162.7 N: 5 y : 1 Y: 0 N:28 F:22 A:13
## Median : 281.9 Y:34 Y :84 y: 1 M:21 B:12
## Mean : 429.0 Y : 1 Y:57 C: 2
## 3rd Qu.: 583.3 D: 2
## Max. :1714.7
##
## G1L_CM G2L_CM GW_G stomach._sample
## Min. : 1.000 Min. : 0.000 Length:86 Length:86
## 1st Qu.: 2.250 1st Qu.: 2.200 Class :character Class :character
## Median : 3.800 Median : 3.600 Mode :character Mode :character
## Mean : 4.441 Mean : 4.261
## 3rd Qu.: 5.950 3rd Qu.: 5.500
## Max. :11.500 Max. :11.600
## NA's :27 NA's :29#save the df as a csv for further steps
write.csv(ysdf_2506, "ys2506df.csv")Subset the VS data into a new df
vsdf_2506 <- filter(snappers_df2506, species == "Rhomboplites aurorubens")
#remove the columns with no weight measurements
vsdf_2506 <- vsdf_2506 %>% drop_na(W_G)
#remove the columns with no TL_CM measurements
vsdf_2506 <- vsdf_2506 %>% drop_na(TL_CM)
#remove gutted samples
vsdf_2506 <- subset(filter(vsdf_2506, gutted == "N"))
View(vsdf_2506)
summary(vsdf_2506)## catch_date catch_month landing_time dissection_date
## Length:61 Sep :31 Length:61 Length:61
## Class :character Jun :15 Class :character Class :character
## Mode :character Jul : 9 Mode :character Mode :character
## May : 5
## Apr : 1
## : 0
## (Other): 0
## dissection_time year month observer
## Length:61 2023:49 Length:61 Length:61
## Class :character 2024:12 Class :character Class :character
## Mode :character Mode :character Mode :character
##
##
##
##
## species common_name fish_code
## Etelis oculatus : 0 Blackfin Snapper : 0 Length:61
## Lutjanus buccanella : 0 Lane Snapper : 0 Class :character
## Lutjanus synagris : 0 Queen Snapper : 0 Mode :character
## Lutjanus vivanus : 0 Vermilion Snapper:61
## Pristipomoides aquilonaris: 0 Wenchman Snapper : 0
## Rhomboplites aurorubens :61 Yelloweye Snapper: 0
##
## frozen catch_method bait area
## N:12 :49 :49 C2 :30
## Y:49 Dropline : 0 Cowskin : 0 :19
## Lobster trap: 0 Japanese bait :12 D5 : 9
## Redfish trap:12 Japanese bait; Squid: 0 D3 : 2
## D4 : 1
## A3/A4 : 0
## (Other): 0
## SL_CM FL_CM TL_CM HH_CM
## Min. :16.90 Min. :14.00 Min. :14.90 Min. :3.400
## 1st Qu.:18.70 1st Qu.:16.50 1st Qu.:17.90 1st Qu.:3.700
## Median :19.40 Median :19.90 Median :21.60 Median :4.000
## Mean :20.98 Mean :20.76 Mean :22.81 Mean :4.245
## 3rd Qu.:24.00 3rd Qu.:25.20 3rd Qu.:28.00 3rd Qu.:4.800
## Max. :27.00 Max. :29.90 Max. :34.50 Max. :5.600
## NA's :48 NA's :50
## ED_CM W_G finclip otoliths gutted gonads_present sex
## Min. :1.100 Min. : 52.7 :29 N : 0 N:61 : 0 :12
## 1st Qu.:1.500 1st Qu.: 81.4 N: 3 y : 0 Y: 0 N: 5 F:33
## Median :1.600 Median :132.2 Y:29 Y :61 y: 0 M:16
## Mean :1.618 Mean :182.6 Y : 0 Y:56
## 3rd Qu.:1.800 3rd Qu.:281.2
## Max. :2.100 Max. :481.6
## NA's :50
## maturity G1L_CM G2L_CM GW_G stomach._sample
## :49 Min. :1.000 Min. :0.500 Length:61 Length:61
## A: 0 1st Qu.:2.500 1st Qu.:2.300 Class :character Class :character
## B: 4 Median :3.500 Median :3.200 Mode :character Mode :character
## C: 8 Mean :3.668 Mean :3.532
## D: 0 3rd Qu.:4.600 3rd Qu.:4.800
## Max. :6.500 Max. :6.500
## NA's :8 NA's :8#save the df as a csv for further steps
write.csv(vsdf_2506, "vs2506df.csv")Subset the LS data into a new df
