Goals

Describe the Montipora capitata coral colony collections under State of Hawai`i SAP2024-35 and tank acclimation prior to spawn night research activities in June & July of 2024.

Install & load packages

## Install packages
if (!require("ggmap", character.only = TRUE)){ install.packages("ggmap")}

if (!require("ggplot2", character.only = TRUE)){ install.packages("ggplot2")}

if (!require("cowplot", character.only = TRUE)){ install.packages("cowplot")}

if (!require("ggplotify", character.only = TRUE)){ install.packages("ggplotify")}


## Load packages
library(ggplotify)
library(tidyverse)
library(leaflet)
library(ggmap)
library(ggplot2)
library(cowplot)

Coral collection location

Lagoon snorkel entrance to fringing reef surrounding HIMB

Leaflet interactive map

coral_collection <- data.frame(
  site = 'HIMB',
  reef = 1,
  lat = 21.431619,
  lon = -157.787127,
  collection_date = as.Date('06/30/2024', format = '%m/%d/%Y'),
  colony_count = 20,
  colony_size_cm = 30,
  permit = 'SAP2024-35') 


# Prepare the text for the tooltip:
mytext <- paste(
   "Patch Reef: ", coral_collection$reef, "<br/>", 
   "Collection Date: ", coral_collection$collection_date) %>%
  lapply(htmltools::HTML)

# Generate Map
KB <- leaflet(coral_collection) %>% 
  addTiles()  %>% 
  setView( lng = -157.787347, lat = 21.431229, zoom = 18 ) %>% 
  addProviderTiles("Esri.WorldImagery") %>% 
  addCircleMarkers(~lon, ~lat, 
    fillColor = "orange", fillOpacity = 0.7, color="white", radius=8, stroke=FALSE,
    label = mytext,
    labelOptions = labelOptions( style = list("font-weight" = "normal", padding = "3px 8px"), textsize = "13px", direction = "auto")
  )%>%
  # Add a visible range (e.g., 100 meters)
  addCircles(~lon, ~lat,
    radius = 60,  # in meters
    color = "blue", fill = FALSE, weight = 2
  )

# Display map
KB

Google static ggmap with cowplot

# Define coordinates
location <- c(lon = -157.78, lat = 21.43)

# Get map
main_basemap <- get_map(location = location, zoom = 16, maptype = "satellite")

ℹ <https://maps.googleapis.com/maps/api/staticmap?center=21.43,-157.78&zoom=16&size=640x640&scale=2&maptype=satellite&language=en-EN&key=xxx-_B4kLVVnbt4gpWJqCcY>

Google main map

# Plot
main_map <- ggmap(main_basemap) +
  geom_point(
    data = coral_collection,
    aes(x = lon, y = lat),
    color = "orange",
    size = 4
  ) +
  theme_minimal()

main_map

Warning: Removed 1 row containing missing values or values outside the scale range
(`geom_point()`).

Stadia main map

bbox <- c(left = -158, bottom = 21.2, right = -157.4, top = 21.8)

get_stadiamap(
  bbox,
  zoom = 8,
  maptype = "alidade_smooth" 
) %>% ggmap()

ℹ © Stadia Maps © Stamen Design © OpenMapTiles © OpenStreetMap contributors.

# Define coordinates
location <- c(lon = -157.787347, lat = 21.431215)

# Get map
main_basemap <- get_map(location = location, zoom = 17, maptype = "satellite")

ℹ <https://maps.googleapis.com/maps/api/staticmap?center=21.431215,-157.787347&zoom=17&size=640x640&scale=2&maptype=satellite&language=en-EN&key=xxx-_B4kLVVnbt4gpWJqCcY>

inset_basemap <- get_stadiamap(
  bbox = c(left = -158, bottom = 21.2, right = -157.4, top = 21.8),
  zoom = 8,
  filetype = "stamen_watercolor" 
)

ℹ © Stadia Maps © Stamen Design © OpenMapTiles © OpenStreetMap contributors.

# 1. Bounding box from main map
main_bbox <- attr(main_basemap, "bb")

# 2. Inset map with bounding box from main map
inset_map <- ggmap(inset_basemap) +
  annotate("rect", 
           xmin = main_bbox$ll.lon, xmax = main_bbox$ur.lon,
           ymin = main_bbox$ll.lat, ymax = main_bbox$ur.lat,
           color = "yellow", fill = NA, linewidth = 1) +
  theme_void()

# 3. Convert both to standard ggplot objects
main_map_plot <- as.ggplot(main_map)

Warning: Removed 1 row containing missing values or values outside the scale range
(`geom_point()`).

inset_map_plot <- as.ggplot(inset_map)

# 4. Compose using cowplot
final_plot <- ggdraw() +
  draw_plot(main_map_plot) +
  draw_plot(inset_map_plot, x = 0.65, y = 0.65, width = 0.3, height = 0.3)

print(final_plot)

Tank acclimation

In inches the tank dimensions are 48in W x 55in L x 18in D. The water height was variable, and determined by the level of the stand-pipe. During acclimation 30cm diameter corals were kept in water ~15in deep. Total volume of water that corals were acclimated in was therefore:

incube <- 48*15*55
print(paste(incube,'inches cubed'))

[1] "39600 inches cubed"

1in³ (1 cubic inch) is equal to 0.0043290043 US gallons.

The volume of water in gallons is therefore:

gal <- incube*0.0043290043
print(paste(gal, 'gallons'))

[1] "171.42857028 gallons"

Finally, 1US gallon = 3.78541 liters

L <- gal*3.78541
print(paste(L, 'liters'))

[1] "648.927424223615 liters"

We used 12qt(11.4L) cambro chambers as the individual bins for spawning.

