Quick-start

Example Workflow

“What is the mean density of Red Hind (Epinephelus guttatus) over time in St. Thomas U.S. Virgin Islands”

1. load necessary libraries

library(rvc)
library(kableExtra)# Display a pretty table
library(ggplot2)
library(dplyr)

Attaching package: 'dplyr'

The following object is masked from 'package:kableExtra':

    group_rows

The following objects are masked from 'package:stats':

    filter, lag

The following objects are masked from 'package:base':

    intersect, setdiff, setequal, union

2. download region and years of interest

STTSTJ <- getRvcData(years = 2017:2023, regions = "STTSTJ")

3. estimate density using the data object downloading from step 2

RH_density <- getDomainDensity(STTSTJ, "EPI GUTT")

head(RH_density) %>% select(YEAR:n) %>% kable()

YEAR	REGION	SPECIES_CD	density	var	n
2017	STTSTJ	EPI GUTT	0.4459786	0.0038043	236
2019	STTSTJ	EPI GUTT	0.5158166	0.0030699	322
2021	STTSTJ	EPI GUTT	0.4815063	0.0028042	165
2023	STTSTJ	EPI GUTT	0.4351223	0.0020429	287

4. create additional column and plot via ggplot2

RH_density %>% 
  mutate(SE = sqrt(var)) %>% 
  ggplot(aes(x = YEAR, y = density)) +
    geom_line() +
    geom_point(size = 2) +
    geom_errorbar(aes(ymin = density - SE, ymax = density + SE),                  
                  width = 0.25,
                  size = 0.5) +
  theme_classic()+
  ylab(expression(paste("Density (ind/", m^2 ,")"))) +
  xlab("Year") +
  ggtitle("St. Thomas & St. John Red Hind Density") +
  theme(plot.title = element_text(hjust = 0.5))