Generate sampling design

The final step is to generate the sampling design that underpins the monitoring program. In synthos, the design parameters are organized into two complementary components:

• Large-scale design: locates sites within reefs selected across the spatial domain and creates unevenly repeated surveys when random site allocation is selected.
  
• Fine-scale design: specifies the sampling hierarchy within each site, including transects, photo frames, and points for point-based data, as well as quadrats for cover data.

Both components can be easily customised through the function generateSettings, allowing users to tailor the sampling design to their specific monitoring aspirations.

The synthos table is then generated including the selection of surveyed reefs and primary metadata. It summarizes the data at the transect scale by summing the number of count in point-based observation data and averaging cover at the quadrat-level.

The table includes the following:

Variable	Description
survey_depth	Depth in metres.
project_name	Name of the monitoring program.
site_name	Combined reef–site identifier.
survey_transect_number	Transect number within a site.
site_latitude, site_longitude	Geographic coordinates of a site.
survey_start_date	Survey date and time (year/month/day/hour).
point_machine_classification	Benthic community class for each annotation point.
COUNT_TRUE	“True” number of counts available for every reef across the spatial domain.
TOTAL	Total number of annotation points.
COVER_TRUE	“True” percent cover available for every reef across the spatial domain.
year	Year extracted from survey_start_date.
reef	Reef extracted from site_name.
site	Site extracted from site_name.
COUNT	Number of counts for selected reefs only (NA for non-selected reefs).
COVER	Percent cover for selected reefs only (NA for non-selected reefs).

Setting up

# Load packages
library(sf)
library(stars)
library(gstat)
library(INLA)
library(ggplot2)
library(synthos)
library(stringr)
library(ggpubr)
library(scico)

1. Generate settings

surveys <-  "random" # or  "fixed"
data_type <- "points" # or "cover"

synthos::generateSettings(nreefs = 25, nsites = 3, nyears = 15, dhw_eff = 0.5, cyc_eff = 0.3, other_eff = 0.2)

2. Generate sampling design

benthos_reefs_pts <- synthos::create_synthetic_reef_landscape(spatial_grid, config_sp)

if (surveys == "fixed") {
  locs_sf <- synthos::sampling_design_large_scale_fixed(
    benthos_reefs_pts, config_lrge
  )
  obs <- synthos::sampling_design_fine_scale_fixed(
    locs_sf, config_fine
  )
  
} else if (surveys == "random") {
  locs_sf <- synthos::sampling_design_large_scale_random(
    benthos_reefs_pts, config_lrge
  )
  obs <- synthos::sampling_design_fine_scale_random(
    locs_sf, config_fine
  )
} else {
  stop("surveys must be 'fixed' or 'random'.")
}


if (data_type == "points") {
  pts <- synthos::sampling_design_fine_scale_points(obs, config_pt)
  synthos_data <- synthos::prepare_table(pts)  
  
} else if (data_type == "cover") {
  cov <- synthos::sampling_design_fine_scale_cover(obs, config_pt)
  synthos_data <- synthos::prepare_table(cov) 
  
} else {
  stop("data_type must be 'points' or 'cover'.")
}

3. Vizualisation

X_sf <- synthos_data %>%
  filter(!is.na(COUNT)) %>%
  st_as_sf(coords = c("site_longitude", "site_latitude"),
           crs = st_crs(4326))

ggplot() + 
  geom_sf(data = reefs.sf$simulated_reefs_sf, fill = "gray95") + 
  geom_sf(data = X_sf, col = "red", size = 1.2) +
  xlab("Longitude") + ylab("Latitude")  +
  coord_sf(crs = 4326) +
  theme_pubr() +
  theme(
    axis.title = element_text(size = 13),
    axis.text = element_text(size = 11)
  )

Figure 1: Locations of the surveyed reefs.