--- title: "Coral collections & tank acclimation protocol" subtitle: "For spawning of Montipora capitata rice corals" author: "Sarah Tanja" date: 2024-07-09 date-format: long date-modified: today categories: [protocols] --- # Goals Describe the *Montipora capitata* coral colony collections under State of Hawai\`i SAP2024-35 and tank acclimation prior to spawn night research activities in June & July of 2024. # Install & load packages ```{r echo=TRUE, message=FALSE, warning=FALSE} ## Install packages if (!require("ggmap", character.only = TRUE)){ install.packages("ggmap")} if (!require("ggplot2", character.only = TRUE)){ install.packages("ggplot2")} if (!require("cowplot", character.only = TRUE)){ install.packages("cowplot")} if (!require("ggplotify", character.only = TRUE)){ install.packages("ggplotify")} ## Load packages library(ggplotify) library(tidyverse) library(leaflet) library(ggmap) library(ggplot2) library(cowplot) ``` # Coral collection location ![Lagoon snorkel entrance to fringing reef surrounding HIMB](Lagoon%20surrounding%20HIMB%2021.431215°N,%20-157.787347°W.png) ![](KB-patchreefs-1.jpg) ![](KB-patchreef-latlon.jpg) # Leaflet interactive map ```{r} coral_collection <- data.frame( site = 'HIMB', reef = 1, lat = 21.431619, lon = -157.787127, collection_date = as.Date('06/30/2024', format = '%m/%d/%Y'), colony_count = 20, colony_size_cm = 30, permit = 'SAP2024-35') # Prepare the text for the tooltip: mytext <- paste( "Patch Reef: ", coral_collection$reef, "<br/>", "Collection Date: ", coral_collection$collection_date) %>% lapply(htmltools::HTML) # Generate Map KB <- leaflet(coral_collection) %>% addTiles() %>% setView( lng = -157.787347, lat = 21.431229, zoom = 18 ) %>% addProviderTiles("Esri.WorldImagery") %>% addCircleMarkers(~lon, ~lat, fillColor = "orange", fillOpacity = 0.7, color="white", radius=8, stroke=FALSE, label = mytext, labelOptions = labelOptions( style = list("font-weight" = "normal", padding = "3px 8px"), textsize = "13px", direction = "auto") )%>% # Add a visible range (e.g., 100 meters) addCircles(~lon, ~lat, radius = 60, # in meters color = "blue", fill = FALSE, weight = 2 ) # Display map KB ``` # Google static ggmap with cowplot Register your API key with `register_google(key = "your api key here")` ```{r} #| include: false # Register your API key register_google(key = "AIzaSyC6_foVMJfxD3w-_B4kLVVnbt4gpWJqCcY") ``` ```{r} # Define coordinates location <- c(lon = -157.78, lat = 21.43) # Get map main_basemap <- get_map(location = location, zoom = 16, maptype = "satellite") ``` ## Google main map ```{r} # Plot main_map <- ggmap(main_basemap) + geom_point( data = coral_collection, aes(x = lon, y = lat), color = "orange", size = 4 ) + theme_minimal() main_map ``` ## Stadia main map Register API key ```{r, include=FALSE} register_stadiamaps(key = "5850d823-fdbc-449e-ac23-123836628ba8", write = TRUE) ``` ```{r} bbox <- c(left = -158, bottom = 21.2, right = -157.4, top = 21.8) get_stadiamap( bbox, zoom = 8, maptype = "alidade_smooth" ) %>% ggmap() ``` ```{r} # Define coordinates location <- c(lon = -157.787347, lat = 21.431215) # Get map main_basemap <- get_map(location = location, zoom = 17, maptype = "satellite") inset_basemap <- get_stadiamap( bbox = c(left = -158, bottom = 21.2, right = -157.4, top = 21.8), zoom = 8, filetype = "stamen_watercolor" ) # 1. Bounding box from main map main_bbox <- attr(main_basemap, "bb") # 2. Inset map with bounding box from main map inset_map <- ggmap(inset_basemap) + annotate("rect", xmin = main_bbox$ll.lon, xmax = main_bbox$ur.lon, ymin = main_bbox$ll.lat, ymax = main_bbox$ur.lat, color = "yellow", fill = NA, linewidth = 1) + theme_void() # 3. Convert both to standard ggplot objects main_map_plot <- as.ggplot(main_map) inset_map_plot <- as.ggplot(inset_map) # 4. Compose using cowplot final_plot <- ggdraw() + draw_plot(main_map_plot) + draw_plot(inset_map_plot, x = 0.65, y = 0.65, width = 0.3, height = 0.3) print(final_plot) ``` # Tank acclimation ![HIMB blue tank dimensions](PXL_20220612_035159238~2.jpg) In inches the tank dimensions are 48in W x 55in L x 18in D. The water height was variable, and determined by the level of the stand-pipe. During acclimation 30cm diameter corals were kept in water \~15in deep. Total volume of water that corals were acclimated in was therefore: ```{r} incube <- 48*15*55 print(paste(incube,'inches cubed')) ``` 1in^3^ (1 cubic inch) is equal to 0.0043290043 US gallons. The volume of water in gallons is therefore: ```{r} gal <- incube*0.0043290043 print(paste(gal, 'gallons')) ``` Finally, 1US gallon = 3.78541 liters ```{r} L <- gal*3.78541 print(paste(L, 'liters')) ``` We used [12qt(11.4L) cambro chambers](https://www.cambro.com/Products/food-storage/square-food-storage-containers/camsquares-classic-food-storage-containers/camsquares-camwear/12SFSCW135) as the individual bins for spawning.