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index.qmd
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---
title: Robinson Preserve Sportfish Tagging Project
toc: false
sidebar: false
format:
html:
css: styles_splash.css
anchor-sections: false
title-block-banner: images/robinson3.jpeg
---
## Tracking juvenile sport fish movement from a habitat restoration site to fished populations of Tampa Bay
Many commercially and recreationally important fishes use estuarine habitats as juvenile nursery grounds. However, many of these habitats are threatened by a number of stressors, including rising sea levels and increasing urbanization. Restoration and preservation of affected juvenile habitats can help support adult populations. To see our team in action and get a taste for the project, check out [this Youtube Short reel](https://youtube.com/shorts/2IWgYjh7rh8?feature=share) featuring FWRI staff.
```{r}
#| echo: false
#| warning: false
#### Load required packages ####
library(tidyverse)
library(sf)
library(mapview)
library(ggpubr)
library(png)
library(icons)
#### Prep spatial data layers ####
# read in Tampa Bay Shoreline shapefile
TBshore <- st_read('shapefiles/Tampa_Bay_Shoreline.shp', quiet = T) %>%
st_transform(4326)
# read in Robinson Preserve outline polygon from Manatee County
preservedat <- st_read('shapefiles/Parks_and_Preserves.shp', quiet = T) %>%
filter(NAME == 'Robinson Preserve') %>%
select(NAME, TOTADDRESS, ZIPCODE, PARK_TYPE, ACREAGE, MANAGEMENT, OWNER_NAME, geometry)
preservedat.shp <- preservedat %>%
st_transform(4326)
# the county shapefile is in WGS 84 and is a multipolygon
# read in Robinson Preserve expansion project outline polygon
expansiondat <- st_read('shapefiles/RobPres_Expansion_Poly.shp', quiet = T) %>%
select(Entity, Layer, DocName, DocType, geometry) %>%
#need to transform from NAD83 to WGS 84
st_transform(4326)
#read in FIM pond outlines
ponddat <- st_read('shapefiles/Robinson_Preserve.shp', quiet = T) %>%
mutate(Pond = str_sub(FolderPath, 24, 29)) %>%
mutate(Type = case_when(Pond %in% c("Pond_6", "Pond_7") ~ "Natural",
TRUE ~ "Restored")) %>%
#group by ponds and make them into polygon outlines
group_by(Pond, Type) %>%
summarise() %>%
# st_cast("POLYGON") %>%
#for the outer polygon
st_convex_hull()
# ponddat
# the FIM pond outlines are WGS 84 and are points
#pond outlines, as points, are also readable as individual layers from
#test <- st_read("Robinson_Preserve_2019.final.kml")
#locations of water loggers installed during restoration monitoring (different grant than acoustics)
loggerdat <- read.csv("shapefiles/RobPres_WaterLogger_loc.csv", header = T, stringsAsFactors = F)
logger.shp <- loggerdat %>%
filter(Logger.. != 31) %>%
select(Logger.Type, Pond = Location, Notes, LAT_DD, LONG_DD) %>%
#specify lat/long and the WGS coord system as 4326
st_as_sf(coords = c('LONG_DD', 'LAT_DD'), crs = 4326)
# logger.shp
#POTENTIAL locations of acoustic receivers
receiverdat <- read.csv("shapefiles/RobPres_PotAcousticReceiver_loc.csv", header = T, stringsAsFactors = F)
receiver.shp <- receiverdat %>%
#specify lat/long and the WGS coord system as 4326
st_as_sf(coords = c('LONG_DD', 'LAT_DD'), crs = 4326)
# receiver.shp
#appprocimate location of Rob Preserve entry/exit points
openingdat <- read.csv("shapefiles/RobPres_IngressEgress_loc.csv", header = T, stringsAsFactors = F)
opening.shp <- openingdat %>%
#specify lat/long and the WGS coord system as 4326
st_as_sf(coords = c('LONG_DD', 'LAT_DD'), crs = 4326)
# opening.shp
#### Interactive Mapview Map ####
mapviewOptions(basemaps = c("Esri.WorldImagery", "OpenStreetMap"),
legend.pos = "topright")
mapview(preservedat, col.regions = "lightgreen", alpha.regions = 0.2, layer.name = "Robinson Preserve") +
mapview(ponddat, col.regions = "lightblue", layer.name = "Waterbodies") +
mapview(opening.shp, zcol = "Type", col.regions = c("Red", "Black"),
alpha.regions = 10, cex = 5, layer.name = "Potential Exit/Entry Points")
# mapview(logger.shp, col.regions = "blue", cex = 4.5, layer.name = "Water_Air Loggers") +
# mapview(receiver.shp, col.regions = "yellow", cex = 8, alpha.regions = 10, layer.name = "Possible Receiver Locations")
#### Static Map ####
## NEED TO WORK ON THIS ##
#set fill colors in order used
#let's combine all point data to make a simple legend
pointdat <- read.csv("shapefiles/RobPres_pointstructures.csv", header = T, stringsAsFactors = F)
pointdat$Structure_Type <- factor(pointdat$Structure_Type, levels = c("Main ingress/egress",
"Mosquito ditching",
"Water logger",
"Air logger",
"Acoustic receiver"),
labels = c("Main ingress/egress",
"Mosquito ditch ingress/egress",
"Water logger",
"Air logger",
"Acoustic receiver"))
pointdat.shp <- pointdat %>%
#specify lat/long and the WGS coord system as 4326
st_as_sf(coords = c('LONG_DD', 'LAT_DD'), crs = 4326)
custom_icons <- icon_set('images/icons')