lsdf_2506 <- filter(snappers_df2506, species == "Lutjanus synagris")
#remove the columns with no weight measurements
lsdf_2506 <- lsdf_2506 %>% drop_na(W_G)
#remove gutted samples
lsdf_2506 <- subset(filter(lsdf_2506, gutted == "N"))
View(lsdf_2506)
#save the df as a csv for further steps
write.csv(lsdf_2506, "ls2506df.csv")Subset the WRN data into a new df
wrndf_2506 <- filter(snappers_df2506, species == "Pristipomoides aquilonaris")
#remove the columns with no weight measurements
wrndf_2506 <- wrndf_2506 %>% drop_na(W_G)
#remove gutted samples
wrndf_2506 <- subset(filter(wrndf_2506, gutted == "N"))
View(wrndf_2506)
#save the df as a csv for further steps
write.csv(wrndf_2506, "wrn2506df.csv")Subset the QS data into a new df
qsdf_2506 <- filter(snappers_df2506, species == "Etelis oculatus")
View(qsdf_2506)
summary(qsdf_2506)## catch_date catch_month landing_time dissection_date
## Length:7 Sep :7 Length:7 Length:7
## Class :character :0 Class :character Class :character
## Mode :character Apr :0 Mode :character Mode :character
## Aug :0
## Dec :0
## Jul :0
## (Other):0
## dissection_time year month observer
## Length:7 2023:7 Length:7 Length:7
## Class :character 2024:0 Class :character Class :character
## Mode :character Mode :character Mode :character
##
##
##
##
## species common_name fish_code
## Etelis oculatus :7 Blackfin Snapper :0 Length:7
## Lutjanus buccanella :0 Lane Snapper :0 Class :character
## Lutjanus synagris :0 Queen Snapper :7 Mode :character
## Lutjanus vivanus :0 Vermilion Snapper:0
## Pristipomoides aquilonaris:0 Wenchman Snapper :0
## Rhomboplites aurorubens :0 Yelloweye Snapper:0
##
## frozen catch_method bait area SL_CM
## N:0 :0 :0 B4 :7 Min. :22.00
## Y:7 Dropline :7 Cowskin :0 :0 1st Qu.:25.80
## Lobster trap:0 Japanese bait :0 A3/A4 :0 Median :31.30
## Redfish trap:0 Japanese bait; Squid:7 A4/A5 :0 Mean :37.57
## B3 :0 3rd Qu.:48.50
## B3/4 :0 Max. :61.10
## (Other):0
## FL_CM TL_CM HH_CM ED_CM W_G
## Min. :23.50 Min. :28.60 Min. : NA Min. : NA Min. : 228.2
## 1st Qu.:27.85 1st Qu.:34.30 1st Qu.: NA 1st Qu.: NA 1st Qu.: 379.9
## Median :33.30 Median :41.70 Median : NA Median : NA Median : 618.8
## Mean :40.27 Mean :50.17 Mean :NaN Mean :NaN Mean :1440.1
## 3rd Qu.:51.95 3rd Qu.:66.90 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.:2177.8
## Max. :65.50 Max. :78.50 Max. : NA Max. : NA Max. :4118.8
## NA's :7 NA's :7
## finclip otoliths gutted gonads_present sex maturity G1L_CM
## :0 N :0 N:7 :0 :3 :7 Min. : 4.10
## N:0 y :0 Y:0 N:0 F:4 A:0 1st Qu.: 5.70
## Y:7 Y :7 y:0 M:0 B:0 Median : 6.40
## Y :0 Y:7 C:0 Mean :10.01
## D:0 3rd Qu.:13.55
## Max. :21.10
##
## G2L_CM GW_G stomach._sample
## Min. : 3.80 Length:7 Length:7
## 1st Qu.: 5.65 Class :character Class :character
## Median : 7.10 Mode :character Mode :character
## Mean :10.36
## 3rd Qu.:13.75
## Max. :22.80
## #save the df as a csv for further steps
write.csv(qsdf_2506, "qs2506df.csv")