# pallette <- c("red", "black", "blue", "pink", "yellow")
# shapes <- c(17, 17, 19, 13, 7)
#
# p <- ggplot(data = TBshore) +
# geom_sf(data = subset(TBshore, ATTRIBUTE == "LAND", select = c("OBJECTID", "ATTRIBUTE", "geometry")), fill = "light gray") +
# geom_sf(data = subset(TBshore, ATTRIBUTE == "WATER", select = c("OBJECTID", "ATTRIBUTE", "geometry")), fill = "light blue") +
# geom_sf(data = preservedat, fill = "light green", color = "dark green", alpha = 0.5) +
# geom_sf(data = ponddat, fill = "light blue") +
# geom_sf(data = pointdat.shp, aes(col = Structure_Type, shape = Structure_Type), size = 3.5) +
# scale_color_manual(values = pallette) +
# scale_shape_manual(values = shapes) +
# coord_sf(xlim = c(-82.692, -82.65), ylim = c(27.49, 27.53), expand = FALSE) +
# theme(
# panel.background = element_rect(fill = "transparent"), # bg of the panel
# plot.background = element_rect(fill = "transparent", color = NA), # bg of the plot
# panel.grid.major = element_blank(), # get rid of major grid
# panel.grid.minor = element_blank(), # get rid of minor grid
# legend.background = element_rect(fill = "transparent"), # get rid of legend bg
# legend.box.background = element_rect(fill = "transparent") # get rid of legend panel bg
# )
#
# p
#
#
# ggsave(p, filename = "test1.png", bg = "transparent")
#### A better option for printing/saving to a static map ####
# mapviewOptions(basemaps = c("Esri.WorldImagery"),
# legend.pos = "topright")
# mapview(preservedat, color = "lightgreen", lwd = 3, col.regions = "lightgreen", alpha.regions = 0.02,
# layer.name = "Robinson Preserve", legend.opacity = 1) +
# mapview(expansiondat, color = "lightcyan3", lwd = 3, col.regions = "lightcyan3", alpha.regions = 0.05,
# layer.name = "Restoration Phase IIB", legend.opacity = 1) +
# #mapview(ponddat, col.regions = "lightblue", layer.name = "Ponds") +
# mapview(pointdat.shp, zcol = "Structure_Type",
# col.regions = c("red", "orange", "blue", "pink", "yellow"),
# layer.name = "Structure Type",
# alpha.regions = 10,
# legend.opacity = 1)
```
The Robinson Preserve Sport Fish Tagging Project was initiated to determine the extent to which the habitat restoration at [Robinson Preserve](https://www.mymanatee.org/departments/natural_resources/preserves/robinson), a 682-acre area with a variety of restored fisheries nursery habitat, contributes juvenile sport fish to adult populations in the greater Tampa Bay area. The contribution of juveniles is a major information gap that exists for many habitat restoration projects, despite being a realistic metric for evaluating restoration success. With the help of the [Manatee County Natural Resources Department](https://www.mymanatee.org/departments/natural_resources) and the [National Oceanic and Atmospheric Administration Office of Habitat Conservation](https://www.fisheries.noaa.gov/about/office-habitat-conservation), researchers at the [Florida Fish and Wildlife Research Institute](https://myfwc.com/research/) are seeking to fill this information gap by tagging and tracking the movement of juvenile sport fishes from and within Robinson Preserve.
::: {.light-mode style="text-align: center; justify-content: center; align-items: center;"}
::: {.light-mode layout-ncol="3" style="text-align: center; justify-content: center; align-items: center;"}
### `r icon_style(fontawesome("tower-broadcast", style = "solid"), scale = 4)`
<font size="+3">11</font>\
Receivers Placed
### `r icon_style(fontawesome("download", style = "solid"), scale = 4, 'text-align'="center")`
<font size="+3">9</font>\
Data Downloads
### `r icon_style(custom_icons('fishing-net-svgrepo-com'), scale = 4)`
<font size="+3">92</font>\
Fish Caught
:::
::: {.light-mode layout-ncol="3" style="text-align: center; justify-content: center; align-items: center;"}
### `r icon_style(fontawesome("fish-fins", style = "solid"), scale = 4)`
<font size="+3">6</font>\
Species Tagged
### `r icon_style(fontawesome("tag", style = "solid"), scale = 4)`
<font size="+3">80</font>\
Tags Implanted
### `r icon_style(fontawesome("location-crosshairs", style = "solid"), scale = 4)`
<font size="+3">2.7 million</font>\
Detections
:::
###
:::
::: {.dark-mode style="text-align: center; justify-content: center; align-items: center;"}
::: {.dark-mode layout-ncol="3" style="text-align: center; justify-content: center; align-items: center;"}
### `r icon_style(fontawesome("tower-broadcast", style = "solid"), fill = "white", scale = 4)`
<font size="+3">11</font>\
Receivers Placed
### `r icon_style(fontawesome("download", style = "solid"), fill = "white", scale = 4, 'text-align'="center")`
<font size="+3">9</font>\
Data Downloads
### `r icon_style(custom_icons('fishing-net-svgrepo-com'), scale = 4, fill = 'white')`
<font size="+3">92</font>\
Fish Caught
:::
::: {.dark-mode layout-ncol="3" style="text-align: center; justify-content: center; align-items: center;"}
### `r icon_style(fontawesome("fish-fins", style = "solid"), fill = "white", scale = 4)`
<font size="+3">6</font>\
Species Tagged
### `r icon_style(fontawesome("tag", style = "solid"), fill = "white", scale = 4)`
<font size="+3">80</font>\
Tags Implanted
### `r icon_style(fontawesome("location-crosshairs", style = "solid"), fill = "white", scale = 4)`
<font size="+3">2.7 million</font>\
Detections
:::
:::